Adverse Outcomes following Inpatient Rehabilitation: Trends and Reasons
Why have rates of mortality and rehospitalization following inpatient rehabilitation (IRF) care increased? Age, functional independence, and impairment groups served have not changed sufficiently to explain these adverse trends. Research is needed to develop the knowledge base and tools necessary to address the problem and to examine explanations for adverse outcomes. The proposed research will do this.
Descriptive analyses will be conducted first to describe important trends in mortality and rehospitalizations and to provide a basis for further analyses. Multivariate risk adjustment models -- based on impairments, functional level, age, and other patient characteristics in extant databases -- will then be developed to predict adverse outcomes. These risk adjustment models will provide the necessary basis to distinguish the effects of patient severity and caseload from other factors that affect adverse outcomes. We will then examine and test the effects of important facility characteristics that may affect rates of adverse outcomes. The primary outcomes to be studied will be mortality and rehospitalization; functional decline will also be studied, as it too may indicate medical instability, and all three outcomes may - or may not - be predicted and affected by the same set of factors.
Two major extant sources of data on patient characteristics, functional gain, and outcomes after IRF care will be analyzed:
- the ITHealth Track (ITH) database, which has data on all patients and payors from participating IRFs (98 IRFs, 44,156 cases in 2003), including 90 day follow-up data;
- CMS's IRF- Patient Assessment Inventory (PAI) database and the Medicare Provider Analysis and Review (MedPAR) database. The IRF-PAI database has over 400,000 cases annually; MedPAR has data on institutional and status outcomes for these patients.
Multivariate statistical analysis methods will be employed, including logistic regression and multilevel models.
The risk adjustment models developed will provide a validated tool for distinguishing patient-severity from treatment quality and other factors affecting adverse outcomes - an essential basis for targeting efforts to address and manage the problem. This research is designed to provide clinical professionals, policy makers, and persons with disability with explanations for high and increasing rates of adverse outcomes, the first step towards solving or managing the problem.
For more information, contact:
Mark V. Johnston, PhD,
Principal Investigator, Professor, UWM
(414) 229-3616 firstname.lastname@example.org