Address correspondence to Chenghui Li, Ph.D., Assistant Professor, Department of Pharmacy Practice, Division of Pharmaceutical Evaluation and Policy, College of Pharmacy, University of Arkansas for Medical Sciences, 4301 W. Markham Street Slot # 522, Little Rock, AR 72205; e-mail: email@example.com. Donna West-Strum, R.Ph., Ph.D., Chair and Associate Professor of Pharmacy Administration, Research Associate Professor, Research Institute of Pharmaceutical Sciences, School of Pharmacy, The University of Mississippi, Oxford, MS.
Patient Panel of Underserved Populations and Adoption of Electronic Medical Record Systems by Office-Based Physicians
Article first published online: 9 APR 2010
© Health Research and Educational Trust
Health Services Research
Volume 45, Issue 4, pages 963–984, August 2010
How to Cite
Li, C. and West-Strum, D. (2010), Patient Panel of Underserved Populations and Adoption of Electronic Medical Record Systems by Office-Based Physicians. Health Services Research, 45: 963–984. doi: 10.1111/j.1475-6773.2010.01113.x
- Issue published online: 8 JUL 2010
- Article first published online: 9 APR 2010
- Health information technology;
- underserved populations
Objectives. To examine the association between patient panels of underserved populations and adoption of electronic medical records (EMRs) among office-based physicians.
Data Sources. Two thousand three hundred and twenty-six office-based physicians who responded and saw patients in the 2005 and 2006 National Ambulatory Medical Care Surveys.
Study Design. This study used a cross-sectional design. The unit of analysis was the office-based physician. EMR adoption was defined based on functionalities (No EMR, Limited, or Comprehensive). An EMR was considered to have “comprehensive” functionalities if it included computerized orders for prescriptions and tests, test results, and clinical notes by physicians. Patient panels of underserved populations were measured as proportions of racial/ethnic minorities, Medicaid recipients, or self-pay/no charge/charity care patients treated by a physician using the reported sociodemographic characteristics in patient records linked to their treating physicians. Data were analyzed using multivariate regression analyses controlling for other patient-panel characteristics and characteristics of physicians and their practices.
Principal Findings. We found a negative association between the proportion of Hispanics treated by a physician and physician adoption of EMRs with “comprehensive” functionalities after adjusting for other covariates.
Conclusions. Physicians treating high shares of Hispanic patients may have lower access to EMRs with essential functionalities.