By Paul Rossi, Director of Client Services, Foothold Technology
Recently, I had the privilege of presenting on a panel at the 2017 Governor’s Conference on Housing and Economic Development in Atlantic City, New Jersey. The session, The Intersection of Homelessness and Medicaid Use, featured Dr. Joel Cantor, Director of the Center for State Health Policy (CSHP) at Rutgers University, together with Katelyn Cunningham, formerly of Monarch Housing.
As part of the presentation, Ms. Cunningham provided an overview of research highlighting Medicaid and homelessness data from studies in Connecticut, Massachusetts and Michigan. I provided background on Continuum of Care programs, Homeless Management Information Systems (HMIS), the use of HMIS in New Jersey and the process by which de-duplicated services data was pulled from the HMIS to match with Medicaid claims data. While still very early in the research, Dr. Cantor provided a broader context for the study’s purpose and was able to share some preliminary findings. Monarch Housing published some of the early findings on its website.
As panelists, we were excited to speak with attendees about these types of research studies and the use of data to drive policy, support decision-making, and provide a deeper analysis of outcomes. As I described in the presentation, for this project, in order to satisfy privacy concerns and comply with the law, the identification of HMIS and Medicaid matches was done outside of the principal research team. Once all of the data use agreements were in place, NJHMIS provided a dataset, containing client identifiers with an Encrypted Client ID (ECID) to the New Jersey Department of Human Services, Division of Medical Assistance and Health Services (DMAHS), to de-duplicate and match against five years of Medicaid and CHIP claims data. DMAHS provided the de-identified results (including the ECID) to CSHP and the NJHMIS provided a de-identified file of demographic and service data (linked to the ECID) to CSHP for the study.
Having been involved in NJ HMIS since its inception in 2003, I was delighted to see that years of data were being examined with a goal of identifying high utilizers of both homeless services and healthcare. With an eye towards identifying interventions and systems changes, this data can be used to help reduce both the length of time someone is homeless and the intensity of the use of healthcare services, while also reducing the demand on the system. Most importantly, by taking this approach, it’s my hope data can be used, in part, to support an overall improvement in health outcomes for some of the most vulnerable among us.