The adoption of interoperable EMR systems could produce efficiency and safety savings of $142–$371 billion.
ABSTRACT: To broadly examine the potential health and financial benefits of health infor-mation technology (HIT), this paper compares health care with the use of IT in other indus-tries. It estimates potential savings and costs of widespread adoption of electronic medical record (EMR) systems, models important health and safety benefits, and concludes that ef-fective EMR implementation and networking could eventually save more than $81 billion annually—by improving health care efficiency and safety—and that HIT-enabled prevention and management of chronic disease could eventually double those savings while increas-ing health and other social benefits. However, this is unlikely to be realized without related changes to the health care system.
heu.s.healthcareindustryis arguably the world’s largest, most in-efficient information enterprise. However, although health absorbs more than $1.7 trillion per year—twice the Organization for Economic Coopera-tion and Development (OECD) average—premature mortality in the United States is much higher than OECD averages.1 Most medical records are still stored on paper, which means that they cannot be used to coordinate care, routinely mea-sure quality, or reduce medical errors. Also, consumers generally lack the informa-tion they need about costs or quality to make informed decisions about their care.
It is widely believed that broad adoption of electronic medical record (EMR) systems will lead to major health care savings, reduce medical errors, and improve health.2 But there has been little progress toward attaining these benefits. The United States trails a number of other countries in the use of EMR systems.3 Only
Richard Hillestad (Richard_Hillestad@rand.org) and James Bigelow are senior management scientists at RAND in Santa Monica, California. Anthony Bower is a senior economist there; Federico Girosi is a policy researcher; and Robin Meili is a senior management systems analyst. Richard Scoville and Roger Taylor are senior consultants at RAND Health—Scoville, in Chapel Hill, North Carolina, and Taylor, in Laguna Beach, California.
15–20 percent of U.S. physicians’ offices and 20–25 percent of hospitals have adopted such systems.4 Barriers to adoption include high costs, lack of certifica-tion and standardization, concerns about privacy, and a disconnect between who pays for EMR systems and who profits from them.
In 2003 the RAND Health Information Technology (HIT) Project team began a studyto(1) betterunderstandthe role andimportanceofEMRsinimproving health care and (2) inform government actions that could maximize the benefits of EMRs and increase their use. This paper summarizes that study’s results about benefits and costs. A companion paper by Roger Taylor and colleagues in this vol-ume describes the policy implications of our findings.5
Here we summarize the methodologies we used to estimate the current adop-tion of EMR systems and the potential savings, costs, and health and safety bene-fits.Weuse theword potential to mean “assuming that interconnected and interoperable EMR systems are adopted widely and used effectively.” Thus, our es-timates of potential savings are not predictions of what will happen but of what could happen with HIT and appropriate changes in health care. We also provide a more thorough explanation of our data and methods in an online supplement.6
In general, the currently useful evidence is not robust enough to make strong predictions, and we describe our results only as “potential.” However, we do not believethattheyrepresent the“best-casescenario,”for threereasons:(1) We have not included many other effects (such as transaction savings, reductions in mal
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practice costs, and research and public health savings), and there may be more siz-able savings from HIT-motivated health care changes that we are not able to pre-dict: Modern EMR systems may be more effective than the legacy systems reporting evidence; (2) we have not included certain domains such as long-term care; and (3) we do not report possible values above the mean.
The results are not worst-case, either. We chose to interpret reported evidence of negative or no effect of HIT as likely being attributable to ineffective or not-yet-effective implementation. Characteristics of the provider organizations that re-ported the savings were used to scale the results for cases of broader EMR adop-tion. Assuming ten-and fifteen-year HIT adoption periods, we used Monte Carlo simulation to generate the range of savings that might be achieved at different points in the future, assuming that at least part of the reported benefit could be achieved by each newly adopting provider organization. We generally report the mean value of the potential savings.
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age. For ambulatory care, our model used error and adverse drug event reductions reported in the literature for ambulatory CPOE. Using the 2000 National Ambula-tory Medical Care Survey (NAMCS) database on office visits, we extrapolated the effects to full national adoption and show the likely distribution of possible savings and adverse drug events avoided as a function of practice characteristics and size.12
� Estimating other potential health benefits. We considered two kinds of in-terventions—disease prevention and chronic disease management—that would ex-ploit key features of HIT. To estimate the potential effects enabled by EMR systems, we used several years of the MEPS data to develop a representative national patient sample, with its associated information on health care use, diagnosis, and self-reported health status. We applied recommended disease management and preven-tion interventions to appropriate members of that population. Then, given the liter-ature and clinicians’ opinions regarding the effect of the interventions, we calculated the differences in cost, use, health status, and other outcomes measured in MEPS, such as sick days in bed and workdays lost. We evaluated a representative sample of near-term (some effects within one or two years of intervention) prevention, near-term disease management, and long-term (most effects five or more years into the future) chronic disease management and prevention interventions. We report the health benefits and savings associated with various degrees of patient participation in these programs, as might be obtained with HIT support.
We examined a range of industries to understand IT’s effects on productivity and related enabling factors. During the 1990s, many industries—most notably, telecommunications, securities trading, and retail and general merchandising— invested heavily in IT.13 Consumerssaw thefruitsofthisinvestmentinbar-coded retail checkouts, automated teller machines, consumer reservation systems, and online shopping and brokerages. During the late 1990s and continuing into this century, these industries recorded 6–8 percent annual productivity growth, of which at least one-third to one-fourth annually can be attributed to IT. But dra-matic productivity improvements did not follow automatically from IT invest-ments. For example, the hotel industry, which underused its IT investment in the late 1990s, did not see sizable productivity increases.
What if health care could produce productivity gains similar to those in tele-communications, retail, or wholesale? Exhibit 1 superimposes a range of produc-tivity improvements on a plot of estimated growth in national health care spend-ing from 2002 to 2016. The smaller improvement (1.5 percent per year) is similar to the productivity gains in retail/wholesale attributed to IT; the upper end (4 per-cent per year) is half the IT-enabled gains in telecommunications. Either level of productivity improvement could greatly reduce national health care spending. The lower improvement implies an average annual spending decrease of $346 bil-lion, and the upper end, $813 billion.
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EXHIBIT 1 Possible Improved Productivity Effects Of Health Information Technology (IT) On Future National Health Spending, 2002–2016
Annual health spending (billions of dollars) 4,000
Effect of 1.5% annual productivity 3,500 improvement (like retail industry)
National health spending 2,500 projection
Effect of 4% annual productivity improvement 1,000 (half of telecom industry increase)
2002 2004 2006 2008 2010 2021 2014 2016
SOURCE: Authors’ analysis based on data from Centers for Medicare and Medicaid Services, “National Health Accounts,” 17 March 2005, www.cms.hhs.gov/statistics/nhe (26 May 2005).
However, we believe that when thought leaders discuss transforming health care with HIT, they are talking about the kinds of benefits seen in the telecom and securities industries: gains of 8 percent or more per year, year after year. These sec-tors illustrate that it can be done. But our analysis found that the ingredients needed to achieve this growth (strong competition on quality and cost, substan-tial investments in EMR systems, an enhanced infrastructure that can accommo-date increased future demand or reduce costs without increasing labor, a strong champion firm or institution that drives change, and integrated systems) are mostly absent in today’s health care industry. Achieving savings at the upper end of the range will be limited by the degree of transformation that accompanies HIT.
There are few comprehensive estimates of savings from HIT at the national level.14 Using a simulation model of HIT adoption and scaling literature-based HIT effects, we built a national estimate.15
At 90 percent adoption, we estimate that the potential HIT-enabled efficiency savings for both inpatient and outpatient care could average more than $77 billion per year (an average annual savings of $42 billion during the adoption period). Ex-hibit 2 shows the most important sources of the savings we estimated: The largest come from reducing hospital lengths-of-stay, nurses’ administrative time, drug us-age in hospitals, and drug and radiology usage in the outpatient setting.16
Thesepotential savings, whilequite large, areconsiderablylower than thean-nual IT-enabled productivity gains just described in other industries. Although achieving these more limited savings would not require radical changes in the
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EXHIBIT 2 Potential Efficiency Savings With Adoption Of Electronic Medical Record (EMR) Systems
|Savings category||Mean yearly savings ($ billions)||Cumulative savings by year 15 ($ billions) Annual savings ($ billions) Year 5 Year 10||Year 15 (90% adoption)a|
|Outpatient Transcription Chart pulls Lab test||0.9 0.8 1.1||13.4 11.9 15.9||0.4 0.4 0.5||1.2 1.1 1.5||1.7 1.5 2.0|
|Drug usage Radiology Total outpatient savings||6.2 1.7 10.6||92.3 25.6 159.0||3.0 0.8 5.2||8.6 2.4 14.8||11.0 3.3 20.4|
|Inpatient Nursing time Lab test||7.1 1.6||106.4 23.4||3.4 0.8||10.0 2.2||13.7 2.6|
|Drug usage Length-of-stay Medical records||2.0 19.3 1.3||29.3 289.6 19.9||1.0 10.1 0.7||2.8 27.6 1.9||3.5 34.7 2.4|
|Total inpatient savings||31.2||468.5||16.1||44.5||57.1|
Monica, Calif.: RAND, 2005), sec. 4.2.6.
NOTE: These savings have not been discounted, nor do they take into account inflation in health care expenditures.
a The potential savings at 100 percent adoption would obviously be larger, but the uncertainty about when and whether that
level can be reached is very high. We have assumed a fifteen-year adoption period, based on A. Bower, The Diffusion and
Value of Healthcare Information Technology, Pub. no. MG-272-HLTH (Santa Monica, Calif.: RAND, 2005).
health care delivery system, it would require process changes and, in some cases, resource reduction. Also, the potential savings would not be realized immediately. They would require widespread adoption of HIT by providers, and most of the savings would start only after a successful implementation period and associated process changes or resource reductions had taken place. Also, the efficiencies could be used to improve health care quality rather than to reduce costs.
Although the savings would accrue to different stakeholders, in the long run they should accrue to payers. If we allocate the savings using the current level of spending from the National Health Accounts (kept by the Centers for Medicare and Medicaid Services), Medicare would receive about $23 billion of the potential savings per year, and private payers would receive $31 billion per year. Thus, both have a strong incentive to encourage the adoption of EMR systems. Providers face limited incentives to purchase EMRs because their investment typically trans-lates into revenue losses for them and health care spending savings for payers.
Studies showing improved patient safety from EMR use in hospital and ambu-latory care largely focus on alerts, reminders, and other components of CPOE.17 CPOE makes information available to physicians at the time they enter an order— for example, warning about potential interactions with a patient’s other drugs.
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Once the order has been entered, the system can track the steps involved in exe-cuting the order, providing an additional mechanism for identifying and eliminat-ing errors. In the longer term, CPOE provides the information needed to redesign the order-execution process so that errors become even harder to make. To pro-vide these benefits, CPOE must be an integrated component of a more compre-hensive health care information system that is designed and used well.18 We ad-dressed the safety benefits of CPOE by using models to extrapolate existing evidence to the national level and estimated separately the potential to reduce ad-verse drug events in inpatient and outpatient settings.
Our models also show that to obtain the benefits of ambulatory CPOE, one can-not ignore small providers. About 37 percent of the potential savings and error avoidance would come from solo practitioners. Recent estimates suggest that CPOE systems can be cost-effective even for small offices.21
Beyond safety, the literature provides little evidence about EMR systems’ ef-fects on health. We must, therefore, hypothesize about both mechanisms and magnitudes of effects. We considered two kinds of interventions intended to keep people healthy (or healthier): disease prevention measures and chronic disease management.
These interventions are key to understanding HIT’s potential. First, they would exploit important features and capabilities of EMR systems: communication, co-ordination, measurement, and decision support. Second, they are potentially high-
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leverage areas for improving health care. Physicians deliver recommended care only about half of the time, and care for patients with chronic illnesses absorbs more than 75 percent of the nation’s health care dollars.22 Third, evidence from re-gional health information network (RHIN) demonstrations suggests that these are key applications of HIT.23
EMR systems can be instrumental throughout the disease management proc-ess. Predictive-modeling algorithms can identify patients in need of services. EMR systems can track the frequency of preventive services and remind physicians to offer needed tests during patients’ visits. Condition-specific encounter templates implemented in an EMR system can ensure consistent recording of disease-specific clinical results, leading to better clinical decisions and outcomes. Connec-tion to national disease registries allows practices to compare their performance with that of others. Electronic messaging offers a low-cost, efficient means of dis-tributing reminders to patients and responding to patients’ inquiries. Web-based
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EXHIBIT 3 Summary Of EstimatedResults ForIncreasingFivePreventiveServices
|Program description||Influenza vaccination||Pneumococcal vaccination||Screening for breast cancer||Screening for cervical cancer||Screening for colorectal cancer|
|Target population (age)||65 and older||65 and older||Women 40 and older||Women 18–64||50 and older|
|Frequency||1 per year||1 per lifetime||0.5–1 per year||0.33–1 per year||0.1–0.2. per year|
|Population not||13.2 million||17.4 million||18.9 million||13.0 million||52.0 million|
|currently compliant||backlog; 2.1|
|Program cost (with 100% compliance)||$134–$327 million per yea||r $90 million per year||$1–$3 billion per year||$152–$456 million per yea||r $1.7–$7.2 billion per year|
|Financial benefits Health benefits||$32–$72 millioper year||n $500–$1,000 million per year||$0–$643 millioper year||n $52–$160 million per yea||r $1.16–$1.77 billion per year|
|Reduced workdays missed||180,000– 325,000 per year||100,000– 200,000 per year||–a||–a||–a|
|Reduced bed days||1.0–1.8 million per year||1.5–3.0 million per year||–a||–a||–a|
|Deaths avoided||5,200–11,700 per year||15,000–27,000 per year||2,200–6,600 per year||533 per year||17,000–38,000 per year|
|Life-years gained||–a||–a||–a||13,000 per year||138,000 per year|
patient education can increase the patient’s knowledge of a disease and compli-ance with protocols.
For higher-risk patients, case management systems help coordinate workflows, including communication between multiple specialists and patients. In what may prove to be a transformative innovation, remote monitoring systems can transmit patients’ vital signs and other biodata directly from their homes to their providers, allowing nurse case managers to respond quickly to incipient problems. Health information exchange via RHINs or personal health records promises great bene-fits for patients with multiple chronic illnesses, who receive care from multiple providers in many settings.
We examined disease management programs for four conditions: asthma, con-gestiveheart failure(CHF),chronic obstructivepulmonary disease(COPD), and diabetes (Exhibit 4) and estimated the effects of 100 percent participation of peo-pleeligiblefor each program.29 By controlling acute care episodes, these programs greatly reduce hospital use at the cost of increased physician office visits and use
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EXHIBIT 4 Potential Annual Effects Of Near-Term Disease Management Programs For Four Diseases: Asthma, Congestive Heart Failure (CHF), Chronic Obstructive Pulmonary Disease(COPD), AndDiabetes
|Hospital outpatient visits||–5|
|Physician office visits||33|
|School days lost||–13|
of prescription drugs. As shown, the programs could generate potential annual savings of tens of billions of dollars. Keeping people out of the hospital is, of course, a health benefit, but we can also expect important outcomes such as re-ductions in days lost from school and work and in days spent sick in bed.
Exhibit 4 also highlights an important disincentive for health care providers to offer these kinds of services or to invest in HIT to effectively perform them: The savings come out of provider receipts, as patients spend less time in acute care. This key misalignment of incentives is an important barrier to EMR adoption and, more generally, to health care transformation.
� Using HIT for long-term chronic disease prevention and management. A program of EMR-enhanced prevention and disease management should change the incidence of chronic conditions and their complications. We considered cardiovas-cular diseases (hypertension, hyperlipidemia, coronary artery disease/acute myo-cardial infarction, CHF, cerebrovascular disease/stroke, and other heart diseases), diabetes and its complications (retinopathy, neuropathy, lower extremity/foot ulcers and amputations, kidney diseases, and heart diseases), COPD (emphysema and chronic bronchitis), and the cancers most strongly associated with smoking (can-cers of the bronchus and lung, head and neck, and esophagus, and other respiratory and intrathoracic cancers). Using our MEPS-based model, we estimated how com-binations of lifestyle changes and medications that reduced the incidence of these conditions would affect health care use, spending, and outcomes (Exhibit 5).
Savings are evenly divided between the populations under age sixty-five and those age sixty-five and older, despite the fact that the older population consti
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EXHIBIT 5 Estimated Long-Term Effects Of Prevention And Management Of Selected Chronic Conditions, By Age Group
|Under age 65||Age 65 and older||Total|
|Hospital outpatient and ER visits||–8.8||–3.7||–12.5|
|School days lost||–1.6||0.0||–1.6|
|Total bed days||–132.1||–125.1||–257.3|
tutes only 13 percent of the total. Since chronic diseases are, by and large, diseases of the elderly, a large fraction of the long-term savings attributable to prevention and disease management would accrue to Medicare. Yet, to realize these benefits, people would have to begin participating in these programs as relatively young adults.
We combined the effects of the reduced incidence attributable to long-term prevention and management and reduced acute care due to disease management. We estimated the potential combined savings, again assuming 100 percent partici-pation, to be $147 billion per year.30
� Realizing the potential of these interventions. Realizing the benefits of pre-vention and disease management requires that a substantial portion of providers and consumers participate. Since, on average, patients comply with medication regi-mens about half the time, it is plausible to assume that about half of the chronically ill would participate in disease management programs and, therefore, the health care system would reap about half of the estimated short-term benefits, assuming that EMR systems and community-based connectivity were operational.31
Patients comply with their physician’s lifestyle recommendations only about 10 percent of the time.32 We assumed that in a future with EMR-based reminders and decision support and patient-physician messaging, we could realize at least 20 percent of the long-term benefits shown in Exhibit 5. Under these assumptions,
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the net savings would be on the order of $40 billion per year. We varied the partic-ipation in disease management and prevention activities parametrically to show the potential beyond these estimates.33
There are a few published estimates of the costs of widespread implementation of EMR systems in the United States. Samuel Wang and colleagues have provided a model for estimating the cost and return on investment for a physician office practice.34 Jan Walker and colleagues have estimated the costs ($28 billion per year during a ten-year deployment, $16 billion per year thereafter) and net savings ($21.6–$77.8 billion per year, depending on the level of standardization) of a broadly adopted, interoperable EMR system.35 The Patient Safety Institute esti-mated the initial cost of widespread connectivity of EMR systems (not of the EMR system itself) to be $2.5 billion.36
Exhibit 6 plots the net cumulative and yearly potential savings (benefits over costs) from EMR systems in hospital and outpatient settings over time. Because we do not take credit for savings from providers already in the adoption process and because process changes and related benefits take time to develop, net savings are initially low and then rise steeply. Over fifteen years, the cumulative potential net efficiency and safety savings from hospital systems could be nearly $371 bil-lion; potential cumulative savings from physician practice EMR systems could be $142 billion. This potential net financial benefit could double if the health savings produced by chronic disease prevention and management were included.
Our analysis shows that moving the U.S. health care system quickly to broad adoption of standards-based EMR systems could dramatically reduce national health care spending at a cost far below the savings. Further, these potential sav-ings would outweigh the costs relatively quickly during the adoption cycle. But
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EXHIBIT 6 Net Potential Savings (Efficiency Benefits Over Adoption Costs) For Hospital And Physician Electronic Medical Record (EMR) Systems Adoption During A Fifteen-Year Adoption Period (2004–2018)
300 Cumulative inpatient 250 Cumulative outpatient Yearly inpatient 200 Yearly outpatient
0 2004 2006 2008 2010 2012 2014 2016 2018
key barriers in the HIT market directly impede adoption and effective application of EMR systems; these include acquisition and implementation costs, slow and uncertain financial payoffs, and disruptive effects on practices.38 In addition, pro-viders must absorb the costs of EMR systems, but consumers and payers are the most likely to reap the savings. Also, even if EMR systems were widely adopted, the market might fail to develop interoperability and robust information exchange networks.
Given our analysis, we believe that there is substantial rationale for government policy to facilitate widespread diffusion of interoperable HIT. Actions now, in the early stages of adoption, would provide the most leverage. Taylor and colleagues discuss several alternatives for government action to remove barriers, correct mar-ket failures, and speed the realization of EMR system benefits.39
We have shown some of the potential benefits of HIT in the current health care system. However, broad adoption of EMR systems and connectivity are necessary but not sufficient steps toward real health care transformation. For example, adoption of EMR systems and valid comparative performance reporting would en-able the development of value-based competition and quality improvement to drive transformation. HIT also should facilitate system integration for broader op-timization, and comparative benchmarking should encourage development of market-leading examples of ways to better organize, pay for, and deliver care.
It is not known what changes should or will take place after widespread EMR
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system adoption—for example, increased consumer-directed care, new methods of organizing care delivery, and new approaches to financing. But it is increasingly clear that a lengthy, uneven adoption of nonstandardized, noninteroperable EMR systems will only delay the chance to move closer to a transformed health care sys-tem. The government and other payers have an important stake in not letting this happen. Thetimetoact is now.
This report is a product of the RAND HIT Project. It benefited from the guidance of an independent Steering Committee, chaired by David Lawrence, and was sponsored by Cerner, General Electric, Hewlett-Packard, Johnson and Johnson, and Xerox.
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ary 2005, content.healthaffairs.org/cgi/content/abstract/hlthaff.w5.10 (2 May 2005). Laurence Baker ar-gued that these savings were overestimated. L.C. Baker, “Benefits of Interoperability: A Closer Look at the Estimates,” Health Affairs, 19 January 2005, content.healthaffairs.org.cgi/content/abstract/hlthaff.w5.22 (26 May 2005).
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