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Does the Complications Screening Program flag cases with process of care problems? Using explicit criteria to judge
L I Iezzoni1, R B Davis, R H Palmer
1Department of Medicine, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA. liezzoni@bidmc.harvard.edu
Summary
The Complications Screening Program (CSP) did not effectively identify hospital discharges with more process problems. This quality indicator needs cautious evaluation for identifying preventable complications in patient care.
Area of Science:
- Healthcare Quality Improvement
- Patient Safety
- Medical Informatics
Background:
- The Complications Screening Program (CSP) uses computerized discharge abstracts to identify 28 potentially preventable complications of hospital care.
- It analyzes demographic information, diagnosis, and procedure codes to flag potential issues.
Purpose of the Study:
- To validate the CSP as a quality indicator for hospital care.
- To determine if CSP-flagged discharges have higher rates of process problems compared to unflagged discharges using explicit criteria.
Main Methods:
- The CSP was applied to discharge abstracts of Medicare beneficiaries over 65 in California and Connecticut from 1994.
- Physicians defined explicit criteria for 'key steps' in care processes; nurses abstracted medical records to compare process problem rates between flagged (cases) and unflagged (controls) discharges.
Main Results:
- The study included 740 surgical and 416 medical discharges.
- High rates of process problems were observed across CSP screens for both surgical (24.4–82.5%) and medical (2.0–69.1%) cases.
- Crucially, rates of process problems did not significantly differ between CSP-flagged and unflagged discharges.
Conclusions:
- The CSP did not successfully flag discharges with significantly higher rates of explicit process problems.
- Findings suggest that approaches similar to the CSP for identifying complications of care warrant cautious evaluation.
- The study highlights the need for rigorous validation of automated quality indicators in healthcare.