Community-Wide Assessment of Intensive Care Outcomes Using a Physiologically Based Prognostic Measure: APACHE III

2 Aug
2014

In 1989, a collaborative and cooperative strategy formulated by hospitals, physicians, and employers in a large metropolitan region led to the implementation of a standardized measurement system to evaluate patient outcomes of intensive care and other services in acute care hospitals serving the region. This effort, Cleveland Health Quality Choice (CHQC), can be traced to the coalescence of concurrent initiatives undertaken by seven local founding organizations in the provider and business communities to examine the cost and quality of care, The underlying philosophy of this ongoing initiative is that availability of timely health-care outcomes data will lead to improved quality of care and more effective decision-making by purchasers. Importantly, this focus emphasizes the importance of quality indicators in appropriately evaluating the value derived from health-care services.
To measure patient outcomes in ICUs, hospitals have collected data to determine the severity of illness of each patient admitted to the ICU. The data are then used to determine a predicted risk of in-hospital death, on the basis of a validated prognostic system—APACHE III (acute physiology and chronic health evaluation). For each hospital, actual and predicted mortality rates are then compared. The current study reports important observations from the first 4 years of data collection and analysis canadianfamilypharmacy. Specifically, we examine the predictive validity of the APACHE III method, as applied in actual practice in a large community-based cohort of patients, and the utility of applying a previously derived normative risk prediction equation to this cohort. In addition, we examined variations in standardized mortality across individual hospitals and changes in mortality rates that have occurred over the 4-year study period. The findings provide important insights into using physiologically based prognostic tools for ICU patients and interpreting currently accepted clinical end points, such as hospital mortality, in the evaluation of ICU performance.

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