A methodology for targeting hospital cases for quality of care record reviews.
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
The results indicate that most of the characteristics are associated with higher percentages of quality of care problems than cases chosen at random, and that the methodology has promise as a tool for targeting cases for medical record review.
Abstract
We tested the efficacy of selected case characteristics in targeting quality of care problems for medical record review. The case characteristics, all of which apply to patients who die in a hospital, consist primarily of procedures and DRGs (diagnosis-related groups) for which death rarely occurs, and a set of complications of surgical care. All characteristics are obtainable from combinations of the principal and secondary diagnoses and procedures in the case, and are available from discharge abstracts. The presence of a quality of care problem is confirmed through a review of the medical record by a nurse and two or more physicians. A logistic regression model that controls for various patient and hospital variables is used as a measure of each of the proposed case characteristics. The results indicate that most of the characteristics are associated with higher percentages of quality of care problems than cases chosen at random, and that the methodology has promise as a tool for targeting cases for medical record review.
