Description
Procurement Overview and Goals.
The Health Economics Program at the Minnesota Department of Health (MDH) requests proposals to conduct an analytic study on low-value health care services in Minnesota (“low-value care”). Low-value care has been defined as “services that provide little or no benefit to patients, have potential to cause harm, incur unnecessary cost to patients, or waste limited healthcare resources” (see Maratt et al., 2019 https://pubmed.ncbi.nlm.nih.gov/31250366/).
In the 2023 session, the Minnesota Legislature directed the Minnesota Department of Health (MDH) to develop recommendations for strategies to reduce the magnitude of low-value care delivered to Minnesota residents (2023 Minnesota Statutes, 62J.0416, available at: https://www.revisor.mn.gov/statutes/cite/62J.0416). To inform these recommendations, MDH is directed to:
1. Review the availability of data and identify gaps in the data infrastructure to estimate
low-value care.
2. Based on available data, estimate the volume and change over time of low-value
care in Minnesota.
3. Conduct an environmental scan and key informant interviews with experts in health
care finance, health economics, health care management or administration, and the
administration of health insurance benefits to determine drivers of the provision of
low-value care.
Within MDH, the Health Economics Program (HEP) is directing these activities.
This solicitation is for a research or data analytics vendor team to conduct these three activities and produce a written report summarizing the methodological approach, key findings, and policy implications. The report will be used to inform the development of strategies and recommendations to reduce the magnitude of low-value services in Minnesota as well as broader agency efforts to better understand and address rising health care costs.
While MDH requires the use of Minnesota-specific data from the Minnesota All Payer Claims Database (MN APCD) for this project, proposals that include additional relevant data sources available to the consulting team are welcomed. As applicable, responses must include clear indications of how other data sources, including data not specific to Minnesota, could be effective tools to support the study and meaningfully inform policy development in Minnesota related to low-value care. The vendor will be required to complete analyses using the MN APCD and must agree to complete MDH requirements for access to and protection of data in the MN APCD. This includes state access and data security training.
Information about the MN APCD may be found on the MDH MN APCD website: https://www.health.state.mn.us/data/apcd/. Briefly, the MN APCD is a state repository of de-identified health care claims data that is derived from billing records sent by medical providers to insurance companies, plan administrators, and public payers. The MN APCD includes enrollment information and claims for Minnesotans covered by private insurance plans, Medicare, and Minnesota Health Care Programs (including the state’s Medicaid program and Basic Health Plan). Approved MN APCD users for this project will have access to an Amazon Redshift database and SQL client (SQL Workbench) and will be provided access to a project-specific schema in the database. The MN APCD users will connect to this secure research environment via their computer platform. The Amazon Redshift database and SQL client will be the primary tools available to users for querying the MN APCD and conducting upstream data management required to create analytic datasets. In addition, MDH will provide a set of software for statistical analysis (SAS, Stata, R). Claims grouping is performed by MDH as part of each extract (3M Core Grouping Software, John’s Hopkins ACG System). Common office and productivity software will also be available in the research environment (Word, Excel, PowerPoint). If a vendor intends to use additional tools or data sources on the MN APCD secure research environment, they must describe them in their proposal.
Responses must also include a description of the approach to conducting the environmental scan and key informant interviews.