A Randomized Controlled Trial Testing the Effects of a Social Needs Navigation Intervention on Health Outcomes and Healthcare Utilization among Medicaid Members with Type 2 Diabetes.
Amy McQueenDavid von NordheimCharlene CaburnayLinda LiCynthia HerrickLauren GrimesDarrell BroussardRachel E SmithDana LawsonYan YanMatthew KreuterPublished in: International journal of environmental research and public health (2024)
Health systems are increasingly assessing and addressing social needs with referrals to community resources. The objective of this randomized controlled trial was to randomize adult Medicaid members with type 2 diabetes to receive usual care ( n = 239) or social needs navigation ( n = 234) for 6 months and compare HbA1c (primary outcome), quality of life (secondary outcome), and other exploratory outcomes with t -tests and mixed-effects regression. Eligible participants had an HbA1c test in claims in the past 120 days and reported 1+ social needs. Data were collected from November 2019 to July 2023. Surveys were completed at baseline and at 3-, 6-, and 12-month follow-up. Health plan data included care management records and medical and pharmacy claims. The sample was from Louisiana, USA, M = 51.6 (SD = 9.5) years old, 76.1% female, 66.5% Black, 29.4% White, and 3.0% Hispanic. By design, more navigation (91.5%) vs. usual care (6.7%) participants had a care plan. Social needs persisted for both groups. No group differences in HbA1c tests and values were observed, though the large amount of missing HbA1c lab values reduced statistical power. No group differences were observed for other outcomes. Proactively eliciting and attempting to provide referrals and resources for social needs did not demonstrate significant health benefits or decrease healthcare utilization in this sample.
Keyphrases
- healthcare
- randomized controlled trial
- mental health
- affordable care act
- health insurance
- palliative care
- public health
- health information
- machine learning
- clinical trial
- quality improvement
- type diabetes
- study protocol
- big data
- risk assessment
- adipose tissue
- young adults
- deep learning
- data analysis
- social media
- human health