Patient-centered care, collaboration, communication, and coordination: a report from AMIA's 2013 Policy Meeting.

In alignment with a major shift toward patient-centered care as the model for improving care in our health system, informatics is transforming patient-provider relationships and overall care delivery. AMIA's 2013 Health Policy Invitational was focused on examining existing challenges surrounding full engagement of the patient and crafting a research agenda and policy framework encouraging the use of informatics solutions to achieve this goal. The group tackled this challenge from educational, technical, and research perspectives. Recommendations include the need for consumer education regarding rights to data access, the need for consumers to access their health information in real time, and further research on effective methods to engage patients. This paper summarizes the meeting as well as the research agenda and policy recommendations prioritized among the invited experts and stakeholders.

Using design science and artificial intelligence to improve health communication: ChronologyMD case example.

OBJECTIVE: This paper describes how design science theory and methods and use of artificial intelligence (AI) components can improve the effectiveness of health communication. METHODS: We identified key weaknesses of traditional health communication and features of more successful eHealth/AI communication. We examined characteristics of the design science paradigm and the value of its user-centered methods to develop eHealth/AI communication. We analyzed a case example of the participatory design of AI components in the ChronologyMD project intended to improve management of Crohn's disease. RESULTS: eHealth/AI communication created with user-centered design shows improved relevance to users' needs for personalized, timely and interactive communication and is associated with better health outcomes than traditional approaches. Participatory design was essential to develop ChronologyMD system architecture and software applications that benefitted patients. CONCLUSION: AI components can greatly improve eHealth/AI communication, if designed with the intended audiences. Design science theory and its iterative, participatory methods linked with traditional health communication theory and methods can create effective AI health communication. PRACTICE IMPLICATIONS: eHealth/AI communication researchers, developers and practitioners can benefit from a holistic approach that draws from theory and methods in both design sciences and also human and social sciences to create successful AI health communication.