A New Data Resource to Examine Meals on Wheels Clients' Health Care Utilization and Costs

Med Care. 2019 Mar;57(3):e15-e21. doi: 10.1097/MLR.0000000000000951.

Abstract

Background: Access to social services (eg, nutrition) can impact older adults' health care utilization and health outcomes. However, data documenting the relationship between receiving services and objective measures of health care utilization remain limited.

Objectives: To link Meals on Wheels (MOW) program data to Medicare claims to enable examination of clients' health and health care utilization and to highlight the utility of this linked dataset.

Research design: Using probabilistic linking techniques, we matched MOW client data to Medicare enrollment and claims data. Descriptive information is presented on clients' health and health care utilization before and after receiving services from MOW.

Subjects: In total, 29,501 clients were from 13 MOW programs.

Measures: Clients' demographics, chronic conditions, and hospitalization, emergency department (ED), and nursing home (NH) utilization rates.

Results: We obtained a one-to-one link for 25,279 clients. Among these, 14,019 were Medicare fee-for-service (FFS) beneficiaries and met inclusion criteria for additional analyses. MOW clients had high rates of chronic conditions (eg, almost 90% of FFS clients were diagnosed with hypertension, compared with 63% of FFS beneficiaries in their communities). In the 6 months before receiving MOW services, 31.6% of clients were hospitalized, 24.9% were admitted to the ED and 13% received care in a NH. In the 6 months after receiving meals, 24.2% were hospitalized, 19.3% were admitted to the ED, and 9.5% received care in a NH.

Conclusions: Linking MOW data to Medicare claims has the potential to shed additional light on the relationships among social services, health status, health care use, and benefits to clients' well-being.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Costs and Cost Analysis*
  • Fee-for-Service Plans
  • Female
  • Food Services / statistics & numerical data*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Information Storage and Retrieval
  • Insurance Claim Review
  • Male
  • Medicare / statistics & numerical data*
  • Patient Acceptance of Health Care / statistics & numerical data*
  • United States