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What data do California HMOs use to select hospitals for contracting?
Julie A Rainwater1, Patrick S Romano
1Division of General Medicine, Center for Health Services Research in Primary Care, School of Medicine, University of California, Davis, 4150 V Street, PSSB Suite 2400, Sacramento, CA 95817, USA.
The American Journal of Managed Care
|August 19, 2003
Summary
Health maintenance organization (HMO) executives consider hospital report cards, but rely on accreditation and reputation over data. They need improved data validity and usefulness for effective hospital selection.
Area of Science:
- Healthcare Management
- Health Services Research
- Quality Improvement
Background:
- Health maintenance organizations (HMOs) are increasingly evaluated on hospital performance.
- Hospital report cards aim to provide quality data for informed decision-making.
- Understanding executive perspectives is crucial for effective quality reporting.
Purpose of the Study:
- To assess HMO executive awareness and perceived usefulness of hospital report cards.
- To determine how HMO executives weigh report card data against other hospital selection factors.
- To identify barriers to the adoption and utilization of hospital quality data.
Main Methods:
- A cross-sectional survey was conducted in 1999.
- HMO executives from licensed HMOs and employee medical benefit plans in California were surveyed.
- Response data were collected via written responses and telephone interviews.
Main Results:
- HMO executives prioritize hospital accreditation, location, and price for contracting decisions.
- Quality is considered, but measured through accreditation, disciplinary actions, reputation, and member satisfaction.
- Concerns exist regarding the validity and utility of current process and outcome data.
Conclusions:
- HMO executives express interest in hospital quality information but are hesitant due to data limitations.
- They currently rely on surrogate quality measures and informal evaluations.
- Producers of report cards must enhance data timeliness, longitudinal follow-up, and external validation.