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N/A N=96,759

Impact of Medicaid Health Home on Patients With Diabetes in New York City

Type 2 Diabetes Mellitus

Enrolled (actual)
96,759
Serious AEs
Results posted
Jul 2025
Primary outcome: Primary: Number of Enrollees With Diabetes-related Preventable Hospitalizations — 48; 109; 48; 90 Participants

Study Design & Population

Study type
Observational
Phase
N/A
Interventions
Age
Adult, Older Adult · 18+ yrs
Sex
All
Sponsor
Icahn School of Medicine at Mount Sinai
Primary completion
Aug 2021

Outcome Measures

OutcomeResultp-value
PRIMARY
Number of Enrollees With Diabetes-related Preventable Hospitalizations
48; 109; 48; 90
SECONDARY
Number of Primary Care Visits
10.9; 8.7
SECONDARY
Number of Months of Medicaid Coverage
11.7; 10.7

Summary

Type 2 diabetes is common in the United States; about 1 in 10 people have the disease. Diabetes can cause devastating health events, such as hospitalizations, kidney failure, blindness, amputation, heart attack, stroke, painful nerve damage (neuropathy), and death. There are many barriers for patients with diabetes that get in the way of controlling risk factors, following recommendations, and getting the care they need from the health system to help prevent these complications; this is especially true for those with other health problems too. Those living in poverty and racial/ethnic minorities are more likely to have complications from diabetes, and less likely to get recommended care from health systems. In order to improve care and outcomes for people with complex medical problems, several states have started the Medicaid Health Home (HH) program, including New York State (NYS) in 2012. This program is for people with two or more chronic health conditions, such as diabetes and heart disease, people with HIV, and people with a serious mental health condition. HHs are meant to manage and coordinate care, by helping health care providers, social service agencies, community-based organizations, and health insurance plans work together. Similar programs have been shown, on a smaller scale, to improve some results for patients with diabetes, such as lab tests indicating level of diabetes control. Studies have not yet looked at how a large program like HHs impacts the way healthcare is delivered and impacts the health events that matter most to patients with diabetes. Also, few studies include stakeholders on the research team, even though they stand to benefit the most from such programs, and have the experience needed as patients, clinicians, advocates, and administrators to guide efforts. The investigators have gathered a research team that includes scientific investigators along with a diverse group of partners, including patients, clinicians, and program administrators. The investigators plan to use two data sources that show what happens to individual patients over time: 1) NYS Medicaid insurance data 2) the New York City-Clinical Data Research Network (NYC-CDRN). The NYC-CDRN has identified a group of patients with diabetes from 7 large health systems; it has also developed a system for putting together the same set of information for each patient, and removing any identifying information. The investigator will look at patients who have diabetes and are part of a HH and study what happened to them over time. The investigator will also look at a comparison group of patients who are very similar to the HH patients, but they did not join a HH, and follow them over time. The investigator will then compare these two groups to each other. The investigator will look at the quality of healthcare they received and their health outcomes. The investigator will focus on health outcomes that are meaningful to patients. This study can provide important knowledge about the effects of the HH program on patients with diabetes.

Eligibility Criteria

Inclusion Criteria

  • adults over age 18
  • Type II diabetes
  • insured by Medicaid
  • low income
  • data included in the New York City Clinical Data Research Network (NYC-CDRN)
  • for intervention group,Health Home enrollment
  • comparison group will be obtained through propensity score matching
View full record on ClinicalTrials.gov →

Data sourced from ClinicalTrials.gov (NCT02713321). Outcome figures and adverse-event rates are extracted automatically from the registry's posted results and are provided for clinician reference, not as a substitute for the primary publication.

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