ArticleJournal of the American Medical Informatics Association : JAMIA2021
"A catalyst for action": Factors for implementing clinical risk prediction models of infection in home care settings.
Article in Journal of the American Medical Informatics Association : JAMIA, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Infection prevention and control knowledge, attitudes, and practices among patients and informal caregivers in home-based care: A systematic review.American journal of infection control · 2026Pooled it
- Making Community-Based Palliative Care Eligibility Determinations: Palliative Care Team Member Perspectives on Access to Information and Algorithm Use.The American journal of hospice & palliative care · 2025Article
- Clinician-identified health characteristics and palliative care eligibility: is dementia overlooked?The American journal of managed care · 2025Article
- Using Generative AI to Translate Administrative Claims Data into Narrative Summaries for Palliative Care Needs Assessment: A Case Study.Studies in health technology and informatics · 2024Article
- Implementation and clinical utility of a Computer-Aided Risk Score for Mortality (CARM): a qualitative study.BMJ open · 2023Article
- Adding Functional Ability Measures to a Mortality Algorithm to Support Palliative Care Eligibility Decisions.Research in gerontological nursingArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
objectiveThe study sought to outline how a clinical risk prediction model for identifying patients at risk of infection is perceived by home care nurses, and to inform how the output of the model could be integrated into a clinical workflow. MATERIALS AND
methodsThis was a qualitative study using semi-structured interviews with 50 home care nurses. Interviews explored nurses' perceptions of clinical risk prediction models, their experiences using them in practice, and what elements are important for the implementation of a clinical risk prediction model focusing on infection. Interviews were audio-taped and transcribed, with data evaluated using thematic analysis.
resultsTwo themes were derived from the data: (1) informing nursing practice, which outlined how a clinical risk prediction model could inform nurse clinical judgment and be used to modify their care plan interventions, and (2) operationalizing the score, which summarized how the clinical risk prediction model could be incorporated in home care settings. DISCUSSION: The findings indicate that home care nurses would find a clinical risk prediction model for infection useful, as long as it provided both context around the reasons why a patient was deemed to be at high risk and provided some guidance for action.
conclusionsIt is important to evaluate the potential feasibility and acceptability of a clinical risk prediction model, to inform the intervention design and implementation strategy. The results of this study can provide guidance for the development of the clinical risk prediction tool as an intervention for integration in home care settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.