Modeling Community Discharge of Medicaid Nursing Home Residents: Implications for Money Follows the Person

Zachary Hass, Mark Woodhouse, Robert Kane, Greg Arling

Research output: Contribution to journalArticle

2 Scopus citations


Objective: To build and test a model that predicts community discharge probabilities for Medicaid-eligible nursing home (NH) residents who remain in the nursing home at 90 days after admission and, thus, would be candidates for the Money Follows the Person (MFP) program. Data Source: The Minimum Data Set, Medicaid Management Information Systems, and Minnesota Vital Statistics file. Data: Cohort of 33, 590 nursing home stays that qualified for Medicaid by the 90th day of their stay from 383 Minnesota nursing homes from July 2011 to June 2013. Study Design: Mixed effects logistic regression model to predict community discharge. Principal Findings: The scoring system had a high level of accuracy in predicting community discharge for both the fitting and validation cohorts. Subpopulations with severe mental illness or intellectual disability were well represented across the entire score range. Conclusions: Findings are being applied in the Minnesota's MFP initiative (Moving Home Minnesota) to target Medicaid-eligible NH residents for transitioning to the community. This approach could be applied to MFP in other states.

Original languageEnglish (US)
Pages (from-to)2787-2802
Number of pages16
JournalHealth services research
StatePublished - Aug 2018



  • Medicaid
  • Modeling
  • long-term care
  • multi-level
  • quality improvement

ASJC Scopus subject areas

  • Health Policy

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