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Effect of population-based interventions on laboratory utilization: a time-series analysis
C van Walraven1, V Goel, B Chan
1Clinical Epidemiology Unit, Ottawa Hospital, Ontario, Canada. carlv@lri.ca
JAMA
|December 24, 1998
Summary
Population-based interventions significantly reduced laboratory test utilization in Ontario. Physician guidelines, form changes, and funding policy adjustments decreased test volumes, saving over 625,000 tests.
Area of Science:
- Health Services Research
- Clinical Pathology
- Health Policy
Background:
- Previous research on reducing laboratory utilization was often limited by being hospital-based, small-scale, single-centered, or short-term.
- Effective strategies for population-wide laboratory test utilization reduction are needed.
Purpose of the Study:
- To evaluate the impact of three population-based interventions on laboratory utilization in Ontario.
- Interventions included physician guidelines, laboratory requisition form modifications, and funding policy changes.
Main Methods:
- An interventional time-series analysis was conducted using claims data from the Ontario Health Insurance Program (July 1991-April 1997).
- The study focused on clinical laboratories outside of hospitals in Ontario.
- Utilization rates of specific laboratory tests (e.g., ESR, urinalysis, iron, thyroid function) were analyzed before and after interventions.
Main Results:
- Significant decreases in utilization were observed for erythrocyte sedimentation rate (ESR) and urea determination (58% and 57% reduction, respectively).
- Microscopic urinalysis decreased by 14%, while non-microscopic urinalysis increased by 1700% following policy changes.
- Iron determination decreased by 80%, total thyroxine by 96%, and thyroid-stimulating hormone (TSH) by 12%.
- These interventions resulted in savings of over 625,000 tests and $210,400 by April 1997.
Conclusions:
- A combined approach of guideline dissemination, requisition form modification, and funding policy changes effectively reduced laboratory test utilization.
- These population-based interventions demonstrate a successful model for optimizing laboratory resource use.