Electronic Medical Record Availability and Primary Care Depression Treatment
Electronic medical records (EMR) are commonly believed to improve quality of care. Primary care patients with multiple chronic conditions have potentially greater opportunity to benefit from receiving care at practices with EMRs if these systems help coordinate complex care.
To examine how chronic conditions impact the odds that depressed patients receive depression treatment in primary care practices with EMRs compared to practices without EMRs.
The study uses logistic regression to analyze cross-sectional data of primary care physician office visits in freestanding, office-based practices from the 2006–2008 National Ambulatory Medical Care Surveys.
All visits to primary care providers made by patients ages 18 and older with physician-identified depression (N = 3,467).
Outcomes include depression treatment which is defined as receipt or ordering of antidepressant medication and/or mental health counseling.
EMRs were associated with significantly lowered odds that depressed patients received depression treatment (OR = 0.75, p = 0.009, 95% CI: 0.61-0.93); however when stratified by the number of chronic conditions, this association was observed only in patients with three or more chronic conditions (OR = 0.50, p > 0.001, 95% CI: 0.36-0.70). EMRs did not have a significant association with depression treatment for patients with two or fewer chronic conditions.
EMRs appear to have an unintended negative association with depression care provided during visits made by primary care patients with multiple chronic conditions.
Key Wordselectronic medical records depression chronic conditions
- 2.U.S. Department of Health and Human Services. Mental Health : A Report of the Surgeon General. Rockville, MD: U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Mental Health Services, National Institutes of Health, National Institutes of Mental Health.;1999.Google Scholar
- 12.Institute of Medicine. Crossing the quality chasm: a new health system for the 21st century. Washington D.C.: National Academy Press; 2001a.Google Scholar
- 16.Romano MJ, Stafford RS. Electronic Health Records and Clinical Decision Support Systems: Impact on National Ambulatory Care Quality. Arch Intern Med. Forthcoming:archinternmed.2010.2527.Google Scholar
- 21.Bryant E, Shimizu I. Sample design, sampling variance, and estimation procedures for the National Ambulatory Medical Care Survey. Vital and health statistics Series 2, Data evaluation and methods research 1988 Sep(108): 1-39. Google Scholar
- 22.StataCorp. Stata Statistical Software: Release 10.0 Special Edition. College Station, TX: Stata Corporation; 2007.Google Scholar
- 23.Hsu J, Huang J, Fung V, Robertson N, Jimison H, Frankel R. Health information technology and physician-patient interactions: impact of computers on communication during outpatient primary care visits. Journal of the American Medical Informatics Association:. 2005;12(4):474–80.PubMedCrossRefGoogle Scholar