Physician Electronic Health Record Adoption and Potentially Preventable Hospital Admissions: Panel Data Evidence from 2010 - 2013
Data Sources. SK&A Information Services Survey of Physicians (a market research firm that collects information in each quarter from a census of ambulatory health care sites), American Hospital Association General Survey and Information Technology Supplement; hospital use measures come from the Medicare Provider Analysis and Review files. Our study population consists of fee for service (FFS) Medicare beneficiaries aged 65 and older. We used criteria from the Agency for Healthcare Research and Quality to identify ACSC admissions.
Study Design. A fixed effects model estimated the relationship between Hospital Referral Region (HRR) level measures of physician EHR adoption and ACSC admissions and readmissions. Our sample of 14.8 million beneficiaries with one or more of four chronic conditions accounts for 54 percent of all elderly Medicare FFS beneficiaries. We used the hospital stay-level data to construct rates of admissions per beneficiary at the HRR level (restricting the denominator to beneficiaries in our sample). In particular, we aggregated condition-specific ACSC admission rates into one overall composite rate; all rates were adjusted for differences across HRRs in Medicare beneficiary age, sex, and race. Our calculations of readmission rates capture unplanned readmissions within 30 days of discharge and are risk-adjusted to account for clinically relevant variables, including age, principal discharge diagnosis, and comorbid diseases. We calculated physician EHR adoption rates as the percentage of physicians in each HRR who report using EHR in ambulatory care settings. We included a measure of hospital adoption as the percentage of Medicare discharges from acute care general hospitals that satisfied criteria analogous to Meaningful Use (MU) Stage 1 requirements.
Principal Findings. Increasing market-level EHR adoption by physicians is correlated with a statistically significant decline of 1.06 ACSC admissions per 10,000 beneficiaries over the study period, controlling for the overall time trend as well as market fixed effects and characteristics that changed over time. This finding implies 26,689 fewer ACSC admissions in our study population during 2010 to 2013 that were related to physician ambulatory EHR adoption. This represents 3.2% fewer ACSC admissions relative to the total number of such admissions in our study population in 2010. We found no evidence of a correlation between EHR use, by either physicians or hospitals, and hospital readmissions at either the market level or hospital level.
Conclusions. This study extends knowledge about health IT’s relationship to quality of care and utilization. The results suggest a significant association between EHR use in ambulatory care settings and ACSC admissions that is consistent with policy goals to improve the quality of ambulatory care for patients with chronic conditions. The null findings for readmissions support the need for improved interoperability between ambulatory care EHRs and hospital EHRs to realize improvements in readmissions.