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Depression Quality of Care: Measuring Quality over Time Using VA Electronic Medical Record Data
- Source :
- Journal of General Internal Medicine. 31:36-45
- Publication Year :
- 2016
- Publisher :
- Springer Science and Business Media LLC, 2016.
-
Abstract
- The Veterans Health Administration (VA) has invested substantially in evidence-based mental health care. Yet no electronic performance measures for assessing the level at which the population of Veterans with depression receive appropriate care have proven robust enough to support rigorous evaluation of the VA's depression initiatives.Our objectives were to develop prototype longitudinal electronic population-based measures of depression care quality, validate the measures using expert panel judgment by VA and non-VA experts, and examine detection, follow-up and treatment rates over a decade (2000-2010). We describe our development methodology and the challenges to creating measures that capture the longitudinal course of clinical care from detection to treatment.Data come from the National Patient Care Database and Pharmacy Benefits Management Database for primary care patients from 1999 to 2011, from nine Veteran Integrated Service Networks.We developed four population-based quality metrics for depression care that incorporate a 6-month look back and 1-year follow-up: detection of a new episode of depression, 84 and 180 day follow-up, and minimum appropriate treatment 1-year post detection. Expert panel techniques were used to evaluate the measure development methodology and results. Key challenges to creating valid longitudinal measures are discussed.Over the decade, the rates for detection of new episodes of depression remained stable at 7-8 %. Follow-up at 84 and 180 days were 37 % and 45 % in 2000 and increased to 56 % and 63 % by 2010. Minimum appropriate treatment remained relatively stable over the decade (82-84 %).The development of valid longitudinal, population-based quality measures for depression care is a complex process with numerous challenges. If the full spectrum of care from detection to follow-up and treatment is not captured, performance measures could actually mask the clinical areas in need of quality improvement efforts.
- Subjects :
- medicine.medical_specialty
Databases, Factual
Delphi Technique
media_common.quotation_subject
Population
Alternative medicine
Cohort Studies
03 medical and health sciences
0302 clinical medicine
Internal Medicine
Electronic Health Records
Humans
Medicine
Performance measurement
Quality (business)
Longitudinal Studies
030212 general & internal medicine
Quality of care
Psychiatry
education
health care economics and organizations
Depression (differential diagnoses)
Quality of Health Care
Veterans
Original Research
media_common
education.field_of_study
Depression
business.industry
030503 health policy & services
Decision Trees
Electronic medical record
United States
humanities
United States Department of Veterans Affairs
Population Surveillance
Family medicine
Mental health care
0305 other medical science
business
Follow-Up Studies
Subjects
Details
- ISSN :
- 15251497 and 08848734
- Volume :
- 31
- Database :
- OpenAIRE
- Journal :
- Journal of General Internal Medicine
- Accession number :
- edsair.doi.dedup.....c392477b2cbe7e74218bc22189e58e1e
- Full Text :
- https://doi.org/10.1007/s11606-015-3563-4