Observational studyJournal of the American Medical Informatics Association : JAMIA2020
Unmet information needs of clinical teams delivering care to complex patients and design strategies to address those needs.
Observational study in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 19 citations in OpenAlex.
- Development of a digital tool to support overview in complex patient cases: Which information elements support the clinical workflow?BMC health services research · 2026Article
- Understanding the Reasons Why Patients With Food Insecurity Decline Social Assistance at a Large Academic Medical Center.AJPM focus · 2025Article
- Factors impacting clinical data and documentation quality in Australian aged care and disability services: a user-centred perspective.BMC geriatrics · 2024Article
- Shifting Information Needs in Clinical Practice: The Evolving Role of Generative AI in Addressing Clinician Demands for Context-Specific Knowledge.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Health Related Social Needs Screening and Referral Fulfillment: Toward a Complex Model.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- The NeoRoo mobile app: Initial design and prototyping of an Android-based digital health tool to support Kangaroo Mother Care in low/middle-income countries (LMICs).PLOS digital health · 2023Article
- Involving Health Care Professionals in the Development of Electronic Health Records: Scoping Review.JMIR human factors · 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
- Documentation and review of social determinants of health data in the EHR: measures and associated insights.Journal of the American Medical Informatics Association : JAMIA · 2021Review
- A roadmap for cardiovascular care after release from incarceration: uses of a smartphone application.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Human Factors and Organizational Issues in Health Informatics: Innovations and Opportunities.Yearbook of medical informatics · 2021Review
- Agile Innovation to transform healthcare: innovating in complex adaptive systems is an everyday process, not a light bulb event.BMJ innovations · 2021Article
- Celebrating the International Year of the Nurse and Midwife: A look at nursing in JAMIA.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Uncovering the Value of a Historical Paper-Based Collaborative Artifact: The Nursing Unit's Kardex System.Frontiers in digital health · 2020Article
- Optimizing the Collection, Integration, and Use of Health-Related Social Needs Data in the Primary Care Setting: Recommendations Derived From Key Interest-Holders.Journal of primary care & community healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
objectivesTo identify the unmet information needs of clinical teams delivering care to patients with complex medical, social, and economic needs; and to propose principles for redesigning electronic health records (EHR) to address these needs. MATERIALS AND
methodsIn this observational study, we interviewed and observed care teams in 9 community health centers in Oregon and Washington to understand their use of the EHR when caring for patients with complex medical and socioeconomic needs. Data were analyzed using a comparative approach to identify EHR users' information needs, which were then used to produce EHR design principles.
resultsAnalyses of > 300 hours of observations and 51 interviews identified 4 major categories of information needs related to: consistency of social determinants of health (SDH) documentation; SDH information prioritization and changes to this prioritization; initiation and follow-up of community resource referrals; and timely communication of SDH information. Within these categories were 10 unmet information needs to be addressed by EHR designers. We propose the following EHR design principles to address these needs: enhance the flexibility of EHR documentation workflows; expand the ability to exchange information within teams and between systems; balance innovation and standardization of health information technology systems; organize and simplify information displays; and prioritize and reduce information.
conclusionDeveloping EHR tools that are simple, accessible, easy to use, and able to be updated by a range of professionals is critical. The identified information needs and design principles should inform developers and implementers working in community health centers and other settings where complex patients receive care.
Indexed as
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What OpenQuestion holds
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.