ArticleJournal of the American Medical Informatics Association : JAMIA2019
Psychosocial information use for clinical decisions in diabetes care.
Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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The trial behind it
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Who cites it
22 citing papers in PubMed.
- Patient-Reported Outcome Measures in Adults with Type 2 Diabetes-With a Focus on Older Populations: An AI-Assisted Rapid Review of Use and Implementation in Clinical and Organizational Practice.Healthcare (Basel, Switzerland) · 2025Review
- Help us document what we already do: pilot study of clinical decision support tools targeting social risk-informed care.JAMIA open · 2025Article
- "The start of something that I hope could be greater": Health information technology tools for social care.SSM. Qualitative research in health · 2025Article
- Getting Inside Closed-Loop Referrals: Exploring the Patient Experience of Finding and Connecting to Social Care With a Community Resource Referral System Using a Community-Based Participatory Approach.Health services research · 2025Article
- Perspectives of nurses and patients on the misplacement of supportive care information for type 2 diabetes mellitus: a qualitative study in China.BMC nursing · 2025Article
- Stressful life events in electronic health records: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Realizing the potential of social determinants data in EHR systems: A scoping review of approaches for screening, linkage, extraction, analysis, and interventions.Journal of clinical and translational science · 2024Article
- Stressful life events in electronic health records: a scoping review.Research square · 2023Article
- Partner-developed electronic health record tools to facilitate social risk-informed care planning.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Association of Health-Related Social Needs With Quality and Utilization Outcomes in a Medicare Advantage Population With Diabetes.JAMA network open · 2023Article
- Understanding care coordination for Veterans with complex care needs: protocol of a multiple-methods study to build evidence for an effectiveness and implementation study.Frontiers in health services · 2023Article
- Provocations for Reimagining Informatics Approaches to Health Equity.Yearbook of medical informatics · 2022Article
- Psychosocial barriers and facilitators for adherence to a healthy lifestyle among patients with chronic kidney disease: a focus group study.BMC nephrology · 2022Article
- Health informatics interventions to minimize out-of-pocket medication costs for patients: what providers want.JAMIA open · 2022Article
- Health complexity assessment in primary care: A validity and feasibility study of the INTERMED tool.PloS one · 2022Article
- Using Electronic Health Record-Based Clinical Decision Support to Provide Social Risk-Informed Care in Community Health Centers: Protocol for the Design and Assessment of a Clinical Decision Support Tool.JMIR research protocols · 2021Article
- Detecting and Treating Psychosocial and Lifestyle-Related Difficulties in Chronic Disease: Development and Treatment Protocol of the E-GOAL eHealth Care Pathway.International journal of environmental research and public health · 2021Article
- Unmet information needs of clinical teams delivering care to complex patients and design strategies to address those needs.Journal of the American Medical Informatics Association : JAMIA · 2020Observational
- Health informatics and health equity: improving our reach and impact.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- "We Need to Know These Things": Use Cases for Combined Social and Clinical Data Among Primary Care-Based Clinical and Social Care Providers.Journal of primary care & community healthArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThere are increasing efforts to capture psychosocial information in outpatient care in order to enhance health equity. To advance clinical decision support systems (CDSS), this study investigated which psychosocial information clinicians value, who values it, and when and how clinicians use this information for clinical decision-making in outpatient type 2 diabetes care. MATERIALS AND
methodsThis mixed methods study involved physician interviews (n = 17) and a survey of physicians, nurse practitioners (NPs), and diabetes educators (n = 198). We used the grounded theory approach to analyze interview data and descriptive statistics and tests of difference by clinician type for survey data.
resultsParticipants viewed financial strain, mental health status, and life stressors as most important. NPs and diabetes educators perceived psychosocial information to be more important, and used it significantly more often for 1 decision, than did physicians. While some clinicians always used psychosocial information, others did so when patients were not doing well. Physicians used psychosocial information to judge patient capabilities, understanding, and needs; this informed assessment of the risks and the feasibility of options and patient needs. These assessments influenced 4 key clinical decisions. DISCUSSION: Triggers for psychosocially informed CDSS should include psychosocial screening results, new or newly diagnosed patients, and changes in patient status. CDSS should support cost-sensitive medication prescribing, and psychosocially based assessment of hypoglycemia risk. Electronic health records should capture rationales for care that do not conform to guidelines for panel management. NPs and diabetes educators are key stakeholders in psychosocially informed CDSS.
conclusionFindings highlight opportunities for psychosocially informed CDSS-a vital next step for improving health equity.
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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.