Measuring case mix and severity of illness in Canada: case mix groups versus refined diagnosis related groups.

This study compares the effectiveness of Case Mix Groups (CMG*) groups and Refined Diagnosis Related Groups (RDRG) in reducing Canadian length of stay (LOS) variability. The effectiveness of the two case mix grouping methodologies was assessed with a common data base, 282,459 abstracts with ICD-9 CM diagnosis codes reported to the Hospital Medical Records Institute (HMRI) from January to March 1989. Death, signouts, transfers to or from acute care institutions and cases with an outlier LOS ("atypical" cases) were excluded from the analysis. HMRI utilization management reports to acute care hospitals use a data base defined in this way. On the basis of the variance reduction statistic (R2) from ordinary least squares regression analysis, CMG groups were found to be slightly more effective than RDRGs in reducing LOS variability. R2 statistics were 45.7 and 43.8 for CMG groups and RDRGs, respectively. Within subgroups of cases, CMG groups were found to be markedly more effective with the newborn/neonate group and to a lesser extent with non-surgical cases. The severity of illness categories within RDRGs did not, over all "typical" cases in the data base, yield more homogeneous groups of cases than CMG groups, which have half the number of categories. The value of tailoring severity measurement to Canadian medical practice and Canadian diagnosis coding is highlighted.

Tracing the missing link between nursing workload and case mix groups: a validation study.

This paper reports on the creation of a nursing workload data base of over 40,000 inpatient records by the Hospital Medical Records Institute (HMRI). During the 1989-90 fiscal year, five Ontario hospitals (four teaching, one community) reported total hours of nursing on the HMRI abstract along with standard clinical and demographic information. The accuracy of nursing workload data varied across hospitals and seemed to reflect differences in how data collection was implemented. When the data base was grouped by Case Mix Groups (CMGs), analysis demonstrated that patterns of resource utilization in nursing workload and length of stay were similar across CMGs. Results of this analysis indicate that the nursing workload component of the Resource Intensity Weight may be useful for estimating a hospital's nursing costs by CMG.