Combining i Google and Personal Health Records to Create a Prototype Personal Health Application for Diabetes Self-Management

This article describes the design process for a personal health application (PHA), including architecture, workflow, and functionality. Focus groups with people who have diabetes (n = 21) were conducted to ascertain their needs for a PHA. An Internet-based prototype was developed. Feedback was provided on the design, which led to changes in the PHA's presentation and function. The prototype PHA retrieves data for diabetes self-management from a personal health record, displays those data using gadgets in the consumer's iGoogle page, and makes the data available to a decision-support component that provides lifestyle-oriented advice. This PHA can provide the backbone for a decision support system that can bring together the cornerstones of diabetes self-management and integrate them into the life of the person with diabetes. Objective: The aim of this project is to create a prototype for a personal health application (PHA) for patients (i.e., consumers) with diabetes by employing a user-centered design process. This article describes the design process for and resulting architecture, workflow, and functionality of such a PHA. Materials and Methods: For the design process, we conducted focus groups with people who have diabetes (n = 21) to ascertain their needs for a PHA. We then developed a prototype in response to these needs, and through additional focus groups and step-by-step demonstrations for people with diabetes as well as healthcare providers, we obtained feedback about the prototype. The feedback led to changes in the PHA's presentation and function. Results: Focus group participants said they wanted a tool that could give them timely, readily available information on how diabetes-related domains interact, how their behaviors affect them, and what to do next. Thus, the prototype PHA is Internet-based, retrieves data for diabetes self-management from a personal health record, displays those data using gadgets in the consumer's iGoogle page, and makes the data available to a decision-support component that provides lifestyle-oriented advice. Manipulation of the data enables consumers to anticipate the results of future actions and to see interrelationships. Conclusions: A user-centered design process resulted in a PHA that uses technology that is publicly available, employs a personal health record, and is Internet based. This PHA can provide the backbone for a decision support system that can bring together the cornerstones of diabetes self-management and integrate them into the life of the person with diabetes.