Data quality. An illustration of its potential impact upon a diagnosis-related group's case mix index and reimbursement

Abstract

The Health Care Finance Administration has developed a Medicare reimbursement methodology that will include an adjustment factor for hospital case mix. The patient classification scheme proposed for use in determining a hospital's case mix is the AUTOGRP Diagnosis-Related Groups (DRG) methodology developed at Yale University. The reliability of a case mix measure calculated using the DRG methodology is dependent on complete and accurate diagnostic and surgical data. The source of this data for the HCFA data base (MEDPAR) is the Medicare billing form, which is based on the patient medical record. Data from the MEDPAR file, the original medical record discharge order, and a reabstracted record are compared and analyzed for their effect upon DRG classification and the resultant Medicare reimbursement ceiling for one large teaching hospital. The study results show widely divergent diagnostic and surgical data that results in a significant variation in DRG classification and reimbursement ceilings.