July 30, 2018 Ian Stockwell, PhD Fei Han, PhD

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Presentation transcript:

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

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.

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 * https://www.medicare.gov/pubs/pdf/10153.pdf

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

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.

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

Contact Information Fei Han, PhD Policy Analyst 410.455.6516 fhan@hilltop.umbc.edu