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Policies and Regulations (Poster Session)

(P28-002-24) Impact of Medically Tailored Meals on Healthcare Use and Expenditures in 50 U.S. States

Monday, July 1, 2024
12:45 PM – 1:45 PM CT
Location: Poster Board 72

    Presenting Author(s)

  • Shuyue Deng, MS (she/her/hers)

    Ph.D. Student
    Friedman School of Nutrition Science and Policy at Tufts University
    Everett, Massachusetts, United States

    • Co-Author(s)

  • FC

    Frederick Cudhea

    Food is Medicine Institute, Friedman School of Nutrition Science & Policy, Tufts University, United States

  • KH

    Kurt Hager

    Population and Quantitative Health Sciences, University of Massachusetts Medical School, United States

  • DK

    David Kim

    University of Chicago, Division of Hospital Medicine, Department of Medicine, United States

  • Dariush Mozaffarian, MD, DrPH

    Dean
    Friedman School of Nutrition Science and Policy at Tufts University
    Boston, Massachusetts, United States

  • LW

    Lu Wang

    Research Assistant Professor
    Tufts University
    BOSTON, Massachusetts, United States

  • JW

    John B. Wong, MD

    Tufts Medical Center

Disclosure(s):
Shuyue Deng, MS: No relevant financial relationship(s) with ineligible companies to disclose.


Objectives: Medically tailored meals (MTMs) reduce healthcare utilization among high-risk patients with complex diet-sensitive conditions. The potential impact of MTMs across 50 U.S. states, where many Medicaid and commercial plans’ coverage decisions are made for MTM, remains unknown.

Methods: We estimated the potential impact of MTMs in each state, based on restricted state-level 2010-2019 Medical Expenditure Panel Survey data representing 6.9M adults with one or more diet-sensitive conditions and limited activities of daily living, enrolled in Medicare, Medicaid, or private-payer insurance. The policy effect size was estimated by conducting a meta-analysis of published interventional studies offering an average of 10 meals/week for 8 months per year for one year. A population-based, open-cohort health policy simulation model estimated changes in annual program costs, hospitalizations, and healthcare expenditures, compared to the base scenario of without the MTMs.

Results: California reported the largest eligible patient population for MTM treatment (n=888,387), while Arizona has the smallest (n=57,867 ). MTMs would avert from 1 hospitalization per 2.3 treated patients per year in Maryland to 1 per 7.1 in Colorado. Accounting for implementation costs, MTMs are projected to generate net cost savings across all states, with the largest savings per-patient treated in Pennsylvania ($4,280), followed by Massachusetts ($4,088), Connecticut ($3,783), and New York ($3,496); and lowest, in Oregon ($908) and Alabama ($227).

Conclusions: MTM therapy for high-risk patients with chronic illnesses are projected to reduce hospitalizations and produce net savings in all 50 states, but with important variations which help inform state-level decision-makers on coverage for MTMs through Medicaid 1115 waivers, Medicare shared savings and Accountable Care Organization programs, and commercial plans.

Funding Sources: National Heart, Lung, & Blood Institute (NHLBI), National Institutes of Health (NIH)