Apache-L

A principal concern regarding Medicare's diagnosis-related group (DRG)-based prospective payment system is whether hospitals caring for more severely ill patients may be undercompensated for the services they provide. Research on possible inequities in hospital payment has been hampered by the absence of an objective, easily obtained, and valid measure of patients' severity of illness. Because laboratory data are objective and computerized in most of our nation's hospitals, a system utilizing such data, if shown to discriminate between patients of differing expected resource use, could prove most helpful in examining possible inequities in prospective payment system hospital payment. At a major teaching hospital, data were used from length of stay inlier patients in the 10 most frequent medical DRGs in the U.S. to develop and evaluate a severity of illness system called APACHE-L. APACHE-L uses the laboratory component of the original APACHE score. Whereas DRGs explained 20% of the variation in length of stay for the top ten DRGs, APACHE-L explained up to an additional 14% of the variation. For ancillary resource use, DRGs explained 10% of the variance, and APACHE-L explained up to an additional 15%. Diagnosis-related group-specific analyses demonstrated that the amount of resource use variance explained by APACHE-L varied widely depending on the DRG (from R2 = .00 for DRG 410, chemotherapy; to R2 = .38 for DRG 320, kidney and urinary tract infections, age greater than 17 years with complications or comorbidities). The APACHE-L score, which is objective and readily available in our nation's hospitals, shows considerable promise as a severity of illness adjuster for a subset of DRGs

Illness behavior · Medical illness · MEDLINE · Psychiatry · Emergency Medicine · Health Systems, Economic Evaluations, Quality of Life · Healthcare cost, quality, practices · Healthcare Policy and Management · Medicine · Psychology

• The Integrated Inpatient Management Model

  Annette M Bernard, Rodney A Hayward et al.•Medical Care•1995

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• An Evaluation of Generic Screens for Poor Quality of Hospital Care on a General Medicine Service

  Rodney A Hayward, Annette M Bernard et al.•Medical Care•1993

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• Changes in Prognosis After the First Postoperative Complication

  Jeffrey H Silber, Paul R Rosenbaum et al.•Medical Care•2005

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• Risk-Adjusting Hospital Inpatient Mortality Using Automated Inpatient, Outpatient, and Laboratory Databases

  Gabriel J Escobar, J Greene et al.•Medical Care•2008

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• Statistical validation of a severity of illness measure

  Douglas P Wagner, W A Knaus et al.•American Journal of Public Health•1983

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