1. Predictors of Hospitalization during a Medicare Skilled Nursing Facility Stay
July 30, 2018
Ian Stockwell, PhD
Fei Han, PhD
2018 Joint Statistical Meetings

2. The Hilltop Institute
Hilltop is a nonpartisan research organization at the University of Maryland, Baltimore County (UMBC) dedicated to improving the health and wellbeing of people and communities.
Mission: Hilltop works to advance the health and wellbeing of people and communities through research and analysis.
Vision: Hilltop strives to be a pre-eminent resource for federal, state, and local policymakers, and to contribute to the broad understanding of how better to serve people and communities.

3. Introduction U.S. Skilled Nursing Facility (SNF) Care*
Medicare covers care in a SNF up to 100 days
The Maryland Department of Health requested that Hilltop determine the predictive value of questions present on a Minimum Data Set (MDS) assessment for subsequent hospitalization during a SNF stay *

4. Methodology Minimum Data Set
A standardized assessment tool
22 sections, 600+ fields
Contains cognitive patterns, mood, behavior, functional status, health diagnoses, clinical conditions, clinical treatments, skin conditions, medication, et al.
Health Services Cost Review Commission (HSCRC) Data Files
Record hospital avoidable/unavoidable admission/readmission status
Cox Proportional Hazard Model

5. Results Interested events include: avoidable admission (22 predictors)
unavoidable admission (13 predictors)
avoidable readmission (21 predictors)
unavoidable readmission (20 predictors)
For example, if one SNF resident has heart failure, the hazard of avoidable admission for this resident during his/her SNF stay is 28% higher than that of a resident without heart failure. For more details, please see our poster handout.

6. Policy Implications Potential to:
direct appropriate health intervention
increase patient safety and quality
reduce health care cost
Current work: Integrate the model with Maryland health care database to provide hospitalization risk scores for SNF population

7. Contact Information
Fei Han, PhD
Policy Analyst