E VI R S Y S T E M S Can Electronic Medical Record Systems Transform Health Care Potential Health Benefits Savings And Costs The adoption of interoperable EMR systems could produce efficiency and safety savings of 142 371 billion by Richard Hillestad James Bigeiow Anthony Bower Federico Girosi Robin Meiii Richard Scoviile and Roger Tayior ABSTRACT To broadly examine the potential health and financial benefits of health information technology HIT this paper compares health care with the use of iT in other industries It estimates potential savings and costs of widespread adoption of electronic medical record EMR systems models important health and safety benefits and concludes that effective 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 increasing health and other social benefits However this is unlikely to be realized without related changes to the health care system HE U S HEALTH CARE INDUSTRY is arguably the world s largest most inefficient information enterprise However although health absorbs more than 1 7 trillion per year twice the Organization for Economic Cooperation and Development OECD average premature mortality in the United States is much higher than OECD averages Most medical records are still stored on paper which means that they cannot be used to coordinate care routinely measure quality or reduce medical errors Also consumers generally lack the information 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 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 Only T Richard HiUestad Richard HiUcstad rand org andjamcs Bigclow are senior management scientists at RAND in Santa Monica Caiiforma Anthony Bower is a senior economist there Federico Girosi isapoiicy researcher and Robin Meili is a senior management systems analyst Richard Scovilk and Roger Taylor are senior consultants at RAND HealthScovillc in Chapel fiill North Carolina and Taylor in Lagma Bcack California HEALTH AFFAIRS Volume 24 Number 5 rX 10 lJ77 hlthaff 24 5 1103 2OO5 Projca HOPE Tbc People ID People Hcakh Foundation Inc 1103 E C O N O M I C S O F H I T 15 20 percent of U S physicians offices and 20 25 percent of hospitals have adopted such systems Barriers to adoption include high costs lack of certification 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 Teehnology HIT Project team began a study to 1 better understand the role and importance of EMRs in improving 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 volume describes the policy implications of our findings Study Data And Methods Here we summarize the methodologies we used to estimate the current adoption of EMR systems and the potential savings costs and health and safety benefits We use the word potential to mean assuming that interconnected and interoperable EMR systems are adopted widely and used effectively Thus our estimates 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 Estimation of current HIT adoption and related factors Our primary data source was the Healthcare Information and Management Systems Society HIMSS Dorenfest survey which represents a broad canvassing of acute care hospitals chronic care facilities and ambulatory practices on their adoption and plans to adopt various HIT components We included in the adoption category the provider organizations that had contracted for but not yet installed an EMR system To examine the factors related to differences in adoption we merged additional data about the providers and then performed probit regression analysis Our lowerbound estimate of HIT adoption assumed an integrated system that had an EMR clinical decision support and a central data repository from the same vendor to ensure interoperability We adjusted the estimates according to the known underreprcsentation of smaller providers in this survey Estimation of potential HiT efficiency savings We conducted a broad liter ature survey to capture evidence of HIT effects The survey was primarily from peerreviewed literature but it included some information from non peer reviewed literature Expert opinion was used to validate some of this evidence In some cases such as savings from transcription reported results covered a broad range and we used these ranges to estimate a possible distribution of savings Eor effects supported by only a few useful artieles we superimposed the same degree of dispersion 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 believe that they represent the best case scenario for three reasons 1 We have not included many other effeets such as transaction savings reductions in mal September October 2005 E M R S Y S T E M S practice costs and research and public health savings and there may be more sizable savings from HIT motivated health care changes that we are not able to predict 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 yeteffective implementation Characteristics of the provider organizations that reported the savings were used to scale the results for cases of broader EMR adoption 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