A Description of Expensive and Long-Staying Patients

by Sally Trude, Grace M. Carter


Download eBook for Free

FormatFile SizeNotes
PDF file 2.1 MB

Use Adobe Acrobat Reader version 10 or higher for the best experience.


Purchase Print Copy

 FormatList Price Price
Add to Cart Paperback58 pages $23.00 $18.40 20% Web Discount

To limit the risk to hospital finances associated with extremely long or expensive patient stays, Medicare supplements the predetermined payments of its Prospective Payment System with outlier payments. However, because outlier cases still cause losses, hospitals have incentives to discourage admissions of potential outliers if these cases can be identified prior to admission. The study reported in this Note used patient characteristics (demographics, chronic disease conditions, number of diseased body systems, and prior hospitalizations) to describe the 5 percent of cases with the largest losses, the 5 percent of longest stays within each diagnosis-related group, and a measure of accounting profit for the case. The Note describes multivariate models of patient characteristics, compares long-stay cases with extreme-loss cases, and discusses the relationship between the hospital and patient characteristics. Finally, it relates the results of the analysis to policy concerns.

This report is part of the RAND Corporation Note series. The note was a product of the RAND Corporation from 1979 to 1993 that reported other outputs of sponsored research for general distribution.

Permission is given to duplicate this electronic document for personal use only, as long as it is unaltered and complete. Copies may not be duplicated for commercial purposes. Unauthorized posting of RAND PDFs to a non-RAND Web site is prohibited. RAND PDFs are protected under copyright law. For information on reprint and linking permissions, please visit the RAND Permissions page.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.