Highlights

SSRS conducts the Minnesota Health Access Survey (MNHA) biennially to document the health insurance coverage and access to health care of Minnesotans. This study is carried out by SSRS on behalf of the State Health Access Data Assistance Center (SHADAC) at the University of Minnesota and the Minnesota Department of Health.

Since 2009 the survey has collected data every other year about Minnesotans’ health insurance, care, and related issues. During 2023, the MNHA collected data from over 15,000 Minnesota residents via the web and phone through an address-based sample (ABS) and MN proprietary panel-based design. The sample was drawn from the adult non-institutionalized population of the state. Stratified sampling of geographic and demographic populations along with sophisticated modeling techniques ensured a representative sample of the MN population.

Challenge

Representing the state’s residents with a large, diverse sample and high-quality data to capture an accurate picture of the health and healthcare needs of the population of Minnesota.

Approach

An adaptive ABS methodology has been employed since 2021. In 2023, the ABS was supplemented with a panel-based sample pulled from the newly established Minnesota Voices on Health Panel. The model-based stratification enabled more precise targeting of desired demographic groups, while the panel sample supplemented the survey with respondents of known demographics, freeing up resources and allowing the ABS design to reach more people from traditionally less-represented groups.

The survey was available in multiple modes including web and telephone, which improves the accessibility of the survey and provides an option for respondents who may not be comfortable with going online.

Results

  • The study routinely provides high-quality data to state officials to make informed decisions about health-related policies.
  • Statistical modeling achieved the desired outcomes of increasing incidence of key groups.
  • Experimentation with outreach protocols are embedded with each cycle to fine-tune the survey’s methods and improve the reliability and representativeness of the data.