Developing a real-time EHR-integrated SDoH clinical tool.

We describe an implementation of a pilot integration to embed SDoH-based data visualizations into the EHR in real time for clinical staff treating children with asthma.

Launching a virtual decision lab: development and field-testing of a web-based patient decision support research platform.

BACKGROUND: Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. METHODS: An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. RESULTS: This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p < 0.01). CONCLUSIONS: Combining decision science and health informatics approaches facilitated rapid development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment, acceptability, and usage. Within this platform, the web-based decision aid component performed comparably with the videobooklet decision aid used in clinical practice. Future studies may use this interactive research platform to study patients' decision making processes in real-time, explore interdisciplinary approaches to designing web-based decision aids, and test strategies for tailoring decision support to meet patients' needs and preferences.

Developing web-based online support tools: the Dartmouth decision support software.

TOPIC: This article discusses the development of Web-based online decision support tools intended for researchers examining the issue of shared decision making for the population of individuals with serious mental illnesses. PURPOSE: The authors describe the background and use of decision support tools to facilitate shared decision-making between individuals diagnosed with a psychiatric condition and clinicians and describes a novel software platform that allows researchers and other system designers to build decision support systems. CONCLUSIONS: In supporting ongoing research efforts, an online decision support tool appears to be useful for individuals facing preference-sensitive decisions and an online designer tool allows for rapid deployment of these research sites to support ongoing research efforts in shared decision making.