Data Analytics to Support Policy Making for Noncommunicable Diseases: Scoping Review.

Abstract

Background: There is an emerging need for evidence-based approaches harnessing large amounts of health care data and novel technologies (such as artificial intelligence) to optimize public health policy making.

Objective: The aim of this review was to explore the data analytics tools designed specifically for policy making in noncommunicable diseases (NCDs) and their implementation.

Methods: A scoping review was conducted after searching the PubMed and IEEE databases for articles published in the last 10 years.

Results: Nine articles that presented 7 data analytics tools designed to inform policy making for NCDs were reviewed. The tools incorporated descriptive and predictive analytics. Some tools were designed to include recommendations for decision support, but no pilot studies applying prescriptive analytics have been published. The tools were piloted with various conditions, with cancer being the least studied condition. Implementation of the tools included use cases, pilots, or evaluation workshops that involved policy makers. However, our findings demonstrate very limited real-world use of analytics by policy makers, which is in line with previous studies.

Conclusions: Despite the availability of tools designed for different purposes and conditions, data analytics is not widely used to support policy making for NCDs. However, the review demonstrates the value and potential use of data analytics to support policy making. Based on the findings, we make suggestions for researchers developing digital tools to support public health policy making. The findings will also serve as input for the European Union-funded research project ONCODIR developing a policy analytics dashboard for the prevention of colorectal cancer as part of an integrated platform.