Analysing health data sources to inform chronic disease management decisions of health insurers: A mixed methods study
Background and Objective: Both health care providers and payers recognize the need to improve chronic disease care. Chronic disease management relies on high-quality health information for people with, and at risk of developing, chronic diseases. This article focuses on the health insurance sector and investigates ways that payment claims data and other data sources can provide useful information to support chronic disease management interventions.
Methods and Results: In this mixed methods study, we first examine methods of selecting target populations from insurance claims data for common chronic conditions-diabetes, cardiovascular disease, and mental health disorders. The analysis of claims data reveals data quality issues and indicates that other data sources should be considered to provide additional information. We undertake a qualitative review of factors influencing the development of information systems for chronic disease management that use multiple data sources.
Conclusions: Claims data should be supplemented with other data to inform chronic disease management. The article proposes a conceptual framework with four domains that need to be considered when developing chronic disease information systems using multiple data sources-information requirements, data sources, data collection, and information systems integration. There are policy and organizational factors that influence framework implementation.