Predicting Nursing Home Admissions
To develop an effective policy that promotes the use of home- and community-based long-term care as an alternative to institutional care, policymakers and leaders must fully understand the disease, risk, frailty and social characteristics of the specific population groups who are at risk of nursing home admission. Additionally, federal approval of any state policy to modify the Medicaid program design requires that a budget neutrality analysis – or an evaluation of program costs – be carefully conducted and be based upon data and credible information.

Targeting and Identifying Intervention Strategies for Elderly Persons at Risk of Nursing Home Admission
JAI has developed a model that is specifically designed for predicting individuals who are at risk of long-term nursing facility admission. The model estimates the probability that an individual would have a future nursing-home admission, using the existing data from the Medicaid and Medicare program. The JAI probability score is based on several factors, including impairment, age, gender, and payer, and is specifically designed to target and identify the population of elderly individuals eligible for intervention strategies. Predictive Modeling Solutions

In addition to predicting individuals that are at risk of a nursing home admission, the JAI predictive model is flexible enough to be used for designing an effective long-term care program, including: (1) targeting candidates for screening and evaluation for the Demonstration Waiver Program; (2) supporting design and clinical/social intervention strategies of the program; and, (3) performing a waiver analysis and/or budget neutrality analysis as required by the federal government. Federal Waiver, Budget Neutrality Analyses

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