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2 Imperative: Managing Rapidly Increasing Complexity Dr. Charles Bennett, an academic oncologist whose clinical prac- tice has been devoted solely to prostate cancer for 25 years, was diagnosed with prostate cancer in 2006. Upon examining his own biopsy results under the microscope, he was confronted with the same decision so many of his patients had faced before: surgery, radiation, or active surveillance? In an effort to be an informed patient, Dr. Bennett pursued opinions from medical, surgical, and radiation oncologists, and eventually chose to undergo a radical prostatectomy, convinced that his risks were small and the benefits would be great. Five years later, he remains cancer-free, but his right arm and leg are permanently weak, a dysfunction that ap- peared immediately after the surgery. Looking back, Dr. Bennett would have made a different decision. Prostatectomy provides the benefit of high prostate cancer–specific 20-year survival rates; even when performed by skilled surgeons, however, it carries significant risks of sexual, bladder, and bowel dysfunction, along with less common side effects such as Dr. Bennett’s. Active surveillance, coupled with regular screening tests and physical examinations, is associated with much lower rates of these effects and allows for appropriate identification of when to switch from surveillance to treatment. Knowing what he now knows, Dr. Bennett would have opted for active surveillance, proving that even the most informed members of the health care system have difficulty making informed medical decisions as patients (Bennett, 2012). 63

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64 BEST CARE AT LOWER COST Over the past century, the health of the U.S. population has improved dramatically. Life expectancy has increased by almost 60 percent, ma- ternal mortality has declined by almost 99 percent, and infant mortality has dropped by more than 90 percent (Guyer et al., 2000). While these increases in survival have been due to many factors, such as public health efforts (CDC, 1999, 2011b), technical improvements in health care have played an increasingly significant role. The health care field today has a better understanding of the causes of individual diseases, as well as new techniques, treatments, and interventions for managing these diseases. At the same time, the resulting complexity has implications for both patients and providers. The complexity of different health care options—in terms of treatments, diagnostics, and care management—increases the dif- ficulty of the care decisions patients face. When making these decisions, patients often lack clear and understandable information on their options, the risks and benefits of each, and the actions they can take in managing their condition. For those working in the health care enterprise, the cur- rent complexity of clinical decision making challenges human cognitive capacity to manage information. One notable example of this complexity is advances in genetics, which offer unprecedented opportunities for personal- ized treatments but add to the already expansive array of clinical consid- erations for patients and providers. Moreover, administrative complexities, from complicated workflows to fragmented financing, add inefficiency and waste at the system level and prevent health care from centering its efforts on the patients it serves. CLINICAL COMPLEXITY Advances in clinical knowledge have allowed for dramatic improve- ments in the health of the U.S. population. One area in which these im- provements are notable is the treatment of heart attack, or myocardial infarction. During most of the twentieth century, little could be done for a patient who had just suffered a heart attack. The most common interven- tion was to prescribe weeks of bed rest in the hope that the patient would heal on his or her own. Some patients did heal, but many lost skeletal muscle mass and the ability to care for themselves after the prolonged time in bed (Certo, 1985). Recent decades have seen a transformation in cardiac care. Today, diagnostics recognize the different types of heart attacks, allowing for customized treatments for patients. Pharmaceutical therapies, such as beta- blockers and thrombolytics, improve survival and reduce the chances of subsequent heart attacks for many groups of patients. Finally, interventions such as percutaneous coronary intervention (PCI) and coronary artery by- pass grafting (CABG) can reopen or bypass blockages in blood vessels and

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MANAGING RAPIDLY INCREASING COMPLEXITY 65 restore blood flow to the heart (Antman et al., 2004, 2008; Braunwald et al., 2000, 2002). As illustrated in Figure 2-1, the research in cardiovascular disease has allowed for better understanding of the disease and new options in cardiac care (Nabel and Braunwald, 2012). These improvements in care, along with improvements in prevention, have contributed to decades-long declines in both acute and long-term mortality from heart attack (Heidenreich and McClellan, 2001; Rogers et al., 2008). For example, one study found that improvements in medications and interventions over the past three decades were associated with better hospital survival rates, which increased from 81 percent in 1975 to 91 percent in 2005 (Floyd et al., 2009). Similarly, another assessment found that in-hospital fatalities for heart attack patients dropped by almost two-thirds from 1979 to 2005 (Fang et al., 2010). FIGURE 2-1  Timeline of advances in cardiac care, highlighting how improvements in care, prevention, and reduction in risk factors have contributed to declines in cardiovascular mortality over the same time frame. NOTE: ALLHAT = Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial; CASS = Coronary Artery Surgery Study; GISSI = Italian Group for the Study of Survival in Myocardial Infarction; HMG-CoA = key enzyme for cholesterol synthesis; ISIS-2 = Second International Study of Infarct Survival; MI = myocardial infarction; NCEP = National Cholesterol Education Program; NHBPEP = National High Blood Pressure Education Program; PCI = percutaneous coronary intervention; SAVE = Survival and Ventricular Englargement; TIMI 1 = Thrombolysis in Myocardial Infarction trial 1. SOURCE: Reprinted with permission from Nabel and Braunwald, 2012.

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66 BEST CARE AT LOWER COST Comparable advances have been achieved in the treatment of many other diseases. One notable example is in care for HIV/AIDS, as summa- rized in Figure 2-2. In the three decades since this disease was first docu- mented, 35 medications have been introduced for its treatment, sensitive tests have been developed to diagnose the disease at even earlier stages, and other tests have been developed to allow clinicians to identify specific genetic characteristics of the virus in a given patient (Fauci, 2003; FDA, 2011a; Fischl et al., 1987; Simon et al., 2006). These advances have trans- formed HIV from an almost entirely fatal disease to a chronic condition. At the same time, this remarkable achievement brings new complexity to clinical care. Clinicians must understand the resistance profiles of patients, tailoring the combination of therapies accordingly. They must monitor the patient’s viral load to ensure that the treatment continues to work, assess over the course of treatment whether it is causing any adverse effects, and seek to prevent interactions between the patient’s HIV drugs and treat- ments for other health conditions (from antacids to cardiac medications). Further, the pace of treatment advances, as well as mutations in the virus found in the general population, requires that clinicians who work in this 2003 First fusion 30 inhibitor approved 1996 1996 FDA approves Reports on first FDA-Approved HIV Drugs test for viral clinical trials load on HAART 2007 1983-4 HIV documented First entry inhibitor and integrase strand 20 as cause of AIDS transfer inhibitor 1995 approved 1987 First protease First HIV treatment inhibitor (PI) 2001 approved (AZT) approved FDA approves test 1981 to identify resistance First documented 1992 profiles First clinical trials 10 case of AIDS of combination 1984 First HIV test therapies approved 1996 First NNRTI approved 0 1980 1985 1990 1995 2000 2005 2010 Year FIGURE 2-2  Timeline of advances in HIV treatment, highlighting increases in Food and Drug Administration (FDA)-approved HIV drugs in the same time frame. NOTE: HAART = highly active antiretroviral therapy; NNRTI = non-nucleotide reverse transcriptase inhibitor. SOURCE: Data derived from Fauci, 2003; FDA, 2011a,b; Fischl et al., 1987; Simon et al., 2006.

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MANAGING RAPIDLY INCREASING COMPLEXITY 67 80 1997 FDA approves 70 Cancer 5-Year Survival Rate (%) first monoclonal antibody (rituximab) 1967 Combination chemotherapy 2001 60 found to be effective FDA approves first for leukemia targeted therapy (imatinib) 1974 Adjuvant chemotherapy introduced for breast cancer 50 1985 1994 First successful Genetic factors linked 1977 immunotherapy to breast cancer Hormone receptor therapy (IL-2) (BRCA1) 2002 40 for breast cancer approved by FDA (tamoxifen) mRNAs and epigenetics 1971 1988 linked to cancers National Cancer Act New mode of targeted passed radiation introduced (IMRT) 30 1955 1965 1975 1985 1995 2005 Year FIGURE 2-3  Timeline of advances in cancer care, highlighting improvements in the 5-year survival rate in the same time frame. Figure 2-3 NOTE: BRCAI = breast cancer susceptibility gene 1; FDA = Food and Drug Ad- ministration; IL-2 = interleukin-2; IMRT = intensity modulated radiation therapy; mRNA = messenger ribonucleic acid. SOURCE: Data derived from DeVita and Chu, 2008; DeVita and Rosenberg, 2012. area constantly update the way they practice care (Panel on Antiretroviral Guidelines for Adults and Adolescents, 2011). Such advances are not limited to these two diseases but are widespread, as illustrated for the example of cancer care in Figure 2-3. As a result of improved scientific understanding, new treatments and interventions, and new diagnostic technologies, the U.S. health care system now is character- ized by more to do, more to know, and more to manage than at any time in history. The result is a paradox: advances in science and technology have improved the ability of the health care system to treat diseases, yet the sheer volume of new discoveries stresses the capabilities of the system to effectively generate and manage knowledge and apply it to regular care. As discussed in Chapter 3, these advances have occurred at the same time as, and sometimes have contributed to, challenges of health care quality and value.

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68 BEST CARE AT LOWER COST Implications of Complexity for Clinical Decision Making The complexity of the U.S. health care system means that patients and clinicians have more information to consider and more decisions to make than ever before. Often, these decisions are neither easy nor straightfor- ward, and they include varying options, trade-offs, benefits, and risks. Further complicating matters, patients often lack the information they need to make decisions. Fewer than half of patients receive clear information on the benefits and trade-offs of the treatments for their condition (Fagerlin et al., 2010; Sepucha et al., 2010; Zikmund-Fisher et al., 2010). As the description of Dr. Bennett’s case at the beginning of this chapter demonstrates, one condition that entails difficult decisions is prostate can- cer. Prostate cancer is common, developed by one in six men during their lifetime. In at least 80 percent of cases, it is diagnosed at a stage when it is still localized to the prostate gland (Howlader et al., 2011). Patients receiv- ing a diagnosis of localized prostate cancer then must decide what course of action to take. They may choose either to wait and monitor the cancer for any changes (watchful waiting) or to treat it immediately. If they choose to treat it, they have a number of options to consider, including surgery to remove the prostate gland (traditional, laparoscopic, and robotic-assisted versions), various forms of radiation treatment (such as intensity modu- lated radiation therapy [IMRT], brachytherapy, and proton beam therapy), freezing of the prostate (cryotherapy), and hormone treatment (androgen deprivation therapy) (Institute for Clinical and Economic Review, 2010; Wilt et al., 2008b). The difficulty of this decision is that localized prostate cancer gener- ally is slow-growing and often causes no harm during the patient’s lifetime. In addition, there is a distinct lack of evidence on which treatment works best for a given patient with localized cancer. This absence of evidence is acutely felt for emerging technologies, such as IMRT, proton beam therapy, laparoscopic and robotic-assisted prostatectomy, and cryotherapy, which nevertheless are increasingly being used (Hegarty et al., 2010; Institute for Clinical and Economic Review, 2010; Makarov et al., 2011; Wilt et al., 2008a,b). All treatments for this disease have varying, potentially long- lasting side effects, including sexual, urinary, and bowel problems. While it is unknown which treatment option is the right choice for a given patient, the cost of the treatments varies widely. For example, the Medicare reim- bursement for traditional surgical removal of the prostate is approximately $10,000, while the first-year costs for proton beam therapy are nearly $40,000 (Institute for Clinical and Economic Review, 2010).

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MANAGING RAPIDLY INCREASING COMPLEXITY 69 Increasing Occurrence of Multiple Chronic Conditions Prostate cancer is not a unique case. For many conditions, patients and clinicians are presented with many diagnostic and treatment options but lack the evidence to know which option would be most effective. This situation is particularly prevalent for patients with chronic conditions. The prevalence of chronic conditions has increased over time. In 2000, 125 million people suffered from chronic conditions; by 2020, that number is projected to grow to an estimated 157 million (Anderson et al., 2010). Today one such condition, diabetes, affects almost 10 percent of the U.S. population (CDC, 2011a). Furthermore, approximately 75 million people in the United States have multiple, concurrent chronic conditions (Parekh and Barton, 2010). The costs of treating chronic conditions are high, with one study estimating that the care of patients with these conditions consti- tutes almost 80 percent of health care costs (Anderson and Horvath, 2004). A related finding illustrates the importance of caring for patients with seri- ous health needs. An analysis of health care expenditures found that while patients with the highest health care costs represent just 5 percent of the total U.S. population, their care consumes 50 percent of total health care resources (Cohen and Yu, 2011). The role of chronic conditions has changed as the demographics of the population have shifted. In general, the population has gotten older, with the portion of the population over the age of 65 having increased at 1.5 times the rate of the rest of the population in the past decade (Howden and Meyer, 2011). Almost half of the individuals in this population receive treatment for at least one chronic condition (Schneider et al., 2009); one- quarter are affected by just one of those conditions, diabetes (CDC, 2011a; Schneider et al., 2009). Furthermore, more than 20 percent of the elderly are receiving treatment for multiple chronic conditions (Schneider et al., 2009). The complexity of care is particularly acute for patients with multiple chronic conditions. Treating these patients requires a holistic approach, because the use of multiple clinical practice guidelines developed for single diseases may have adverse effects (Boyd et al., 2005; Parekh and Barton, 2010; Tinetti et al., 2004). For example, various existing clinical practice guidelines would suggest that a hypothetical 79-year-old woman with os- teoporosis, osteoarthritis, type 2 diabetes, hypertension, and chronic ob- structive pulmonary disease should take as many as 19 doses of medication per day. Adherence to five separate sets of clinical practice guidelines for the woman’s five diseases could result in adverse interactions between her medications, or a medication for one disease could exacerbate the symp- toms of another (see Table 2-1 for potential treatment interactions). Such guidelines might also make conflicting recommendations for the woman’s

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70 BEST CARE AT LOWER COST TABLE 2-1  Potential Treatment Interactions for a Hypothetical 79-Year- Old Woman with Multiple Chronic Diseases Type of Interaction Medications with Medication and Medications for Disease Potential Interactions Other Disease Different Diseases Hypertension Hydrochlorothiazide, Diabetes: diuretics • Diabetes medications: lisinopril increase serum hydrochlorothiazide glucose and lipids may decrease the effectiveness of glyburide Diabetes Glyburide, None known • Osteoarthritis metformin, aspirin, medications: NSAIDs atorvastatin plus aspirin increase the risk of bleeding • Diabetes medications: glyburide plus aspirin increase the risk of hypoglycemia; aspirin may decrease the effectiveness of lisinopril Osteoarthritis Nonsteroidal anti- Hypertension: • Diabetes medications: inflammatory drugs NSAIDs raise NSAIDs in (NSAIDs) blood pressure; combination with NSAIDs plus aspirin increase the hypertension risk of bleeding increase risk of • Hypertension renal failure medications: NSAIDs decrease the efficacy of diuretics Osteoporosis Calcium, alendronate None known • Diabetes medications: calcium may decrease the efficacy of aspirin; aspirin plus alendronate can cause upset stomach • Osteoporosis medications: calcium may lower serum alendronate level Chronic Short-acting None known • None known Obstructive β-agonists Pulmonary Disease SOURCE: Reprinted with permission from Boyd et al., 2005. Copyright © (2005) American Medical Association. All rights reserved.

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MANAGING RAPIDLY INCREASING COMPLEXITY 71 care. If she had peripheral neuropathy, guidelines for osteoporosis would recommend that she perform weight-bearing exercise, while guidelines for diabetes would recommend that she avoid such exercise (Boyd et al., 2005). These situations create uncertainty for clinicians and patients as to the best course of action to pursue as they attempt to manage the treatments for multiple conditions. A Strain on Human Capacity As clinicians endeavor to provide the best and most appropriate care for their patients, they also struggle with the cognitive complexities inher- ent in making care decisions. In the clinical setting, providers begin the d ­ ecision-making process from the moment they set eyes on their patients. For example, an emergency medicine clinician must make decisions on clini- cal factors such as the patient’s medical history, test ordering, interpretation of laboratory results, diagnosis, treatment, and patient preferences, as well as nonclinical factors such as cost, allocation of resources, and administra- tive considerations (Croskerry, 2002). Like the emergency department, the intensive care unit (ICU) is a par- ticularly difficult environment for clinicians. These specialized units help the sickest and most fragile patients, who could not survive without the support of specialized technologies and equipment. The price of these new capabili- ties is extraordinary complexity that stresses the capabilities of individual clinicians. One observational study found that clinicians in ICUs perform in the range of 180 activities per patient per day, from replacing intravenous fluids, to calibrating a transducer, to administering drugs (Donchin et al., 2003). With new monitoring technologies, clinicians are able to observe the patient’s health status precisely. For example, a patient who enters the ICU with acute respiratory distress is monitored with more than 20 vital sign parameters. With 6 to 12 patients in a typical ICU, a provider must moni- tor and act on up to 240 vital sign inputs, which stresses any individual provider’s cognitive capabilities (Donchin and Seagull, 2002). The growth in complexity is not limited to hospital environments. Physicians, nurses, physician assistants, and other health care profession- als in outpatient settings are managing a great number of conditions and interventions. Quantifying the range of conditions managed by clinicians, a 2008 study of a large multispecialty practice in Massachusetts found that the practice managed more than 5,600 unique primary diagnoses and 6,400 unique secondary diagnoses, or almost half of all known identified diagnoses. Each clinician managed a median of approximately 250 unique primary diagnoses, 280 unique medications, and 130 unique laboratory tests. These figures were even higher for those clinicians in primary care fields, such as internal medicine, who managed a median of 370 unique

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72 BEST CARE AT LOWER COST primary diagnoses, 600 unique medications, and approximately 150 unique laboratory tests (Semel et al., 2010). These findings highlight the variety of needs clinicians now address, along with the variety of interventions and diagnostic tests they must manage. Further, physicians often feel as though they do not have enough time to meet their patients’ care needs (Burdi and Baker, 1999; Trude, 2003). Among primary care physicians responding to one survey, 30 percent re- ported not having adequate time to spend with their patients during a typi- cal visit (Center for Studying Health System Change, 2004-2005), and a similar percentage of patients reported concerns about the amount of time their providers have to spend with them (AHRQ, 2010)—this despite evi- dence that the average length of a primary care visit has actually increased in recent years (Mechanic et al., 2001). Evidence suggests, however, that clinicians’ perceptions are warranted. One study found that meeting a standard patient panel’s acute, preventive, and chronic disease manage- ment needs would require more than 21 hours a day, as shown in Figure 2-4 (Yarnall et al., 2009). As outlined above, the complexity of modern health care is reaching levels that challenge human cognitive capacity. Research in several areas has found that complexity can have negative effects on people’s ability to make decisions (Simon, 1979, 1990; Weick and Sutcliffe, 2001). Complex- ity can cause people to defer making a decision, choose the default option, make no decision at all, or make an incorrect decision (Dhar, 1997; Shafir and Tversky, 1992; Shafir et al., 1993). As one example, when confronted with highly complex situations, people tend to use mental shortcuts, or heuristics, to manage the volume of evidence (Berner and Graber, 2008; Bullen and Sacks, 2003; Kampmann and Sterman, 1998; Payne et al., 1993; The average family physician spends... Acute Chronic Preventive Care Care Care 3.7 hrs 3.0 hrs 1.3 = 8.0 hours/day on direct patient care hrs Following guidelines would require that physician to spend... Acute Chronic Preventive Care Care Care 3.7 hrs 10.6 hrs 7.4 hrs = 21.7 hours/day FIGURE 2-4  Time requirements for a primary care physician to treat a standard patient panel. SOURCE: Data derived from Yarnall et al., 2009. Figure 2-4

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MANAGING RAPIDLY INCREASING COMPLEXITY 73 TABLE 2-2  Common Cognitive Errors in Clinical Decision Making Error Type Definition Anchoring Relying on initial impressions too early in the diagnostic process; failing to adjust initial impressions in light of new information Availability Judging a situation as being more likely or frequent if it easily comes to mind; judging based on the ease of recalling past cases Framing bias Tending to be swayed by subtleties in how a situation is presented (e.g., description of the risks and benefits of treatment options) Premature closure Accepting a diagnosis before it has been fully verified; believing in a single explanation of a situation without investigating other possibilities Reliance on authority Relying unduly on authority or technology SOURCE: Reprinted with permission from Redelmeier, 2005. Timmermans, 1993; Tversky and Kahneman, 1973, 1974). These mental shortcuts range from overrelying on memorable past experiences to accept- ing data that confirm preexisting expectations and ignoring data that do not (see Table 2-2 for a summary of five of the most common cognitive er- rors). Several studies suggest that heuristics are used in health care settings and can have real impacts on patient care (Gandhi et al., 2006; Graber et al., 2005). In most cases, the shortcut works well to solve the problem at hand (Redelmeier, 2005). Precisely because these shortcuts usually produce the desired outcome, however, most people are unaware of their own suscep- tibility to cognitive errors. While strategies to overcome cognitive errors in clinical decision making are beginning to be identified (Croskerry, 2002, 2003; Redelmeier, 2005), time and resource constraints, increasing stress among providers, and growing complexity are all barriers to overcoming the risks of these errors. The volume of biomedical and clinical knowledge being produced has increased steadily over the past few decades. The number of journal ar- ticles in biomedical and clinical research fields has quadrupled since 1970, rising from more than 200,000 a year in 1970 to more than 750,000 in 2010 (see Figure 2-5).1 The pace of research now averages 75 trials and 1The number of peer-reviewed journal publications was determined from searches of PubMed for MEDLINE articles published during a given year using the following MeSH terms: Guideline [V02.515], Journal Article [V02.600], Review [V02.912], Technical Report [V02.989] (National Library of Medicine; http://www.ncbi.nlm.nih.gov/pubmed/).

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80 BEST CARE AT LOWER COST Complicated Workflows The health care system is characterized by administrative complex- ity that can waste clinicians’ time and interfere with their caring for their patients, as well as increase costs and adversely impact patient outcomes. For example, a study investigating waste in the activities of front-line health care workers found that 35 percent of the workers’ time was wasted (Wallace and Savitz, 2008). Even accomplishing a seemingly straightforward activity such as filling a medication order is marked by unexpected intricacies. As illustrated in Figure 2-8, a medication order at one academic medical center can be filled in 786 different ways, involving a number of different health care profes- sionals and technological channels (Thompson et al., 2003). Another study found that inefficient medication administration practices at one hospital caused nurses to waste 50 minutes per shift looking for the keys to the nar- cotics cabinet (Spear and Schmidhofer, 2005; Thompson et al., 2003). The results of this administrative complexity and inefficiency are delayed medi- cations, potential errors, waste, and higher costs. Inefficient workflows also restrict the amount of time nurses can spend directly caring for patients; indeed, it has been found that hospital nurses spend only about 30 percent of their time in direct patient care (Hendrich et al., 2008; Hendrickson et al., 1990; Tucker and Spear, 2006). Studies also have revealed the effects of system complexity on hospital staffing, and in turn on patient outcomes. Despite an average bed occu- pancy rate of 65 percent, hospitals frequently are overcrowded (Litvak, 2005; Litvak and Bisognano, 2011). Hospital admissions generally come from two sources: emergency departments (EDs), which are unpredictable as a source of admissions, and scheduled elective procedures, which are a seemingly predictable source (Litvak et al., 2005). Because hospitals staff for average occupancy and not for peaks, an unexpected influx of patients creates demands for resources and staff time that are impossible to meet, which can cause problems such as emergency room overcrowding, ICU readmissions, and ICU workload and safety problems (Baker et al., 2009; Carayon and Gurses, 2005; IOM, 2007). Studies have found associations between overcrowding and increased mortality (Needleman et al., 2011), as well as decreased adherence to safety practices, such as reconciling of medications, prevention practices for central-line-associated bloodstream infection, and handwashing (Jayawardhana et al., 2011). Fragmented Financing Approximately 60 percent of Americans under age 65 obtain health insurance from more than 1.5 million different employers that purchase

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Orders filled by first Print labels for new available medication 32 batch pathways 768 pathways for a drug All orders and phone Medication Pharmacon to follow calls go to first available. New orders warnings Printer Inventory Accudose Pull new data meds Accudose updates Pharmacy Order Entry STAT R Ph Report to RN Not clear who Phone has done what Pharm Tech External Accudose Phone Phone refill Comp PT 2 RN questions to R Ph R Ph Phone What is mix, volume, Reg and timing of order? PT 3 Fax Comp R Ph Reg External Fax Fax PT 4 STAT Fax R Ph Accudose Comp R Ph ASAP Fax Accudose Accudose Inventory R PH goes to batch and Refill Refill batch room fills STAT order Pharm STAT Tech Tube system PRN RN packs up med dose Pharm Tech FIGURE 2-8  Diagram of processes for filling a medication order at one academic medical center. SOURCE: Adapted and reprinted with permission from Thompson et al., 2003. 81

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82 BEST CARE AT LOWER COST insurance plans from more than 1,200 insurers (Cebul et al., 2008). In a typical year, moreover, roughly 20 percent of health insurance policy- holders change their plans (Cebul et al., 2008; Cunningham and Kohn, 2000). Switches in health plans can occur because of transitions in job status, changes in eligibility for public programs (such as Medicaid or the Children’s Health Insurance Program [CHIP]), or decisions to enroll in another employer-sponsored or individual plan. This frequent turnover in insurance relationships has implications for health care costs and outcomes. While many payers support preventive care and chronic care management, frequent changes in insurance enrollment lessen the incentives for investing in early interventions that can reduce long-term health care costs (Cebul et al., 2008). Managing the requirements of many different health benefit plans places a heavy administrative burden on clinicians. A recent study found that physicians reported spending an average of 43 minutes a day on inter- actions with health plans—adding up to almost 3 weeks per year on such activities. Nursing staff spent 9 hours per physician per week interacting with health plans, and clerical staff 30 hours per physician per week. In monetary terms, in 2006 practices spent an average of $68,274 per physi- cian per year, the equivalent of roughly $31 billion, interacting with health plans (Casalino et al., 2009). Continuity of care is compromised as a result of fragmented financing. A study of the overlap among health maintenance organizations (HMOs) in the same cities found that a person switching from one HMO to an- other had a 50 percent chance of having to change his or her primary care physician (Chernew et al., 2004). This finding is significantly problematic, as continuity of care is associated with a reduced likelihood of future hos- pitalizations and emergency visits (Gill and Mainous, 1998; Mainous and Gill, 1998; Menec et al., 2006; van Walraven et al., 2010). A recent study of low-income veterans found that as financing become more fragmented, patients were more likely to be hospitalized; the effect of fragmented financ- ing on hospitalizations was similar to that of being diagnosed with a major chronic disease (Pizer and Gardner, 2011). Finally, it is important to recognize that health care delivery did not begin this way. Rather, it has evolved into a fragmented, disorganized amalgamation characterized by increasingly unmanageable complexity. Pre- vailing incentives—economic and cultural—allowed for and facilitated this development, and because many health care stakeholders contributed to this evolutionary process, all will need to be engaged in the transition to a continuously learning health care system.

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MANAGING RAPIDLY INCREASING COMPLEXITY 83 Conclusion 2-3: Care delivery has become increasingly fragmented, leading to coordination and communication challenges for patients and clinicians. Related findings: • Coordinating a patient’s care has become more demanding for clinicians. One study found that in a single year, a typical primary care physician coordinated with an average of 229 other physi- cians in 117 different practices just for his or her Medicare patient population (see Chapter 3). • Patients see a large number and variety of clinicians for their care. Between 2000 and 2002, fee-for-service Medicare patients saw an average of seven physicians, including five specialists, split among four different practices (see Chapter 3). • The involvement of multiple providers tends to blur accountability. One survey found that 75 percent of hospital patients were unable to identify the clinician in charge of their care (see Chapter 3). REFERENCES AHRQ (Agency for Healthcare Research and Quality). 2010. The CAHPS database: Prelimi- nary comparative data for the CAHPS clinician & group survey (12-month version). Rockville, MD: AHRQ. American Diabetes Association. 2011. Diagnosis and classification of diabetes mellitus. Dia- betes Care 34(Suppl. 1):S62-S69. Anderson, G. F. 2010. Chronic care: Making the case for ongoing care. Princeton, NJ: Robert Wood Johnson Foundation. Anderson, G. F., and J. Horvath. 2004. The growing burden of chronic disease in America. Public Health Reports 119(3):263. Antman, E. M., J. Lau, B. Kupelnick, F. Mosteller, and T. C. Chalmers. 1992. A comparison of results of meta-analyses of randomized control trials and recommendations of clinical experts. Treatments for myocardial infarction. Journal of the American Medical Associa- tion 268(2):240-248. Antman, E. M., D. T. Anbe, P. W. Armstrong, E. R. Bates, L. A. Green, M. Hand, J. S. Hochman, H. M. Krumholz, F. G. Kushner, G. A. Lamas, C. J. Mullany, J. P. Ornato, D. L. Pearle, M. A. Sloan, S. C. Smith, J. S. Alpert, J. L. Anderson, D. P. Faxon, V. Fuster, R. J. Gibbons, G. Gregoratos, J. L. Halperin, L. F. Hiratzka, S. A. Hunt, A. K. Jacobs, American College of Cardiology, American Heart Association Task Force on Practice Guidelines, and Canadian Cardiovascular Society. 2004. ACC/AHA guidelines for the management of patients with ST-elevation myocardial infarction: A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (committee to revise the 1999 guidelines for the management of patients with acute myocardial infarction). Circulation 110(9):e82-e292.

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