Geographic Variation in Ambulatory EHR Adoption and Implications for Underserved Communities

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1 Geographic Variation in Ambulatory EHR Adoption and Implications for Underserved Communities Jennifer King and Michael Furukawa Office of the National Coordinator for Health IT (ONC) Melinda Buntin formerly of ONC

2 Substantial recent growth in physician EHR adoption 45% Basic EHR Adoption by Office-Based Physicians 40% 39% Primary Care 35% 30% 30% 34% Total 25% 20% 15% 10% 20% 17% 21% 25% 20% 5% 0% Data source: National Ambulatory Medical Care Survey (NAMCS) Electronic Health Record Supplement mail surveys,

3 Ensuring benefits accrue equally across patient populations is critical Currently, substantial variation across states Previously, variation within some states according to market characteristics Previously, variation according to patient characteristics nationally Insurance status Race/ethnicity Lack of data on current local area variation 2

4 Study aims Describe extent of local area variation in ambulatory EHR adoption Assess whether adoption in areas with traditionally underserved populations is keeping pace Racial and ethnic minority population Low income population Rural areas and inner cities 3

5 Data Data on census of ambulatory health care sites in 2011 from SK&A 262,000 sites with 716,600 physicians, NPs, PAs Data on local areas using Public Use Microdata Area (PUMA) boundaries Areas with at least 100,000 population Contiguous census tracts or counties; designed to represent homogeneous communities N =

6 Key measures: Local area EHR adoption rates (1) Local area EHR adoption rate not adjusted for site characteristics Share of providers in PUMA at site with any EHR with e-prescribing functionality (2) Probability of EHR adoption for standard site Calculated from multilevel linear probability model with site-level covariates and PUMA random effects 6/26/2012 Office of the National Coordinator for Health Information Technology 5

7 Key measures: Local area characteristics High concentration of minority population Areas in 75 th percentile of share of population that is non-white race or Hispanic ethnicity High concentration of low income population Areas in 75 th percentile of share of population with family income below 200% of poverty Metropolitan status Large central metropolitan (akin to inner cities) Large fringe metropolitan (akin to suburbs) Medium/small metropolitan Non-metropolitan 6/26/2012 Office of the National Coordinator for Health Information Technology 6

8 Range in local area EHR adoption between and within states 7

9 Distribution of local area EHR adoption rates by priority population characteristics 8

10 Association between local area characteristics and EHR adoption Pr(LowAdoption) = f(highminority + HighLowIncome + LargeCentralMetro + LargeFringeMetro + NonMetro) Low Adoption Area is below 25 th percentile of local area EHR adoption rates Estimate for nation overall and within census regions 9

11 Association between local area characteristics and EHR adoption EHR adoption rate unadjusted for site characteristics US Northeast Midwest South West Cutoff for lowest quartile 32% 29% 35% 33% 33% Incremental effect on likelihood of being a low adoption area Area has high concentration of minority population No --- a --- a --- a --- a --- a Yes 0.12 *** 0.19 ** ** Area has high concentration of low income population No --- a --- a --- a --- a --- a Yes ** Metropolitan status Large central metropolitan 0.11 *** 0.19 ** * 0.10 * Large fringe metropolitan 0.12 *** 0.27 *** Medium or small metropolitan --- a --- a --- a --- a --- a Non-metropolitan N 2, Incremental effects are the percentage point differences in the probability of being a low adoption area for the area type relative to the reference category based on logistic regression coefficient estimates. a Reference category. ***(**)(*) Marginal effect estimate statistically different from zero at p < 0.001(0.01)(0.05) based on standard errors obtained by the delta method. 10

12 Association between local area characteristics and EHR adoption Probability of adoption for a standard health care site US Northeast Midwest South West Cutoff for lowest quartile 39% 37% 39% 40% 38% Incremental effect on likelihood of being a low adoption area Area has concentration of minority population No --- a --- a --- a --- a --- a Yes 0.09 ** 0.14 * * Area has high concentration of low income population No --- a --- a --- a --- a --- a Yes 0.08 ** ** Metropolitan status Large central metropolitan 0.09 ** ** Large fringe metropolitan 0.08 ** 0.14 * * Medium or small metropolitan --- a --- a --- a --- a --- a Non-metropolitan * N 2, Incremental effects are the percentage point differences in the probability of being a low adoption area for the area type relative to the reference category based on logistic regression coefficient estimates. a Reference category. ***(**)(*) Marginal effect estimate statistically different from zero at p < 0.001(0.01)(0.05) based on standard errors obtained by the delta method. 11

13 Key findings Substantial variation between and within regions and states Minority, low income, and large metropolitan areas lag behind on average Patterns vary by region Nonmetropolitan areas keeping pace Substantial variation within all types of communities Both high and low adoption areas are heterogeneous 12

14 Limitations Ecologic associations only Crude measure of EHR adoption Patterns may be different for more robust EHR systems and Meaningful Use attainment 13

15 Implications Going forward, will be critical to monitor: Patterns of Meaningful Use diffusion Effects of HHS programs designed to support adoption in all types of communities Opportunities exist for low adoption communities to borrow lessons from communities with similar characteristics and higher rates of ambulatory EHR adoption 14

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