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Physician Adoption of HIT AHRQ 2007 Annual Meeting September 26, 2007 Melissa M. Goldstein, JD Department of Health Policy School of Public Health and Health Services The George Washington University Medical Center
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Background U.S. Healthcare System: High Costs, Variable Quality Greater use of HIT may improve care Potential annual savings of billions by reducing: »Duplicate services »Administrative costs »Medical errors and adverse events Improve quality Adoption rates low Estimates inconsistent (5% to 65%) and unhelpful
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HIT Adoption Initiative (www.hitadoption.org) HHS -- ONC –GWU Partners/Massachusetts General Hospital Brigham and Women’s Hospital Annual Report (October 2006) – RWJF/ONC
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Objectives Summarize current state of EHR use Describe major barriers and facilitators Examine current state of Health Information Exchange
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Methods Define EHR Synthesize the evidence of EHR use: Environment scan of existing surveys (e.g., NAMCS, NHAMCS, HIMSS) –Some devoted to HIT, some only with sections –Only one survey devoted expressly to assessing adoption among safety net providers Rate using objective criteria
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Results Electronic Health Records Electronic documentation Results reporting Electronic-prescribing Decision support 36 surveys identified 17 surveys had adequate information for quality scoring
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Results: Outpatient EHR Use Summary High Quality Surveys (5): –EHR adoption rate in U.S.: 17% - 27% Highest quality survey (2005): 24% use some EHR Summary of all surveys: –EHR adoption rate in U.S.: 20% - 25%
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Best Estimates of EHR Adoption Range from Medium or High Quality Surveys Best Estimates Based on High Quality Surveys EHRs in physician offices 17 to 25%17% Solo practitioners12.9 to 13%13% Large physicians offices* 19 to 57%39% EHRs in hospitals16+ to 59% ++None CPOE in hospitals4 to 21 %5% * Large is defined as > 20 physicians by one study (with an estimate of 39%) and > 50 physicians (with an estimate of 57%). +Estimate from a survey rated “low” in quality of methodology ++Estimate from a survey quality of content suggested “low” in confidence in the estimate
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Projected diffusion of EHRs among office-based physicians: 2001- 2014 * 2006-2014 %’s are estimated based on current rate of adoption. 3% annual increase 6% annual increase
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Implications of Report EHRs are promising solutions EHR adoption increasing Slow increases At current pace, full EHR use by 2030 Hasn’t yet hit tipping point
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Factors affecting adoption Financial: systems are expensive $50,000 up front per MD in ambulatory care $2-20 Million for hospitals Disruption Often creates significant downtime Changes the way doctors and nurses practice Lack of perceived value Savings accrue to others Lack of standards Privacy concerns
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Factors affecting adoption, cont. EHR adoption contingent on value creation Most adopters have seen a business need »Large practices, multi-site practices Financial barriers critical for small practices »Where most Americans receive healthcare Capturing and re-distributing value »Role of payers? Cultural barriers need to be understood in context »Disruption always difficult »Many have made the change »Generational issues often over-played
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Safety Net Providers HIT Adoption National survey federally funded CHCs (Health Affairs, Sept./Oct. 2007) 26% some EHR capacity 13% minimal set of EHR functionalities CHCs serving the most poor & uninsured less likely to have functional EHR Lack of capital top barrier
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Getting better data on EHR Adoption Define EHR: –Institute of Medicine definition laying out 8 key functionalities –HIT Adoption Initiative modification Define Adoption –Acquisition –Installation –Use Design data collection methods –Development of new survey tools (PM, physician, hospital, consumer) –Identify goals and objectives of policy –Build upon existing federal and private surveys –Develop survey questions that add to and fill in the gaps of other existing programs of data collection
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Getting better data on EHR Value, Barriers and Incentives Define measures of value –Quality –Efficiency –Safety net providers Compare value and efficiency of care with and without EHRs Identify barriers and incentives to adoption Include measures of barriers and incentives in regular data collection activities Real and perceived legal barriers
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Legal barriers Concerns about –New legal exposures –Actual or perceived legal burden of compliance –Actual or perceived legal exposures associated with the disclosure of information
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Melissa M. Goldstein mgoldste@gwu.edu
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