Developing a Creative Framework for Addressing Data and Information Problems in Healthcare: Insights from Multi-Method User Studies (Preprint)

BACKGROUND Data and information problems (incompleteness, inaccuracy, misinterpretation, limited accessibility) continue to impair clinical decision-making, organizational processes, and interdisciplinary collaboration in healthcare. While existing standards, data governance approaches, and human-centered design methods offer valuable guidance, they provide limited support for interdisciplinary teams to systematically identify and discuss such problems in practice. OBJECTIVE This research describes the formative development and evaluation of a human-centered framework and supporting question catalogue designed to support interdisciplinary teams in identifying and addressing data and information problems in healthcare. This framework was developed by adapting principles from ISO 9241-210 for the context of healthcare data and information work. METHODS A sequential mixed-methods design was applied across three studies. Study 1 (N = 88) explored how interdisciplinary participants understand and experience data and information problems. Study 2 (N = 14) assessed experts’ familiarity with key concepts and their perceptions of framework use for data and information problems. Study 3 comprised two online focus-group rounds (N = 15), using consensus measurement, qualitative discussion, and SWOT analysis to evaluate clarity, perceived usefulness, and interdisciplinary applicability of the framework and question catalogue. RESULTS Across studies, data problems were primarily associated with quality and integrity, while information problems centered on accessibility, structuring, comprehension, and communication. Participants encountered such problems frequently but rarely used systematic frameworks to address them. In Study 3, experts perceived the tailored framework and question catalogue as relevant, interdisciplinary, and useful for structured discussion. Iterative refinement improved clarity and consensus. Participants emphasized the need for layered access, prioritization mechanisms, and navigation support. CONCLUSIONS The findings suggest that the framework and its supporting question catalogue constitute a feasible and promising early-stage tool for interdisciplinary reflection on data and information problems in healthcare. Further refinement and pilot testing in real-world settings are needed.