Designing Decision-Support Technologies for Patient-Generated Data in Type 1 Diabetes

Abstract

People living with type 1 diabetes generate data as a byproduct of diabetes management. The development of decision support technologies can be enabled by harnessing these patient-generated data, but a major challenge is for these technologies to provide meaningful and highly personalized guidance to support individual patients' decision-making processes. In this paper, results from a year-long qualitative study were reported. Twenty-six people with type 1 diabetes were interviewed regarding the types of self-generated data they use for decision-making, their decision-making processes using self-generated data, and the difficulties they experience when attempting to use this data for decision-making. These patients' behaviors and difficulties point to new approaches to designing decision support technologies for personal use, including patient-centered and automated data entry, automated and individualized data analysis, and humanized output.