Hospitals play a vital role in providing optimal care for all cardiac arrest patients, regardless of whether a patient suffers an in-hospital cardiac arrest (IHCA) or an out-of-hospital cardiac arrest (OHCA). Survival-to-discharge rates and the likelihood of good neurologic outcomes and functional status following cardiac arrest vary substantially between OHCA and IHCA. These disparities are based on various factors, including the predominant etiologies of IHCA and OHCA, the affected patient populations and related comorbidities, the proximity to trained providers and appropriate treatments, and the number of transitions that must occur between various providers, such as emergency medical services (EMS) professionals and hospital staff. There are also significant differences in outcomes among patients who experience an IHCA and require immediate resuscitation and life support treatments. These differences can be influenced by the quality of hospital personnel training, adherence to evidence-based protocols, the implementation of internal quality control mechanisms, as well as other important factors.
Despite the differences in the onset of, and system response to, IHCA and OHCA, most patients who experience return of spontaneous circulation (ROSC) share one common experience—post-arrest care—which most frequently occurs within a hospital setting. The fundamental goal of post-arrest care is to identify and control factors that precipitated the arrest, improve the probability of favorable neurologic recovery and outcomes, and minimize the consequences of cardiac arrest–associated injury and tissue damage. Additionally, post-arrest care focuses on providing a timely and accurate prognosis for neurologic recovery and managing multisystem organ failure. Studies have demonstrated that when coordinated, high-quality, and comprehensive post-resuscitation
care is provided, survival-to-hospital discharge with favorable neurologic outcome can be dramatically increased (Knafelj et al., 2007; Sunde et al., 2007). However, patient outcomes are limited by the availability of comprehensive treatments and therapies, lack of a system that ensures well-coordinated transitions of care between providers, and variability in quality of care across institutions. These failures by health care systems and hospitals represent an important national health care issue.
Previous chapters described OHCA, and the role of the public and emergency medical service in providing resuscitation care. This chapter focuses on all aspects of hospital-based resuscitation systems of care, from the individual patient’s arrival through discharge. It provides an overview of the transitions of care that occur between the prehospital and hospital setting, as well as within hospitals. The chapter then describes the unique aspects of IHCA, evaluates current resuscitation strategies, and identifies known gaps in knowledge. Next, the current state of postarrest care in the United States is examined, and available treatment options and assessment tools, as well as the deficiencies in care delivery, are discussed. This section also identifies current best practices that have resulted in favorable clinical outcomes, taking into consideration the existing limitations in evidence within the post-arrest care field. Finally, the chapter ties together common themes across resuscitation care settings and proposes strategies aimed toward improving the quality of care for all cardiac arrest patients within hospitals across the nation. The discussion will include care for adult and pediatric populations because the principles used for assessing, monitoring, providing feedback, and ensuring quality are the same.
TRANSITION OF CARE IN CARDIAC ARREST RESUSCITATION SYSTEMS
Transitions of care occur as patients move between different health care providers and departments and are fundamental components of managing care for patients who initially survive cardiac arrest. Although care transitions from the hospital setting to the outpatient setting (following discharge) have been studied more rigorously than care transitions from the prehospital EMS setting to the hospital emergency department, or between hospital wards, the literature largely finds that a number of patient safety and quality deficiencies arise during transitions of care (Coleman and Berenson, 2004; Halasyamani et al., 2006; Snow et al.,
2009). The handoff between providers or care teams can increase adverse events through medication errors, incomplete communication of relevant patient medical history affecting treatments, or lack of appropriate follow-up care (Coleman et al., 2006; Cook et al., 2000; Moore et al., 2003). Studies on the effect of hospital-based care transitions on patient outcomes in the cardiac arrest setting are limited (see Chapter 4 for an in-depth discussion of care transitions from EMS to hospital); much of the following discussion is based on extrapolations of studies done in relevant emergency care settings.
Figure 5-1 illustrates the complex care pathway for cardiac arrest patients. The initial OHCA pathway may involve prehospital responses from bystanders and EMS personnel to the emergency department (ED) care teams. Post-arrest care (e.g., therapeutic hypothermia) for OHCA patients can be initiated prior to arrival in the ED. Therefore, adequate communication between ambulatory care physicians and EMS or hospital physicians is essential for ensuring delivery of continuous, highquality care (Snow et al., 2009). For cardiac arrest patients, important clinical information should include the patient’s clinical history and standardized EMS data (e.g., the location of the arrest, the time from collapse to initiation of cardiopulmonary resuscitation [CPR], initial cardiac rhythm, and administered drugs). As discussed in Chapter 2, establishing a standardized data template for EMS and hospital systems is vital to ensure that clinical decisions requiring timely assessments and implementation occur rapidly and that critical care services are then initiated quickly. Additionally, providers and care teams across multiple settings need to communicate effectively and have access to complete clinical information to be able to make appropriate decisions regarding postarrest care for individual patients.
Within hospitals, resuscitation teams initially evaluate and manage IHCA patients in various nonintensive care areas. Similar to OHCA, IHCA patients who achieve ROSC and are stabilized should be transported to an intensive care unit (ICU) or critical care unit (CCU), and require timely decisions about subsequent post-arrest treatments and care. Hospital transition protocols and communication infrastructure should be in place to ensure that important information regarding cardiac arrest patients be relayed efficiently and seamlessly among health care providers who work in different teams and units. Post-arrest care for patients within, and subsequently transitioning out of, the ICU into
FIGURE 5-1 Transition of care for cardiac arrest patients who survive to hospital discharge.
aIHCA care pathway can begin at any location within the hospital (e.g., emergency department, cardiac catheterization laboratory, intensive care unit, medical/ surgical wards).
bThe location of step-down recovery varies across hospitals.
cOutpatient continued care can be received in rehabilitation units and skilled nursing facilities, as well as home nursing care and hospice care. Patients who survive to discharge with favorable neurologic and functional outcomes recover at home.
NOTES: Post-arrest treatments can begin at any point in this pathway, once patients achieve return of spontaneous circulation following an out-of-hospital cardiac arrest (OHCA) or an in-hospital cardiac arrest (IHCA). EMS = emergency medical services.
hospital-based step-down units is similar for both OHCA and IHCA survivors, and requires care pathways that are individualized to the needs and preferences of the patient. Care focuses on continued rehabilitation and neurologic recovery, therapy focused on prevention of recurrent events (e.g., management of heart failure and myocardial ischemia burdens and placement of implantable cardioverter defibrillators to respond to future arrests), and comfort care, and requires additional coordination between multidisciplinary providers. Following hospital discharge, patients receive continued care in home-based or rehabilitation facilities.
Each of these transitions of care represents opportunities to improve care quality by reducing errors or miscommunication during handoffs. Successful transitions require the establishment of a communication infrastructure to relay important clinical information between providers and departments in an efficient and effective manner, so that critical data are not lost and the care is not compromised in any way (Snow et al., 2009). Thus, emphasis on transitions of care is a good first step to ensure that patients are receiving the care they need in a continuous manner across sites of care.
IN-HOSPITAL CARDIAC ARREST
Approximately 200,000 cases of IHCA (Merchant et al., 2011) are reported in adults, and another 6,000 IHCA cases occur in children each year, representing a major patient safety and public health concern in the United States (Chan et al., 2010; Morrison et al., 2013; Nadkarni et al., 2006). Although survival rates following IHCA have improved over the past decade, currently, approximately half of all adult patients achieve ROSC following an IHCA, and less than one-quarter survive to hospital discharge (Chan, 2015; Girotra, 2012). IHCA outcomes are somewhat better for children, with 43 percent surviving to hospital discharge in 2009 (Girotra et al., 2013). These limited outcomes occur despite a substantial amount of resources that are devoted to the management and care of IHCA patients each year. Recent studies assessing trends in the Get With The Guidelines-Resuscitation (GWTG-R) registry database have found improvements in patient outcomes; the rates of clinically significant neurologic disability (defined as a Cerebral Performance Category [CPC] score >1) decreased (33 to 28 percent) among survivors (Girotra et al., 2012), while survival rates increased from 16 to 24 percent between 2000 and 2013 (Chan, 2015). While this increase in IHCA
survival could be partially due to Hawthorne effects within participating hospitals, or reflect a positive shift in population health, it likely also represents improvements in resuscitation treatments and care.
This section focuses on several unique aspects of IHCA that distinguish it from OHCA. IHCA, in many ways, is a different clinical condition that affects a unique population subset, possibly with more severe illness or comorbidities that can influence treatment strategies and outcomes. This section describes IHCA epidemiology, incidence, and outcomes. It then reviews the current state of evidence regarding hospitals’ approaches to managing and treating IHCA, and describes recent shifts in evidence related to teamwork and leadership efforts on resuscitation teams, along with advances in quality improvement tools and technology.
Although the basic cardiac arrest rhythms and pathophysiology are similar for OHCA and IHCA, their underlying causes can be markedly different. First, approximately 90 percent of OHCAs are of cardiac etiology and occur unexpectedly (Daya et al., 2015). Conversely, IHCA is usually caused by underlying cardiac conditions less than half of the time, and patients often have demonstrable deterioration prior to the event (Chan, 2015; Morrison et al., 2013). The proportions of presenting arrhythmias and corresponding survival rates for OHCA and IHCA also differ, as shown in Table 5-1. The percent of IHCAs that present with pulseless electrical activity (PEA) is more than double that for OHCA, and asystole accounts for approximately 30 percent more cases of OHCAs than IHCAs. Because ventricular fibrillation (VF) or pulseless ventricular tachycardia (pVT) (i.e., shockable rhythms) that are left untreated for several minutes after onset can degenerate into asystole, it is reasonable to suggest that a higher percentage of OHCAs are initiated by shockable rhythms, which transition to asystole. These factors are associated with marked differences in survival rates by arrhythmias and event location.
Typically, IHCA patients also have more secondary comorbidities and additional acute disease processes, which affect overall health outcomes and recovery following cardiac arrest. Additionally, response times to IHCA compared to OHCA are generally shorter, and the arrests are frequently witnessed, which leads to decreased ischemic burden time (i.e., the time between the onset of the arrest and ROSC). Faster ROSC may reduce the risk, duration, and severity of the post-arrest syndrome.
TABLE 5-1 Percentage of Presenting Arrhythmias and Survival to Discharge for IHCA and OHCA
|Percent of Total Cardiac Arrests||Percent Survive to Discharge||Percent of Total Cardiac Arrests||Percent Survive to Discharge|
|Other||Not reported||Not reported||4.5||46.4|
NOTES: The table is created based on two separate studies; proportions therefore do not add up to 100. PEA = pulseless electrical activity; pVT = pulseless ventricular tachycardia; VF = ventricular fibrillation.
SOURCES: Chan, 2015; Daya et al., 2015
Finally, the types of treatments available to OHCA and IHCA patients are similar, but they have been variably studied across the conditions (e.g., therapeutic hypothermia).
Incidence and Outcomes of Pediatric IHCA
Among children, there are substantial differences between IHCA and OHCA, which plays a major role in their care and outcomes. Most children who experience IHCA have an underlying health condition; 61 percent of children experience respiratory failure prior to the event and 29 percent experience shock (Nadkarni et al., 2006; Reis et al., 2002). These underlying illnesses greatly affect post-arrest management.
Infants and children who suffer arrest from respiratory insufficiency often have preceding prolonged periods of increasing hypotension, hypoxia, and acidosis, resulting in extensive asphyxial end-organ damage (Nadkarni et al., 2006). Patients with congenital heart disease often suffer arrest in the post-operative period, and the altered hemodynamics from unique anatomy and physiology complicated by the consequences of prolonged cardiopulmonary bypass require distinctive care protocols. Examples include patients with single-ventricle physiology or pulmonary artery hypertension. Asystole and PEA are the most frequent initial rhythms observed in IHCA pediatric patients, constituting 85 percent of all arrests, while VF and pVT constitutes 15 percent of all arrests (Girotra
et al., 2013). Neonates, especially those in the delivery room, require separate expertise and protocols.
Pediatric outcomes following IHCA, in a select group of hospitals, have improved over the past several decades. The unadjusted survival-to-discharge rate increased from 14.3 percent in 2000 to 43.4 percent in 2009 (Girotra et al., 2012). These improvements have been largely due to improvement in acute resuscitation survival, defined as ROSC for at least 20 minutes, from 43 percent to 81 percent. Encouragingly the number of pediatric survivors with favorable neurologic outcomes is also increasing (Girotra et al., 2013).
Disparities in Incidence and Outcomes of IHCA
There is a paucity of reliable and valid data and subsequently limited studies of IHCA incidence and outcomes among racial and ethnic minority populations. As discussed in Chapter 2, several studies of IHCA have noted disparate outcomes among African American and Hispanic populations, compared to that for white patients. According to the committee’s commissioned analysis of GWTG-R data, African American patients were significantly less likely to survive to hospital discharge than were white patients following an IHCA (20.8 percent survival compared to 25.9 percent, respectively) (Chan, 2015). One study found that the disparate outcomes can be partially accounted for by differences in the proportion of shockable initial cardiac rhythm; African American and Hispanic patients had a shockable rhythm 17 and 21 percent of the time, respectively, compared to white patients who had a shockable rhythm 27 percent of the time (Meaney et al., 2010).
The increased IHCA incidence among racial and ethnic minority populations may be due, in part, to differences in socioeconomic factors or individual characteristics, but could also potentially be caused by elements of the health care system. One study found greater delays in time to defibrillation for African American patients compared to white patients (Chan et al., 2008). The same study also noted delayed defibrillation for Hispanic patients; however, these results were not statistically significant. Following arrest, studies have found that African Americans have longer lengths of stay in EDs compared to patients of other races and ethnicities. These longer lengths of stay are associated with adverse outcomes in ICU patients. Adjustment for the hospital location explains a large portion of these IHCA differences. IHCA incidence appears to be highest, and likelihood of survival lower, in hospitals with higher propor-
tions of African American patients compared to hospitals that serve predominantly white populations (Chan et al., 2009). Additionally, decision-support tools to predict IHCA outcomes do not accurately predict mortality in African American patients, which could have profound effects on treatment courses and outcomes. In order to reduce IHCA events and improve survival for all racial and ethnic groups, it is imperative to examine overall process and quality measures in hospitals with high rates of IHCAs. Findings from these reviews must then be used to inform changes in practice that elevate accountability and work toward better outcomes for all patients.
Numerous studies have documented notable variation in outcomes for IHCA across institutions. One study reported that risk-adjusted survival rates varied from 12.4 percent in the bottom decile of hospitals to 22.7 percent in the top decile of hospitals included in the GWTG-R registry (Merchant et al., 2011). Similar variation across hospitals exists for pediatric IHCA survival rates as well, ranging from unadjusted rates of 29 to 48 percent (Jayaram et al., 2014). Differences in patient and health system characteristics can account for some of this variation. There are also additional limitations in availability of reliable, standardized IHCA data that make measurement and interpretation of patient outcomes challenging, described in the following section.
Challenges of Measuring Incidence and Outcomes
Determining accurate IHCA incidence has been challenging because of a lack of standardized definitions and robust surveillance data (see Chapter 2). Different approaches for calculating IHCA incidence have been used in the literature, ranging from counting the number of activations of a resuscitation team to the number of times that chest compressions or defibrillation are used in order to identify the numerator. However, because code teams are not always activated in critical care areas such as EDs, ICUs, or the operating room, counting these activations as a proxy for cardiac arrest can underestimate IHCA incidence (Morrison et al., 2013). Defining an appropriate at-risk population for the denominator of the incidence rates also has been variable, and questions exist about whether only individuals who experience a cardiac arrest after being admitted to the hospital should be counted or whether all visits to the hospital (e.g., those to the emergency department, outpatient clinic, procedure or operating rooms, long-term care units) should be included. Additionally, there is concern about variability in do-not-attempt-
resuscitation (DNAR) status orders across hospitals and how these orders may affect reported incidence rates for IHCA.
A recent consensus document by the American Heart Association’s (AHA’s) recommended definition of IHCA incidence in admitted patients proposes a numerator that includes all patients who receive chest compressions and/or defibrillation, while the denominator reflects the total number of patients admitted to the hospital, including those in the ICUs and the operating and procedure rooms, along with their recovery areas (Morrison et al., 2013). The consensus document also recommended that patients with DNAR status be removed from both the numerator and the denominator. This could be particularly challenging for the denominator using currently available hospital claims data systems, because DNAR status is not routinely collected. This could change substantially with greater use of electronic health records.
The consensus document also suggests incidence of IHCA be reported separately by location for procedure or operating rooms, emergency department, and long-term care patients (Morrison et al., 2013). Patients in these areas often reflect unique clinical circumstances that differentiate them from the acute hospitalized patients and may not use the same hospital response systems. Within hospitals, patients who arrest in nonmonitored units and the ICU are often the least likely to survive to discharge (Chan, 2015). While the nonmonitored unit results are to be expected because of a lack of possible witnesses, factors such as severity of illness could explain the ICU findings.
Even with standardized definitions of incidence, detecting IHCA in administrative claims data can be an arduous task, because of the lack of a specific International Classification of Diseases (ICD) diagnostic code distinguishing it from other types of cardiac arrest (e.g., OHCA). There are also no diagnosis-related group (DRG) codes distinguishing IHCA and OHCA, although a DRG does exist for unexplained cardiac arrest. Subsequently, investigators have relied on a combination of algorithms (e.g., counting CPR or defibrillation and hospital admission rates) to calculate incidence, but these have not been clearly validated. The current barriers and potential opportunities for improving IHCA surveillance and identification are discussed later in this chapter.
The process of measuring IHCA outcomes shares many of the same challenges, such as determining the most appropriate patients for inclusion, and selecting an appropriate standard metric. Possible outcome metrics include ROSC for at least 20 minutes and survival to discharge. Other standardized outcomes, including 30-day or longer-term survival
rates, neurologic outcome assessments and quality-of-life metrics or functional status assessments, are less frequently reported in the literature. However, these types of measures have not been widely incorporated into studies to date, because they require much greater effort to collect. As with incidence of IHCA, patient DNAR status and eligibility for resuscitation care affect the measurement of outcomes. The types of patients who undergo CPR and resuscitation care for IHCA may vary across hospitals and may significantly influence risk-adjusted survival rates across hospitals.
Hospital Response to IHCA
Cardiac arrest remains a largely unpredictable event that can happen at any time with outcomes that are highly dependent on rapid diagnosis and treatment. The nature of IHCA provides a number of challenges for hospitals and health care systems. For example, smaller facilities may have limited resources for 24-hour, on-site physician availability. Furthermore, many health care providers—including physicians with experience in medical specialties with a low rate of cardiac arrest—may lack the necessary experience and expertise to appropriately respond to an IHCA. A final factor that may affect IHCA outcomes is that most academic or teaching hospitals have historically relied on physicians-in-training (e.g., residents and fellows) to provide resuscitation care. Studies have shown that younger physicians and physicians-in-training may lack competence and confidence in the nontechnical skills, such as leadership and teamwork, required to respond to cardiac arrests (Hayes et al., 2007). Resuscitation teams may have limited opportunities to work together over time in emergency situations, frequently coming together on an ad hoc basis to respond to an IHCA. This approach is innately more stressful and requires greater levels of leadership and teamwork in order to successfully deliver resuscitation care.
Substantial variability in IHCA care delivery throughout the United States, which suggests an opportunity for improving IHCA care processes and closing gaps in care across hospitals. For example, one study determined that delayed defibrillation (defined as provision of defibrillation more than 2 minutes after the initial arrest) occurred in care for approximately 30 percent of patients and was associated with a significantly lower probability of surviving to hospital discharge after multivariable risk adjustment (Chan et al., 2008). Another study reported adjusted rates of delays in time to defibrillation that was nearly 25-fold (delayed
defibrillation rates ranging from 2 to 51 percent) across hospitals for patients with VF and pVT cardiac arrests, likely because of differences in hospital-level factors (Chan et al., 2009; Merchant et al., 2009). More recently, Ornato and colleagues (2012) found system-based error rates during IHCA. Some errors identified include discrepancies in alerting hospital-wide resuscitation response, chest compressions, defibrillation, airway management, hyperventilation, medications, vascular access, leadership, protocol deviation, and equipment function problems (Abella et al., 2005; Donoghue et al., 2006; Ornato et al., 2012). Similar deficiencies, related to provision of incorrect compression rate and depth, delays to defibrillation and hyperventilation, have also been noted during IHCA resuscitation in children (Cheng et al., 2015a; McInnes et al., 2011; Sullivan et al., 2014; Sutton et al., 2009, 2013).
Overall IHCA incidence represents the patient burden of illness, the facility’s ability to detect deterioration in patients and prevent the cardiac arrest from occuring, and the effectiveness of a faculty’s resuscitation response system (Morrison et al., 2013). Hospitals and health care systems have developed a myriad of ways to evaluate and assess patients who suffer cardiac arrest using emergency response plans that are often tailored to their local resources. The following section first describes some of the standard responses used by hospitals across the nation in cardiac arrest care.
Individual hospitals have varying emergency response protocols and capacities for responding to cardiac arrests. With the exception of patients in CCUs, ICUs, and EDs, designated resuscitation teams are generally alerted to respond to an IHCA occurring anywhere within the hospital using a facility-wide activation system. Typically, team members provide immediate basic and advanced life support (CPR and defibrillation) before transferring patients who achieve ROSC to CCUs or cardiac catherization laboratories for continued diagnostic testing, advanced therapies, neurologic assessment, and post-arrest care. For patients who are deteriorating but have not yet experienced an IHCA, rapid response teams (RRTs), otherwise known as medical emergency teams (METs) in some hospitals, may be activated. These teams differ from resuscitation teams in that their purpose is to prevent an IHCA and not provide resuscitation, through quick evaluation and escalation of care as needed. Similar to resuscitation teams, the composition and organization
of RRTs varies substantially across facilities. Box 5-1 describes some of the different types of response teams in the hospital, distinguishing between resuscitation teams and RRTs.
In-Hospital Cardiac Arrest Response Teams
Resuscitation Team (i.e., Emergency Code Team). Although The Joint Commission requires that staff be available to respond to the need for resuscitation, and be trained in the use of resuscitation equipment and techniques, it does not mandate the composition of the staff. Therefore code teams can include physicians, nurses, security personnel, respiratory therapists, pharmacists, and even social workers or clergy. Code teams usually have designated leaders, and members are trained in providing life support treatment. They must be available at all times to respond to codes (designated “blue” in some hospitals).
Rapid Response Teams (RRTs), also known as Medical Emergency Teams (METs) were established to respond to identified clinical deterioration in patients prior to the occurrence of a cardiac arrest (Morrison et al., 2013). They are separate and distinct from traditional resuscitation teams which typically respond upon IHCA recognition (AHRQ, 2014a; Thomas et al., 2007b). Team composition varies but includes combinations of physicians, advanced cardiac life support (ACLS)-trained nurses, respiratory therapists, and pharmacists. While resuscitation teams almost always include a physician, RRT teams may not include physicians and are frequently led by nurses. RRT teams are designed to avoid failure to rescue, which is typically associated with failures in planning, including assessments and treatment delivery; breakdown of communication between patients, family, and staff or among staff members; and failure to recognize early signs of deterioration. The evidence on the effectiveness of RRTs is mixed, although studies have found improved IHCA survival outside the ICU when RRT response is activated (Chan et al., 2010).
Pediatric RRT-METs are similar to adult teams, but consist of varying personnel (such as physicians, nurses, and respiratory therapists) with the special expertise of caring for acutely ill children (Sharek et al., 2007). They are designed to respond to the signs of deterioration prior to a cardiac arrest and have demonstrated limited success in reducing cardiac arrests outside the pediatric ICU or reducing mortality overall.
NOTE: The terms RRT and MET are used interchangeably in the published literature and across care facilities.
High-Functioning Resuscitation Teams in Hospitals
Hospital resuscitation teams are required to possess specific clinical skills and therefore, often include a respiratory therapist, critical care nurse, and a physician specializing in emergency or acute hospital care (Baxter et al., 2008). Training designed specifically for resuscitation teams is also common, and the content of these courses is mostly consistent across programs. Most training includes modules on CPR technique and ACLS medication protocols, identification and prevention, and the development of nontechnical skills such as communication, teamwork, leadership, and situational awareness (Baxter et al., 2008; Gordon et al., 2012; Jankouskas et al., 2011). One literature review identified common behaviors and attributes of existing resuscitation teams, such as mutual trust and respect among team members, adaptive leadership, open communication, and a shared conception among team members of the purpose of the team and their individual roles (Manser, 2009).
Guidelines from multiple professional organizations and scientific organizations highlight key resuscitation team components (see Table 5-2). The AHA and the International Liaison Committee on Resuscitation (ILCOR) recommend that all hospital resuscitation team programs must include components that detect cardiac arrests, trigger response mechanisms, monitor resuscitation team performance, and train resuscitation team members (Bhanji et al., 2010). These organizations have also recognized the importance of nontechnical training targeted to the development of team and leadership skills. ILCOR has developed a data reporting form that measures team performance along multiple, clinically relevant dimensions, including team composition, structure, coverage, activation, and interventions; the patient’s physiological data prior to, and during, the resuscitation; and outcomes for both the patient and the hospital (Peberdy et al., 2007).
Recent AHA and UK Resuscitation Council consensus statements have recognized the importance of developing systems-based approaches to IHCA response (Morrison et al., 2013; Resuscitation Council, 2013). The European consensus statement recommends direct oversight by a resuscitation officer at the facility level and suggests that at least two physicians with advanced life support training are included on the teams, but otherwise, largely avoids commenting on the composition of the team. Recently, there has been an increased emphasis on the importance of nontechnical skills (e.g., leadership and communication) within the
TABLE 5-2 Key Abilities of Resuscitation Teams
|Type of Skills||Key Abilities of Resuscitation Teams|
resuscitation teams because of data demonstrating an association with improved outcomes, with these skills (Bhanji et al., 2010; Hunziker et al., 2011).
There is considerable variability in the implementation of these resuscitation teams. One study used data from a national survey of 439 hospitals from across the United States and found that nearly one-quarter of facilities failed to report having a pre-nontechnical designated, dedicated resuscitation team as part of their approach to IHCA response, while one-third did not have standardized defibrillators available throughout their facility (Edelson et al., 2014). Among those facilities
that did have dedicated resuscitation teams, the composition, leadership roles, and structure of the teams also varied.
Overcoming these challenges has been the recent focus of small quality improvement efforts, many of which emphasize nontechnical skills in addition to core technical skills. In addition to overall leadership, the literature emphasizes the importance of identifying a team leader who is appropriately qualified and trained for this role (Hunziker et al., 2011). Ideally, facilities that have medical training programs should require that physicians in training be backed up by at least one attending physician whose specialty is hospital medicine, intensive care medicine, cardiovascular medicine, or emergency medicine. Teamwork also may be ensured prior to an emergency with a process that clearly delineates team member roles for health care providers who respond to a cardiac arrest. This could include the use of visual tools (e.g., lanyards and badges) and demarcation of positions around a patient (e.g., individual to the left of a patient would be responsible for delivering chest compressions). However, these approaches should never delay the necessary care for a patient experiencing a cardiac arrest. If a team member’s arrival is delayed, then other team members must be prepared to fill in and take on other roles in responding to the IHCA.
Together, these sources describe a set of program components and team member actions and behaviors that clinicians and researchers alike consider to be associated with, or essential to, improved team performance and patient outcomes. Table 5-2 lists some of these attributes.
RRT or MET Instituting Earlier Recognition and Response to IHCA
Multiple studies suggest that health care providers often fail to detect changes or abnormalities in patient vital signs hours before an IHCA occurs. Family members or health care providers typically recognize IHCA when the patient has become acutely unresponsive or when an abnormal rhythm is noted on telemetry monitoring. As noted throughout the report, immediate action following collapse is believed to improve outcomes.
The idea of instituting earlier care builds on prior studies examining the use of RRTs (also referred to as METs in some facilities). Many hospitals have implemented RRTs and METs, although evidence demonstrating their effectiveness in improving overall survival rates remains controversial (Chan et al., 2010). In a report from Denmark, failure of RRTs to properly communicate and activate transitions of care for appropriate patients, was identified as a significant limitation. Similarly,
several studies of pediatric RRT-MET teams, which are also triggered by the signs of deterioration prior to a cardiac arrest, have reported at best, modest success in reducing cardiac arrests outside the pediatric intensive care unit or reducing mortality overall (Bonafide et al., 2012a, 2014; Brilli et al., 2007; Hunt et al., 2008; Sharek et al., 2007; Tibballs and Kinney, 2009; Winberg et al., 2008). A major obstacle to demonstrating effectiveness of RRTs and METs is the low frequency of events overall, as well as a lack of a consensus on event definition.
Cardiac arrest investigators have also explored different methods for detecting deterioration prior to an IHCA using physiological data. Early recognition would allow for an escalation of care (e.g., transfer to ICU for patients on the general medical floor) prior to the event. Currently, multiple risk stratification tools for evaluating patients have been proposed, including the Modified Early Warning Score for adult and pediatric patients. These tools allow for the early assessment, prediction of IHCA, and possible ICU transfer based on vital signs (Ludikhuize et al., 2014). The Pediatric Early Warning Score (PEWS), first proposed in 2006, can provide more proximate outcome measures to identify deterioration in children in EDs and inpatient units and who were likely to need resuscitation (Duncan et al., 2006; Parshuram et al., 2011). The scores comprise multiple variables including vital signs, clinical assessment, and oxygen therapy, and they have been validated in multicenter studies with high sensitivity and specificity. Implementation of the score has been associated with reduction in clinical deterioration rates and emergency calls to the in-house pediatricians. Randhawa and colleagues (2011) found that cardiac arrest frequency was reduced by 23 percent after the implementation of a bedside PEWS tool. Studies have been performed recently in order to improve current systems by using additional information that is available through the electronic health record, such as clinical data and laboratory results (Churpek et al., 2014). Although such tools hold noteworthy promise, they are still in the early stages of development and implementation and have limitations regarding the generalizability for large-scale adoptions or specificity for IHCA.
Clinical deterioration risk scores that are based on non-vital sign criteria (e.g., age, presence of specific underlying disease, enteral tube, and hemoglobin levels) could also improve outcomes (Bonafide et al., 2012b, 2014; Winberg et al., 2008). Using clinical deterioration scores, combined with METs, the cost-benefit ratio of METs was positive, especially in hospitals with bundled reimbursement. Confirmation of these
findings in a broader base of hospitals is needed to develop programs and responses to decrease cardiac arrest among hospitalized patients.
Variability in the use of specific strategies and care processes and their links to patient outcomes has not been adequately studied to date. Box 5-2 presents the current gaps in evidence and points to future research needs.
Post–cardiac arrest syndrome is a complex clinical condition with four primary pathophysiological consequences, which can include any combination of myocardial dysfunction, neurologic injury, systemic
Priority Areas for Research in In-Hospital Care
- Transition of care: Research needed to understand how to best optimize care transitions for cardiac arrest patients at admission, at discharge, and within hospitals, including key elements of the cardiac arrest that should be passed on to subsequent providers
- Hospital resuscitation team structure and skill composition: More research is needed to standardize team composition and technical and nontechnical skillsets and to evaluate the effectiveness of resuscitation teams in improving patient outcomes
- Early detection of IHCA: Research is needed to improve early warning scores and telemetry to improve use of METs teams
- Standardize quality metrics for IHCA: Define and select appropriate IHCA process and performance metrics
- Long-term outcomes of IHCA: Quality-of-life assessments, and patient utilization of health care resources after hospital discharge, should be evaluated
- Advanced directives, DNAR, and care termination: There is a need to understand how to best standardize and implement care decisions around advanced directives, DNAR and care termination, including education of patients and families
- Disparities in IHCA: Better data on race and ethnicity and socioeconomic factors are needed to identify high-risk populations and evaluate disparities in care and access to care
injury because of oxygen loss (ischemia) and subsequent restoration of blood flow (reperfusion), and other precipitating factors (e.g., secondary cardiovascular or pulmonary diseases and pneumonia) (Morrison et al., 2013; Neumar et al., 2008). Post-arrest care therefore focuses on rapidly assessing cardiac arrest patients who have achieved ROSC, optimizing cardiopulmonary function, stabilizing blood flow, minimizing neurologic injury, controlling body temperature, establishing mechanical ventilation to minimize lung injury, and conducting other related prognostication (Peberdy et al., 2010).
Neurologic injury is a concerning and destructive consequence of cardiac arrest affecting the likelihood of short- and long-term survival, disability, and quality of life. One study reported that neurologic injury was the primary cause of death among 68 percent and 23 percent of OHCA and IHCA patients, respectively (Laver et al., 2004; Peberdy et al., 2010). Thus, many interventions related to enhancing post-arrest care are targeted at improving neurologic outcomes. Post–cardiac arrest cardiovascular injury also affects patient outcomes; approximately 30 percent of all deaths among cardiac arrest patients who were initially resuscitated were caused by reduced blood flow. However, multiple studies based on swine models suggest that permanent damage to the left ventricle can be avoided in the immediate period following resuscitation (Kern et al., 1997a,b; Neumar et al., 2008). Thus, it is possible for an individual patient to make a complete cardiac recovery with appropriate hemodynamic support (Laurent et al., 2002; Nolan et al., 2008). Successful management of post–cardiac arrest syndrome requires the availability of well-equipped medical facilities and ICUs, resources, and treatments that can contribute to the rapid stabilization and minimization of tissue damage and organ injuries.
Evaluation and treatment of the patient’s immediate clinical condition and prognosis occur in parallel and involve a multidisciplinary team (including emergency and critical care providers, neurologists, cardiologists, nurses, laboratory technicians, and other specialists) that often provides simultaneous expertise and care. Optimal post-arrest treatment begins when the patient achieves ROSC and can begin prior to an OHCA patient’s arrival in the hospital ED. The time interval between the onset of the cardiac arrest and ROSC is a critical determinant of the severity of the post–cardiac arrest syndrome. With the exception of cardiac arrests
that occur in an ICU, IHCA patients generally have intermediate periods of time between collapse and resuscitation. Collapse-to-treatment times for OHCA patients can be longer and more variable depending on a host of factors (e.g., whether the arrest was witnessed, availability of bystander CPR and EMS response times), thus differentially exposing patients to the conditions that result in post–cardiac arrest syndrome. Patients who experience a brief collapse-to-treatment interval (e.g., an intentionally or inadvertently induced cardiac arrest occurring in a cardiac catheterization or electrophysiology laboratory during diagnostic testing) often do not develop post–cardiac arrest syndrome. Because the cardiovascular system is far more resilient than the neurologic system, patients who achieve ROSC in 5 to 10 minutes may have their hemodynamic status restored, but are more likely to sustain some degree of brain injury. With yet longer delays in ROSC, the likelihood and severity of post–cardiac arrest syndrome increases, and neurologic, hemodynamic and metabolic support all become necessary and more critical for possible recovery.
Studies of optimal post-arrest care are evolving, but there are some important gaps in the current evidence base because of several factors. There is a paucity of published literature on post-arrest care by multidisciplinary investigators, limited basic science research, and relatively few randomized clinical trials evaluating the effectiveness of known postarrest care treatments. Often existing studies are less meaningful because of the small size of the population studied. There are additional gaps in evidence regarding long-term outcomes following post-arrest care. As a result of these limitations, the scientific evidence to support the therapies and care strategies offered for patients with post–cardiac arrest syndrome is less robust than that for the patients with other cardiovascular conditions such as acute myocardial infarction, often the precursor to cardiac arrest. However, a number of promising post-resuscitation treatments and therapies emerged over the past several decades and have demonstrated effectiveness in treating individual components of post–cardiac arrest syndrome in limited settings (Nolan et al., 2008).
Historically, the approach for treating post–cardiac arrest syndrome has been a one-size-fits-all strategy of care, with patients ideally receiving a range of available guideline-recommended treatments for a given clinical presentation whenever possible (e.g., therapeutic hypothermia and percutaneous coronary intervention), with the goal of mitigating neurologic injury. However, recent data have urged providers to customize post-arrest treatment protocol based on the neurologic and functional status of individual patients, which can range from the awake and stabi-
lized to comatose patients with varying degrees of secondary clinical complications (Nolan et al., 2008; Rittenberger et al., 2011). This approach not only is beneficial to the individual patient, but also can reduce the cost of care. The goal of these therapies, described in Box 5-3, is to promote a full recovery and restore and preserve neurologic function.
Post-arrest care algorithms, supported by AHA guidelines, have proposed multidisciplinary early goal-directed therapy (EGDT) as part of an essential bundle of care to improve survival following cardiac arrest (Peberdy et al., 2010). The post-arrest patient may develop severe systemic inflammatory responses and septic shock syndromes that affect
Evidence on Common Treatments for Post-Arrest Syndrome
Targeted Temperature Management (TTM). TTM, also known as therapeutic hypothermia, is an early post-arrest intervention designed to reduce the body temperature in resuscitated, comatose cardiac arrest patients. The rationale is to slow pathophysiological events and biochemical pathways that cause cellular death and complete systemic injury. The original goal was to reduce temperature to 33oC, but recent data suggest that 36oC is sufficient and that the benefit might relate more to prevention of fever than to hypothermia itself. Although TTM has been endorsed by the AHA and ILCOR, the U.S. Food and Drug Administration concluded that existing data do not demonstrate unequivocal therapeutic benefit. The literature is inconclusive about optimal temperature and benefits for patients who present non-shockable initial rhythm. Further research into optimal target temperature and candidate selection is needed.
Special Considerations in Children. The use of therapeutic hypothermia in pediatric populations following cardiac arrest remains an unproven therapy. Studies in infants with birth asphyxia have shown better long-term neurologic outcomes following use of hypothermia (Eicher et al., 2005; Gluckman et al., 2005; Shankaran et al., 2005), but hypothermia in children with traumatic brain injuries appears to worsen outcomes (Hutchison et al., 2008). A multicenter trial of therapeutic hypothermia in children (Therapeutic Hypothermia After Pediatric Cardiac Arrest [THAPCA]) is ongoing.
Cardiovascular and Hemodynamic Management. Post-arrest care to mitigate ischemia or myocardial injury should differentiate between acute myocardial infarction (which can precede and trigger cardiac arrest) and pre-existing chronic myocardial dysfunction that creates
long-term risk for cardiac arrest. Hemodynamic management is needed to improve the impaired pumping function of the heart after ROSC. This requires various medical and device therapies intended to improve blood pressure and blood flow. The optimal blood pressure target in post-arrest patients is unknown, because the relationship between optimal arterial pressure and tissue perfusion, oxygenation, or acidosis requires extensive study.
Cardiac Catheterization and Percutaneous Coronary Intervention (PCI). PCI is a procedure that uses a catheter to place a stent across a blocked artery to hold the artery open. It is most commonly used as a treatment for myocardial ischemia. The goal of cardiac catheterization and PCI is to relieve any potential coronary artery obstruction that contributed to the cardiac arrest, in order to improve immediate electrical and mechanical functions and mitigate the risk of re-arrest. In several observational studies, PCI has emerged as potentially one of the most important hospital-based interventions associated with favorable neurologic outcome. However, there is concern that early PCI may be underutilized in hospitals (Knafelj et al., 2007). This is particularly true in states requiring public reporting of outcomes (Joynt et al., 2012). It is recommended in professional guidelines, but the added benefits conferred by PCI and the associated risks specific to post–cardiac arrest patients with underlying comorbidities are difficult to assess and have not been evaluated in randomized clinical trials. In order to better evaluate the effectiveness of PCI as an intervention for cardiac arrest, encourage its use in these critical patients, and not distort the statistics of facilities that offer these high-risk services, mortality and morbidity laboratory statistics for the post–cardiac arrest patients should be reported separately from the general cardiac catheterization outcomes data. Some studies have found that providers are often reluctant to provide PCI for eligible patients because of concerns regarding public reporting of negative outcomes (Peberdy et al., 2013).
PCI and TTM Combination Therapy. Although the combined effect of PCI and TTM on neurologic outcomes has not been extensively studied, select medical centers report a 60 percent chance of survival to discharge, with 93 percent of patients having good neurologic function if they received a combination of these treatments (Kern, 2012). This combination has not been widely implemented across health care systems because of the limited scientific evidence, as well as the likelihood of poor outcomes for high-risk cardiac arrest patients.
Vasopressors for Hemodynamic Support. Vasopressor therapies, most commonly epinephrine, are used to facilitate the elevation of low blood pressure and have been the accepted standard of care for cardiac arrest patients without immediate ROSC and for post–cardiac arrest patients with compromised hemodynamics. Recent studies of
epinephrine use in adults with OHCA demonstrated improvement in ROSC and survival to hospital admission, but not in survival to discharge or neurologic outcomes. One study found improved outcomes with vasopressin-steroids-epinephrine combination (Mentzelopoulos et al., 2013). One IHCA study found that longer dosing intervals in both shockable and nonshockable rhythms was associated with greater survival rates following cardiac arrest (Warren et al., 2014). Both animal and human studies suggest that vasopressors can diminish cardiac function by impairing myocardial metabolism. However, the use of epinephrine in patients who remain significantly hypotensive after ROSC may have great benefits, but more data are needed. Vasodilator therapies, which are used to reduce blood pressure, have shown some benefit in animal studies, but evidence in humans is lacking.
Special Considerations in Children. Myocardial dysfunction and vascular instability are common among children experiencing cardiac arrest (Checchia et al., 2003), and hypotension may be an independent risk factor for mortality after cardiac arrest (Topjian, 2014a). However, there are very limited data to guide physicians on optimal strategies for supporting pediatric cardiovascular systems following an arrest. Several drugs have been shown to improve blood pressure in low-cardiac output states following open-heart surgery (Hoffman et al., 2003), but it is unclear if any is superior or equivalent. Additionally, a randomized pediatric study demonstrated no survival benefit for high-dose epinephrine and potential increases in mortality (Perondi et al., 2004).
Emerging Hemodynamic Support Therapies. Extracorporeal Membrane Oxygenation (ECMO) and Femoral-Femoral cardiopulmonary bypass are two novel, but highly invasive, therapies that are currently used to support systemic circulation and allow the heart to recover and stabilize following a cardiac arrest (Chen et al., 2003). Although they have the potential to provide lifesaving benefit for some patients, because of known risk factors and a lack of robust clinical data to support their efficacy, these therapies have not yet been recommended for broad use in variable hospital settings. Additional research is needed to identify optimal strategies for providing hemodynamic support for post-arrest patients.
Special Considerations in Children. Data in children support use of hemodynamic support for those with cardiac disease when there is an appropriate ECMO team. But therapy is being widely used without definite documentation of benefit.
Oxygenation and Ventilation. Oxygenation and ventilation are designed to increase the amount of oxygen supplied to the body’s vital organs
and to avoid high fevers. Avoiding hyperventilation is important following a cardiac arrest, because reductions in the partial pressure of carbon dioxide will lead to reductions in cerebral blood flow, vasoconstriction, and potential worsening of any cerebral hypoxic-ischemic injury. Although most patients are intubated during the resuscitative effort, the immediate post-arrest care must also include appropriate monitoring of the airway, oxygenation, and ventilation. This requires the ability to do rapid diagnostic testing such as chest x-rays, blood sample testing, and point-of-care testing, and it may also require computed tomography (CT) scanning.
Special Considerations in Children. Increasing concerns exist about the deleterious effect of excessive oxygen in newborn infants during resuscitation (Davis et al., 2004; Kilgannon et al., 2011; Rabi et al., 2007). Inappropriate ventilation, especially hyperventilation, may reduce systemic and cerebral blood flow, leading to poor outcomes (Donoghue et al., 2006). Despite limited data, current guidelines recommend that 100 percent oxygen be used for resuscitation in children and that supplemental oxygen concentration be targeted to maintain an arterial oxygen saturation of greater than or equal to 94 percent, thus avoiding hypoventilation. However, these goals are infrequently achieved (Bennett, 2013).
Metabolic Management: Glucose Control. Cardiac arrest patients commonly experience hyperglycemia and require close monitoring of glucose levels (Nolan et al., 2008). Some studies have also noted a substantial increase in the incidence of hyperglycemia following hypothermia therapy (Cheung et al., 2006). By default, and based on inference from retrospective analyses, it is suggested that glucose levels post-arrest be maintained in the range of 150 mg/dl or less. Glucose control has been an area of considerable controversy, however, because even though it has been shown to be beneficial in select critical care situations (e.g., sepsis), it has not been uniformly applied to cardiac arrest patients. Moreover, it has not been tested in clinical trials.
Special Considerations in Children. Hypoglycemia and hyperglycemia are both frequently observed following cardiac arrest in children, and both are associated with increased mortality. However, a causal relationship has not been established (Beardsall et al., 2008; Vlasselaers et al., 2009). The few studies of targeted glucose management in critically ill infants or children report frequent hypoglycemia, but they suffer methodological problems and lack of continuous glucose monitoring.
ultimate disability-free survival to hospital discharge. A number of studies have demonstrated a dramatic reduction in mortality in cases of severe sepsis or shock using EGDT, an intervention aimed at maintaining optimal central venous pressure and oxygen saturation (Rivers et al., 2001). Because of the pathophysiological similarities between sepsis and post–cardiac arrest syndrome, EGDT has been adapted for post-arrest care to provide hemodynamic and oxygenation monitoring, in combination with intravenous medication (Nichol et al., 2010). However, based on two recent studies that found no survival benefit related to EGDT in septic shock states, further evaluation of EGDT for the post–cardiac arrest state is needed (Peake et al., 2014; Yealy et al., 2014).
The data to support specific goal-directed therapies for pediatric patients are generally of low quality. Many therapies from adult care, animal models, or different patient populations who are critically ill with conditions other than cardiac arrest have been extrapolated to pediatric populations (Kleinman et al., 2010b). Examples of goal-directed pediatric therapies derived from other sources include titration of inspired oxygen concentration and target saturation, glucose management, vasoactive drugs, and hypothermia (Checchia et al., 2003; Eicher et al., 2005; Finfer et al., 2007; Gandhi et al., 2007; Gluckman et al., 2005; Kern et al., 1997b; Oksanen et al., 2007; Richards et al., 2007; Vasquez et al., 2004; Wiener et al., 2008).
Personalized Medical Care for Cardiac Arrest
Current cardiac arrest care protocols are largely based on formulaic algorithms and guidelines that do not account for individual needs and variations. Differences in etiology, patient characteristics, and rescuer competency can all contribute to variations in AHA-recommended treatment protocols. Personalized medicine, which employs genetic sequencing and other advanced techniques to customize medical care to the needs of the individual patient, represents the final stage in this ongoing progression from generalized to specific health care. With the growth in the catalogue of genetic mutations correlated with specific disease processes, and the equally rapid drop in the cost of gene sequencing, tests to assess a patient’s risk for conditions that can precipitate a cardiac arrest are proliferating (Rubinstein et al., 2013). Long QT syndrome, brugada syndrome, catecholaminergic polymorphic ventricular tachycardia, and hypertrophic cardiomyopathy are all recognized cardiac arrest risk factors that are also associated with one or more genetic mutations
(Ackerman et al., 2011). Tests for these mutations exist and are recommended by the Heart Rhythm Society in some instances. Most importantly, genome-wide association studies have identified at least 36 genetic variants associated with coronary artery disease, which is present in more than 80 percent of patients who die from cardiac arrest in the United States (Roberts and Stewart, 2012). As other genetic risk factors for cardiac arrest are identified, clinicians will increasingly be able to proactively prescribe antiarrhythmic drugs, place implantable cardioverter-defibrillators, and correct structural cardiac abnormalities through surgical intervention.
Customized medicine in the context of cardiac arrest can alter treatment protocols for individual patients based on results from physiological measurements. In contrast to generalized consensus-based guidelines, one approach to individualized resuscitation employs physiologically guided CPR that uses sensor measurements, such as coronary perfusion pressure, blood pressure parameters, or carbon dioxide excretion, to guide a unique resuscitation protocol for each patient (Sutton et al., 2013). As patient monitoring techniques become more precise, CPR protocols can be adapted in real time to the changing physiological status of the arresting patient. In a recent study assessing the efficacy of a dynamic, personalized CPR protocol in animal models, chest compression depth and vasopressor dosage were respectively titrated to systolic blood pressure and coronary perfusion pressure, in order to reach target blood pressure levels. This “patient-centric” CPR protocol was correlated with a significant 24-hour survival benefit over CPR performed according to the AHA guidelines (Sutton et al., 2014b). Another study found that the same experimental protocol improved 45-minute survival over two protocols that coupled the AHA-recommended pharmacological interventions with audiovisual feedback to meet predetermined targets for chest compression depth (Sutton et al., 2014b). These studies support recommendations for physiological monitoring of CPR during resuscitation, in cases where the monitoring systems are already in place (Meaney et al., 2013). As a majority of IHCAs now occur in ICUs, where such monitoring is often already in place, the transition to resuscitation protocols that monitor and adapt to patient vital signs will potentially benefit a large proportion of cardiac arrest patients (Berg et al., 2013; Girotra et al., 2012; Sutton et al., 2014a).
In additional to advances in treatment, new and more powerful diagnostic and prognostic tools allow clinicians to better tailor preventive and emergent care to the needs of the individual patient (Chan et al., 2012).
Highly sensitive imaging techniques such as cardiac magnetic resonance imaging (MRI) and cardiac CT tests can detect specific structural disorders that are known risk factors for cardiac arrest, allowing clinicians to employ preventative care efforts targeted to specific conditions (The Joint Commission, 2011). In post-arrest care, MRI-based imaging techniques provide sensitive and accurate methods of detecting brain lesions and other neurologic features that strongly correlate with poor neurologic outcomes (Choi et al., 2010; Galanaud and Puybasset, 2010; Wijman et al., 2009; Wu et al., 2009), while simple, bedside risk assessments allow for accurate predictions of long-term neurologic status (Chan et al., 2012).
As the list of known risk factors for cardiac arrest grows in tandem with the power of diagnostic tools, it will become easier to preventively treat patients for cardiac arrest, by addressing the specific conditions from which it precipitates. Thus, by fueling continuous refinements in the specificity of treatment protocols, diagnostic and prognostic tools, and preventive risk assessments, the drive to personalize and customize medicine may lead to improvements in cardiac arrest incidence and outcome.
Disparities in Post-Arrest Care
Currently, there is a paucity of literature that specifically examines questions about discrepancies in the application of post-arrest care treatments, leading to differences by gender, race, or ethnicity. The literature suggests that minority populations have not been studied as rigorously for potentially lifesaving therapies such as targeted temperature management (Hypothermia After Cardiac Arrest Study Group). Women were likely underrepresented in the TTM trials focused on patients with an initially shockable rhythm, because women are less likely to have VF as a presenting rhythm (Akahane et al., 2011). Even in more recent research, which included all initial rhythms, women accounted for less than 20 percent of subjects included in the trial (Bro-Jeppesen et al., 2014). Additionally, these studies did not report the racial or ethnic identities of individuals within. However, analysis of CARES data found that therapeutic hypothermia was not differentially used by race or gender among OHCA patients (Mader et al., 2014). Whether there are differences by race and ethnicity in the implementation of TTM in other large database studies, such as the GWTG-R or Resuscitation Outcomes Consortium, remains to be studied.
Disparities in the implementation of cardiac procedures in post-arrest care have been documented. After controlling for potential confounding factors, one study found that among patients admitted to hospitals in California with VF or ventricular tachycardia (VT) arrest, African American patients were significantly less likely than white patients to undergo electrophysiologic studies or to receive an implantable cardioverter-defibrillator (Alexander et al., 2002). Another study determined that younger African Americans had substantially lower odds of receiving at least one potentially lifesaving procedure (e.g., cardiac catheterization or cardioverter-defibrillator) when compared to white patients (Groeneveld et al., 2003). The same study noted a considerable differential in long-term survival, with the life expectancy for white patients (4.1 years) longer than that for African American patients (1.9 years) (Groeneveld et al., 2003). The use of implantable cardioverter-defibrillator has become more widely available, and the use of this technology has increased faster for African American patients than for other populations. However, the disparity in use still exists (Stanley et al., 2007). Similar differences in post-arrest care have been reported for Hispanic patients, with multiple studies demonstrating that Hispanics patients may have poor access to appropriate care with lower odds of receiving implantable defibrillators as well as electrophysiologic studies (Alexander et al., 2002; Groenveld et al., 2003). Although there is limited research devoted to cardiac arrest care for racial and ethnic minority patients, available evidence indicates disparities in both access to care and outcomes. Additional research is required to evaluate the burden of disease among minority populations and to determine the efficacy of appropriate post-arrest treatments for a broader population. Box 5-4 summarizes the key conclusions relevant to disparities in post-arrest treatments.
Disparities in Cardiac Arrest Treatments
- Racial and ethnic minorities more frequently present nonshockable initial rhythms.
- Racial and ethnic minorities are more likely to have delayed defibrillation.
- Racial and ethnic minorities are less likely to receive lifesaving cardiac procedures such as electrophysiologic studies, implantable defibrillators, and cardiac catheterization post cardiac arrest.
Assessment and Prognosis
Cardiac arrest survival with significant neurologic damage can be as devastating, but more burdensome, than death for survivors, family members, and society because it can influence both short-term prognosis and long-term quality of life. Neurologic and functional status needs to be evaluated and addressed promptly. Neurologic assessments may include multidisciplinary care coordination to appropriately and accurately evaluate and treat post–cardiac arrest survivors who do not immediately regain consciousness, in order to maximize the likelihood of complete recovery. The assessment may begin with a neurologic exam and urgent neurologic consultation in the ED, and continues as needed, until discharge. The most robust prognostic estimates are usually obtained from a combination of neurologic examinations and neuro-electrophysiological tests (Booth et al., 2004, Kamps et al., 2013). However, serial neurologic observations beyond the first 24 to 72 hours, and in some cases, more than 96 hours following an arrest, are often required to provide reliable prognostic information (Neumar et al., 2008; Peberdy et al., 2010). During serial observations, trained health care providers (including nurses) systematically record results from clinical neurologic exams in ICUs that use standardized scoring schemes for consciousness (Riker and Fugate, 2014). As shown in Box 5-5, multiple tools available for neurologic assessment and scoring have demonstrated prognostic value. However, more research is needed to refine neurologic prognostic scores and extend observations beyond the acute hospitalization phase of post–cardiac arrest care, in order to more accurately evaluate longer-term cognitive outcomes.
Similar to adults, no single test can clearly provide accurate prognostication in children. Information to guide clinicians on neuroprognostication in the pediatric population is even more limited than in adults, although assessment and testing to assess level of brain function are similar for both populations. Repeated examinations, electrophysiological assessment, and imaging all contribute to determining the extent of brain injury after a cardiac arrest. To date, there are no composite scores similar to CASPRI or GO-FAR (see Box 5-1) for children. The most commonly used score is the Pediatric Cerebral Performance Score, which also has significant shortcomings in differentiating mild from moderate disability and was designed to assess neurologic function after pediatric intensive care—not in-hospital cardiac arrest (Fiser et al., 2000).
Available Tools for Neurologic Assessment Following Cardiac Arrest
Neurologic consultative expertise should be used to assess the patient within the first 24 hours of a cardiac arrest to provide a baseline comprehensive neurologic examination, interval serial monitoring, team-based care regarding therapeutic hypothermia, help with decisions about appropriate neurologic testing, advice on treatment of any seizures, and input on comprehensive prognostication (Booth et al., 2004; Peberdy et al., 2010; Puttgen et al., 2009).
Standard neurologic examination in an unresponsive post–cardiac arrest patient will help document cortical and brainstem functions (e.g., response to verbal commands or physical stimulation, pupillary light and corneal reflex, spontaneous eye movements, gag, cough, and spontaneous breaths). The presence of sedation, neuromuscular blockade, or analgesia, which are sometimes used in post-arrest care, can impair the ability to monitor neurologic examinations.
Neurologic assessment scores have been developed in order to provide insights into short and long-term neurologic outcomes. There are multiple scoring systems, including the following:
- The Cerebral Performance Category (CPCa) has traditionally been used to assess outcomes following cardiac arrest, but has limited ability to differentiate between mild and moderate neurologic injury (Rittenberger et al., 2011).
- The modified Rankin Scale (mRSa) is a clinician-reported measure of global disability, applied in the evaluation of neurologic outcomes following cardiac arrest, stroke, and other brain injuries (Banks and Marotta, 2007; Rittenberger et al., 2011).
- The Glasgow Coma Scores (GCS) assessment can be provided by trained nursing staff and is the most basic form of neurologic monitoring available. It has demonstrated predictive value and is often included as part of serial neurologic examinations.
- The brain arrest neurologic outcome scale is a 16-point scale composed of three variables: duration of arrest, reversed GCS, and Hounsfield unit density ratio of the caudate nucleus over the posterior limb of the internal capsule on noncontrast CT scan of the head (Torbey et al., 2004).
- The seven-point 5-R score consists of the following variables: VF or VT as the first presenting cardiac rhythm, arrest-to-first CPR attempt time interval of less than 5 minutes, arrest-to-ROSC time interval of less than 30 minutes, recovery of pupillary light reflex in the ED, absence of rearrest before leaving the ED (Okada et al., 2012).
- The Cardiac Arrest Survival Post-Resuscitation In-hospital (CASPRI) score was developed specifically for IHCA and includes 11 predictor variables: age, initial cardiac arrest rhythm, duration of resuscitation, mechanical ventilation, defibrillation time, baseline neurologic status, sepsis, malignancy, renal insufficiency, hepatic insufficiency, and hypotension (Chan et al., 2012; Girotra et al., 2014). Although a relatively simple score, it is perceived as being unwieldy and has not been validated in OHCA patients. It can, however, provide estimates of the probability of favorable neurologic survival after IHCA.
- The Good Outcome Following Attempted Resuscitation (GO-FAR) score is used to predict neurologically intact survival after in-hospital cardiopulmonary resuscitation has also been developed. This score is based on 13 pre-arrest variables and can identify patients likely to survive IHCA with good neurologic prognosis or with minimal deficits (Ebell et al., 2013).
Brain imaging with CT or MRI is common for comatose patients. MRI is more sensitive than CT for detecting early ischemic injury but may not be advisable if certain magnetically activated implanted devices (e.g., cardiac pacemakers, insulin pumps, neurostimulators, or cochlear implants) or other metal implants are present, because these devices could impact the usefulness of the data. Brain imaging that shows multilobar, or diffuse, cortical involvement, termed as extensive cortical lesion pattern, was determined to be a reasonable predictor of poor prognosis and adds to the sensitivity of the GCS motor score (Topcuoglu et al., 2009). Additionally, noncontrast brain CT has also been used to predict prognosis.
Various neurophysiological monitoring tests can help assess postarrest patients for seizures and providing prognostic assessments.
- Continuous electroencephalogram (EEG) monitoring is helpful among unresponsive post-arrest patients to assess for status epilepticus and monitor for nonconvulsive status epilepticus. The latter can easily evade detection if no discernable motor movements exist. One study found non-convulsive status epilepticus in 27 percent of post–cardiac arrest patients who were initially unresponsive after hypothermia (Rundgren et al., 2010).
- Continuous amplitude-integrated EEG (aEEG) can begin in the ICU and continued until the patient regains consciousness or for no longer than 120 hours, if the patient remains in coma (Rundgren et al., 2006). Various EEG patterns have been associated with specific possible outcomes including a likelihood of recovery of consciousness, likelihood of major central nervous system (CNS) injury, good neurologic outcomes, poor neurologic prognosis, and persistent comatose state until death (Cloostermans et al., 2012; Rundgren et al., 2010).
- Cortical N20 somatosensory evoked responses can be a reliable indicator of poor prognosis when found to be absent bilaterally and have been reported to have exceptionally low false-positive rates when measured at 4 days among patients treated or not with TTM (Kamps et al., 2013). Long-latency somatosensory evoked potentials on day 4 have been shown to have some association with cognitive recovery (Prohl et al., 2007).
Other measurements that could be helpful to improve neurologic prognostic estimation include the following:
- Noninvasive regional cerebral oxygen saturation after hospital admission.
- Serum levels of neuron-specific enolase (NSE) and neuron-enriched S100 beta (S100β) measured at 24, 48, or 72 hours after cardiac arrest (Prohl et al., 2007; Stammet et al., 2013).
- Bispectral index continuously monitored during the first 48 hours after cardiac arrest (Stammet et al., 2009, 2013).
aNeurologic assessment scores such as the CPC and mRS are described in greater detail in Chapter 2, Box 2-2.
However, some literature suggests that pupillary response within 12 to 24 hours after arrest, NSE and biomarkers, and EEG findings may provide some guidance for clinicians on possible prognosis and outcomes (Nishisaki et al., 2007; Topjian et al., 2014b). Making predictions in children is further complicated by developmental stage and the recognized plasticity of the immature brain.
Appropriate Timing of Prognosis
Post-arrest patients often require sequential and frequent neurologic evaluations in the ICU. Determination of neurologic prognosis can be
difficult during the period immediately following ROSC and, as a result, some experts have recommended waiting at least 72 hours or longer to allow the brain to recover from ischemia after an arrest before making major decisions (Neumar et al., 2008; Peberdy et al., 2010). Neuroprognostication is often delayed to beyond 96 hours for patients who have been treated with TTM, to allow recovery from the possible side effects of sedation and other drugs. One study among adult comatose patients treated with hypothermia, absence of pupillary light responses or corneal reflexes 72 hours after CPR, and absence of somatosensory evoked potentials during and after hypothermia were determined to be reliable predictors of poor outcomes. Other investigators confirm that the motor response to painful stimuli, corneal reflexes at 72 hours and neuron-specific enolase (NSE) levels after cardiac arrest were not a reliable tool for the early prediction of poor outcome for patients who had received TTM (Kamps et al., 2013). The GCS system can also reliable assess post–cardiac arrest patients who are no longer on sedatives and, as a result, its prognostication is delayed for patients who received TTM (Schefold et al., 2009).
Prognostication and Withdrawal of Care
Patient preferences should be of paramount importance in determining end-of-life care decisions (IOM, 2015). But clinical decisions regarding withdrawal of life support for comatose and unresponsive patients following cardiac arrest are complicated, particularly in the absence of advance directives. These decisions are determined by multiple factors: older age and secondary comorbidities of patients, race, a poor initial neurologic exam, and multiple organ failure (Albaeni et al., 2014). Factors such as the existence of living wills, health care proxies, family perspectives, and religious beliefs of patient and family members also influence such decisions.
Although neurologic prognostic assessments can provide reasonable accuracy regarding the likelihood of meaningful recovery, there are no clear guidelines beyond maintaining a 72 hours or longer observation period, with respect to termination of care for cardiac arrest patients.
Albaeni and colleagues found that post-arrest care is withdrawn early (within 48 hours of hospital admission) for more than half of all cardiac arrest patients (Albaeni et al., 2014). This is particularly alarming because less than 20 percent of these patients had advance directives authorizing early care withdrawal (Albaeni et al., 2014). Another study of
89 OHCA patients found that 10 patients regained consciousness 72 hours after receiving hypothermia, which suggests that early care withdrawal may prematurely terminate care that could result in survival with good neurologic recovery (Gold et al., 2014). The factors that influence such decisions have not been studied and require further research.
Existence and early implementation of a DNAR order portends a fatal outcome and has been associated with less aggressive hospital care (Jackson et al., 2004), including lower rates of potentially critical hospital interventions, procedures, and survival to discharge (Richardson et al., 2013). Although there is a paucity of literature on differences between DNAR orders in women versus men for cardiac arrest, evidence from other medical conditions (such as sepsis and trauma) suggests that early DNAR placement may partially explain the differences in postarrest interventions for women compared to men (Chang and Brass, 2014; Salottolo et al., 2015). However, it does not account for the lower rates of cardiac procedures and the placement of implantable cardioverter-defibrillator in racial and ethnic minority patients, because they are more likely to have lower rates of DNAR order placement compared to white patients (Richardson et al., 2013). Survival is never possible if care is withdrawn prematurely, but the patient’s preferences and values should always be the guiding principles in customized approaches to care.
Variability in Post–Cardiac Arrest Care
The literature reports remarkable variation in survival-to-discharge rates that range from 2 to 41.5 percent among all cardiac arrest patients with varying degrees of post–cardiac arrest syndrome (Go et al., 2014; Nadkarni et al., 2006; Sirbaugh et al., 1999). As discussed in previous chapters, this variation in outcomes is partially due to differences in individual patient characteristics or factors unique to the cardiac arrest event (e.g., witness status and availability of bystander CPR), as well as a reflection of differences in health system characteristics, including structural factors such as differences in available resources and care facilities.
Multiple studies have confirmed that varying levels of access to high-quality health care for minority populations (by gender, race and ethnicity, and socioeconomic factors) lead to diminished health outcomes and notable disparities across many diseases and health conditions (IOM, 2003). In 2003, the Institute of Medicine noted, for example, that minority populations are less likely to undergo recommended invasive procedures or to receive life-saving therapies. Additional research on disparities in
post–cardiac arrest care is needed to inform decisions regarding resource allocation to correct access to care, as well as to determine the efficacy and generalizability of treatments to a wider population.
The variation of reported outcomes in post–cardiac arrest patients suggests that there are unique characteristics of high-performing health care systems across the United States that could, in theory, be adopted and implemented more broadly. As discussed in Chapter 2, there is a high degree of variation across communities in terms of survival. Identifying important best practices in these high-performing health care systems is the necessary first step in improving outcomes nationwide and gaining a better understanding of the underlying factors that contribute to positive outcomes. Some high-performing resuscitation systems have implemented regionalization of care, as a way of improving outcomes of cardiac arrest. The following section describes these centers of excellence in greater detail.
Cardiac Arrest Centers of Excellence
Because care for the post-arrest patient is complex and often requires multidisciplinary team approaches, some regions in the United States (Arizona, Minnesota, New York, Ohio, Texas, and Virginia) have developed regional systems-of-care to improve OHCA resuscitation care and patient outcomes (Nichol et al., 2010). The primary goal for regionalizing care is to improve health outcomes by transporting patients to medical facilities with optimal resources and expertise in cardiac arrest care (Bobrow and Kern, 2009; Lurie et al., 2005). However, these established systems do not have common process or performance standards or have similar funding and reimbursement criteria. Moreover, because of the lack of comprehensive evidence for a standard post-arrest care strategy, there are substantial differences between available treatments and therapies at these cardiac arrest centers of care. For example, in some regions, EMS is authorized to bypass the nearest hospital and transport patients to a facility capable of providing specific post-arrest care treatments such as TTM, while in other regions there are no such protocols in effect (Nichol et al., 2010). In spite of these preliminary efforts, regionalization of resuscitation care has not yet become a national practice in the United States (Nichol et al., 2010; van Diepen et al., 2013).
The body of evidence demonstrating the effectiveness of centers of excellence is expanding. A study of a statewide regionalization of postarrest care, along with the implementation of a bypass protocol that
allowed EMS providers to transport select patients (comatose patients with ROSC) to specialized centers, was associated with improved survival and functional outcomes after OHCA (Spaite et al., 2014). A recent study proposed a tiered-transport concept, in which conscious patients with ROSC are transported to the nearest appropriate ED, according to local EMS jurisdictional policies, irrespective of bypass status. For more complicated post–cardiac arrest cases, the concepts of either bypass or early transfer to a higher level cardiac care facility promptly after initial stabilization in the closer facility are being evaluated as potentially useful strategies (Myerburg, 2014). Table 5-2 illustrates a four-tiered priority-based hospital bypass system, which aligns immediate post–cardiac arrest status of patients to the level of required care.
Much of the evidence for regionalization of care in the cardiac arrest field has been based on extrapolation from other similar fields such as trauma or stroke. The health care field has determined that these patients who experience similarly complex conditions (e.g., stroke) are better managed in centers of excellence, or within systems, that are equipped and designated to provide higher levels of advanced care. These centers of excellence have demonstrated improvement in patient outcomes and reduced costs by implementing guideline-based systemwide protocols within a region for prehospital and hospital care, enhancing communication capabilities and creating trauma registries (MacKenzie et al., 2006; Share et al., 2011; Singh and MacDonald, 2009). Outcomes for stroke have also improved because of greater regionalization of care. The American Stroke Association encouraged EMS integration into stroke systems of care and recommended the transport of stroke patients to a specialized facility whenever feasible (Acker et al., 2007).
In an ideal setting, cardiac arrest centers of excellence that receive post-arrest care patients should have the structural components (e.g., cardiac catheterization laboratory) and therapeutic capabilities (e.g., TTM, PCI, dialysis) to be able to provide a bundle of essential treatments that have demonstrated benefit in treating post-arrest care syndrome and improving patient outcomes. For example, patients commonly develop renal failure following cardiac arrest and may thus require hemodialysis (Neumar et al., 2008). These hospitals must also be able to provide a multidisciplinary team that has the requisite knowledge, skills, and abilities to provide advanced, coordinated post-resuscitation care. This multidisciplinary team will require the intensive care team to manage hemodynamic and metabolic status; the electrophysiology teams to assess and manage the arrhythmias; the neurology teams to manage, assess, and
FIGURE 5-2 Targeted urgency scale to reflect a priority-based hospital bypass system.
NOTES: CCU = critical care unit; ED = emergency department; ICU = intensive care unit; NICU = neonatal intensive care unit; PCI = percutaneous coronary intervention; ROSC = return of spontaneous circulation.
SOURCE: Myerburg, 2014.
limit the CNS complications; and the cardiology team to perform cardiac catheterization and coronary angiography. Because of the limitations in scientific evidence described earlier, these elements have not yet been implemented uniformly across existing cardiac arrest centers of excellence.
The complex nature of post-arrest syndrome and the multiple global body injuries that need to be managed simultaneously complicate studies of this condition. As a result, there is limited scientific evidence available that demonstrates the benefit of the therapies designed for post-arrest stabilization for patients who have varying degrees of post-arrest syn-
drome. In some instances, the justification for the use of the therapies that are described in this section is based on extrapolation of benefits that have been found in other clinical situations with the similar initial pathophysiology (e.g., acute myocardial infarction or sepsis). In other instances, the treatments discussed above have demonstrated effectiveness in limited settings using small cohorts, or are supported by using population health data, rather than in large randomized clinical trials. In spite of these challenges and existing knowledge gaps, health care systems and academic medical centers that practice aggressive, multidisciplinary post-resuscitation care often report excellent patient outcomes, with upward of 80 percent of survivors having favorable neurologic outcomes at discharge (Langhelle et al., 2003; Nolan et al., 2010). Some investigators have put forth the concept of a multilevel approach to care delivery based on whether the patient has neurologic function, is comatose, or has biomarkers of severe neurologic injury. This approach suggests a more aggressive treatment protocol (using PCI or hypothermia) in patients with neurologic function and a more metabolically directed approach to care in those with more severe injury. Thus, not only is this an area ripe for further investigation and evidence building, but also it is an area where emulation of local best practices could result in improved survival and outcomes on a broader scale throughout the nation. Box 5-6 presents the current gaps in evidence and points to future research needs.
STRATEGIES TO IMPROVE THE QUALITY OF CARDIAC ARREST CARE IN HOSPITAL SETTINGS
The essential components of any continuous quality improvement (CQI) program are measurement of care processes and outcomes, benchmarking of performance within and among organizations, and implementation of changes in practice in an effort to improve quality and patient outcomes. These iterative processes also inform, and are informed by, revisions to consensus-based guidelines, as discussed in Chapter 6. Hospitals and EMS systems alike have reported improvements in cardiac arrest survival rates after implementing CQI programs (Ewy and Sanders, 2013; Girotra et al., 2013). Such results provide strong support for ongoing efforts to strengthen data collection, research, and CQI activities related to IHCA. Chapter 6 also discusses CQI on a broader level in terms of ensuring the implementation of effective treatments and care settings across communities.
Priority Areas for Next Steps in Post-Arrest Care Research
- Implementation of documented plans and systems for care transitions
- Appropriate composition of the multidisciplinary teams, including skills related to emergency medicine, intensive care, acute cardiac care, and neurology
- Appropriate timing for prognosis and care withdrawal
- Identification of optimal therapies for hemodynamic support, metabolic support, and neurologic recovery
- Implementation of timely deployment of TTM therapy in ED, cardiac catheterization, critical care, neurologic testing and assessment, and appropriate radiology support
- Use of triage to ensure that advance therapies are directed to patients most likely to benefit and where the risks are justified
- Determination of effectiveness of regionalized centers for providing the most appropriate care based on post-arrest clinical status
- Widespread implementation of best practices and care models and continuous quality improvement programs
- Development and adoption of performance measures for IHCA, OHCA, and post-arrest care
- Identification and implementation methods to rectify health care disparities in post-arrest care
Hospital-based resuscitation systems in the United States are an essential component of the cardiac arrest chain of survival and, in addition to responding to IHCA, provide the bulk of specialized post-arrest care for both OHCA and IHCA patients. Recognizing that there are some clear differences in the immediate treatments required by IHCA and post-arrest care patients and that care is provided by different providers, some common themes applicable to both have emerged. Multiple guidelines on IHCA and post-arrest care treatment protocols exist; however, the scientific evidence base demonstrating the effectiveness of specific protocols and guidelines are limited or, at best, mixed. Relatively few hospitals regularly monitor cardiac arrest outcomes, and there are currently few national standards that require performance benchmarking. This section explores some overarching themes and presents strategies to enhance the quality of care within hospitals.
Establish Separate Diagnosis Codes for IHCA and OHCA
Differences in epidemiology, etiology, and treatment for IHCA and OHCA exist. As compared to patients with OHCA, those experiencing a cardiac arrest in the hospital are fewer in number and more likely to survive. Additionally, IHCAs are less likely to occur as a result of preexisting cardiovascular disease and, notwithstanding substantial variations in the quality of care, IHCA patients are more likely to receive early treatment. Hospital systems can benefit from separate administrative billing codes for OHCA and IHCA, because the cost of inpatient care for IHCA patients and OHCA-patients who receive hospital-based post-arrest care are markedly different. To achieve a more nuanced understanding of the differences and commonalities between IHCA and OHCA, formal classification and codification to recognize the conditions as unique is needed.
As described earlier, identifying IHCA using hospital claims and administrative data is challenging because of the lack of a unique diagnostic code for this clinical condition. The ICD coding system, developed and maintained by the World Health Organization, defines medical diagnoses and procedure codes that are commonly used for data collection, research analysis, and billing purposes. The Centers for Disease Control and Prevention’s North American Collaborating Center collaborates with the Centers for Medicare & Medicaid Services (CMS) to adapt ICD diagnosis codes for hospitals in the United States. Currently, no specific ICD diagnosis code exists for IHCA, although ICD-9 and -10 include codes for cardiac arrest in general (shown in Table 5-3). Select medical procedures (e.g., cardiac arrest during surgery, and anesthesia during pregnancy or labor) and at-risk populations (e.g., neonates) also have special codes for cardiac arrest.
Established ICD-9 coding practice defines primary and secondary diagnoses largely based on whether an underlying cause of cardiac arrest can be determined rather than on whether a patient arrives at a hospital in a state of cardiac arrest. As a result, researchers studying IHCA attempt to identify IHCA in administrative data using specific algorithms that often use a combination of diagnosis codes, hospital-specific procedure, and present on admission codes to make educated guesses about the location of the initial event. However, this procedure can be inaccurate. A number of situations may contribute to these low rates of accuracy. For example, if IHCA is identified using codes for the delivery of chest compressions in order to determine a numerator, an individual who dies from cardiac arrest, but does not receive CPR, is not counted in the numerator.
TABLE 5-3 Examples of ICD-9 and -10 Codes for Cardiac Arrest
|V12.53||Personal history of sudden cardiac arrest|
|Pediatric||779.85||Cardiac arrest of newborn|
|ICD-10||Adult||I46.0||Cardiac arrest with successful resuscitation|
|I49.1||Sudden cardiac death|
|I462.1||Cardiac arrest due to underlying cardiac condition|
|I468.1||Cardiac arrest due to other underlying condition|
|I469.1||Cardiac arrest, cause unspecified|
|I9712.0||Postprocedural cardiac arrest|
|I9771.0||Intraoperative cardiac arrest|
|O2911.0||Cardiac arrest due to anesthesia during pregnancy|
|Z8674.1||Personal history of sudden cardiac arrest|
|Pediatric||P2981.1||Cardiac arrest of newborn|
SOURCES: CMS, 2015a,b.
Moreover, current ICD-9 guidance instructs hospital coders not to code for cardiac arrest to indicate an inpatient death if the cause is known because the Uniform Hospital Discharge Data set uses a separate item. A recent study that tried to identify hospitalized patients who had IHCA (and did not have DNR orders) using the ICD-9 codes 427.5 (cardiac arrest), 99.60 (CPR), and 99.63 (closed chest massage) found that this method had only 76 percent positive predictive value (Bucy et al., 2015).
Other available codes do not adequately correct for the absence of separate ICD codes. Moreover, at this time there is only one diagnosis related group (DRG) code for all cardiac arrest used to determine Medicare reimbursement to hospitals for inpatient stays. Although a separate indicator code can be used to identify a diagnosis code (e.g., cardiac arrest) as present on admission, this code (by definition) does not attach to a patient unless that patient is admitted to the hospital. Thus, a person can have a cardiac arrest within a hospital, receive treatment but die within a hospital emergency department, and not be identified in the data as having experienced an IHCA. This affects efforts to measure and improve the quality of cardiac arrest care provided by hospital personnel,
including initial resuscitation efforts and the post-arrest care of patients in ROSC. A separate ICD-10 code differentiating IHCA and OHCA would improve the reliability and validity of research, allow for precise calculation of incidence and survival.
CPR Quality Improvement: Devices, Debriefing, and Simulation Training
Many different strategies have been applied in efforts to improve the quality of resuscitation care for IHCA. CPR feedback devices provide one technology-driven opportunity to improve resuscitation care. These devices give guidance and feedback during CPR and have been used in both training and clinical settings. The devices can assess and provide information on compression rate, depth, and force, ranging in complexity from a simple metronome that guides compression rate to more complex tools that monitor and provide audiovisual feedback about actual CPR performance in real time. Impedance threshold devices (ITDs) and active compression-decompression (ACD) devices also have been studied as tools to augment cardiac and cerebral blood flow during CPR. ITDs create a negative pressure vacuum as the chest recoils during chest compressions, while ACDs are suction tools used during CPR to actively decompress the chest wall. Both enhance blood flow return to the heart and brain (Cochrane, 2013; Resuscitation Central, 2010). Finally, several mechanical devices provide CPR directly to patients in a more standardized manner, completely removing providers from this role. Although studies have demonstrated that mechanical devices are able to be used quickly and may improve the CPR performance, available evidence neither supports nor discourages widespread adoption of these devices (Brooks et al., 2014).
Implementing personnel debriefings immediately following a cardiac arrest presents another opportunity for improving cognitive skills rather than psychomotor skillsets relevant to resuscitation performance. This approach has been examined as a potential strategy for improving CPR performance and resuscitation care for IHCA. Historically, early debriefing as a tool for performance assessment has been challenging, because of the lack of objective data available after resuscitation with the exception of code sheets and medical records. The availability of new technology, however, has made it possible to directly measure resuscitation quality, including factors such as the rate and depth of chest compressions (Idris et al., 2012; Stiell et al., 2014). Using monitoring devices to
provide detailed transcripts of CPR quality from actual resuscitations, a recent report examined the impact of early debriefing on CPR performance for a group of internal medicine residents at a university hospital. During the study period, the residents were required to attend weekly debriefing sessions where the prior week’s resuscitations were discussed and analyzed based on the objective metrics of CPR performance (Edelson et al., 2008). The researchers found that CPR quality and outcomes during the intervention period improved with the early debriefings in terms of both ventilation rate decrease and compression depth increase. Overall, these changes correlated with a higher rate of ROSC in the group with early debriefing (59.4 percent versus 44.6 percent), but there was no change in the survival-to-discharge rates. Other studies have shown similar patterns of results (Couper et al., 2013). In a large tertiary care children’s hospital, implementation of formalized debriefing after cardiac arrest was associated with improved survival to hospital discharge and improved survival with favorable neurologic outcome (Wolfe et al., 2014). Debriefings often involve a post-resuscitation review of provider performance. For example, one study of a debriefing program included analysis of quantitative CPR variables (e.g., chest compression rate and depth, fraction of time during resuscitation spent providing chest compressions, and fraction of chest compressions without rescuer allowing for chest wall recoil) obtained from feedback-enabled defibrillators. Sessions were held within 3 weeks of the event, scheduled during normal educational conference times, and were open to the entire pediatric ICU staff, not just those who participated in the event (Zebuhr et al., 2012).
Simulation training may also improve provider performance during resuscitations (Wayne et al., 2008). In 2011, the Agency for Healthcare Research and Quality (AHRQ) supported multiple demonstration projects to evaluate the effectiveness of various simulation methods in improving patient safety and quality of care delivery, including one specifically on pediatric resuscitation in the emergency department (AHRQ, 2014b). A number of other studies have found an association between targeted simulation training and improvements in the timeliness and quality of CPR (Cheng et al., 2015a; Sullivan et al., 2014) as well as the development of nontechnical leadership skills (Hunziker et al., 2010). One benefit of simulation training, compared to actual cardiac arrests, is that it can provide a controlled and standardized experimental setting that allows assessment of multiple interventions. Subsequently, training is focused on high yield processes and targeted to different types of provid-
ers. Simulation also provides a safe environment where students can learn from mistakes without harming patients. Simulation studies have shown particular insights into the importance of leadership, communication, and teamwork. These studies have also allowed for the tailoring of resuscitation care toward current gaps in treatment, although the link between process improvement during simulation training and real-world resuscitation care remains uncertain.
Team Training to Improve IHCA and Post-Arrest Care Response
Effective resuscitation and post-arrest care requires multidisciplinary teamwork with efficient and coordinated action between prehospital providers and hospital-based staff (including ED nurses or physicians, critical care, neurologists, pediatricians, and laboratory technicians, among others). When a cardiac arrest occurs, these teams need to rapidly execute a care plan for individual patients and then may need to collaborate with providers in the outpatient care setting (primary care providers or rehabilitation staff) following discharge. Developing and implementing training protocols for multidisciplinary resuscitation teams (RRT or MET teams in IHCA care) or post-arrest care teams can enhance and streamline the quality of resuscitation care within hospitals. In their respective guidelines and statements, the ILCOR, the European Resuscitation Council, and the AHA have recognized the importance of teamwork, communication and leadership to the performance of resuscitation teams, and the effectiveness of targeted training to develop these vital behaviors (Bhanji et al., 2010; Mancini et al., 2010; Nolan et al., 2010). Discussion of team dynamics (e.g., communication and roles) and different types of resuscitation teams is included in AHA coursework for ACLS—but not BLS—providers.
The quality of leadership within a resuscitation team affects provision of care, as does the effectiveness of communication, coordination, and collaboration among team members; all of which may influence patient outcomes. Breakdowns of leadership and teamwork alike affect performance, thereby detrimentally affecting patient outcomes (Hunziker et al., 2011; Norris and Lockey, 2012). Fortunately, effective training programs designed to enhance leadership and teamwork exist, and through modification of relevant behaviors these training programs are able to improve team performance and patient survival alike. Although effective leadership is difficult to define, successful leaders in the resuscitation field share similar traits of extroversion, self-confidence, flexibility, and a calm demeanor (Norris and Lockey, 2012). By definition,
good team leaders are also interested in processes and actions that can improve team performance, such as CQI programs and the professional development of team members (Andersen et al., 2010; Norris and Lockey, 2012). Developing these traits is the goal of targeted leadership training, which can be more effective than technical training at improving team performance (Hunziker et al., 2010).
Many leadership training programs exist and can be used to cultivate better leaders throughout the medical field. Simulation training for cardiac arrest resuscitation teams, described in the previous section, is one method of developing necessary technical and nontechnical skills. Crew resource management (also known as crisis resource management)—a proven, and widely employed method of leadership training—was first developed by the aviation industry and has been applied with success in the similarly complex and high-risk environments of emergency medicine (Ornato and Peberdy, 2014). Examples of crew resource management techniques that have been modified for use in resuscitation medicine include checklists for leadership activities; cross-checks to ensure team members are clear of the patients prior to defibrillation; and use of standardized, non-ambiguous calls and responses (DePriest et al., 2013; Ornato and Peberdy, 2014). Effective training programs do not require extensive resources, because even brief leadership training can have a measurable and lasting impact on leadership behaviors (Cooper, 2001). Therefore, this type of training could be useful for a broad spectrum of health care providers involved in resuscitation care whenever possible.
Specific benefits of teamwork training include reductions in human error and improvements in communication, leadership, coordination, decision making, and the cognitive and behavioral capabilities of team members within a team context (Delise et al., 2010; Salas et al., 2008; Schmutz and Manser, 2013; Thomas et al., 2007a). The methods and objectives of team training are varied and affect the impact of training on performance in different ways (Salas et al., 2008). Often combining the use of lectures, demonstrations, and simulations, team training seeks to develop communication strategies, increase practitioner knowledge, prevent errors, and promote utilization of available resources (Weaver et al., 2014). Successful team training often aligns training objectives with institutional goals, provides institutional support for team training initiatives, prepares the health care environment and trainees for team training, promotes use of teamwork skills in the workplace, and monitors the effectiveness of the team training program (Salas et al., 2009).
Develop Standardized Performance Metrics
Accurate measurement is a cornerstone of a quality improvement program. Standards that require the collection of outcome metrics across the continuum of IHCA and post-arrest care are needed in order to promote meaningful improvements in hospitals across the United States. Performance measures are vital to the provision of quality health care because they allow for benchmarking across and within hospitals and provide firm evidentiary basis to guide clinical patient or family decision making.
There is a need for formally endorsed standards that allow benchmarking at the national level. However, currently no quality metrics are endorsed by The Joint Commission, National Quality Forum, or CMS that could be used to specifically assess quality of IHCA or post-arrest care. Hospitals that are accredited by The Joint Commission are required to adhere to some general standards for in-hospital resuscitation services. In 2008, The Joint Commission endorsed a patient safety goal aimed at improving recognition and response to changes in a patient’s clinical condition (Revere, 2008). This could be adapted for assessment of IHCA quality of care, because these patients often present changes in vital signs and show clinical signs of deterioration prior to an arrest. There are general Joint Commission standards related to resuscitation services in hospitals for quality improvement review, evaluation, and action that apply to resuscitation care; however, none are specifically designed for in-hospital cardiac arrest (see Box 5-7 for a summary of relevant standards). Adding specificity to the general standards to support collection of common data elements to enable the identification of people that have experienced in-hospital adult and pediatric arrest would be a good first step to help organizations (and a national performance improvement effort) to understand how best to optimize the outcomes of arrest patients.
Efforts to develop national performance measures for IHCA and post-arrest care have been unsuccessful to date. In 2012, The Joint Commission, in collaboration with private corporations, completed pilot testing of four cardiac arrest–specific inpatient measures (shown in Table 5-4) that have demonstrated effectiveness in improving patient survival and neurologic outcomes (The Joint Commision, 2014). However, due to the small number of participating hospitals (seven) and the estimates of limited data reliability, the measures were not advanced for endorsement (The Joint Commission, 2014). These metrics also did not
The Joint Commission Standards Related to Resuscitation Services in Hospitals
Resuscitation services are available throughout the hospital.
- Policies, procedures, processes, or protocols govern the provision of resuscitation services.
- Equipment is appropriate to the patient population (i.e., adult, pediatric).
- Appropriate equipment is placed strategically throughout the hospital.
- An evidence-based training program(s) is used to train appropriate staff to recognize the need for and use of designated equipment and techniques in resuscitation efforts.
The hospital collects data to monitor the performance of potentially high-risk processes (e.g., resuscitation and its outcomes).
Data are systematically aggregated and analyzed.
- Data are analyzed and compared internally over time and externally with other sources of information when available.
- Comparative data are used to determine whether there is excessive variability or unacceptable levels of performance when available.
Undesirable patterns or trends in performance are analyzed.
Information from data analysis is used to make changes that improve performance and patient safety and reduce the risk of sentinel events.
SOURCE: The Joint Commission, 2007.
capture outcomes longitudinally across the continuum of care or include assessments of care related to the post–cardiac arrest state. Some of these proposed metrics may be difficult for some hospitals to achieve (e.g., determining timeliness to first defibrillation attempt), without making substantial improvements in the care delivery process.
TABLE 5-4 Relevant ICHA and Post-Arrest Measures Piloted by The Joint Commission
|Measure ID||Measure Short Name||Definition and Description|
|SCA-01||Timeliness of First Defibrillation Attempt||IHCA with VF/pVT in which first defibrillation shock is delivered within 2 minutes of cardiac arrest time|
|SCA-02||Timely Confirmation of Correct Endotracheal Tube||Confirmation within 1 minute of initial placement via cap-nometry, electronic waveform capnography, esophageal detection devices, exhaled CO2 colorimetric monitor, or revisualization with direct laryngoscopy that the endotracheal tube is correctly placed in the trachea, rather than in the esophagus|
|SCA-03||Initiation of Therapeutic Hypothermia||Availability and provision of therapeutic hypothermia following OHCA|
|SCA-04||Maintenance of Thermoregulation in Therapeutic Hypothermia||Assessment of the maintenance of the goal temperature of 32°-34°C when therapeutic hypothermia is used for survivors of sudden cardiac arrest|
NOTE: Table created based on information provided by The Joint Commission report.
SOURCE: The Joint Commission, 2014.
The AHA recently developed a set of performance metrics related to IHCA. Unlike previously proposed quality standards, the AHA inpatient metrics aim to monitor overall incidence and survival rates, and CPR quality as a first step, rather than point toward many specific process of care measures. It includes the following metrics applicable to adult and pediatric IHCA populations: (1) IHCA survival rate, (2) IHCA incidence rate in noncritical care, nonprocedural, inpatient areas per 1,000 patient-days, (3) proportion of hospitals (with more than 200 beds) reporting IHCA to a national registry, and (4) proportion of IHCA with attempted
resuscitation, in which CPR performance data were objectively monitored (Neumar, 2015). Studies of existing in-hospital registries such as GWTG-R have shown substantial improvements in patient outcomes over time (overall survival rate increased from approximately 13.7 percent to 22.3 percent from 2000 to 2009) among hospitals that regularly monitor and report data on cardiac arrest and resuscitation related variables. Adopting these standard metrics may be a potential next step in driving in-hospital resuscitation care and patient outcomes (Girotra et al., 2012).
Aligning improvements with related national initiatives has been successful in driving advances in quality of care for other conditions. For example, certified primary and comprehensive stroke centers were developed by The Joint Commission, in collaboration with the American Heart Association and the Brain Attack Coalition, after leaders recognized the parallels between stroke care for patients and the success of trauma centers in improving care and outcomes for people with traumatic injuries (Alberts, 2014). Since the launch of the stroke centers of excellence concept, standard performance measures for stroke treatment have been adopted, and certified centers are required to collect and benchmark their performance as part of CQI programs (The Joint Commision, 2015). Developing and formally endorsing standard performance metrics for cardiac arrest could improve resuscitation care processes, enhance patient outcomes, and support future research efforts to optimize care for IHCA, OHCA, and post-arrest care.
Quality Collaborative to Continuously Assess Performance
Quality improvement collaboratives have been adopted by a number of health care organizations in the United States, across different clinical areas (Schouten et al., 2008). The objective is for participating organizations to close the gap between aspired and actual performance related to a process or outcome of care by testing and implementing best practices across organizations. Although there is limited research on the effectiveness of the method for cardiac arrest and resuscitation care, similar collaborative strategies have improved patient outcomes in other clinical domains (e.g., surgery or stroke). Quality collaboratives and registries share some common challenges including decisions related to evidence standards, measurement, prognostication, and withdrawal of care.
Hospitals generally follow basic performance requirements, typically endorsed by The Joint Commission. In the cardiac arrest care continuum, The Joint Commission requires that appropriate resuscitation care and
equipment be available through a defined protocol, and that outcomes data be collected and reviewed periodically (The Joint Commission, 2007; Morrison et al., 2013). Additionally, the requirements indicate that evidence-based programs should be used to train providers and staff to recognize cardiac arrest and use resuscitation equipment and techniques, with BLS as the required minimum.
Some hospitals in the United States have also opted to participate in national quality improvement programs for cardiac arrest and resuscitation. The GWTG-R registry collects data on every cardiac arrest that receives treatment in a hospital through a standardized Utstein template, which allows for comparability and benchmarking across hospitals. Studies show that participating hospitals see improvements in survival, if not survival to discharge (Bradley et al., 2012). However, participation in a registry or collaborative alone may not be wholly responsible for these improvements, and a multi-pronged approach to improvement may be necessary (Bradley et al., 2012). Finally, it appears that CQI efforts for resuscitation care need to focus directly on the unique aspects of in-hospital cardiac arrests or post-arrest care, because it is unlikely that spillover effects will occur from similar efforts related to other disease processes. In a recent study of hospitals in the GWTG-R registry, there was no correlation between IHCA survival and publicly reported outcomes for acute myocardial infarction, pneumonia, or heart failure (Chen et al., 2013). The committee’s commissioned analyses demonstrate improvements in survival in the GWTG-R database over time (Chan, 2015). This could be a reflection of changing patient populations, as well as potential improvements in resuscitation systems of care within hospitals.
Implementing Patient- and Family-Centered Care
Patient-centered care is an increasingly recognized goal within many health care delivery systems. This can have unique challenges in the field of cardiac arrest, given that resuscitation, and continued post-arrest care may not be desirable for all patients given individual prognoses, care preferences, and values. Possible misconceptions about outcomes following CPR among the general public, and poor explanations about treatment options for cardiac arrest can affect patients and families decisions, which affects outcomes (both desired and unwanted). Recent studies suggest that patient knowledge of CPR is inadequate, but can be improved by brief education videos and discussions with providers
(Heyland et al., 2006; Wilson et al., 2015). Many patients and family members may choose not to have aggressive care, when they are appropriately educated about resuscitation (Choudry et al., 2003). As discussed in earlier sections, there is wide variability in institutional withdrawal of care protocols for patients with severe neurologic deficit. Although advanced directives and end-of-life discussions are encouraged for many types of high-risk patients, large proportions of patients with significant cardiac comorbidities (such as advanced heart failure), implantable defibrillators, and pacemakers do not participate (Dunlay et al., 2012; Pasalic et al., 2014; Tajouri et al., 2012). Because withholding resuscitation care requires an order that establishes DNAR status, hospitals should have a standard protocol for discussing advance directives with patients, emphasizing patient autonomy and informed decision making. Studies have demonstrated that these discussions are not harmful and may ultimately reduce unnecessary or unwanted aggressive resuscitation and continued post-arrest care interventions in patients (Temel et al., 2010; Wright et al., 2008).
An important, but controversial, aspect of in-hospital resuscitation efforts involves whether, and in what way, family members should be present during resuscitation efforts following an IHCA (Kramer and Mitchell, 2013). Although there is no broad consensus, inviting family presence during resuscitation has been weakly endorsed by the AHA as being potentially beneficial, with no evidence of harm to family members at risk of posttraumatic stress or anxiety (Goldberger et al., 2015; Morrison et al., 2010). Theoretical benefits include transparency, a sense of closure for family members, and possible assurance that delivery of resuscitation was, in fact, congruent with patient wishes. Potential harms include introduction of legal risks, interference with resuscitation, and exposure of family members to what may be an intense and unsettling scene. Pediatric settings potentially magnify the need for transparency and closure for parents and loved ones of children experiencing cardiac arrest. Despite initial concerns, recent data indicate that both families and staff support the concept, with many families expressing a strong desire to be close to their child in the final moments of their life (Duran et al., 2007). Multiple pediatric associations support family presence (ENA, 2009; Henderson and Knapp, 2005; Kleinman et al., 2010a).
In either adults or children, the collective literature suggests that ideally family presence should not be an ad hoc experience. Rather, hospitals should have explicit, detailed policies regarding whether family presence will be invited. These policies should also identify specific
roles for resuscitation team members, such as escorting family members to the scene, explaining the events, and—critically—debriefing with the family afterward to answer questions and identify potential adverse effects of the experience. Box 5-8 summarizes the key points in this chapter.
Chapter Summary and Key Points
- In-Hospital Cardiac Arrest
- IHCA is in many ways different from OHCA, and represents a unique population subset.
- There are a number of knowledge gaps in this field, and challenges related to measurement of IHCA incidence resulting from the absence of separate diagnostic and procedure codes for OHCA and IHCA.
- Substantial variability exists in the approach, availability, and quality of resuscitation care provided by hospitals around the nation.
- Post-Arrest Care
- Treatments (such as therapeutic hypothermia) have demonstrated the potential to improve patient outcomes, but scientific evidence to support many post-arrest treatments are still nascent.
- More research is needed to develop standardized tools for accurate neurologic prognosis.
- Ethical questions regarding withdrawal of care remain challenging to answer.
- Strategies for Improvement
- Separate diagnosis codes for IHCA and OHCA should be established.
- More research targeting simulation training, debriefing strategies, and mechanical devices can improve quality of CPR and resuscitation care.
- Team training is needed to improve IHCA and post-arrest care response.
- Standardized performance metrics for cardiac arrest need to be developed and endorsed by national organizations to assess the quality of hospital care.
- Create and maintain multicenter collaboratives can promote and advance continuous quality improvement efforts.
- Patient- and family-centered cardiac arrest care can emphasize advanced directives, DNAR, withdrawal of care, and family presence during resuscitation.
There are many opportunities to improve and optimize care for cardiac arrest patients within hospitals, and to increase the likelihood of survival with good neurologic outcomes for all cardiac arrest patients. Today, there are remarkable variations between hospitals in treatments protocols for IHCA and post-arrest care, which lead to differential and often poor outcomes. These differences occur partially because of a lack of scientific evidence and known standards in resuscitation care. In response to the growing literature that highlights these systemic failures, experts in the resuscitation field, guideline-setting organizations, and some hospital administrators are placing an increased emphasis on developing quality improvement strategies. This requires stakeholders to sequentially prioritize performance-standard setting, the measurement and collection of patient data, and the development and implementation of continuous quality improvement programs within hospital-based resuscitation systems of care. This will allow each system to assess its performance and benchmark against other similar institutions and will drive improvements in quality of care.
Abella, B. S., J. P. Alvarado, H. Myklebust, D. P. Edelson, A. Barry, N. O’Hearn, and L. B. Becker. 2005. Quality of cardiopulmonary resuscitation during in-hospital cardiac arrest. Journal of the American Medical Association 293(3):305-310.
Acker, J. E., 3rd, A. M. Pancioli, T. J. Crocco, M. K. Eckstein, E. C. Jauch, H. Larrabee, N. M. Meltzer, W. C. Mergendahl, J. W. Munn, S. M. Prentiss, C. Sand, J. L. Saver, B. Eigel, B. R. Gilpin, M. Schoeberl, P. Solis, J. R. Bailey, K. B. Horton, and S. K. Stranne. 2007. Implementation strategies for emergency medical services within stroke systems of care: A policy statement from the American Heart Association/American Stroke Association Expert Panel on Emergency Medical Services Systems and the Stroke Council. Stroke 38(11):3097-3115.
Ackerman, M. J., S. G. Priori, S. Willems, C. Berul, R. Brugada, H. Calkins, A. J. Camm, P. T. Ellinor, M. Gollob, R. Hamilton, R. E. Hershberger, D. P. Judge, H. Le Marec, W. J. McKenna, E. Schulze-Bahr, C. Semsarian, J. A. Towbin, H. Watkins, A. Wilde, C. Wolpert, and D. P. Zipes. 2011. HRSA/EHRA expert consensus statement on the state of genetic testing for the channelopathies and cardiomyopathies this document was developed as
a partnership between the Heart Rhythm Society (HRS) and the European Heart Rhythm Association (EHRA). Heart Rhythm 8(8):1308-1339.
AHRQ (Agency for Healthcare Research and Quality). 2014a. Rapid response systems. http://psnet.ahrq.gov/primer.aspx?primerID=4 (accessed April 2, 2015).
AHRQ. 2014b. Improving patient safety through simulation research: Improving pediatric resuscitation: A simulation program for the community Ed. http://www.ahrq.gov/research/findings/factsheets/errorssafety/simulproj11/index.html (accessed June 19, 2015).
Akahane, M., T. Ogawa, S. Koike, S. Tanabe, H. Horiguchi, T. Mizoguchi, H. Yasunaga, and T. Imamura. 2011. The effects of sex on out-of-hospital cardiac arrest outcomes. American Journal of Medicine 124(4):325-333.
Albaeni, A., N. Chandra-Strobos, D. Vaidya, and S. M. Eid. 2014. Predictors of early care withdrawal following out-of-hospital cardiac arrest. Resuscitation 85(11):1455-1461.
Alberts, M. J. 2014. Do primary stroke centers occur randomly? Stroke 45(12):3499-3500.
Alexander, M., L. Baker, C. Clark, K. M. McDonald, R. Rowell, O. Saynina, and M. A. Hlatky. 2002. Management of ventricular arrhythmias in diverse populations in California. American Heart Journal 144(3):431-439.
Andersen, P. O., M. K. Jensen, A. Lippert, and D. Ostergaard. 2010. Identifying nontechnical skills and barriers for improvement of teamwork in cardiac arrest teams. Resuscitation 81(6):695-702.
Banks, J. L., and C. A. Marotta. 2007. Outcomes validity and reliability of the modified Rankin scale: Implications for stroke clinical trials: A literature review and synthesis. Stroke 38(3):1091-1096.
Baxter, A. D., P. Cardinal, J. Hooper, and R. Patel. 2008. Medical emergency teams at the Ottawa hospital: The first two years. Canadian Journal of Anaesthesia 55(4):223-231.
Beardsall, K., S. Vanhaesebrouck, A. L. Ogilvy-Stuart, C. Vanhole, C. R. Palmer, M. van Weissenbruch, P. Midgley, M. Thompson, M. Thio, L. Cornette, I. Ossuetta, I. Iglesias, C. Theyskens, M. de Jong, J. S. Ahluwalia, F. de Zegher, and D. B. Dunger. 2008. Early insulin therapy in very-low-birth-weight infants. New England Journal of Medicine 359(18):1873-1884.
Bennett, K. S. 2013. Brain monitoring during extracorporeal membrane oxygenation: Will it alter care? Pediatric Critical Care Medicine 14(6):648-649.
Berg, R. A., R. M. Sutton, R. Holubkov, C. E. Nicholson, J. M. Dean, R. Harrison, S. Heidemann, K. Meert, C. Newth, F. Moler, M. Pollack, H. Dalton, A. Doctor, D. Wessel, J. Berger, T. Shanley, J. Carcillo, and V. M. Nadkarni. 2013. Ratio of picu versus ward cardiopulmonary resuscitation events is increasing. Critical Care Medicine 41(10):2292-2297.
Bhanji, F., M. E. Mancini, E. Sinz, D. L. Rodgers, M. A. McNeil, T. A. Hoadley, R. A. Meeks, M. F. Hamilton, P. A. Meaney, E. A. Hunt, V. M.
Nadkarni, and M. F. Hazinski. 2010. Part 16: Education, implementation, and teams: 2010 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation 122(18 Suppl 3):S920-S933.
Bobrow, B. J., and K. B. Kern. 2009. Regionalization of postcardiac arrest care. Current Opinion in Critical Care 15(3):221-227.
Bonafide, C. P., K. E. Roberts, M. A. Priestley, K. M. Tibbetts, E. Huang, V. M. Nadkarni, and R. Keren. 2012a. Development of a pragmatic measure for evaluating and optimizing rapid response systems. Pediatrics 129(4):e874-e881.
Bonafide, C. P., Holmes, J. H., Nadkarni, V. M., Lin, R., Landis, J. R., and Keren, R. 2012b. Development of a score to predict clinical deterioration in hospitalized children. Journal of Hospital Medicine 7(4):345-349.
Bonafide, C. P., A. R. Localio, K. E. Roberts, V. M. Nadkarni, C. M. Weirich, and R. Keren. 2014. Impact of rapid response system implementation on critical deterioration events in children. JAMA Pediatrics 168(1):25-33.
Booth, C. M., R. H. Boone, G. Tomlinson, and A. S. Detsky. 2004. Is this patient dead, vegetative, or severely neurologicly impaired? Assessing outcome for comatose survivors of cardiac arrest. JAMA 291(7):870-879.
Bradley, S. M., E. Huszti, S. A. Warren, R. M. Merchant, M. R. Sayre, and G. Nichol. 2012. Duration of hospital participation in Get With The Guidelines-Resuscitation and survival of in-hospital cardiac arrest. Resuscitation 83(11):1349-1357.
Brilli, R. J., R. Gibson, J. W. Luria, T. A. Wheeler, J. Shaw, M. Linam, J. Kheir, P. McLain, T. Lingsch, A. Hall-Haering, and M. McBride. 2007. Implementation of a medical emergency team in a large pediatric teaching hospital prevents respiratory and cardiopulmonary arrests outside the intensive care unit. Pediatric Critical Care Medicine 8(3):236-246; quiz 247.
Bro-Jeppesen, J., C. Hassager, M. Wanscher, M. Ostergaard, N. Nielsen, D. Erlinge, H. Friberg, L. Kober, and J. Kjaergaard. 2014. Targeted temperature management at 33 degrees Celsius versus 36 degrees Celsius and impact on systemic vascular resistance and myocardial function after out-of-hospital cardiac arrest: A sub-study of the target temperature management trial. Circulation: Cardiovascular Interventions 7(5):663-672.
Brooks, S. C., N. Hassan, B. L. Bigham, and L. J. Morrison. 2014. Mechanical versus manual chest compressions for cardiac arrest. Cochrane Database Systematic Reviews 2:Cd007260.
Bucy, R., K. Hanisko, L. Ewing, J. Davis, K. Kepreos, B. Youles, J. Lehrich, K. M. Nord, P. Chan, B. K. Nallamothu, and T. J. Iwashyna. 2015. Abstract 281: Validity of in-hospital cardiac arrest ICD-9-CM codes in veterans. Circulation: Cardiovascular Quality and Outcomes 8(Suppl 2):A281.
Chan, P. S. 2015. Public health burden of in-hospital cardiac arrest. IOM commissioned report. http://www.iom.edu/~/media/Files/Report%20Files/2015/GWTG.pdf (accessed June 19, 2015).
Chan, P. S., H. M. Krumholz, G. Nichol, and B. K. Nallamothu. 2008. Delayed time to defibrillation after in-hospital cardiac arrest. New England Journal of Medicine 358(1):9-17.
Chan, P. S., G. Nichol, H. M. Krumholz, J. A. Spertus, P. G. Jones, E. D. Peterson, S. S. Rathore, and B. K. Nallamothu. 2009. Racial differences in survival after in-hospital cardiac arrest. JAMA 302(11):1195-1201.
Chan, P. S., R. Jain, B. K. Nallmothu, R. A. Berg, and C. Sasson. 2010. Rapid response teams: a systematic review and meta-analysis. Archives of Internal Medicine 170(1):18-26.
Chan, P. S., J. A. Spertus, H. M. Krumholz, R. A. Berg, Y. Li, C. Sasson, and B. K. Nallamothu. 2012. A validated prediction tool for initial survivors of in-hospital cardiac arrest. Archives of Internal Medicine 172(12):947-953.
Chang, D. W., and E. P. Brass. 2014. Patient and hospital-level characteristics associated with the use of do-not-resuscitate orders in patients hospitalized for sepsis. Journal of General Internal Medicine 29(9):1256-1262.
Checchia, P. A., R. Sehra, J. Moynihan, N. Daher, W. Tang, and M. H. Weil. 2003. Myocardial injury in children following resuscitation after cardiac arrest. Resuscitation 57(2):131-137.
Chen, L. M., B. K. Nallamothu, H. M. Krumholz, J. A. Spertus, F. Tang, and P. S. Chan. 2013. Association between a hospital’s quality performance for in-hospital cardiac arrest and common medical conditions. Circulation: Cardiovascular Quality and Outcomes 6(6):700-707.
Chen, Y. S., A. Chao, H. Yu, W. Ko, I. Wu, R. J.C. Chen, S. Huang, F. Lin, and S. Wang. 2003. Analysis and results of prolonged resuscitation in cardiac arrest patients rescued by extracorporeal membrane oxygenation. Journal of the American College of Cardiology 41(2):197-203.
Cheng, A., L. L. Brown, J. P. Duff, J. Davidson, F. Overly, N. M. Tofil, D. T. Peterson, M. L. White, F. Bhanji, I. Bank, R. Gottesman, M. Adler, J. Zhong, V. Grant, D. J. Grant, S. N. Sudikoff, K. Marohn, A. Charnovich, E. A. Hunt, D. O. Kessler, H. Wong, N. Robertson, Y. Lin, Q. Doan, J. M. Duval-Arnould, and V. M. Nadkarni. 2015a. Improving cardiopulmonary resuscitation with a CPR feedback device and refresher simulations (CPR CARES study): A randomized clinical trial. JAMA Pediatrics 169(2):137-144.
Cheung, K. W., R. S. Green, and K. D. Magee. 2006. Systematic review of randomized controlled trials of therapeutic hypothermia as a neuroprotectant in post cardiac arrest patients. Canadian Journal of Emergency Medicine 8(5):329-337.
Choi, S. P., K. N. Park, H. K. Park, J. Y. Kim, C. S. Youn, K. J. Ahn, and H. W. Yim. 2010. Diffusion-weighted magnetic resonance imaging for predicting the clinical outcome of comatose survivors after cardiac arrest: A cohort study. Critical Care 14(1):R17.
Choudry, N. K., S. Choudry, and P.A. Singer. 2003. CPR for patients labeled DNR: the role of the limited aggressive therapy order. Annals of Internal Medicine 138(1):65-69.
Churpek, M. M., T. C. Yuen, S. Y. Park, R. Gibbons, and D. P. Edelson. 2014. Using electronic health record data to develop and validate a prediction model for adverse outcomes on the wards. Critical Care Medicine 42(4): 841-848.
Cloostermans, M. C., F. B. van Meulen, C. J. Eertman, H. W. Hom, and M. J. van Putten. 2012. Continuous electroencephalography monitoring for early prediction of neurologic outcome in postanoxic patients after cardiac arrest: A prospective cohort study. Critical Care Medicine 40(10):2867-2875.
CMS (Centers for Medicare & Medicaid Services). 2015a. ICD-10-CM and GEMs. http://www.cms.gov/Medicare/Coding/ICD10/2015-ICD-10-CM-and-GEMs.html (accessed on April 1, 2015).
CMS. 2015b. ICD-9 code lookup. http://www.cms.gov/medicare-coverage-database/staticpages/icd-9-code-lookup.aspx (accessed on April 1, 2015).
Cochrane. 2013. Active compression-decompression using a hand-held device for emergency heart massage. http://www.cochrane.org/CD002751/VASC_active-compression-decompression-using-a-hand-held-device-for-emergencyheart-massage (accessed June 19, 2015).
Coleman, E. A., and R. A. Berenson. 2004. Lost in transition: Challenges and opportunities for improving the quality of transitional care. Annals of Internal Medicine 141(7):533-536.
Coleman, E. A., C. Parry, S. Chalmers, and S. J. Min. 2006. The care transitions intervention: Results of a randomized controlled trial. Archives of Internal Medicine 166(17):1822-1828.
Cook, R. I., M. Render, and D. D. Woods. 2000. Gaps in the continuity of care and progress on patient safety. British Medical Journal 320(7237):791-794.
Cooper, S. 2001. Developing leaders for advanced life support: Evaluation of a training programme. Resuscitation 49(1):33-38.
Couper, K., B. Salman, J. Soar, J. Finn, and G. D. Perkins. 2013. Debriefing to improve outcomes from critical illness: a systematic review and metaanalysis. Intensive Care Medicine 39(9):1513-1523.
Davis, P. G., A. Tan, C. P. O’Donnell, and A. Schulze. 2004. Resuscitation of newborn infants with 100% oxygen or air: A systematic review and metaanalysis. Lancet 364(9442):1329-1333.
Daya, M., R. Schmicker, S. May, and L. Morrison. 2015. Current burden of cardiac arrest in the United States: Report from the Resuscitation Outcomes Consortium. Paper commissioned by the Committee on the Treatment of Cardiac Arrest: Current Status and Future Directions. http://www.iom.edu/~/media/Files/Report%20Files/2015/ROC.pdf (accessed June 30, 2015).
Delise, L. A., C. Allen Gorman, A. M. Brooks, J. R. Rentsch, and D. Steele-Johnson. 2010. The effects of team training on team outcomes: a metaanalysis. Performance Improvement Quarterly 22(4):53-80.
DePriest, J., A. L. Fee-Mulhearn, and A. Teleron. 2013. A novel ACLS team leader checklist implemented to improve resuscitation efforts. Resuscitation 84(9):e115.
Donoghue, A. J., V. M. Nadkarni, M. Elliott, and D. Durbin. 2006. Effect of hospital characteristics on outcomes from pediatric cardiopulmonary resuscitation: A report from the national registry of cardiopulmonary resuscitation. Pediatrics 118(3):995-1001.
Duncan, H., Hutchison, J., and Parshuram, C. S. 2006. The Pediatric Early Warning System score: A severity of illness score to predict urgent medical need in hospitalized children. Journal of Critical Care 21(3):271-278.
Dunlay, S. M., K. M. Swetz, P. S. Mueller, and V. L. Roger. 2012. Advance directives in community patients with heart failure. Circulation: Cardiovascular Quality and Outcomes 5(3):283-289.
Duran, C. R., K. S. Oman, J. J. Abel, V. M. Koziel, and D. Szymanski. 2007. Attitudes toward and beliefs about family presence: A survey of healthcare providers, patients’ families, and patients. American Journal of Critical Care 16(3):270-279; quiz 280; discussion 281-282.
Ebell, M. H., W. Jang, Y. Shen, and R. G. Geocadin. 2013. Development and validation of the good outcome following attempted resuscitation (GO-FAR) score to predict neurologicly intact survival after in-hospital cardiopulmonary resuscitation. JAMA Internal Medicine 173(20):1872-1878.
Edelson, D. P., B. Litzinger, V. Arora, D. Walsh, S. Kim, D. S. Lauderdale, T. L. Vanden Hoek, L. B. Becker, and B. S. Abella. 2008. Improving in-hospital cardiac arrest process and outcomes with performance debriefing. Archives of Internal Medicine 168(10):1063-1069.
Edelson, D. P., T. C. Yuen, M. E. Mancini, D. P. Davis, E. A. Hunt, J. A. Miller, and B. A. Abella. 2014. Hospital cardiac arrest resuscitation practice in the United States: A nationally representative survey. Journal of Hospital Medicine 9(6):353-357.
Eicher, D. J., C. L. Wagner, L. P. Katikaneni, T. C. Hulsey, W. T. Bass, D. A. Kaufman, M. J. Horgan, S. Languani, J. J. Bhatia, L. M. Givelichian, K. Sankaran, and J. Y. Yager. 2005. Moderate hypothermia in neonatal encephalopathy: Safety outcomes. Pediatric Neurology 32(1):18-24.
ENA (Emergency Nurses Association). 2009. Family presence during invasive procedures and resuscitation in the emergency department. https://www.ena.org/SiteCollectionDocuments/Position%20Statements/Archived/FamilyPresence.pdf (accessed April 2, 2015).
Ewy, G. A., and A. B. Sanders. 2013. Alternative approach to improving survival of patients with out-of-hospital primary cardiac arrest. Journal of the American College of Cardiology 61(2):113-118.
Finfer, S., J. Myburgh, and R. Bellomo. 2007. Albumin supplementation and organ function. Critical Care Medicine 35(3):987-988.
First Response. 2013. Cardiopump. http://www.resqpod.com.au/cardiopump.htm (accessed June 19, 2015).
Fiser, D. H., N. Long, P. K. Roberson, G. Hefley, K. Zolten, and M. BrodieFowler. 2000. Relationship of pediatric overall performance category and pediatric cerebral performance category scores at pediatric intensive care
unit discharge with outcome measures collected at hospital discharge and 1- and 6-month follow-up assessments. Critical Care Medicine 28(7):2616-2620.
Galanaud, D., and L. Puybasset. 2010. Cardiac arrest—has the time of MRI come? Critical Care 14(2):135.
Gandhi, G. Y., G. A. Nuttall, M. D. Abel, C. J. Mullany, H. V. Schaff, P. C. O’Brien, M. G. Johnson, A. R. Williams, S. M. Cutshall, L. M. Mundy, R. A. Rizza, and M. M. McMahon. 2007. Intensive intraoperative insulin therapy versus conventional glucose management during cardiac surgery: A randomized trial. Annals of Internal Medicine 146(4):233-243.
Girotra, S., B. K. Nallamothu, J. A. Spertus, Y. Li, H. M. Krumholz, and P. S. Chan. 2012. Trends in survival after in-hospital cardiac arrest. New England Journal of Medicine 367(20):1912-1920.
Girotra, S., J. A. Spertus, Y. Li, R. A. Berg, V. M. Nadkarni, and P. S. Chan. 2013. Survival trends in pediatric in-hospital cardiac arrests: An analysis from Get With The Guidelines-Resuscitation. Circulation: Cardiovascular Quality and Outcomes 6(1):42-49.
Girotra, S., B. K. Nallamothu, and P. S. Chan. 2014. Using risk prediction tools in survivors of in-hospital cardiac arrest. Current Cardiology Reports 16(3):457.
Gluckman, P. D., J. S. Wyatt, D. Azzopardi, R. Ballard, A. D. Edwards, D. M. Ferriero, R. A. Polin, C. M. Robertson, M. Thoresen, A. Whitelaw, and A. J. Gunn. 2005. Selective head cooling with mild systemic hypothermia after neonatal encephalopathy: Multicentre randomised trial. Lancet 365(9460): 663-670.
Go, A. S., D. Mozaffarian, V. L. Roger, E. J. Benjamin, J. D. Berry, M. J. Blaha, S. Dai, E. S. Ford, C. S. Fox, S. Franco, H. J. Fullerton, C. Gillespie, S. M. Hailpern, J. A. Heit, V. J. Howard, M. D. Huffman, S. E. Judd, B. M. Kissela, S. J. Kittner, D. T. Lackland, J. H. Lichtman, L. D. Lisabeth, R. H. Mackey, D. J. Magid, G. M. Marcus, A. Marelli, D. B. Matchar, D. K. McGuire, E. R. Mohler, 3rd, C. S. Moy, M. E. Mussolino, R. W. Neumar, G. Nichol, D. K. Pandey, N. P. Paynter, M. J. Reeves, P. D. Sorlie, J. Stein, A. Towfighi, T. N. Turan, S. S. Virani, N. D. Wong, D. Woo, and M. B. Turner. 2014. Heart disease and stroke statistics—2014 update: A report from the American Heart Association. Circulation 129(3):e28-e292.
Gold, B., L. Puertas, S. P. Davis, A. Metzger, D. Yannopoulos, D. A. Oakes, C. J. Lick, D. L. Gillquist, S. Y. Holm, J. D. Olsen, S. Jain, and K. G. Lurie. 2014. Awakening after cardiac arrest and post resuscitation hypothermia: Are we pulling the plug too early? Resuscitation 85(2):211-214.
Goldberger, Z. D., B. K. Nallamothu, G. Nichol, P. S. Chan, J. R. Curtis, and C. R. Cooke. 2015. Policies allowing family presence during resuscitation and patterns of care during in-hospital cardiac arrest. Circulation: Cardiovascular Quality and Outcomes 8(3):226-234.
Gordon, M., D. Darbyshire, and P. Baker. 2012. Non-technical skills training to enhance patient safety: A systematic review. Medical Education 46(11): 1042-1054.
Groeneveld, P. W., P. A. Heidenreich, and A. M. Garber. 2003. Racial disparity in cardiac procedures and mortality among long-term survivors of cardiac arrest. Circulation 108(3):286-291.
Halasyamani, L., S. Kripalani, E. Coleman, J. Schnipper, C. van Walraven, J. Nagamine, P. Torcson, T. Bookwalter, T. Budnitz, and D. Manning. 2006. Transition of care for hospitalized elderly patients—development of a discharge checklist for hospitalists. Journal of Hospital Medicine 1(6):354-360.
Hayes, C. W., A. Rhee, M. E. Detsky, V. R. Leblanc, and R. S. Wax. 2007. Residents feel unprepared and unsupervised as leaders of cardiac arrest teams in teaching hospitals: A survey of internal medicine residents. Critical Care Medicine 35(7):1668-1672.
Henderson, D. P., and J. F. Knapp. 2005. Report of the national consensus conference on family presence during pediatric cardiopulmonary resuscitation and procedures. Pediatric Emergency Care 21(11):787-791.
Heyland, D. K., C. Frank, D. Groll, D. Pichora, P. Dodek, G. Rocker, and A. Gafni. 2006. Understanding cardiopulmonary resuscitation decision making: Perspectives of seriously ill hospitalized patients and family members. CHEST Journal 130(2):419-428.
Hoffman, T. M., G. Wernovsky, A. M. Atz, T. J. Kulik, D. P. Nelson, A. C. Chang, J. M. Bailey, A. Akbary, J. F. Kocsis, R. Kaczmarek, T. L. Spray, and D. L. Wessel. 2003. Efficacy and safety of milrinone in preventing low cardiac output syndrome in infants and children after corrective surgery for congenital heart disease. Circulation 107(7):996-1002.
Hunt, E. A., K. P. Zimmer, M. L. Rinke, N. A. Shilkofski, C. Matlin, C. Garger, C. Dickson, and M. R. Miller. 2008. Transition from a traditional code team to a medical emergency team and categorization of cardiopulmonary arrests in a children’s center. Archives of Pediatric and Adolescent Medicine 162(2):117-122.
Hunziker, S., C. Buhlmann, F. Tschan, G. Balestra, C. Legeret, C. Schumacher, N. K. Semmer, P. Hunziker, and S. Marsch. 2010. Brief leadership instructions improve cardiopulmonary resuscitation in a high-fidelity simulation: A randomized controlled trial. Critical Care Medicine 38(4):1086-1091.
Hunziker, S., A. C. Johansson, F. Tschan, N. K. Semmer, L. Rock, M. D. Howell, and S. Marsch. 2011. Teamwork and leadership in cardiopulmonary resuscitation. Journal of the American College of Cardiology 57(24):2381-2388.
Hutchison, J. S., R. E. Ward, J. Lacroix, P. C. Hebert, M. A. Barnes, D. J. Bohn, and P. W. Skippen. 2008. Hypothermia therapy after traumatic brain injury in children. New England Journal of Medicine 358(23):2447-2456.
Hypothermia After Cardiac Arrest Study Group. 2002. Mild therapeutic hypothermia to improve the neurologic outcome after cardiac arrest. New England Journal of Medicine 346(8):549-556.
Idris, A. H., D. Guffey, T. P. Aufderheide, S. Brown, L. J. Morrison, P. Nichols, J. Powell, M. Daya, B. L. Bigham, D. L. Atkins, R. Berg, D. Davis, I. Stiell, G. Sopko, and G. Nichol. 2012. Relationship between chest compression rates and outcomes from cardiac arrest. Circulation 125(24):3004-3012.
IOM (Institute of Medicine). 2003. Unequal treatment: Confronting racial and ethnic disparities in health care. Washington, DC: The National Academies Press.
IOM. 2015. Dying in America: Improving quality and honoring individual preferences near the end of life. Washington, DC: The National Academies Press.
Jackson, E. A., J. L. Yarzebski, R. J. Goldberg, B. Wheeler, J. H. Gurwitz, D. M. Lessard, S. E. Bedell, and J. M. Gore. 2004. Do-not-resuscitate orders in patients hospitalized with acute myocardial infarction: The Worcester Heart Attack Study. Archives of Internal Medicine 164(7):776-783.
Jankouskas, T. S., K. K. Haidet, J. E. Hupcey, A. Kolanowski, and W. B. Murray. 2011. Targeted crisis resource management training improves performance among randomized nursing and medical students. Simulation in Healthcare 6(6):316-326.
Jayaram, N., J. A. Spertus, V. Nadkarni, R. A. Berg, F. Tang, T. Raymond, A. M. Guerguerian, and P. S. Chan. 2014. Hospital variation in survival after pediatric in-hospital cardiac arrest. Circulation: Cardiovascular Quality and Outcomes 7(4):517-523.
The Joint Commission. 2007. Hospital accreditation standards. http://www.resuscitationcentral.com/documentation/jcaho-health-care-hospital-accreditation (accessed June 19, 2015)
The Joint Commission. 2011. Sudden Cardiac Arrest: Meeting the Challenge. http://www.jointcommission.org/assets/1/6/Sudden_Cardiac_Arrest-final_2.pdf (accessed April 1, 2015).
The Joint Commission. 2014. Sudden cardiac arrest initiatives. http://www.jointcommission.org/sudden_cardiac_arrest_initiatives (accessed June 19, 2015).
The Joint Commision. 2015. Facts about primary stroke center certification. http://www.jointcommission.org/facts_about_primary_stroke_center_certification (accessed June 19, 2015).
Joshi, M. S., and D. B. Bernard. 1999. Clinical performance improvement series. Classic CQI integrated with comprehensive disease management as a model for performance improvement. Joint Commission Journal on Quality Improvement 25(8):383-395.
Joynt, K. E., D. M. Blumenthal, E. Orav, F. S. Resnic, and A. K. Jha. 2012. Association of public reporting for percutaneous coronary intervention with utilization and outcomes among Medicare beneficiaries with acute
myocardial infarction. Journal of the American Medical Association 308(14):1460-1468.
Kamps, M. J., J. Horn, M. Oddo, J. E. Fugate, C. Storm, T. Cronberg, C. A. Wijman, O. Wu, J. M. Binnekade, and C. W. Hoedemaekers. 2013. Prognostication of neurologic outcome in cardiac arrest patients after mild therapeutic hypothermia: A meta-analysis of the current literature. Intensive Care Medicine 39(10):1671-1682.
Kern, J. H., C. J. Hayes, R. E. Michler, W. M. Gersony, and J. M. Quaegebeur. 1997a. Survival and risk factor analysis for the Norwood procedure for hypoplastic left heart syndrome. American Journal of Cardiology 80(2):170-174.
Kern, K. B. 2012. Optimal treatment of patients surviving out-of-hospital cardiac arrest. JACC: Cardiovascular Interventions 5(6):597-605.
Kern, K. B., R. W. Hilwig, R. A. Berg, K. H. Rhee, A. B. Sanders, C. W. Otto, and G. A. Ewy. 1997b. Postresuscitation left ventricular systolic and diastolic dysfunction. Treatment with dobutamine. Circulation 95(12): 2610-2613.
Kilgannon, J. H., A. E. Jones, J. E. Parrillo, R. P. Dellinger, B. Milcarek, K. Hunter, N. I. Shapiro, and S. Trzeciak. 2011. Relationship between supranormal oxygen tension and outcome after resuscitation from cardiac arrest. Circulation 123(23):2717-2722.
Kleinman, M. E., L. Chameides, S. M. Schexnayder, R. A. Samson, M. F. Hazinski, D. L. Atkins, M. D. Berg, A. R. de Caen, E. L. Fink, E. B. Freid, R. W. Hickey, B. S. Marino, V. M. Nadkarni, L. T. Proctor, F. A. Qureshi, K. Sartorelli, A. Topjian, E. W. van der Jagt, and A. L. Zaritsky. 2010a. Part 14: Pediatric advanced life support: 2010 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation 122(18 Suppl 3):S876-S908.
Kleinman, M. E., A. R. de Caen, L. Chameides, D. L. Atkins, R. A. Berg, M. D. Berg, F. Bhanji, D. Biarent, R. Bingham, A. H. Coovadia, M. F. Hazinski, R. W. Hickey, V. M. Nadkarni, A. G. Reis, A. Rodriguez-Nunez, J. Tibballs, A. L. Zaritsky, and D. Zideman. 2010b. Part 10: Pediatric basic and advanced life support: 2010 international consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations. Circulation 122(16 Suppl 2):S466-S515.
Knafelj, R., P. Radsel, T. Ploj, and M. Noc. 2007. Primary percutaneous coronary intervention and mild induced hypothermia in comatose survivors of ventricular fibrillation with ST-elevation acute myocardial infarction. Resuscitation 74:227-234.
Kramer, D. B., and S. L. Mitchell. 2013. Weighing the benefits and burdens of witnessed resuscitation. New England Journal of Medicine 368(11):1058-1059.
Langhelle, A., S. S. Tyvold, K. Lexow, S. A. Hapnes, K. Sunde, and P. A. Steen. 2003. In-hospital factors associated with improved outcome after out-of-hospital cardiac arrest. A comparison between four regions in Norway. Resuscitation 56(3):247-263.
Laurent, I., M. Monchi, J. D. Chiche, L. M. Joly, C. Spaulding, B. Bourgeois, A. Cariou, A. Rozenberg, P. Carli, S. Weber, and J. F. Dhainaut. 2002. Reversible myocardial dysfunction in survivors of out-of-hospital cardiac arrest. Journal of the American College of Cardiology 40(12):2110-2116.
Laver, S., C. Farrow, D. Turner, and J. Nolan. 2004. Mode of death after admission to an intensive care unit following cardiac arrest. Intensive Care Medicine 30(11):2126-2128.
Ludikhuize, J., M. Borgert, J. Binnekade, C. Subbe, D. Dongelmans, and A. Goossens. 2014. Standardized measurement of the Modified Early Warning Score results in enhanced implementation of a Rapid Response System: A quasi-experimental study. Resuscitation 85(5):676-682.
Lurie, K. G., A. Idris, and J. B. Holcomb. 2005. Level 1 cardiac arrest centers: Learning from the trauma surgeons. Academic Emergency Medicine 12(1):79-80.
MacKenzie, E. J., F. P. Rivara, G. J. Jurkovich, A. B. Nathens, K. P. Frey, B. L. Egleston, D. S. Salkever, and D. O. Scharfstein. 2006. A national evaluation of the effect of trauma-center care on mortality. New England Journal of Medicine 354(4):366-378.
Mader, T. J., B. H. Nathanson, W. E. Soares, 3rd, R. A. Coute, and B. F. McNally. 2014. Comparative effectiveness of therapeutic hypothermia after out-of-hospital cardiac arrest: Insight from a large data registry. Therapeutic Hypothermia and Temperature Management 4(1):21-31.
Mancini, M. E., J. Soar, F. Bhanji, J. E. Billi, J. Dennett, J. Finn, M. H. Ma, G. D. Perkins, D. L. Rodgers, M. F. Hazinski, I. Jacobs, and P. T. Morley. 2010. Part 12: Education, implementation, and teams: 2010 international consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations. Circulation 122(16 Suppl 2):S539-S581.
Manser, T. 2009. Teamwork and patient safety in dynamic domains of healthcare: A review of the literature. Acta Anaesthesiologica Scandinavica 53(2):143-151.
McInnes, A. D., R. M. Sutton, A. Orioles, A. Nishisaki, D. Niles, B. S. Abella, M. R. Maltese, R. A. Berg, and V. Nadkarni. 2011. The first quantitative report of ventilation rate during in-hospital resuscitation of older children and adolescents. Resuscitation 82(8):1025-1029.
Meaney, P. A., V. M. Nadkarni, K. B. Kern, J. H. Indik, H. R. Halperin, and R. A. Berg. 2010. Rhythms and outcomes of adult in-hospital cardiac arrest. Critical Care Medicine 38:101-108.
Meaney, P. A., B. J. Bobrow, M. E. Mancini, J. Christenson, A. R. de Caen, F. Bhanji, B. S. Abella, M. E. Kleinman, D. P. Edelson, R. A. Berg, T. P. Aufderheide, V. Menon, and M. Leary. 2013. Cardiopulmonary resuscitation quality: Improving cardiac resuscitation outcomes both inside and outside the hospital: A consensus statement from the American Heart Association. Circulation 128(4):417-435.
Mentzelopoulos, S. D., S. Malachias, C. Chamos, D. Konstantopoulos, T. Ntaidou, A. Papastylianou, I. Kolliantzaki. 2013. Vasopressin, steroids, and epinephrine and neurologically favorable survival after in-hospital cardiac arrest: A randomized clinical trial. JAMA 310(3):270-279.
Merchant, R. M., L. B. Becker, B. S. Abella, D. A. Asch, and P. W. Groeneveld. 2009. Cost-effectiveness of therapeutic hypothermia after cardiac arrest. Circulation: Cardiovascular Quality and Outcomes 2(5):421-428.
Merchant, R. M., L. Yang, L. B. Becker, R. A. Berg, V. Nadkarni, G. Nichol, B. G. Carr, N. Mitra, S. M. Bradley, B. S. Abella, and P. W. Groeneveld. 2011. Incidence of treated cardiac arrest in hospitalized patients in the United States. Critical Care Medicine 39(11):2401-2406.
Moore, C., J. Wisnivesky, S. Williams, and T. McGinn. 2003. Medical errors related to discontinuity of care from an inpatient to an outpatient setting. Journal of General Internal Medicine 18(8):646-651.
Morrison, L. J., G. Kierzek, D. S. Diekema, M. R. Sayre, S. M. Silvers, A. H. Idris, and M. E. Mancini. 2010. Part 3: Ethics: 2010 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation 122(18 Suppl 3):S665-S675.
Morrison, L. J., R. W. Neumar, J. L. Zimmerman, M. S. Link, L. K. Newby, P. W. McMullan, Jr., T. V. Hoek, C. C. Halverson, L. Doering, M. A. Peberdy, and D. P. Edelson. 2013. Strategies for improving survival after in-hospital cardiac arrest in the United States: 2013 consensus recommendations: A consensus statement from the American Heart Association. Circulation 127(14):1538-1563.
Myerburg, R. J. 2014. Initiatives for improving out-of-hospital cardiac arrest outcomes. Circulation 130(21):1840-1843.
Nadkarni, V. M., G. L. Larkin, M. A. Peberdy, S. M. Carey, W. Kaye, M. E. Mancini, G. Nichol, T. Lane-Truitt, J. Potts, J. P. Ornato, and R. A. Berg. 2006. First documented rhythm and clinical outcome from in-hospital cardiac arrest among children and adults. Journal of the American Medical Association 295(1):50-57.
Neumar, R. W. 2015. Letter to IOM Committee on Treatment of Cardiac Arrest. http://www8.nationalacademies.org/cp/ManageRequest.aspx?key=49604 (accessed April 1, 2015).
Neumar, R. W., J. P. Nolan, C. Adrie, M. Aibiki, R. A. Berg, B. W. Bottiger, C. Callaway, R. S. Clark, R. G. Geocadin, E. C. Jauch, K. B. Kern, I. Laurent, W. T. Longstreth, Jr., R. M. Merchant, P. Morley, L. J. Morrison, V. Nadkarni, M. A. Peberdy, E. P. Rivers, A. Rodriguez-Nunez, F. W. Sellke, C. Spaulding, K. Sunde, and T. Vanden Hoek. 2008. Post-cardiac arrest syndrome: Epidemiology, pathophysiology, treatment, and prognostication. A consensus statement from the International Liaison Committee on Resuscitation (American Heart Association, Australian and New Zealand Council on Resuscitation, European Resuscitation Council, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation,
Resuscitation Council of Asia, and the Resuscitation Council of Southern Africa); the American Heart Association Emergency Cardiovascular Care Committee; the Council on Cardiovascular Surgery and Anesthesia; the Council on Cardiopulmonary, Perioperative, and Critical Care; the Council on Clinical Cardiology; and the Stroke Council. Circulation 118(23):2452-2483.
Nichol, G., T. P. Aufderheide, B. Eigel, R. W. Neumar, K. G. Lurie, V. J. Bufalino, C. W. Callaway, V. Menon, R. R. Bass, B. S. Abella, M. Sayre, C. M. Dougherty, E. M. Racht, M. E. Kleinman, R. E. O’Connor, J. P. Reilly, E. W. Ossmann, and E. Peterson. 2010. Regional systems of care for out-of-hospital cardiac arrest: A policy statement from the American Heart Association. Circulation 121(5):709-729.
Nishisaki, A., J. Sullivan, 3rd, B. Steger, C. R. Bayer, D. Dlugos, R. Lin, R. Ichord, M. A. Helfaer, and V. Nadkarni. 2007. Retrospective analysis of the prognostic value of electroencephalography patterns obtained in pediatric in-hospital cardiac arrest survivors during three years. Pediatric Critical Care Medicine 8(1):10-17.
Nolan, J. P., R. W. Neumar, C. Adrie, M. Aibiki, R. A. Berg, B. W. Bottiger, C. Callaway, R. S. Clark, R. G. Geocadin, E. C. Jauch, K. B. Kern, I. Laurent, W. T. Longstreth, R. M. Merchant, P. Morley, L. J. Morrison, V. Nadkarni, M. A. Peberdy, E. P. Rivers, A. Rodriguez-Nunez, F. W. Sellke, C. Spaulding, K. Sunde, and T. V. Hoek. 2008. Post-cardiac arrest syndrome: Epidemiology, pathophysiology, treatment, and prognostication. A scientific statement from the International Liaison Committee on Resuscitation; the American Heart Association Emergency Cardiovascular Care Committee; the Council on Cardiovascular Surgery and Anesthesia; the Council on Cardiopulmonary, Perioperative, and Critical Care; the Council on Clinical Cardiology; the Council on Stroke. Resuscitation 79(3):350-379.
Nolan, J. P., J. Soar, D. A. Zideman, D. Biarent, L. L. Bossaert, C. Deakin, R. W. Koster, J. Wyllie, and B. Bottiger. 2010. European Resuscitation Council guidelines for resuscitation 2010 section 1. Executive summary. Resuscitation 81(10):1219-1276.
Norris, E. M., and A. S. Lockey. 2012. Human factors in resuscitation teaching. Resuscitation 83(4):423-427.
Okada, K., S. Ohde, N. Otani, T. Sera, T. Mochizuki, M. Aoki, and S. Ishimatsu. 2012. Prediction protocol for neurologic outcome for survivors of out-of-hospital cardiac arrest treated with targeted temperature management. Resuscitation 83(6):734-739.
Oksanen, T., M. B. Skrifvars, T. Varpula, A. Kuitunen, V. Pettila, J. Nurmi, and M. Castren. 2007. Strict versus moderate glucose control after resuscitation from ventricular fibrillation. Intensive Care Medicine 33(12):2093-2100.
Ornato, J. P., and M. A. Peberdy. 2014. Applying lessons from commercial aviation safety and operations to resuscitation. Resuscitation 85(2):173-176.
Ornato, J. P., M. A. Peberdy, R. D. Reid, V. R. Feeser, and H. S. Dhindsa. 2012. Impact of resuscitation system errors on survival from in-hospital cardiac arrest. Resuscitation 83(1):63-69.
Parshuram, C. S., H. P. Duncan, A. R. Joffe, C. A. Farrell, J. R. Lacroix, K. L. Middaugh, J. S. Hutchison, D. Wensley, N. Blanchard, J. Beyene, and P. C. Parkin. 2011. Multicentre validation of the bedside paediatric early warning system score: A severity of illness score to detect evolving critical illness in hospitalised children. Critical Care 15(4):R184.
Pasalic, D., T. H. Tajouri, A. L. Ottenberg, and P. S. Mueller. 2014. The prevalence and contents of advance directives in patients with pacemakers. Pacing and Clinical Electrophysiology 37(4):473-480.
Peake, S. L., A. Delaney, M. Bailey, R. Bellomo, P. A. Cameron, D. J. Cooper, A. M. Higgins, A. Holdgate, B. D. Howe, S. A. Webb, and P. Williams. 2014. Goal-directed resuscitation for patients with early septic shock. New England Journal of Medicine 371(16):1496.
Peberdy, M. A., M. Cretikos, B. S. Abella, M. DeVita, D. Goldhill, W. Kloeck, S. L. Kronick, L. J. Morrison, V. M. Nadkarni, G. Nichol, J. P. Nolan, M. Parr, J. Tibballs, E. W. van der Jagt, and L. Young. 2007. Recommended guidelines for monitoring, reporting, and conducting research on medical emergency team, outreach, and rapid response systems: An Utstein-Style scientific statement: A scientific statement from the International Liaison Committee on Resuscitation (American Heart Association, Australian Resuscitation Council, European Resuscitation Council, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation, Resuscitation Council of Southern Africa, and the New Zealand Resuscitation Council); the American Heart Association Emergency Cardiovascular Care Committee; the Council on Cardiopulmonary, Perioperative, and Critical Care; and the Interdisciplinary Working Group on Quality of Care and Outcomes Research. Circulation 116(21):2481-2500.
Peberdy, M. A., C. W. Callaway, R. W. Neumar, R. G. Geocadin, J. L. Zimmerman, M. Donnino, A. Gabrielli, S. M. Silvers, A. L. Zaritsky, R. Merchant, T. L. Vanden Hoek, and S. L. Kronick; for the American Heart Association. 2010. Part 9: Post-cardiac arrest care: 2010 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation 122(18 Suppl 3):S768-S786.
Peberdy, M. A., M. W. Donnino, C. W. Callaway, J. M. DiMaio, R. G. Geocadin, C. A. Ghaemmaghami, A. K. Jacobs, K. B. Kern, J. H. Levy, M. S. Link, V. Menon, J. P. Ornato, D. S. Pinto, J. Sugarman, J. Yannopoulos, and T. B. Ferguson. 2013. Impact of percutaneous coronary intervention performance reporting on cardiac resuscitation centers: A scientific statement from the American Heart Association. Circulation 128(7):762-773.
Perondi, M. B., A. G. Reis, E. F. Paiva, V. M. Nadkarni, and R. A. Berg. 2004. A comparison of high-dose and standard-dose epinephrine in children with cardiac arrest. New England Journal of Medicine 350(17):1722-1730.
Prohl, J., J. Rother, S. Kluge, G. de Heer, J. Liepert, S. Bodenburg, K. Pawlik, and G. Kreymann. 2007. Prediction of short-term and long-term outcomes after cardiac arrest: A prospective multivariate approach combining biochemical, clinical, electrophysiological, and neuropsychological investigations. Critical Care Medicine 35(5):1230-1237.
Puttgen, H. A., H. Pantle, and R. G. Geocadin. 2009. Management of cardiac arrest patients to maximize neurologic outcome. Current Opinion in Critical Care 15(2):118-124.
Rabi, Y., D. Rabi, and W. Yee. 2007. Room air resuscitation of the depressed newborn: A systematic review and meta-analysis. Resuscitation 72(3):353-363.
Randhawa, S., R. Roberts-Turner, K. Woronick, and J. DuVal. 2011. Implementing and sustaining evidence-based nursing practice to reduce pediatric cardiopulmonary arrest. Western Journal of Nursing Research 33(3):443-456.
Reis, A. G., V. Nadkarni, M. B. Perondi, S. Grisi, and R. A. Berg. 2002. A prospective investigation into the epidemiology of in-hospital pediatric cardiopulmonary resuscitation using the international Utstein reporting style. Pediatrics 109(2):200-209.
Resuscitation Central. 2010. Impendance threshold devices. http://www.resuscitationcentral.com/ventilation/impedance-threshold-device (accessed June 19, 2015).
Resuscitation Council (UK). 2013. Quality standards for cardiopulmonary resuscitation practice and training acute care. https://www.resus.org.uk/quality-standards/acute-care-quality-standards-for-cpr/ (accessed August 3, 2015).
Revere, A. 2008. Joint Commision national patient safety goals for 2008. Topics in Patient Safety 12(1). http://www.patientsafety.va.gov/docs/TIPS/TIPS_JanFeb08.pdf (accessed August 3, 2015).
Richards, E. M., G. Fiskum, R. E. Rosenthal, I. Hopkins, and M. C. McKenna. 2007. Hyperoxic reperfusion after global ischemia decreases hippocampal energy metabolism. Stroke 38(5):1578-1584.
Richardson, D. K., D. Zive, M. Daya, and C. D. Newgard. 2013. The impact of early do not resuscitate (DNR) orders on patient care and outcomes following resuscitation from out of hospital cardiac arrest. Resuscitation 84(4):483-487.
Riker, R. R., and J. E. Fugate. 2014. Clinical monitoring scales in acute brain injury: Assessment of coma, pain, agitation, and delirium. Neurocritical Care 21 (Suppl 2):S27-S37.
Rittenberger, J. C., K. Raina, M. B. Holm, Y. J. Kim, and C. W. Callaway. 2011. Association between cerebral performance category, modified Rankin scale, and discharge disposition after cardiac arrest. Resuscitation 82(8):1036-1040.
Rivers, E. P., D. S. Ander, and D. Powell. 2001. Central venous oxygen saturation monitoring in the critically ill patient. Current Opinion in Critical Care 7(3):204-211.
Roberts, R., and A. F. Stewart. 2012. Genetics of coronary artery disease in the 21st century. Clinical Cardiology 35(9):536-540.
Rubinstein, W. S., D. R. Maglott, J. M. Lee, B. L. Kattman, A. J. Malheiro, M. Ovetsky, V. Hem, V. Gorelenkov, G. Song, C. Wallin, N. Husain, S. Chitipiralla, K. S. Katz, D. Hoffman, W. Jang, M. Johnson, F. Karmanov, A. Ukrainchik, M. Denisenko, C. Fomous, K. Hudson, and J. M. Ostell. 2013. The NIH genetic testing registry: A new, centralized database of genetic tests to enable access to comprehensive information and improve transparency. Nucleic Acids Research 41(Database issue):D925-D935.
Rundgren, M., I. Rosen, and H. Friberg. 2006. Amplitude-integrated EEG (AEEG) predicts outcome after cardiac arrest and induced hypothermia. Intensive Care Medicine 32(6):836-842.
Rundgren, M., E. Westhall, T. Cronberg, I. Rosen, and H. Friberg. 2010. Continuous amplitude-integrated electroencephalogram predicts outcome in hypothermia-treated cardiac arrest patients. Critical Care Medicine 38(9):1838-1844.
Salas, E., D. DiazGranados, C. Klein, C. S. Burke, K. C. Stagl, G. F. Goodwin, and S. M. Halpin. 2008. Does team training improve team performance? A meta-analysis. Human Factors 50(6):903-933.
Salas, E., S. A. Almeida, M. Salisbury, H. King, E. H. Lazzara, R. Lyons, K. A. Wilson, P. A. Almeida, and R. McQuillan. 2009. What are the critical success factors for team training in health care? Joint Commission Journal of Quality and Patient Safety 35(8):398-405.
Salottolo, K., P. J. Offner, A. Orlando, D. S. Slone, C. W. Mains, M. Carrick, and D. Bar-Or. 2015. The epidemiology of do-not-resuscitate orders in patients with trauma: a community level one trauma center observational experience. Scandinavian Journal of Trauma and Resuscitation Emergency Medicine 23(1):9.
Schefold, J. C., C. Storm, A. Kruger, C. J. Ploner, and D. Hasper. 2009. The Glasgow coma score is a predictor of good outcome in cardiac arrest patients treated with therapeutic hypothermia. Resuscitation 80(6):658-661.
Schmutz, J., and T. Manser. 2013. Do team processes really have an effect on clinical performance? A systematic literature review. British Journal of Anaesthesia 110(4):529-544.
Schouten, L. M., M. E. Hulscher, J. J. van Everdingen, R. Huijsman, and R. P. Grol. 2008. Evidence for the impact of quality improvement collaboratives: Systematic review. British Medical Journal 336(7659):1491-1494.
Shankaran, S., A. R. Laptook, R. A. Ehrenkranz, J. E. Tyson, S. A. McDonald, E. F. Donovan, A. A. Fanaroff, W. K. Poole, L. L. Wright, R. D. Higgins, N. N. Finer, W. A. Carlo, S. Duara, W. Oh, C. M. Cotten, D. K. Stevenson, B. J. Stoll, J. A. Lemons, R. Guillet, and A. H. Jobe. 2005. Whole-body
hypothermia for neonates with hypoxic-ischemic encephalopathy. New England Journal of Medicine 353(15):1574-1584.
Share, D. A., D. A. Campbell, N. Birkmeyer, R. L. Prager, H. S. Gurm, M. Moscucci, M. Udow-Phillips, and J. D. Birkmeyer. 2011. How a regional collaborative of hospitals and physicians in Michigan cut costs and improved the quality of care. Health Affairs 30(4):636-645.
Sharek, P. J., L. M. Parast, K. Leong, J. Coombs, K. Earnest, J. Sullivan, L. R. Frankel, and S. J. Roth. 2007. Effect of a rapid response team on hospital-wide mortality and code rates outside the ICU in a children’s hospital. Journal of the American Medical Association 298(19):2267-2274.
Singh, J. M., and R. D. MacDonald. 2009. Pro/con debate: Do the benefits of regionalized critical care delivery outweigh the risks of interfacility patient transport? Critical Care 13(4):219.
Sirbaugh, P. E., P. E. Pepe, J. E. Shook, K. T. Kimball, M. J. Goldman, M. A. Ward, and D. M. Mann. 1999. A prospective, population-based study of the demographics, epidemiology, management, and outcome of out-of-hospital pediatric cardiopulmonary arrest. Annals of Emergency Medicine 33(2):174-184.
Snow, V., D. Beck, T. Budnitz, D. C. Miller, J. Potter, R. L. Wears, K. B. Weiss, and M. V. Williams. 2009. Transitions of care consensus policy statement: American College of Physicians, Society of General Internal Medicine, Society of Hospital Medicine, American Geriatrics Society, American College of Emergency Physicians, and Society for Academic Emergency Medicine. Journal of Hospital Medicine 4(6):364-370.
Spaite, D. W., B. J. Bobrow, U. Stolz, R. A. Berg, A. B. Sanders, K. B. Kern, V. Chikani, W. Humble, T. Mullins, J. S. Stapczynski, and G. A. Ewy. 2014. Statewide regionalization of postarrest care for out-of-hospital cardiac arrest: Association with survival and neurologic outcome. Annals of Emergency Medicine 64(5):496-506.
Stammet, P., C. Werer, L. Mertens, C. Lorang, and M. Hemmer. 2009. Bispectral index (BIS) helps predicting bad neurologic outcome in comatose survivors after cardiac arrest and induced therapeutic hypothermia. Resuscitation 80(4):437-442.
Stammet, P., D. R. Wagner, G. Gilson, and Y. Devaux. 2013. Modeling serum level of s100beta and bispectral index to predict outcome after cardiac arrest. Journal of the American College of Cardiology 62(9):851-858.
Stanley, A., D. DeLia, and J. C. Cantor. 2007. Racial disparity and technology diffusion: the case of cardioverter defibrillator implants, 1996-2001. Journal of the National Medical Association 99(3):201-207.
Stiell, I. G., S. P. Brown, G. Nichol, S. Cheskes, C. Vaillancourt, C. W. Callaway, L. J. Morrison, J. Christenson, T. P. Aufderheide, D. P. Davis, C. Free, D. Hostler, J. A. Stouffer, and A. H. Idris. 2014. What is the optimal chest compression depth during out-of-hospital cardiac arrest resuscitation of adult patients? Circulation 130(22):1962-1970.
Sullivan, N. J., J. Duval-Arnould, M. Twilley, S. P. Smith, D. Aksamit, P. Boone-Guercio, P. R. Jeffries, and E. A. Hunt. 2014. Simulation exercise to improve retention of cardiopulmonary resuscitation priorities for in-hospital cardiac arrests: A randomized controlled trial. Resuscitation 86:6-13.
Sunde, K., M. Pytte, D. Jacobsen, A. Mangschau, L. P. Jensen, C. Smedsrud, T. Draegni, and P. A. Steen. 2007. Implementation of a standardised treatment protocol for post resuscitation care after out-of-hospital cardiac arrest. Resuscitation 73(1):29-39.
Sutton, R. M., D. Niles, J. Nysaether, B. S. Abella, K. B. Arbogast, A. Nishisaki, M. R. Maltese, A. Donoghue, R. Bishnoi, M. A. Helfaer, H. Myklebust, and V. Nadkarni. 2009. Quantitative analysis of CPR quality during in-hospital resuscitation of older children and adolescents. Pediatrics 124(2):494-499.
Sutton, R. M., H. Wolfe, A. Nishisaki, J. Leffelman, D. Niles, P. A. Meaney, A. Donoghue, M. R. Maltese, R. A. Berg, and V. M. Nadkarni. 2013. Pushing harder, pushing faster, minimizing interruptions... But falling short of 2010 cardiopulmonary resuscitation targets during in-hospital pediatric and adolescent resuscitation. Resuscitation 84(12):1680-1684.
Sutton, R. M., S. H. Friess, M. R. Maltese, M. Y. Naim, G. Bratinov, T. R. Weiland, M. Garuccio, U. Bhalala, V. M. Nadkarni, L. B. Becker, and R. A. Berg. 2014a. Hemodynamic-directed cardiopulmonary resuscitation during in-hospital cardiac arrest. Resuscitation 85(8):983-986.
Sutton, R. M., S. H. Friess, M. Y. Naim, J. W. Lampe, G. Bratinov, T. R. Weiland, 3rd, M. Garuccio, V. M. Nadkarni, L. B. Becker, and R. A. Berg. 2014b. Patient-centric blood pressure-targeted cardiopulmonary resuscitation improves survival from cardiac arrest. American Journal of Respiratory Critical Care Medicine 190(11):1255-1262.
Tajouri, T. H., A. L. Ottenberg, D. L. Hayes, and P. S. Mueller. 2012. The use of advance directives among patients with implantable cardioverter defibrillators. Pacing and Clinical Electrophysiology 35(5):567-573.
Temel, J. S., J. A. Greer, A. Muzikansky, E. R. Gallagher, S. Admane, V. A. Jackson, C. M. Dahlin, C. D. Blinderman, J. Jacobsen, W. F. Pirl, J. A. Billings, and T. J. Lynch. 2010. Early palliative care for patients with metastatic non-small-cell lung cancer. New England Journal of Medicine 363(8):733-742.
Thomas, E. J., B. Taggart, S. Crandell, R. E. Lasky, A. L. Williams, L. J. Love, J. B. Sexton, J. E. Tyson, and R. L. Helmreich. 2007a. Teaching teamwork during the neonatal resuscitation program: a randomized trial. Journal of Perinatology 27(7):409-414.
Thomas, K., M. VanOyen Force, D. Rasmussen, D. Dodd, and S. Whildin. 2007b. Rapid response team: Challenges, solutions, benefits. Critical Care Nurse 27(1):20-27; quiz 28.
Tibballs, J., and S. Kinney. 2009. Reduction of hospital mortality and of preventable cardiac arrest and death on introduction of a pediatric medical emergency team. Pediatric Critical Care Medicine 10(3):306-312.
Topcuoglu, M. A., K. K. Oguz, G. Buyukserbetci, and E. Bulut. 2009. Prognostic value of magnetic resonance imaging in post-resuscitation encephalopathy. Internal Medicine 48(18):1635-1645.
Topjian, A. A., B. French, R. M. Sutton, T. Conlon, V. M. Nadkarni, F. W. Moler, J. M. Dean, and R. A. Berg. 2014a. Early postresuscitation hypotension is associated with increased mortality following pediatric cardiac arrest. Critical Care Medicine 42(6):1518-1523.
Topjian, A. A., A. Stuart, A. A. Pabalan, A. Clair, T. J. Kilbaugh, N. S. Abend, P. B. Storm, R. A. Berg, J. W. Huh, and S. H. Friess. 2014b. Greater fluctuations in serum sodium levels are associated with increased mortality in children with externalized ventriculostomy drains in a PICU. Pediatric Critical Care Medicine 15(9):846-855.
Torbey, M. T., R. Geocadin, and A. Bhardwaj. 2004. Brain arrest neurologic outcome scale (BRANOS): Predicting mortality and severe disability following cardiac arrest. Resuscitation 63(1):55-63.
Van Diepen, S., B. S. Abella, B. J. Bobrow, G. Nichol, J. G. Jollis, J. Mellor, E. M. Racht, D. Yannopoulos, C. B. Granger, and M. R. Sayre. 2013. Multistate implementation of guideline-based cardiac resuscitation systems of care: Description of the HeartRescue Project. American Heart Journal 166(4):647-653.e642.
Vasquez, A., K. B. Kern, R. W. Hilwig, J. Heidenreich, R. A. Berg, and G. A. Ewy. 2004. Optimal dosing of dobutamine for treating post-resuscitation left ventricular dysfunction. Resuscitation 61(2):199-207.
Vlasselaers, D., I. Milants, L. Desmet, P. J. Wouters, I. Vanhorebeek, I. van den Heuvel, D. Mesotten, M. P. Casaer, G. Meyfroidt, C. Ingels, J. Muller, S. Van Cromphaut, M. Schetz, and G. Van den Berghe. 2009. Intensive insulin therapy for patients in paediatric intensive care: A prospective, randomised controlled study. Lancet 373(9663):547-556.
Warren, S. A., E. Huszti, S. M. Bradley, P. S. Chan, C. L. Bryson, A. L. Fitzpatrick, and G. Nichol. 2014. Adrenaline (epinephrine) dosing period and survival after in-hospital cardiac arrest: a retrospective review of prospectively collected data. Resuscitation 85(3):350-358.
Wayne, D. B., A. Didwania, J. Feinglass, M. J. Fudala, J. H. Barsuk, and W. C. McGaghie. 2008. Simulation-based education improves quality of care during cardiac arrest team responses at an academic teaching hospital: A case-control study. Chest Journal 133(1):56-61.
Weaver, S. J., S. M. Dy, and M. A. Rosen. 2014. Team-training in healthcare: A narrative synthesis of the literature. British Medical Journal of Quality and Safety 23(5):359-372.
Wiener, R. S., D. C. Wiener, and R. J. Larson. 2008. Benefits and risks of tight glucose control in critically ill adults: A meta-analysis. Journal of the American Medical Association 300(8):933-944.
Wijman, C. A., M. Mlynash, A. F. Caulfield, A. W. Hsia, I. Eyngorn, R. Bammer, N. Fischbein, G. W. Albers, and M. Moseley. 2009. Prognostic value of
brain diffusion-weighted imaging after cardiac arrest. Annals of Neurology 65(4):394-402.
Wilson, M. E., A. Krupa, R. F. Hinds, J. M. Litell, K. M. Swetz, A. Akhoundi, R. Kashyap, O. Gajic, and K. Kashani. 2015. A video to improve patient and surrogate understanding of cardiopulmonary resuscitation choices in the ICU: a randomized controlled trial. Critical Care Medicine 43(3):621-629.
Winberg, H., K. Nilsson, and A. Aneman. 2008. Paediatric rapid response systems: A literature review. Acta Anaesthesiologica Scandinavica 52(7):890-896.
Wolfe, H., C. Zebuhr, A. A. Topjian, A. Nishisaki, D. E. Niles, P. A. Meaney, L. Boyle, R. T. Giordano, D. Davis, M. Priestley, M. Apkon, R. A. Berg, V. M. Nadkarni, and R. M. Sutton. 2014. Interdisciplinary ICU cardiac arrest debriefing improves survival outcomes. Critical Care Medicine 42(7):1688-1695.
Wright, A. A., B. Zhang, A. Ray, J. W. Mack, E. Trice, T. Balboni, S. L. Mitchell, V. A. Jackson, S. D. Block, P. K. Maciejewski, and H. G. Prigerson. 2008. Associations between end-of-life discussions, patient mental health, medical care near death, and caregiver bereavement adjustment. Journal of the American Medical Association 300(14):1665-1673.
Wu, O., A. G. Sorensen, T. Benner, A. B. Singhal, K. L. Furie, and D. M. Greer. 2009. Comatose patients with cardiac arrest: Predicting clinical outcome with diffusion-weighted MR imaging. Radiology 252(1):173-181.
Yealy, D. M., J. A. Kellum, D. T. Huang, A. E. Barnato, L. A. Weissfeld, F. Pike, T. Terndrup, H. E. Wang, P. C. Hou, F. LoVecchio, M. R. Filbin, N. I. Shapiro, and D. C. Angus. 2014. A randomized trial of protocol-based care for early septic shock. New England Journal of Medicine 370(18):1683-1693.
Zebuhr, C., R. M. Sutton, W. Morrison, D. Niles, L. Boyle, A. Nishisaki, P. Meaney, J. Leffelman, R. A. Berg, and V. M. Nadkarni. 2012. Evaluation of quantitative debriefing after pediatric cardiac arrest. Resuscitation 83(9):1124-1128.