Determining engagement in services for high-need individuals with serious mental illness.

This study examined whether Medicaid claims and other administrative data could identify high-need individuals with serious mental illness in need of outreach in a large urban setting. A claims-based notification algorithm identified individuals belonging to high-need cohorts who may not be receiving needed services. Reviewers contacted providers who previously served the individuals to confirm whether they were in need of outreach. Over 10,000 individuals set a notification flag over 12-months. Disengagement was confirmed in 55 % of completed reviews, but outreach was initiated for only 30 %. Disengagement and outreach status varied by high-need cohort.

Reengagement of high-need individuals with serious mental illness after discontinuation of services.

OBJECTIVE: The study determined rates of reengagement in services for individuals with serious mental illness who had discontinued services. METHODS: As part of a quality assurance program in New York City involving continuous review of Medicaid claims and other administrative data, clinician care monitors identified 2,834 individuals with serious mental illness who were apparently in need of care but disengaged from services. The care monitors reviewed monthly updates of Medicaid claims, encouraged outreach from providers who had previously worked with identified individuals, and determined whether individuals had reengaged in services. RESULTS: Reengagement rates over a 12-month follow-up period were low, particularly for individuals who had been incarcerated or for whom no service provider was available to provide outreach. CONCLUSIONS: Subgroups of disengaged individuals with serious mental illness have different rates of reengagement. Active outreach by providers might benefit some, but such targeting is inefficient when the individual cannot be located.

Public-academic partnerships: using Medicaid claims data to identify service gaps for high-need clients: the NYC Mental Health Care Monitoring Initiative.

Public mental health authorities have access to large administrative databases. Advances in information technology now make it possible to use secondary analyses of these data to inform policy and clinical interventions. New York City and State mental health authorities developed an initiative using Medicaid claims and other administrative data to identify individuals with serious mental illness living in New York City (NYC) who are at risk of lapses in care. The NYC Mental Health Care Monitoring Initiative represents one of the first efforts to create "evidence-based policy." The authors describe the initiative's background, development, and key collaborations.

Use of administrative data to identify potential service gaps for individuals with serious mental illness.

OBJECTIVE: The New York City Mental Health Care Monitoring Initiative uses Medicaid claims data to identify individuals with serious mental illness who are experiencing or at risk for gaps in services. In this study the authors assessed whether proposed service use algorithms accurately identified such individuals. METHODS: A random sample of 500 individuals with serious mental illness was identified. Individuals belonged to specific high-need cohorts and met predefined claims-based criteria for potential service gaps. Clinical staff initiated reviews with prior service providers for 230 individuals. RESULTS: Over a two-week period staff completed reviews for 188 cases (88%). In 66 cases (35%) the individual was fully engaged in care; 84 (45%) had a recent episode of disengagement that was appropriately addressed, and 38 (20%) were not receiving adequate services. CONCLUSIONS: The proposed service use algorithms successfully identified high-need individuals with serious mental illness at risk for gaps in services.