Organizational Climate and Decision Aid Sustainability in Lupus Care: Mixed Methods Study.

Background: Digital decision aids (DAs) are increasingly used in health care to support shared decision-making and promote patient engagement. In the context of systemic lupus erythematosus (SLE), a complex autoimmune disease characterized by diverse symptoms and uncertain prognoses, DAs offer guidance to patients in navigating treatment risks and benefits. Although numerous studies have examined the initial implementation of evidence-based tools, there is limited evidence on the organizational factors that influence their long-term sustainability in clinical practice. This gap is particularly salient for digital interventions, where integration into routine workflows and ongoing use require alignment with clinic readiness and culture. This study focuses on an evidence-based, electronic DA designed to support patients with lupus and investigates how dimensions of organizational climate, particularly learning climate and change readiness, are associated with the tool's sustained use across diverse practice settings. Objective: This study aims to examine the relationship among the learning climate, change readiness climate, and perceived permanence of a DA for patients with lupus in 15 geographically diverse rheumatology clinics in the United States. Methods: This study was conducted as part of a broader multisite implementation project. We used a concurrent mixed methods design, integrating longitudinal quantitative survey data with qualitative interviews. Quantitative data were collected via web-based surveys at 3 time points (6-, 12-, and 24-mo postimplementation) from physicians, nurses, medical assistants, and administrative personnel (n=204 responses across rounds). The primary outcome was perceived DA permanence, measured with a validated 5-item scale. Independent variables included internal and external learning climates, change commitment, and change efficacy. Data were aggregated to the clinic level and analyzed using generalized estimating equations with clustered SEs. Qualitative data were collected through 36 semistructured interviews with clinic staff to explore contextual factors affecting sustainment. Results: Quantitative findings revealed that change efficacy climate was significantly associated with greater perceived permanence of the DA (β=4.00; P<.001) while internal (β=-1.39; P<.05) and external learning climates (β=-2.11; P<.01) were negatively associated. Change in commitment was not statistically significant. Qualitative data highlighted challenges to sustainment, including poor workflow integration, lack of physician buy-in, and limited applicability of the DA to certain patient populations. Conclusions: Sustaining digital health tools like DAs requires not only technical integration but also a supportive organizational climate. This study demonstrates that perceptions of a clinic's collective ability to sustain change (change efficacy) are critical while learning climates may expose barriers that hinder long-term use. These findings underscore the importance of assessing organizational readiness and tailoring implementation strategies to foster DA sustainment in real-world settings.