ArticleJournal of medical Internet research2026
Data Maturity Assessment in Long-Term Care: Mixed Methods Study.
Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
6 authors.
Funding
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Abstract
Background: The use of data to support decision-making and primary processes is central to establishing data-informed care. Yet, data remain underutilized for quality improvement in long-term care (LTC). Data maturity reflects an organization's capability to use data, for example, to guide strategic objectives. Objective: This study aimed to assess the data maturity of LTC organizations and evaluate the opinions and ideas of different stakeholders (eg, client representatives, care professionals, and data and IT specialists) within these organizations regarding their data maturity. Methods: An exploratory mixed methods study was conducted in 3 Dutch LTC organizations. Quantitative data were collected using a 7-domain data maturity assessment comprising 77 items with 3 response options (applicable, not applicable, or in progress), which was completed through consensus-based scoring. Each organization established an interprofessional community of practice (CoP), consisting of 5 to 6 purposively recruited stakeholders representing care professionals, managers, client representatives, IT and data specialists, and researchers. Qualitative data were collected through consensus meetings with the same CoP stakeholders to elaborate on and contextualize their data maturity assessments. Quantitative data were analyzed descriptively, while qualitative data were analyzed using hybrid thematic analysis. Results: Findings highlighted that LTC organizations currently operate at a low data maturity level. Domains regarding strategy, governance, and data quality were low yet consistent across organizations, whereas variability and substantial gaps were mainly present in the domain regarding leadership and culture. The consensus meetings with 15 stakeholders in the CoPs (mean age 43, SD 11 y; mean organizational work experience 10, SD 9 y) identified 4 overarching themes: (1) the absence of a clear vision for data-informed care reflects low data maturity, (2) a data culture is a prerequisite for continuous learning and improvement, (3) innovation and transformation are constrained by limited interdisciplinary engagement and ineffective communication, and (4) sustainable data use is hindered by infrastructural capacity and cultural readiness. Conclusions: This study contributes to the limited evidence on data maturity in LTC, revealing generally low levels of data maturity across organizations. Advancing data-informed care requires integrated strategies that align technical, cultural, and interprofessional conditions. Future research should adopt longitudinal designs and broader stakeholder involvement to strengthen data-informed care in LTC.
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