Appendix A
Workshop Discussion Background Paper
PRESENTATIONS AND RELATED LITERATURE SUMMARY OF THE ESTIMATES

Prepared for


The Healthcare Imperative:

Lowering Costs and Improving Outcomes

Workshop Series

May, July, September 2009

Institute of Medicine

Washington, DC

This paper was prepared by Pierre Yong with the assistance of Michael Punzalan and Erin Taylor.



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Appendix A Workshop Discussion Background Paper Presentations and related literature summary of the estimates Prepared for The Healthcare Imperative: Lowering Costs and Improving Outcomes Workshop Series May, July, September 2009 Institute of Medicine Washington, DC This paper was prepared by Pierre Yong with the assistance of Michael Punzalan and Erin Taylor. 

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 THE HEALTHCARE IMPERATIVE Introduction 637 Overview of the Workshop Series 639 Understanding the Targets 640 Session 1: Unnecessary Services, 640 Session 2: Inefficiently Delivered Services, 646 Session 3: Excess Administrative Costs, 658 Session 4: Prices That Are Too High, 664 Session 5: Missed Prevention Opportunities, 673 Strategies That Work 678 Session 1: Knowledge Enhancement-Based Strategies, 678 Session 2: Care Culture and System Redesign-Based Strategies, 685 Session 3: Transparency of Cost and Performance, 697 Session 4: Payment- and Payer-Based Strategies, 704 Session 5: Community-Based and Transitional Care Strategies, 712 Session 6: Entrepreneurial Strategies and Potential Changes in the State of Play, 718 Summary Table of Estimates 738 Summing the Lower Bound Estimates 753

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 APPENDIX A INTRODUCTION The presentations throughout the first two workshops in the Insti- tute of Medicine (IOM) Roundtable on Value & Science-Driven Health Care’s series The Healthcare Imperative: Lowering Costs and Improving Outcomes, provided a vast survey of the impact of waste and inefficiency on national healthcare expenditures and the potential cost-saving strate- gies available for implementation now. To supplement this information, a working paper was commissioned, which placed the presenters’ estimates in the context of similar national estimates published in the peer-reviewed literature and by think tanks and government agencies. Health reform in the United States has long focused on the means to expand health insurance coverage to the growing numbers of uninsured. In the current debates, significant attention has also been drawn to the necessity to simultaneously address our rapidly escalating national health expenditures, which fully consume one-sixth of our economy. To more fully explore the drivers and solutions to controlling our healthcare spending, the IOM Roundtable on Value & Science-Driven Health Care, with the support of the Peter G. Peterson Foundation, engaged in a three-part workshop series titled The Healthcare Imperative: Lowering Costs and Improving Outcomes. The goals of the series were threefold: (1) to identify, characterize, and discuss the major causes of excess healthcare spending, waste, and inef- ficiency in the United States; (2) to consider strategies that might reduce per capita health spending in the United States while improving health outcomes; and (3) to explore policy options relevant to those strategies. The presentations at the first two workshops in the series offered many estimates on the costs of inefficiency and the potential savings that could be realized through application of much discussed cost-control strategies. This working paper aims to provide brief summaries of estimates provided during those two workshops, including the methods of calculation and any limitations as noted by the presenters. In addition, these estimates are placed in the context of similar national estimates published in the peer- reviewed literature and by think tanks and government agencies. By doing so, a broader sense of the range of costs and savings available throughout the healthcare system will emerge. Several observations noted in the course of completing this work are discussed in the following sections. Varying sources of presentation estimates T he estimates presented throughout the workshop series were calculated by varying methods, in- cluding original peer-reviewed research by the presenter and the presenter’s

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 THE HEALTHCARE IMPERATIVE synthesis of the published literature. In the case of the latter, few additional national estimates were found that were not referenced by the presenter. Differences in underlying methodologies Variation in the estimates within each category often stemmed from differing methodologies, sources of data, study time periods, and scope of work, often making direct comparisons between estimates extremely difficult. Variations in number of available comparison estimates The number of national estimates identified within each category varied significantly, with several well-studied categories containing multiple estimates while other topics containing few or zero comparisons. Limited focus to national estimates While estimates existed for several topics detailing potential costs and/or savings at an institutional or state- wide level, this paper focused on national estimates (if they could be identified). As this paper focused on the estimates provided throughout the IOM workshops, our preliminary literature survey focused primarily on compa- rable national estimates on waste, inefficiency, and cost-savings strategies as applied to the healthcare delivery system. In the course of the work, two notable observations arose and are discussed in the following sections. Range of estimates varied For those estimates in which multiple compari- sons existed, some estimates, such as those for tort reform and telehealth, grouped closely with those in the literature while others lay amidst a large range of estimates, such as those for tertiary prevention and health infor- mation technology. These variations often stemmed from differing method- ologies, study time periods, sources of data, and scope of work, and made direct comparisons between estimates extremely difficult. Need for additional research As the number of national estimates iden- tified within each category varied significantly, with several well-studied categories containing multiple estimates while other topics containing few or zero comparisons, those with few comparisons, such as transparency and retail clinics, indicate areas in need of additional research to calculate national impacts and could build on the studies of smaller scope noted throughout the report. In addition, in areas with large ranges in estimates, further rigorous research would be beneficial in resolving the differences. The next sections contain brief summaries highlighting the workshop estimates as well as identified literature estimates. A table summarizing the estimates discussed throughout the paper is included as an appendix. Also

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9 APPENDIX A included in the appendixes is a summary of the lower-bound estimates developed by the staff of the IOM Roundtable on Value & Science-Driven Health Care based on the information cited throughout the background paper. OVERVIEW OF THE WORKSHOP SERIES In 2009, the IOM Roundtable on Value & Science-Driven Health Care, with the support of the Peter G. Peterson Foundation, engaged in a three- part workshop series titled The Healthcare Imperative: Lowering Costs and Improving Outcomes. The goal of the series was three-fold: • Identify, characterize, and discuss the major causes of excess health- care spending, waste, and inefficiency in the United States. • Consider strategies that might reduce health spending in the United States while improving health outcomes. • Explore policy options relevant to those strategies. Through the efforts of a planning committee consisting of leaders rep- resenting the various stakeholders throughout the healthcare sector, a series of three workshops were defined: • The first workshop, titled Understanding the Targets and convened May 21-22, explored the major drivers of healthcare spending growth, focusing on five broad categories: unnecessary services; inefficiently delivered services; excess administrative costs; prices that are too high; and missed prevention opportunities. • The second workshop, titled Strategies That Work and held July 16- 17, focused on the potential of various strategies to lower health- care spending while improving outcomes, including knowledge enhancement-based strategies; care culture and system redesign- based strategies; transparency of cost and performance; payment- and payer-based strategies; community-based and transitional care strategies; and entrepreneurial strategies and potential changes in the state of play. • The final workshop in the series, titled The Policy Agenda and held September 9-10, delved into the policy options relevant to imple- mentation and adoption of the strategies discussed in July in ways that maximize their impact on controlling the drivers of healthcare spending.

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0 THE HEALTHCARE IMPERATIVE UNDERSTANDING THE TARGETS The initial workshop focused on the identification of categories of waste and inefficiency in the healthcare system and their respective order of magnitude as a percentage of U.S. care spending, including: • Unnecessary services; • Inefficiently delivered services; • Excess administrative costs; • Prices that are too high; and • Missed prevention opportunities. Session 1: Unnecessary Services In a climate of growing concerns about how much the United States spends on health care, it has been estimated that as much as 30 percent of spending could be saved without compromising outcomes (Fisher et al., 2003a, 2003b). Indeed, existing studies find no relationship between higher levels of spending and the quality of care received by patients (Baicker and Chandra, 2004; Yasaitis et al., 2009). The presenters in this session on the provision of unnecessary services focused on • Overuse of services beyond evidence-established benchmarks; • Use of services beyond benchmarks where evidence is not estab- lished; and • Choice of higher-cost services over evidence-established equivalents. Overuse of Services Beyond Evidence-Established Benchmarks Several studies examining the drivers of excess spending have focused on overuse of services and testing that may not bring clinical benefits to patients, highlighting excessive use of antibiotics, imaging and diagnostic tests, avoidable emergency department (ED) use, and surgical procedures (Bentley et al., 2008; Chassin et al., 1987; Merenstein et al., 2006; Winslow et al., 1988). This section presents analyses presented by Amitabh Chandra that ex- amined the degree to which costs and mortality could be simultaneously re- duced. Subsequently, comparable estimates are presented, and the authors’ findings are placed in the context of the existing empirical literature. Savings from reducing overuse of services Chandra (2009) made the ar- gument that healthcare reform could save both money and lives. Chandra

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 APPENDIX A estimated that improving hospital performance to the level of the highest- performing hospitals (based on mortality and cost data) could result in 8 percent reductions in both cost and mortality for three high-mortality conditions (acute myocardial infarction, hip fraction, and colon cancer), saving over $1 billion annually and enabling more than 11,500 patients to live at least 1 more year. Chandra also found evidence suggesting that greater use of bundled payments within Medicare is a viable option for restraining cost growth. In this analysis, the authors extended their prior work demonstrating a lack of association between spending and quality (Yasaitis et al., 2009). Using mortality as a quality measure and actual Medicare spending per beneficiary as the expenditure measure, they failed to find an association between spending and outcomes but rather found high-quality providers at each level of spending. To quantify the savings that might be achieved by improving performance, they first assigned each hospital to one of five categories, ranging from highest to lowest performance, based on spend- ing and quality. Those in the highest performance category had both low mortality and costs; those in the lowest performance category had both high mortality and costs. The authors then simulated what would happen if lower-rated hospitals could perform like those in the higher-rated groups to arrive at the reductions noted above. The authors also found that half of the variation in spending could be explained by the use of Part B services. Given that Part A payments are bundled and Part B payments are not, this finding suggested that combin- ing reimbursements for inpatient, outpatient, and home health into a single payment might achieve savings. The authors noted two main limitations to their study. First, the valid- ity of the authors’ findings relies on the accuracy of their risk adjustment measure (the International Statistical Classification of Diseases and Related Health Problems [ICD]-9 diagnoses codes from Part A claims records), as survival is substantially more sensitive to risk adjustment than quality mea- sures such as those used in Yasaitis and colleagues (2009). Second, as with all other work that relies on benchmarking methods, their study cannot speak about what policy levers could be used to achieve their estimated cost and mortality improvements. Hence, it is not certain how their estimated savings could be realized. Additional estimates Chandra and colleagues’ analysis was one of the first to examine the relationship between hospital-level mortality and spending. A subsequent literature review found that Yasaitis and colleagues (2009), as referenced above, was the study closest to Chandra (2009). There is a sizeable empirical literature that uses more technical methods (and makes more restrictive assumptions) to estimate hospital inefficiency holding qual- ity constant, including stochastic frontier analyses and data envelopment

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2 THE HEALTHCARE IMPERATIVE analysis. Studies analyzing national hospital data using stochastic frontier analyses estimate uniformly higher cost inefficiencies, in the range of 10.8 to 25.5 percent. As mentioned above, Bentley and colleagues (2008) estimated that spending on eight selected wasteful services—excessive antibiotic use, avoidable ED use, and overuse of noninvasive diagnostic imaging, among others—might be as much as $65.1 billion, the equivalent of 3.4 percent of U.S. healthcare spending. Merenstein and colleagues (2006) found that uri- nalyses, electrocardiograms, and x-rays were frequently performed despite evidence and guidelines recommending against their use in asymptomatic patients at an estimated annual direct medical cost of up to $194 million. It has been estimated that the cost of excess medical and surgical services, including coronary artery bypass surgery and percutaneous coronary in- terventions is $600 billion (Delaune and Everett, 2008). Avoidable ED use has been estimated to cost $21.4 billion nationally, and the overuse of antibiotics has been estimated to cost $1.1 billion annually (Delaune and Everett, 2008). Kaplan (2009) discussed analyses indicating that $5.1 bil- lion annually could be saved from a 50 percent decline in unnecessary visits for common conditions—headaches, back pain, and benign breast condi- tions. Additionally, the same author estimated $6.5 billion in annual sav- ings from reducing unnecessary MRI testing for back pain and headaches, extrapolating from their institution’s experience after implementation of an evidence-based protocol. Others have calculated $300 million in annual spending on unnecessary MRI scans for back pain (Delaune and Everett, 2008). While focusing on duplicative and redundant testing, Jha (2009) found that costs amounted to $8.2 billion in 2004. Estimates comparison As above, the finding by Chandra (2009) that hospital-level mortality and spending are uncorrelated in their data is consistent with the findings in Yasaitis and colleagues (2009). That being said, Chandra and colleagues’ (2009) percentage cost savings estimate ap- pears to fall within a reasonable range. The dozens of data envelopment analysis studies of U.S. hospitals cited by Bruce Hollingsworth (2003) have not yet been surveyed. However, Chirikos and Sear (2000) compared the inefficiency estimates generated by these different empirical strategies using data from hospitals in Florida from 1982 to 1983 and found that the data yielded convergent evidence about hospital efficiency at the industry level. This is suggestive, if weak, evidence for the notion that the data envelop- ment analysis and stochastic frontier analyses estimates for national savings would roughly be of the same magnitude. Although the costs of overuse of clinical services cannot be directly compared given the inclusion of different services in each estimate, it is worth noting that the estimates of Bentley and colleagues (2008) cover the

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 APPENDIX A broadest range of services in their analyses, including excessive antibiotic use for viral upper respiratory infections and otitis media, avoidable ED use, avoidable hospitalizations of nursing home patients, overuse of cytol- ogy for cervical cancer screening, inappropriate hysterectomies, unnecessary hospital admissions in ED triage of patients with chest pain, overuse of noninvasive radiologic imaging, and inappropriate spinal fusion surgeries. Although the estimates of Bentley and colleagues (2008) of $18.2 million to $33.3 million in 2004 dollars (1 to 1.8 percent of U.S. healthcare spending) for overuse of noninvasive radiologic imaging far exceeded that of Meck- lenburg and Kaplan (2009), the latter included only MRIs while the former included use of other imaging modalities in their calculations. Use of Services Beyond Benchmarks Where Evidence Is Not Established A number of studies have found that the amount of spending across regions of the United States can vary twofold or greater (CBO, 2008; Fisher et al., 2003a); yet low-spending regions arguably deliver equal or higher quality care than high-spending regions (Baicker et al., 2004; Fisher et al., 2003a). The variation in spending appears to be driven by the use of discretionary medical services (Fisher et al., 2003b; Sirovich et al., 2008). This suggests that interregional comparisons might provide insights into the savings that could be achieved from coaxing better performance out of existing medical institutions. This section reviews estimates presented by Elliot S. Fisher that calcu- lated the potential annual savings that could be achieved within Medicare by eliminating excess use of discretionary services. Comparable estimates are presented and compared. Savings from reducing use of services beyond benchmarks Exploiting this interregional variation in spending, Fisher and Bronner (2009) estimated that annual savings in the area of $50 billion (an 18 to 20 percent reduc- tion) could be achieved within Medicare. By ranking U.S. hospital referral regions according to the intensity of care provided, estimates of potential savings could be calculated by shifting use rates in high-use regions to patterns seen in low-use regions. In particu- lar, they compared regions against benchmarks defined by hospital referral regions ranked in the best decile and quintile. Drawing from sources such as the Dartmouth Atlas of Health Care, Fisher and Bronner found the potential reductions in use rates for a num- ber of services could be substantial. For example, inpatient days could be reduced by up to 21.3 percent and medical specialist visits could be reduced by up to 44.1 percent. In fact, they find large potential reductions across all five services they considered (see Table A-1 below), and the decrease in

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 THE HEALTHCARE IMPERATIVE TABLE A-1 Percentage Reduction in Discretionary Services by Benchmark Care Intensity Benchmark Best Quintile (%) Best Decile (%) Medical discharges 17.8 21.3 Inpatient days 23.4 28.4 Physician visits (overall) 21.9 27.4 Primary care visits 11.7 16.1 Medical specialist visits 37.2 44.1 these use rates would result in an expenditure reduction of $47.8 billion to $53.9 billion, when moving to the top quintile and top decile benchmarks, respectively. There are two main limitations to Fisher and Bronner’s approach. First, benchmarking by hospital referral region unavoidably ignores the substan- tial variation in cost and quality within each region. For example, the gains from improving administrative efficiency or reducing defensive medicine practices through tort reform do not enter into the authors’ calculations. Along the same lines, possible expenditure reductions from reforming the payment system or implementing greater integration and coordination of care are also excluded. Therefore, the authors may actually be underesti- mating the potential gains to healthcare reform. Second, benchmarking methods in general are silent on how the predicted benefits might actually be achieved. Even if the authors’ analysis suggests that savings of $50 billion or more in Medicare are achievable in principle, it does not say by what mechanism these savings can be manifested nor does it account for the costs of improving performance to the benchmarked regions. Additional estimates Based on a similar type of benchmarking analysis, Wennberg and colleagues (Wennberg et al., 2002) estimated that $40 bil- lion, or 28.9 percent of spending, could have been saved in 1996 if Medi- care spending levels were reduced to the lowest spending decile nationally. Reviews in recent reports from the Council of Economic Advisers (Romer, 2009) and the Congressional Budget Office (CBO) (2008) relied very heav- ily on this paper’s findings, and subsequent searches identified few other estimates in the literature. Estimates comparison Although the absolute savings of approximately $50 billion presented by Fisher and Bronner (2009) is larger than the

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 APPENDIX A literature estimate of $40 billion by Wennberg and colleagues (2002), the latter estimate represents a 10 percentage point difference in total spending. While the reasons underlying the difference remain unclear, perhaps factors other than discretionary services, such as the burden of chronic illness or the efficiency of delivery of clinical services, may have become relatively more significant drivers of Medicare spending over time. Also, as Fisher and Bronner (2009) analyzed disaggregated data from a more recent time period, their estimate may be more relevant to the current policy debate than prior estimates. Choice of Higher-Cost Services Over Evidence-Established Benchmarks Roughly one-third of all medical decisions require choosing between or among two or more treatment options (Center for the Evaluative Clinical Sciences, 2005). These “preference-sensitive” care decisions drive approxi- mately one-fourth of all Medicare expenditures (Wennberg et al., 2009). Treatment options often range from conservative to aggressive and range in costs as well, but recent studies have found that patients exposed to de- cision aids were more likely to choose conservative treatment (O’Connor et al., 1999, 2003). These findings suggest that preference-sensitive care may present a significant opportunity to reduce costs without affecting outcomes. In this section, analyses by David Wennberg are presented. The author estimated the potential savings from increased use of shared decision mak- ing (SDM). A comparison to other estimates is also presented. Savings from reduced choice of higher-cost services Shared decision- making programs are designed to assist patients confronted with two or more treatment options in making informed decisions. Often facilitated with decision aids, SDM aims to provide unbiased estimates of the risks and benefits for each treatment option available to the patient. By foster- ing communication and collaboration between patients and their provid- ers, patients become empowered to make informed choices. Patients using SDM often choose more conservative (and less expensive) treatment after carefully weighing the trade-offs. After reviewing the literature, the author concluded that a 1 to 1.5 percent reduction in net health spending could be achieved with systematic use of SDM, while the combination of SDM with changes in provider incentives and benefit design could lead to a greater than 5 percent reduction in net health costs. The author expressed three caveats. First, no other healthcare system could provide a counterfactual system on which he could base his estimate as SDM has not been systematically applied in any other healthcare sys-

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Summary Table of Estimates (Continued)  Topic/Presenter Presenter Estimate Relevant Comparisons Estimates Remarks No evidence of cost savings (CBO, 2004b; Delaune and Everett, 2008; Elmendorf, 2009; Goetzel et al., 2005; Mattke et al., 2007; Russell, 2009) Savings from Increased Tertiary Prevention Michael P. $45 billion annual Please see Flottemesch (2009) for more details Please see Flottemesch (2009) Pignone spending reduction for more details from increased tertiary prevention BIR = billing and insurance-related; DME = durable medical equipment; SDM = shared-decision making. *Estimate presented during May workshop. STRATEGIES THAT WORK Session 1: Knowledge Enhancement-Based Strategies Comparative Effectiveness Research Carolyn M. N/A $480 billion over 10 years (2010-2019) (Collins et al., 2009) Given uncertainty in predicting Clancy adoption, others (Berenson et al., 2009; CBO, 2007) have noted potential for savings but declined to provide specific estimates

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Evidence-Based Clinical Protocols Lucy A. $2 billion annual savings $175 billion over 10 years (2010-2019) from implementation Estimates are not directly Savitz for evidence-based of an integrated medical management program in Medicare comparable as one is based on protocol for treating and application of evidence-based standards to reimbursement savings from a single clinical febrile infants policies (UnitedHealth Group, 2009a) protocol; the other estimates saving for federal spending Electronic Health Records with Decision Support Rainu $1 to $2.7 million $77 billion in annual savings due to efficiency gains; Significant variation exists in the Kaushal annually per hospital $371 billion for hospital systems ($142 billion physician offices) estimates of savings associated after an initial investment over 15 years when including gains from safety (Hillestad et al., with adoption of EHRs and HIT from adoption 2005) depending on the time horizon of computerized analyzed, the type of technology physician order being examined, and the extent entry (Massachusetts to which the authors assume the Technology Collaborative technology will be adopted & New England Healthcare Institute, 2009) $86,400 per provider $180 billion over 10 years from investment in HIT (Collins over five years from et al., 2009) adoption of EHRs in $800 billion spillover effects from adoption of EHR (Russo, the ambulatory setting 2009) (Wang et al., 2003) $97 billion in 10-year savings from adoption of EHRs (Berenson et al., 2009) Likely no cost savings (CBO, 2008)  continued

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Summary Table of Estimates (Continued)  Topic/Presenter Presenter Estimate Relevant Comparisons Estimates Remarks Session 2: Care Culture and System Redesign-Based Strategies Improved Provider Profile and Use Michelle J. N/A $8.3 billion in savings if half of outpatient visits for Though the interventions are Lyn uncomplicated patients could be handled capably by qualified related, broadly speaking, the non-physicians (Mecklenburg and Kaplan, 2009)* savings estimates are not directly comparable $16 billion in savings from community-based wellness programs (Trust for America’s Health, 2008) $2 to $7.5 billion in savings from retail clinics (Thygeson, 2009)* Jason Hwang N/A Care Site Efficiency and Productivity Initiatives and Incentives Kim R. $57.8 billion in savings Please see Milstein (Milstein, 2009) for more details Please see Milstein (2009) for Pittenger from widespread more details implementation of Virginia Mason Production System Sandeep $35 to $112 billion Green annual savings from Vaswani national implementation of Variability Methodology in hospitals

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Care Site Integration Initiatives Timothy G. $0.6 and $1.5 billion $367.4 billion in total savings to federal government over Estimates are not directly Ferris for Medicare over a ten years from bundle of interventions (UnitedHealth Group, comparable due to specificity two year period from 2009a) of the intervention described implementation of care in Ferris; regardless of the $175 billion in savings from patient-centered medical homes delivery model targeting approach taken, all the reviewed over ten years (Collins et al., 2009) the highest risk patients papers endorse the concept of $14.8 billion over the next decade for Medicare and Medicaid care coordination as a potential from lowering payment for potentially preventable readmissions method of improving health and within 15 days of discharge to 60 percent of the usual payment care coordination; please Owens (Berenson et al., 2009) (2009) for more details Antitrust Interventions Roger N/A N/A Please see Capps (2009) for Feldman more details Promoting Information Technology Interoperability/Connectivity Ashish Jha $81 billion through Please see Kaushal (2009) for more details Both of these studies have improvements in HIT been subject to significant safety and efficiency methodological critiques; please (Hillestad et al., 2005) see Kaushal (2009) for more details $337 billion during a 10-year implementation period and annual savings of nearly $78 billion in each subsequent year (amounts measured in 2003 dollars) (Walker et al., 2005)  continued

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Summary Table of Estimates (Continued)  Topic/Presenter Presenter Estimate Relevant Comparisons Estimates Remarks Service Capacity Restrictions Frank A. N/A N/A Author suggested that Sloan effectiveness of capacity restrictions depends on other policy decisions on cost containment; recent work (Grabowski et al., 2003; Ho, 2007) support the notion that CON programs have not succeeded in cost containment Medical Liability Reform Randall R. $20 billion (0.9%) of $210.0 billion in savings from reduction in defensive medicine PriceWaterhouseCoopers’ Health Bovbjerg annual health spending (PriceWaterhouseCoopers, 2009) Research Institute estimate far could be saved with exceeds bounds established in conventional tort reform majority of econometric research publications on this topic Session 3: Transparency of Cost and Performance Transparency in Prices John Santa N/A N/A N/A Transparency in Comparative Value of Treatment Options G. Scott N/A N/A N/A Gazelle

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Transparency in Comparative Value of Providers Paul B. N/A $14.5 billion (2010-2019) from sharing quality data in N/A Ginsburg Medicare (UnitedHealth Group, 2009b) Transparency in Comparative Value of Hospitals and Integrated Systems Peter K. $2.5 to $5 billion in N/A N/A Lindenauer annual savings from public reporting requirements related to hospitals Transparency in Comparative Value of Health Plans Margaret E. N/A N/A N/A O’Kane Session 4: Payment and Payer-Based Strategies Bundled and Fee-for-Episode Payments Amita $165 billion from $96.4 billion over 5 years for Medicare if shift to episode-of- Difficult to compare savings Rastogi utilization of bundled care based payments (Schoen et al., 2007) estimates due to focus on payment for 13 specific different conditions and conditions in commercial populations population Managed Competition David R. N/A $17.4 billion in 2010 (federal savings) due to operation of a N/A Reimer public plan option in a health insurance exchange (Berenson et al., 2009) 9 continued

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Summary Table of Estimates (Continued) 0 Topic/Presenter Presenter Estimate Relevant Comparisons Estimates Remarks Value-Based Insurance Design Niteesh K. $2 billion if VBID N/A N/A Choudhry applied to five common conditions Lisa Carrara 3% to 4% savings in 3% to 7% decrease in premiums from use of more efficient Aetna (from which Carrara’s patient’s claims in the providers (GAO, 2007) estimate were drawn) was one of first year by designating the insurers included in the GAO $37 billion (2010-2019) from implementation of a program specialists based on high study; as neither the Carrara or designed to provide Medicare beneficiaries with information on quality and efficiency GAO estimate translated savings quality and efficiency variations among providers (UnitedHealth into dollar amounts, direct Group, 2009a) comparison are not possible Administrative Simplification David S. $322 billion based on $337 billion in administrative savings over 10 years due to a Estimates are not directly Wichmann application of technology national health insurance exchange with a public plan option comparable due to targeting of to administrative (The Commonwealth Fund, 2009) different means of simplification, activities (UnitedHealth though there is some degree of Group, 2009b) overlap Robin $3 billion if CORE is Thomashauer implemented nationwide (IBM Global Business Services, 2009)

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Session 5: Community-Based and Transitional Care Strategies Care Management for Medically Complex Patients Kenneth E. $75 billion savings Please see Owens (2009) and Ferris (2009) for more details Please see Owens (2009) and Thorpe over ten years from Ferris (2009) for more details investment in transitional care from frail elders (Naylor et al., 2004) Palliative Care Diane E. $4.8 billion in annual $6.4 billion in savings in 2010 (Berenson et al., 2009) Meier and Berenson et al. Meier savings from increased estimates draw on overlapping $18 billion in savings between 2010 and 2019 (UnitedHealth palliative care literature; UnitedHealth Group Group, 2009a) estimate difficult to compare given decade long estimate Wellness and Community Programs Jeffrey Levi $16 billion in annual $7 billion in annual savings from increased primary preventive Estimates not directly savings within five years services (Flottemesch, 2009)* comparable since Flottemesch analyzed clinical preventive services while Levi analyzed community wellness and prevention programs  continued

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Summary Table of Estimates (Continued) 2 Topic/Presenter Presenter Estimate Relevant Comparisons Estimates Remarks Session 6: Entrepreneurial Strategies and Potential Changes in the State of Play Retail Clinics N. Marcus $2 to $7.5 billion in N/A Multiple studies support findings Thygeson annual savings from of improved quality and lower increased utilization of costs from use of retail clinics, retail clinics though none offer national savings estimates (Eibner et al., 2009; Mehrotra et al., 2009) Technological Innovation Adam $1.7 billion in annual $3.6 billion in savings from national implementation of Estimates not directly Darkins cost savings from telehealth technology (Vo, 2008) comparable given different increased usage of Care interventions in different settings $4.3 billion in annual savings from widespread implementation Coordination/Home of telehealth systems (Pan et al., 2008) Telehealth NOTE: CORE = Committee on Operating Rules for Information Exchange; EHR = electronic health record; HIT = health information technology; MedPAC = Medicare Payment Advisory Commission; VBID = value-based insurance design. *Estimate presented during May workshop.

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 APPENDIX A SUMMING THE LOWER BOUND ESTIMATES To provide an informal contextual perspective on the magnitude and distribution of the excess healthcare costs estimated from the workshop presentations and supplemental literature review, the staff of the Insti- tute of Medicine’s Roundtable on Value & Science-Driven Health Care considered the estimates cited in the background paper and identified the lowest estimate within each category of excess expenditure considered. After adjustment to 2009 expenditure levels, these estimates were summed and are indicated on the preceding table with a condensed summary in Box A-1. It should be emphasized that these are virtually all unvalidated extrapolations, based on assumptions from limited observations, and, in the face of obvious overlaps, duplications and uncertainties in the component estimates. They are therefore offered purely for illustrative purposes and to prompt the follow-on analyses necessary for a clearer understanding of the nature, magnitude, and interrelationships of excess health expenditures in the United States, as well as of the strategies necessary to address them. Examples of the follow-up analyses required include the following questions and issues: • Where are there large differences in estimates addressing similar issues, what are the methodologic differences, and how can they be accommodated or revised to improve the estimates? • Which areas and topics need the most additional work, and are there other areas and topics to be addressed? • To minimize double counting among categories, and account for intervention synergy, how might the crosswalk delineating areas and degrees of overlap be best approached? • Which benchmarks in the variety of topics covered within this sum- mary reflect the most appropriate benchmark levels to guide further analyses? • To what degree can cost findings based on national Medicare data be applied to other populations such as those commercially insured? • How might additional analyses be further refined to ensure accu- racy of the analytics and capture of the significant dimensions and nuances of the areas covered? • What additional research is needed to identify the specific, action- able interventions and the steps needed to achieve net savings?

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 THE HEALTHCARE IMPERATIVE BOX A-1 Excess Cost Domain Estimates: Lower bound totals from workshop discussions* UNNECESSARY SERVICES Total excess = $210 B* • Overuse: services beyond evidence-established levels • Discretionary use beyond benchmarks – Defensive medicine • Unnecessary choice of higher cost services INEFFICIENTLY DELIVERED SERVICES Total excess = $130 B* • Mistakes—medical errors, preventable complications • Care fragmentation • Unnecessary use of higher cost providers • Operational inefficiencies at care delivery sites – Physician offices – Hospitals EXCESS ADMINISTRATIVE COSTS Total excess = $190 B* • Insurance-related administrative costs beyond benchmarks – Insurers – Physician offices – Hospitals – Other providers • Insurer administrative inefficiencies • Care documentation requirement inefficiencies PRICES THAT ARE TOO HIGH Total excess = $105 B* • Service prices beyond competitive benchmarks – Physician services i. Specialists ii. Generalists – Hospital services • Product prices beyond competitive benchmarks – Pharmaceuticals – Medical devices – Durable medical equipment MISSED PREVENTION OPPORTUNITIES Total excess = $55 B* • Primary prevention • Secondary prevention • Tertiary prevention FRAUD Total excess = $75 B* • All sources—payer, clinician, patient fraud *Lower bound totals of various estimates, adjusted to 2009 total expenditure level.