A longitudinal analysis for the identification of the factors that affect the case mix index of hospitals in the U.S

Abstract

The present thesis is an analysis of longitudinal data collected through the years 2011-2013, from a complex of four hospitals located in Indiana, USA. The aim of the analysis was the detection of changes (especially a decline) in the disease related group (DRG) weights (and thus, the case mix index (CMI)), and the determination of the predictors that significantly affect these changes.

The document is divided in four major parts. In the first part it is described the statistical theory required for the the analysis, in the second part the reimbursement strategies for the hospitals in the USA, are briefly described and the concept of the DRG and CMI are explained. In the third part the actual analysis is presented while the last part contains a summary of the findings and some conclusions.

The correlation between the observations was taken into account by modeling the data using linearmixed models (LMM). Three major factors were studied for their effect on the DRG weight of thehospitals: the changes in the type of cases (i.e. the product lines), the changes in the number of the Surgical cases, and also the changes of the length of stay (LOS). The analysis did not indicate any significant DRG change in any of the hospitals except from the H4. The H4 hospital has a significant decline over time regarding the Cardio-vascular (CV) DRG weights. For the hospitals H1, H2 and H3 the only decline observed in the product lines was that for the Medical-Surgical DRG. Finally, no significant change was observed for the LOS, or the number of Surgical cases.

In addition to the three predictors studied, changes in the coding system, the documentation etc. may also affect the DRG and CMI. However, these changes are not possible to be detected through this analysis, since no available information was given in the present data.