6
Approaches to Improving Value— Organization and Structure of Care

INTRODUCTION

At the present moment in U.S. political history, the possibility of health reform seems more likely than it has for the past decade and a half (Iglehart, 2009), making the capitalization of value in health care—and the organizational and structural changes that would help achieve it—particularly timely. The current fragmentation and disarray of the healthcare system greatly affect costs, quality of care, and patient and provider satisfaction (Stange, 2009; Wiggins, 2008). Some of the attempts to promote reorganization of the delivery of care—such as pay-for-performance and value-based insurance design—have been explored earlier in this summary. Yet prior discussions have also highlighted the need to specifically focus on organizational and structural issues in the healthcare system.

This chapter delves into three promising tools specifically intended to improve healthcare organization and structure. Electronic health records (EHRs), discussed by Douglas Johnston, are considered a key piece of infrastructure for overall health system improvements. EHRs can enable increased coordination across multiple service providers, augment patient engagement, decrease medical errors, and facilitate overall efficiency improvements (Chaudhry et al., 2006; Kaushal et al., 2003). Yet, despite their obvious value and ability to enable progressive strides in care delivery, Johnston argues that, ultimately, EHRs are a necessary but not a sufficient tool for reform of the health system.

Arnold Milstein focuses on medical “home runs,” describing four primary care practices that were able to deliver high-quality care while simul-



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6 Approaches to Improving Value— Organization and Structure of Care INTRODUCTION At the present moment in U.S. political history, the possibility of health reform seems more likely than it has for the past decade and a half (Iglehart, 2009), making the capitalization of value in health care—and the organi- zational and structural changes that would help achieve it—particularly timely. The current fragmentation and disarray of the healthcare system greatly affect costs, quality of care, and patient and provider satisfaction (Stange, 2009; Wiggins, 2008). Some of the attempts to promote reorgani- zation of the delivery of care—such as pay-for-performance and value-based insurance design—have been explored earlier in this summary. Yet prior discussions have also highlighted the need to specifically focus on organi- zational and structural issues in the healthcare system. This chapter delves into three promising tools specifically intended to improve healthcare organization and structure. Electronic health records (EHRs), discussed by Douglas Johnston, are considered a key piece of infrastructure for overall health system improvements. EHRs can enable increased coordination across multiple service providers, augment patient engagement, decrease medical errors, and facilitate overall efficiency improvements (Chaudhry et al., 2006; Kaushal et al., 2003). Yet, despite their obvious value and ability to enable progressive strides in care delivery, Johnston argues that, ultimately, EHRs are a necessary but not a sufficient tool for reform of the health system. Arnold Milstein focuses on medical “home runs,” describing four pri- mary care practices that were able to deliver high-quality care while simul- 

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 VALUE IN HEALTH CARE taneously enabling their patients to consume 15-20 percent less total payer spending per year on a risk-adjusted basis than patients being treated by regional peers—all within the current payment environment that rewards volume over outcomes. He identifies two common characteristics of these practices: (1) a focus on preventing urgent and emergent hospitalization for chronic illnesses and (2) a concentration on referral care to high-quality specialists who consciously consider resource use. Yet, he asserts, to achieve these “home runs,” the design of medical homes—a model of deliver- ing primary care that engages individual patients in forming partnerships with their personal physicians in an accessible, continuous, comprehen- sive, patient-centered, coordinated, compassionate, and culturally effec- tive manner (American Academy of Family Physicians et al., 2007)—must explicitly incorporate the lessons learned from these successful examples before they can improve quality while lowering total costs of care in a sustained fashion. Concluding the chapter, Tracey A. Moorhead explores the evolution from “disease management” to “population health improvement,” which ranges from a focus on individuals with chronic illness to an emphasis on health promotion in larger populations. Through case studies demonstrat- ing positive returns on investment in public and private healthcare settings, she parses a process that aligns providers and services with the common goal of improving the health of populations and concurrently yields signifi- cant economic savings. THE VALUE OF ELECTRONIC HEALTH RECORDS Douglas Johnston, M.A., Colene Byrne, Ph.D., Eric Pan, M.D., Adam Vincent, M.P.P., and Blackford Middleton, M.D., M.P.H., M.Sc., Center for IT Leadership Has the U.S. healthcare system finally reached an inflection point in the decades-long effort to adopt health information technology (IT)? Very likely, given unprecedented state, regional, and federal initiatives to support and fund health IT. Many states and regions have invested in consortia and collaborations to further the use of electronic prescribing, electronic health records, and health information exchange (Healthcare Information and Management System Society, 2008).1 At the federal level, most significant is the recently passed American Recovery and Rehabilitation Act (ARRA), whose provisions show the federal government’s commitment to a multi- 1 For current status on state and regional health IT programs, see http://www.himss. org/StateDashboard/.

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 ORGANIZATION AND STRUCTURE OF CARE year, multibillion-dollar investment in health IT (American Recovery and Reinvestment Act, 2009). The value and feasibility of health IT continue to be debated widely, although evidence from a variety of sources—experimental and observa- tional studies, case studies, expert opinion, and analytic models—suggests that, implemented well and used appropriately, these technologies improve quality and safety and potentially reduce costs. The questions of whether, how, and to whom health IT produces value are central to this debate and are as complicated and thorny as other issues such as privacy and security and technical standards. Health IT is comprised of a broad range of information systems and computer-based functions (Blumenthal and Glaser, 2007). This paper dis- cusses issues associated with the value of a central health information tech- nology: EHRs. We begin by defining EHRs and reviewing the characteristics that may impact the creation and capture of EHR value. We then review a selection of the published evidence and projections of EHR benefits and costs and conclude by discussing key issues in assessing the value of this technology. Generally, EHRs and their related functions have been shown to improve the quality, safety, and efficiency of care. Moreover, there is evi- dence, although limited, that EHRs can produce significant financial ben- efits if implemented well. Projections of EHR value, based on the current evidence from the literature and experts, suggest that widespread adoption and use of EHRs and systems containing EHR functions could produce substantial clinical and financial benefits to the U.S. healthcare system. The Center for IT Leadership’s (CITL’s) own projections suggest that millions of avoided medication errors and hundreds of billions in avoided costs are possible from widespread adoption of EHR-related functions such as order entry, decision support, and electronic healthcare information exchange (Bu et al., 2007; Walker et al., 2005). However, given the range of available evidence, we assert that creating and then capturing value from EHRs is a matter of conditions and degrees, because value is likely to accrue differently, and at relatively different rates and levels, depending on the context in which it is adopted. As care pro- viders move toward widespread EHR adoption, the need for more robust evidence on EHR impacts and costs that reflects different characteristics of the U.S. healthcare system is more acute than ever. Defining EHRs and Related Benefits EHRs have been defined in many ways. Common to these definitions is the idea that EHRs are, fundamentally, electronic tools for collecting clinical data from multiple sources and for using these data at the point of

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 VALUE IN HEALTH CARE care to support clinical decision making. One commonly cited definition of EHRs (NAHIT, 2008) is: An electronic record of health-related information on an individual that conforms to nationally recognized interoperability standards and that can be created, managed, and consulted by authorized clinicians and staff across more than one health care organization. In 2003, the Institute of Medicine (IOM) convened a Committee on Data Standards for Patient Safety, one product of which was a statement on the key capabilities of EHRs (IOM, 2003). The committee’s letter report listed eight core EHR functions: 1. Health information and data (clinical documentation): a defined dataset including patient demographics, medical and nursing diagnoses, prob- lems, current medications, allergies, test results, clinical narratives, and other important patient data. 2. Results management: automated, electronic display of current and pre- vious results from laboratory tests, radiology procedures, and other sources. 3. Order entry or order management: electronic entry and management of medication, lab test, radiology, procedure, and other orders. 4. Decision support: computer-based tools that assist clinicians with man- aging knowledge and decisions about patients and their care. Decision support can be passive, as in static information about a drug’s effective- ness, or active, as in automated alerts about potential drug interactions and reminders to deliver recommended care. 5. Electronic communication and connectivity: electronic sharing of patient’s health information and data among care providers and other stakeholders. This sharing ranges from unstructured, free text approaches (e-mail) to fully structured, machine-readable, standards- based exchanges. 6. Patient support: electronic tools that give patients access to their health records, provide interactive education, and help monitor and manage their conditions remotely. 7. Administrative processes: functions that support patient scheduling, verification of insurance status, and electronic claims processing— including automated capture of charges for care services. 8. Reporting and population health management: aggregation, reporting, and analysis of data across patients for multiple purposes including monitoring and managing chronic conditions, tracking key quality indicators, and reporting disease statistics. These functions can be further organized into three categories: those that support different activities in episodes of patient care (functions 1-7); those

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 ORGANIZATION AND STRUCTURE OF CARE that enable monitoring and interventions across populations of patients (functions 1, 5, and 8); and those that support clinical decision making for individuals and groups of patients (functions 1, 2, and 4). While clinicians’ workflows and data needs may differ by care setting and medical specialty, the need for appropriate documentation of a patient’s history, current prob- lems, medications, allergies, test and study results, and demographic infor- mation is consistent, as are needs to order medication, tests, and procedures and to share patient data and coordinate with other caregivers. Likewise, the need to identify, intervene, and monitor a group of patients with a given set of characteristics2 is important to ensure both therapeutic consistency (i.e., that all patients with similar conditions, comorbidities, and severity of illness receive the same recommended care) and collective improvement in the care these patients receive (Greenlick, 1995; Wagner, 1995). Finally, the ability to apply clinical logic to this information in support of diagnosis and treatment of individuals and cohorts of patients, and the ability to offer relevant disease and treatment information to clinicians in real time at the point of care, are also important EHR functions. Used consistently and appropriately, EHRs containing these functions are postulated to produce significant value in the form of the following: • Improved quality—decision support may result in increased adher- ence to care guidelines; • Improved patient safety—interaction and allergy checking at the time of drug orders may decrease rates of medication errors; • Improved outcomes—decreases in the morbidity and mortality associated with acute and chronic conditions; • More integration and better care coordination—improved avail- ability of patient data at the point of care and communication among caregivers and patients; • Improved efficiency—decreases in the frequency of unnecessary and duplicative care and in the costly manual exchange of clinical data; • Decreased costs—both in administrative costs to support clinical operations (maintaining paper medical records) and in the costs of care; • Increased provider revenues—from improved coding and documen- tation; and • Better research data—creating longitudinal data stores on patient’s conditions, histories, and outcomes. 2Characteristics include sex, age, diagnosis, disease severity, insurance type, geography, and others.

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 VALUE IN HEALTH CARE For many of these value categories, experimental and observational studies have found significant, positive changes in the quality, safety (Kaushal and Bates, 2001; Kaushal et al., 2003), and efficiency of care (Chaudhry et al., 2006; Goldzweig et al., 2009) and, in limited instances, financial impacts in terms of cost savings and improved revenues (Middleton, 2005; Miller et al., 2005). However, in some instances, the evidence of the value of EHRs (or of specific EHR capabilities) is equivocal. One study of EHRs reported no conclusive changes in the use of laboratory and radiology services and slight to no changes in intermediate measures of healthcare quality (Garrido et al., 2005). Other studies have suggested that in some care settings, the use of EHR functions such as computerized physician order entry (CPOE) may have actually caused errors (Han et al., 2005; Koppel et al., 2005). As we look from the promise of EHRs to the evidence of EHR impact, a few questions are important to consider: How is value created from EHRs? How is it captured or realized? To whom does EHR value accrue? EHR Value Creation and Value Capture Value creation through EHRs is the process of using these tools to support positive changes in the processes, outcomes, and costs of care; value capture is the process of realizing these changes as benefits as well as determining to whom these benefits accrue. EHRs can create value through producing process efficiencies, replacing manual paper-based clinical and administrative methods with those automated through computers and elec- tronic information networks. Depending on their capabilities, EHRs can also create value through changes in the utilization of services, either by increasing care known to be beneficial and appropriate or by decreasing care that is potentially inappropriate (unnecessary) and even harmful. Cer- tain reductions (or increases) in the costs of care may then follow from these efficiencies and changes in utilization. This potential value is expressed in terms of the benefits listed above: improved quality, safer and more efficient care, and so forth. However, the ability of caregivers, patients, and others to capture this value—to actually change processes of care, avoid medication errors, and decrease costs—is another matter. Some EHR benefits are, arguably, relatively easier to capture (or more likely to be captured) than others. For example, revenue enhancements from EHRs that improve coding are more likely to be recognized than efficiency-related cost savings that require a reduction in clinical or support staff. While physician practices may auto- mate documentation and coding through EHRs and therefore require fewer staff for these tasks, anecdotal evidence suggests that—for certain care settings—they are less likely to shed these resources than to reassign them to other productive tasks.

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9 ORGANIZATION AND STRUCTURE OF CARE EHR stakeholders encompass a broad range of health system actors. The most proximal EHR stakeholders include clinician users, patients, and ancillary providers; more distal are those who finance, regulate, and monitor care (i.e., health plans, government administrators, and public health organizations, respectively) as well as those who research the effects of care delivery.3 EHR adoption and use may result in value to some of these actors, but not others. From the perspective of the U.S. healthcare system, the effects of EHR adoption and use—and the dynamics of value capture—may be experienced and distributed differently depending on sev- eral key characteristics. For instance, in the previous example, the benefits of improved coding (i.e., increased revenues) would accrue to providers under the predominant fee-for-service payment system. Changing the pay- ment system to capitation, where providers would be at risk for the costs of care, would limit the accrual of value since they would not be able to bill for improved services. In addition to payment systems, the sophistication of an EHR system, the settings in which this system is adopted, the size of the organization, the presence or absence of strong leadership and quality improvement programs, and other dimensions impact the type and amount of value EHRs may produce and to whom this value ultimately accrues. Table 6-1 provides a summary of many of the key characteristics that impact EHR value creation and capture. To illustrate the ways in which some of these characteristics may com- bine to effect the creation and capture of EHR value, consider the follow- ing expanded example. A physician practice of 10 clinicians adopts an EHR with clinical documentation and administrative support features. This practice is based in an urban setting with a high volume of relatively complex patients and is reimbursed on a largely fee-for-service (FFS) basis. Successfully adopted and used, an EHR with these functions in this context may decrease the high costs associated with maintaining paper records and producing insurance claims, thereby saving this practice money. Moreover, electronic documentation may improve coding for visits and consequently increase this practice’s revenues. In both of these examples, the practice may receive financial benefit from EHR adoption—one in savings, one in revenues. Health plans, however, may share only in savings related to claims processing (they no longer receive and manually process paper-based claims), but these plans may actually experience increased costs due to improved provider coding. 3 In a report on the costs and benefits of health IT, the Congressional Budget Office (CBO) provides a useful distinction between internal benefits that accrue to providers and external benefits that are enjoyed by entities interacting with providers (see U.S. Congress, 2008, p. 7).

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0 VALUE IN HEALTH CARE TABLE 6-1 Types of Characteristics Impacting EHR Value • EHR system Basic to advanced functions • Commercial vs. institutional (i.e., “home-grown”) • Care setting Inpatient vs. outpatient • Primary vs. specialty • Organization setting Community vs. academic • Open vs. closed model • Urban vs. rural • Organization size Large, medium, or small • Organization leadership Experience with health IT and EHRs • Commitment to success • Financial issues Revenue mix (e.g., risk contracting vs. fee-for-service payments) • Financial incentives (e.g., pay-for-performance, reporting) • EHR adoption and maintenance costs • Workflow and practice patterns Care process variation • Level of EHR adoption and “meaningful” use • Populations served Pediatric, geriatric, or condition-specific Changing a few characteristics in this example would change the dynamics of EHR value creation and capture. If this same practice added order entry and robust decision support capabilities to its EHR, most medication orders would now be entered electronically. Decision support features would check these orders for drug allergies and drug-drug interac- tions, alerting clinicians of possible adverse drug events (ADEs). If clinicians act on these alerts, they decrease the amount of medication errors. This decrease, in turn, reduces visits or hospitalizations stemming from ADEs— clearly, an improvement in safety that benefits both patients and providers. Also, since this practice is reimbursed on a FFS basis, any costs avoided due to reductions in ADE-related events accrue to payers. However, if order entry and decision support features improve adherence to guideline-based care, then this would increase the amount of services delivered to patients— correcting for underuse of proven preventive and chronic care measures. In this instance, care quality would increase, again benefiting patients and clinicians, but so would the costs of care in the short term—costs borne by payers. In the long term, however, improvements in the quality of care might actually precipitate a net decrease in care costs if more serious clinical events were avoided as a result. Here then, all parties—patients, providers, and payers—would likely benefit. This example starts out simply enough, but then value creation and capture become more complicated—seeming to flip-flop once more char- acteristics are changed or introduced. The illustration above is intended

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 ORGANIZATION AND STRUCTURE OF CARE to show how EHR value is complex and influenced by a wide range of attributes. Accordingly, the evidence on EHR impact should be considered in light of these characteristics. Evidence of EHR Value: Research Studies and Cost-Benefit Projections Evidence of EHR value generally falls into two categories: (1) research study data4 and (2) projections of EHR costs and benefits based on this data. The former category answers specific questions about the actual impact of EHRs; the latter addresses questions about their possible impact. Both are important for understanding EHR value. This section reviews summaries of the evidence on EHR value from both categories. We present data from review articles that included studies examining EHRs as well as key EHR capabilities contained in the IOM definition above. Research Studies Related to EHR Impacts on Quality, Safety, and Efficiency In 2006, researchers at RAND published a systematic review on the impact of health information technology (health IT) on the quality, effi- ciency, and costs of medical care (Chaudhry et al., 2006). Subsequently, they published a follow-on review of the evidence on HIT costs and benefits from 2004 to 2007 (Goldzweig et al., 2009). Since EHRs are an important combination of systems and functions within the broader realm of health IT, we selected findings from these reviews that included studies of the key EHR capabilities included in the IOM definition. Generally, RAND found improvements in care quality and safety, but little evidence on costs or cost savings. Findings relevant to EHR functionality are the following: • Increased adherence to guideline-based care: absolute improve- ments in the range of 5 to 66 percent (most clustering in the 12 to 20 percent range). This was particularly the case for preventive care guidelines (e.g., vaccinations and screenings). • Improved medication safety: decreases in serious medication errors in the range of 55 to 86 percent and improvements in the accuracy of drug dosing from 12 to 21 percent. • Enhanced surveillance and monitoring. Evidence in both these review studies was mixed in terms of the impact of health IT and EHR impact on the efficiency of care. The major benefit in terms of efficiency was decreased utilization of care—absolute reductions 4This includes data from and includes experimental, observational, and case studies using quantitative and/or qualitative methods.

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2 VALUE IN HEALTH CARE of between 8.5 and 24 percent, particularly for lab tests and image stud- ies. Since much of the evidence on HIT and EHR impact came from four institutions—three of which were part of academic medical centers—and since many of the systems studied were developed by these institutions (i.e., homegrown), study authors could not say for certain whether or not this evidence would readily translate to other institutions that might use com- mercial systems. Recent evidence published as late as January 2009 indicates that the benefits of EHRs would be realized through the adoption of commercial systems in urban hospitals. Amarasingham and colleagues (2009) performed a cross-sectional study of 72 urban hospitals in Texas and hypothesized that those with higher rates of adoption and use of clinical information technol- ogies would have better outcomes and lower costs of care. Specifically, they examined the degree to which hospital use of many EHR functions—includ- ing clinical documentation, order entry, results reporting, and decision support—was associated with mortality, complications, costs, and length of stay for patients with four medical conditions: myocardial infarction, congestive heart failure, coronary artery bypass grafting, and pneumonia. Patients at hospitals who had adopted and used systems with EHR functions more intensively had lower rates of hospital-based fatalities and lower risk of complications. Of special note is that, for nearly all conditions, greater use of EHR functions was associated with lower hospital costs. Although this study was limited to hospitals and did not determine whether or not clinical automation was the cause of decreased risk of negative outcomes and lower costs, it provides an important piece of evidence for EHR value stemming from the use of commercial systems (Bates, 2009). Research Studies Related to EHR Costs Financial impact—in terms of both costs and revenues—is an important aspect of EHR value. EHR cost considerations include the funds to acquire and maintain systems as well as the savings resulting from EHR adoption and use. Revenues include the ability of EHRs to increase payments to provider organizations through improved coding and greater provider productivity. Data on EHR system costs are very limited, vary widely, differ by set- ting of care, and are often the product of estimations and models—not actual costs incurred. In outpatient settings, the widest range of EHR adop- tion costs reported in a single study by Miller and colleagues is $14,500 to $63,600 per provider, with a median of nearly $46,000 (Miller et al., 2005). Annual EHR maintenance costs from this same study range from approximately $6,000 to nearly $12,000 per provider, with a median of $7,200. Miller’s adoption estimates include opportunity costs: the decrease in revenues resulting from lost productivity during EHR adoption. Creating

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 ORGANIZATION AND STRUCTURE OF CARE a similar range of acquisition costs for outpatient EHRs from other studies yields $25,000 to $45,000 per provider, with a range of support costs from $3,000 to $9,000 per provider annually (U.S. Congress, 2008). In inpatient care settings, acquisition costs for clinical information systems with order entry and decision support capabilities—a proxy for EHR costs—ranged from $2.8 million to $4.1 million for a 200-bed hospital to $9.7 million to $14.7 million for a 1,000-bed hospital; support costs ranged from $174,000 to $468,000 annually for a 200-bed hospital, and $747,000 to $1.5 million for a 1,000-bed hospital annually (Birkmeyer et al., 2002). A cost-benefit analysis of an inpatient CPOE system estimated $11.8 million in costs over 10 years to develop, implement, and operate the system (Kaushal et al., 2006). Other sources have reported inpatient system acquisition costs of $14,500 to $63,000 per bed,5 with annual maintenance costs of approxi- mately 20 to 30 percent of acquisition costs (U.S. Congress, 2008). Research Studies Related to the Financial Impact of EHRs There are several examples of cost savings and revenue gains from case studies of EHRs and their related functions (Kaushal et al., 2006; Middleton and Janas, 2000; Miller et al., 2005; Wang et al., 2003) and some published evidence from observational and experimental studies (Chaudhry et al., 2006; Goldzweig et al., 2009).6 In general, sources of cost savings from EHR functions include those from elimination or reduction of manual administrative processes (e.g., reduced chart pulls and transcription costs) and from changes in the utilization of services (e.g., reduced duplicate and inappropriate diagnostic tests, more appropriate ordering of medications and image studies, reduced hospital stays, avoidance of error-related visits and hospitalizations). Revenue gains typically stem from improvements in coding and provider productivity. Some of the best examples of case studies on EHR financial impact include work completed by Robert Miller and colleagues. In a study of EHR adoption in 14 solo and small-group practices, Miller found that most practices enjoyed a $33,000 financial benefit, approximately half of which was from improved coding and half from practice efficiencies. After EHR adoption cost, providers accrued an average of $23,000 net financial gain, with an average of 2.5 years to break even. Of the 14 practices participating in this study, 2 did not break even within the period of analysis (five years) 5 Though nearly identical to the range of outpatient EHR costs reported by Miller et al. (2005), the range of per bed costs for inpatient CPOE systems was derived from different sources (see First Consulting Group, 2003; Girosi et al., 2005). 2003; 6 As RAND researchers note, much of the evidence on financial value from these studies is based upon monetizing changes in administrative processes and in utilization of different care services.

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90 VALUE IN HEALTH CARE of care. In addition, health benefit plan sponsors would gladly support the higher primary care physician payments that were required to attain such results. However, these four physician practices contain two key features that are not well addressed in current medical home blueprints: (1) personal zealotry in preventing urgent and emergent hospitalization for chronic illnesses and (2) equally zealous concentration of referral care to high- quality medical specialists who are sparing in their use of “supply-sensitive services,” as defined in the Dartmouth Atlas. Personal Zealotry in Preventing Unplanned Hospitalization for Chronic Illness All four primary care medical home runs operate as de facto “hospi- talization prevention organizations” for their chronically ill patients; they make prevention of unplanned hospitalization of these patients a primary objective; and they redesign their practice models accordingly. A key ele- ment of this prioritization is clinical mindset: the physicians and their office staff regard urgent and emergent hospitalizations for patients with chronic illnesses as personal and organizational failure events, study their root causes, and evolve their practice model to prevent recurrences. While the specific clinical innovations to prevent unplanned hospital- izations vary somewhat across the four practices and are discussed else- where, they converge in two ways. At least one primary care team member demonstrates saliently to each chronically ill patient that he or she cares deeply and personally about that person and the protection of the patient’s health. This usually includes mobilizing family members, social services, and other resources required for successful patient self-management. In addition, as soon as a chronically ill patient senses an impending health crisis, a member of the healthcare team familiar with that patient’s history is readily reachable and prepared “to go the extra mile” to prevent hospi- talization, including actively coordinating with emergency room physicians and hospitalists in exploring alternatives to hospitalization (Milstein and Gilbertson, 2009). An attitude of “protection of your health matters to me personally” and “I’m prepared to invest special effort to spare you a health crisis” was memorably captured in Atul Gawande’s 2004 New Yorker magazine portrait of Dr. Warren Warwick in “The Bell Curve.” It is the exception rather than the rule in American healthcare delivery. Because it reflects a personality characteristic of clinical team members rather than a readily teachable behavior or a structural enhancement of a primary care practice, ensuring this expression of patient-centeredness requires new selection cri- teria for medical home team members serving the chronically ill. Given the

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9 ORGANIZATION AND STRUCTURE OF CARE prolonged time frames required to integrate patient-centeredness robustly into medical student selection and into graduate and postgraduate physician training, near-term improvement implies selecting for this attitude among nonphysician team members. Other organizations, such as the retail giant Nordstrom, have shown that selecting employees for high natural service orientation is feasible. Concentrating Referral Care with High-Quality, Conservative Medical Specialists Current methods of comparing specialists on quality and total spend- ing per episode of acute illness care and per year of chronic illness care are imperfect. Nonetheless, each of the four primary care medical home runs used available performance assessments of specialists on quality and total cost of care in order to concentrate specialist referrals with one well- performing specialist or specialist group per specialty. In two of the medi- cal home run practices, conservative resource use by these specialists was reinforced by payer capitation payment of specialists. An estimate of potential healthcare spending reduction associated with preferential use of such highly ranked specialists in Seattle—a low-spending Dartmouth Atlas region—was prepared by Mark Rattray. He found no relationship between low spending and quality for care delivered by most non-primary-care specialties. When he modeled savings from preferential referral to low-spending specialists with above-average quality scores, he found that the opportunity for savings constituted approximately 15 percent of total payer spending controlled by specialists. The savings opportunity is likely greater in the higher-spending Dartmouth Atlas regions. Concentration of referrals also enables more effective care via greater standardization of treatment protocols among physicians treating the same patient, more reliable transfers of patient information between primary and specialist care, and greater clarity regarding the division of responsibility among physicians involved in a patient’s ongoing management. Closing Comment If medical homes deliver better quality without increasing total health- care spending, they will generate social benefit. Social benefit will also increase if medical homes shift physician payments toward primary care. However, for medical homes to profoundly benefit non-affluent adults who do not qualify for Medicaid and to persuade most purchasers to pay higher medical home fees, they must also lower total near-term healthcare payer spending. To achieve such home run status, medical homes’ designs, certification standards, and criteria for reward from payers must explicitly

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92 VALUE IN HEALTH CARE incorporate features from existing primary care practices that achieve low total cost of care and favorable performance on other domains of quality. Observation of four such practices suggests that these design features are likely to enhance, rather than conflict with, current principal medical home quality objectives of improved access, patient-centeredness, and effective- ness of care. While they cannot alone correct the major shortfalls in the value of U.S. health care, medical homes can substantially reduce total near-term healthcare spending while improving quality of care. Today, roughly 60 mil- lion uninsured and underinsured lower-income Americans need physician and health plan leaders to jointly pursue this higher aspiration for medical homes. Otherwise, their numbers and preventable health deterioration will continue to mount. DISEASE MANAGEMENT Tracey A. Moorhead, DMAA: The Care Continuum Alliance Improving health and achieving meaningful system reform demands that we rethink our most basic ideas of how—and when—to provide the best care. Population health improvement in its many forms—prevention, wellness, chronic disease management, and others—offers important direc- tion for this task by demonstrating how good health often is simply a matter of good timing. Population health improvement learned long ago that keeping people healthy and identifying risk, rather than waiting for hospitalization or diag- nosis of chronic disease, brings greater rewards than reactionary care—the all-too-common approach. This is how population health has evolved over the past decade, from managing existing conditions (still an important component of what we do) to a broad spectrum of services and solutions across the continuum of care for chronic disease. These interventions are many and varied: wellness, health promotion, prevention, and even com- plex case management and palliative care. The tools of the trade have expanded greatly too, encompassing health risk assessment, advanced pre- dictive modeling services, personal health record portals, electronic medical records, remote patient monitoring, and other technological innovations that all contribute in some form to stopping a problem before it starts. Underlying all are three core components of population health improve- ment: the central leadership role of the physician, a patient-centered focus, and emphasis on patient and physician engagement. Reform must recognize that physicians and patients cannot go it alone. They need the support of a variety of services and professionals, especially in the sphere of chronic condition prevention and care. Population health can bring to bear the

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9 ORGANIZATION AND STRUCTURE OF CARE technological and staffing resources all too often out of reach for the typi- cal practice, especially small practices. Bringing together all stakeholders this way allows us to align providers and services with the shared goal of improving the health of populations and, in turn, moving more people off the rolls of the at-risk and into the ranks of the chronically well. Often, though, we lose sight of this goal in the debate about whether disease management “works”—a debate that usually starts with the wrong questions: Does disease management save money? is typical and, more often than not, what is meant is: Does disease management always work in every case for every population using the same intervention? The answer is no. If you have seen one disease management program, you have seen only one disease management program. Successful chronic disease programs employ tailored interventions and measurements that reflect the unique needs of the population served and unique resources available to it. Drilling down further, sometimes the question is: What are the short- term medical cost savings for this program? However, this question over- looks the long-term value of sustaining and improving health status and, again, assumes that disease management is a one-size-fits-all, monolithic process that can serve any population in any setting regardless of the resources or the training required. A much better question reformers must consider is: Do population health improvement programs improve quality and deliver value? The population health improvement industry, through its representative orga- nization DMAA: The Care Continuum Alliance has worked diligently over the past three years to answer this question through an evidence-based, consensus approach. The Outcomes Guidelines project has sought, in a rigorously transparent way, to establish the appropriate parameters for answering more productive questions: In what population settings will these strategies have their greatest impact? For which conditions? Which outcomes show positive change and in what sequence? Over what time frame? The Outcomes Guidelines project has further defined the measurement of the impact of population health programs. Recognizing a gap in the understanding of best practices in outcomes measurement for population health improvement, DMAA launched the Outcomes Guidelines project in 2006. While the project sought to bring clarity to the confusion caused by a host of competing methodologies in outcomes measurement, it also delib- erately avoided advocating a single approach. Rather, it set forth guidelines for best practices and for adjusting an evaluation based on population and program variations, all the while keeping a balance between scientific rigor and practicality. The Outcomes Guidelines Report (DMAA, 2008), the work product of this project, now comprises three volumes. The collection incorporates

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9 VALUE IN HEALTH CARE comment and counsel from a wide variety of quality and research leaders, both public and private sector, including the National Committee for Quality Assurance, URAC, the Joint Commission, and the federal Agency for Healthcare Research and Quality. The most recent volume, Volume 3, refines and expands earlier work and explores new areas, notably medica- tion adherence, trends, and small populations. It also reflects the broader industry shift toward keeping people healthy with extensive new work on measuring success in wellness programs, an area DMAA will continue to develop in a fourth phase of the project. With this tool in hand, we can look critically at those relevant ques- tions for population health discussed earlier and narrow our focus on programs that produce the results we seek, based on industry consensus, evidence-based approaches to evaluation. With a clear understanding of best practices in evaluation, we can overcome the challenge of differing expectations and varying populations—the source of so much confusion in the past—and move closer to erasing doubt about the value of population health improvement to a reformed delivery system. Little doubt remains among employers and other private sector pur- chasers of health care. Chief financial officers, health benefits executives, and other human resources professionals need only look at their bottom line to see the value of employee health promotion and wellness programs. They also see the value in improved productivity and presenteeism and reduced absenteeism. The Southern Company, a large southeastern U.S. utility, offers a good case study. It engaged 10,000 employees of an eligible population of about 20,000 and provided, based on the needs of the indi- viduals in this population, wellness, prevention, and disease management services. This successful initiative lowered hospital admission rates for the population by 57 percent for those with chronic obstructive pulmonary dis- ease (COPD) and 100 percent for workers and beneficiaries suffering from depression. For those who did need hospitalization, average length of stay decreased by a similar range. Emergency department visits dropped, too, by a range of 29 to 100 percent. What was the return on investment (ROI)? Southern Company calculated a 2.37:1 ROI, net of program costs: $2.37 back for every dollar invested across the board for this program. Another case study comes to us from J. B. Hunt, a leading national trucking company. J. B. Hunt enrolled 3,200 participants—mostly truck drivers—in a program targeting high blood pressure, which impacted drivers’ ability to stay on the job, created safety issues, and generated unacceptable turnover at the company. The three-year lifestyle health pro- motion program resulted in a 37 percent smoking cessation rate and an average 15-pound weight loss among 49 percent of the targeted population. Disease management generated $213,000 in savings for four chronic condi-

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9 ORGANIZATION AND STRUCTURE OF CARE tions. Equally important to the company, the program reduced preventable accidents by 25 percent and increased employee retention by 6.2 percent. The public sector has seen similar positive results from population health programs. Medicaid, in particular, has served as a breeding ground for extraordinary innovation and flexibility to reach specific populations with tailored programs. Illinois initially engaged nearly 2 million beneficiaries for primary care case management and disease management and provided disease manage- ment for 220,000 chronically ill Medicaid recipients. Working with nurses, social workers, and physicians to support patients and reduce admissions, Illinois realized a net savings in 2007 of $34 million through an 8.5 to 20 percent reduction in admissions and a 13 percent drop in emergency department visits. The program worked so well that the state expanded it to additional populations. Through its EqualityCare program, Wyoming enjoyed similar savings. The program reduced inpatient admissions by 40 percent and created net savings of $13 million in 2005 and $17 million the following year. Like Illinois, on the strength of these results, Wyoming expanded its program to oral health, maternal weight, and childhood behavioral issues in 2007. Florida provides another compelling example: $97 million in savings over three years in a program that brought coaching, education, and other interventions to 180,000 chronically ill residents. Attacking rising rates of asthma, diabetes, hypertension, and congestive heart failure (CHF), Florida reduced CHF admissions by 22 percent and emergency department visits by 12 percent. Florida made a particularly strong effort to work with hospi- tals, physicians, and community organizations, recognizing the broad base of support necessary to effectively fight chronic conditions. Our experience with chronic care coordination and disease manage- ment in Medicare has been somewhat mixed. Medicare fee-for-service beneficiaries present significant challenges to traditional care management interventions, and the program’s mammoth size complicates the task further by hampering the flexibility and midcourse corrections needed to quickly adapt a program to a population’s changing needs. Even so, we have seen some success in fee-for-service Medicare and noteworthy progress in Medicare Advantage plans, which more closely align with the private sec- tor care management models in which population health thrives. Medicare Advantage special needs plans, for example, exhibit the sort of program design flexibility, collaboration, and coordination that we could extend to other segments of the Medicare program to better deliver services to all beneficiaries. Much of our recent experience in fee-for-service Medicare comes from the Medicare Health Support (MHS) pilot, which was launched in 2005 and abruptly ended in 2008 based on initial reports of marginal improve-

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9 VALUE IN HEALTH CARE ments in clinical outcomes and costs savings. Those initial assessments, though, rested on relatively limited data—fewer than three months’ worth, in some cases. Generally, populations served in these pilots were far sicker than anticipated by even the Centers for Medicare and Medicaid Services, and many beneficiaries became ineligible for the program before the pilots could begin interventions. This fact alone would indicate that a longer intervention time, where possible, would be required to derive clinical improvements or financial savings given the severe health status of many of these beneficiaries. Even still, these pilots can offer important lessons to be leveraged in reform efforts. Some pilot programs did report clinical improvements and cost savings, and this should be where we direct our attention for the lessons we can learn about chronic condition care in the FFS population. To dismiss these positive results as anomalies rather than the learning opportunities they surely are is to throw the baby out with the bathwater. We simply cannot afford to ignore promising results when true reform demands so much more. We also must not ignore the strong anec- dotal evidence of high beneficiary satisfaction and high provider engage- ment in MHS. Provider satisfaction with chronic care coordination and population health likely will play an influential role in how these services fit in a reformed healthcare system—a point the population health industry has learned quite a bit about in the past decade. Population health programs must engage physicians and demonstrate clearly how they support the physician’s practice and the patients it serves. Fortunately for the industry, it has innumerable examples of collaboration with physicians. Population health’s prospects for a central place in the medical home appear strong, particularly given its ability to provide the health information technology infrastructure that small practices often cannot afford and to dovetail well with medical home certification requirements. As we look to the continued influx of baby boomers to our healthcare system, population health improvement becomes an increasingly impor- tant component of coordination and collaboration with physicians and other medical providers. We know that with appropriate design, flexibility, accurate and timely data, and sound approaches to program evaluation, population health improvement makes for a powerful weapon in our fight against chronic disease—a fight we must win to achieve lasting health sys- tem reform. REFERENCES Adler-Milstein, J., D. Bu, E. Pan, J. Walker, D. Kendrick, J. M. Hook, D. W. Bates, and B. Middleton. 2007. The cost of information technology-enabled diabetes management. Dis Manag 10(3):115-128.

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