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Background The integration of patient-reported outcomes (PROs) into routine clinical practice remains limited despite their well-documented benefits in facilitating clinical communication and research. Systematic digital PRO collection can enable real-time symptom monitoring, timely clinical interventions, and greater patient empowerment. The Health Outcomes Observatory (H2O) initiative was developed to enable systematic digital patient-reported outcome measures (PROMs) collection and integration with clinical data to support value-based, patient-centered care across health care systems. Objective This study aimed to evaluate the feasibility, usability, acceptability, clinical utility, and implementation of the H2O digital infrastructure from patient and health care professional perspectives across multiple health care settings and medical conditions. Methods A noninterventional, multicenter, convergent mixed methods feasibility study was conducted in Spain, Austria, the Netherlands, and Germany across multiple medical conditions. Locally implemented smartphone, tablet, and web-based solutions captured and displayed PROs. Surveys and interviews assessed usability, acceptability, perceived clinical utility, and implementation conditions among patients and health care professionals. Results Of 241 participants assessed initially, 115 (47.7%) contributed follow-up data. Although 83% (44/53) of the respondents indicated willingness to recommend H2O, the mean System Usability Scale (SUS) score was 44.65/100 (SD 9.78), indicating poor usability. Among 50 participants with paired Patient Satisfaction Questionnaire Short Form assessments, satisfaction with technical quality declined (t49=2.20; P=.03). Interviews identified perceived value alongside login difficulties, technical instability, weak integration with clinical systems, and inconsistent use of PRO data during consultations. Conclusions The H2O infrastructure could be deployed across heterogeneous settings, and participants perceived value in digital PRO collection; however, poor usability, substantial attrition, technical friction, and limited workflow integration qualify conclusions about feasibility and acceptability. More reliable technology, stronger interoperability, and evaluation in larger and more complete samples are needed before broader implementation.
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Long et al. (2026) studied this question.
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