ArticleEGEMS (Washington, DC)2015
A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial.
Article in EGEMS (Washington, DC), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of prognostic prediction models for acute kidney injury (AKI) in general hospital populations.BMJ open · 2017Pooled it
- New Performance Measurement Framework for Realizing Patient-Centered Clinical Decision Support: Qualitative Development Study.Journal of medical Internet research · 2025Article
- A scoping review, novel taxonomy and catalogue of implementation frameworks for clinical decision support systems.BMC medical informatics and decision making · 2024Article
- Alert acceptance: are all acceptance rates the same?Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Evaluating a Prototype Clinical Decision Support Tool for Chronic Pain Treatment in Primary Care.Applied clinical informatics · 2022Article
- Multi-Institutional Implementation of Clinical Decision Support forJournal of personalized medicine · 2021Article
- Integrating the Practical Robust Implementation and Sustainability Model With Best Practices in Clinical Decision Support Design: Implementation Science Approach.Journal of medical Internet research · 2020Article
- E-Health Tools to Improve Antibiotic Use and Resistances: A Systematic Review.Antibiotics (Basel, Switzerland) · 2020Review
- Model-Informed Precision Dosing of Vancomycin in Hospitalized Children: Implementation and Adoption at an Academic Children's Hospital.Frontiers in pharmacology · 2020Article
- Decision-Centered Design of Patient Information Visualizations to Support Chronic Pain Care.Applied clinical informatics · 2019Article
- Clinical Decision Support Systems and Their Role in Antibiotic Stewardship: a Systematic Review.Current infectious disease reports · 2019Article
- A Quality Improvement Initiative to Decrease Platelet Ordering Errors and a Proposed Model for Evaluating Clinical Decision Support Effectiveness.Applied clinical informatics · 2019Article
- An Electronic Clinical Decision Support System for the Assessment and Management of Suicidality in Primary Care: Protocol for a Mixed-Methods Study.JMIR research protocols · 2018Article
- Bridging the Gap Between Academic Research and Pragmatic Needs in Usability: A Hybrid Approach to Usability Evaluation of Health Care Information Systems.JMIR human factors · 2018Article
- Agile Acceptance Test-Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software.JMIR medical informatics · 2018Article
- Integrating data from an online diabetes prevention program into an electronic health record and clinical workflow, a design phase usability study.BMC medical informatics and decision making · 2016Article
- CDS, UX, and System Redesign - Promising Techniques and Tools to Bridge the Evidence Gap.EGEMS (Washington, DC) · 2015Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
introductionThe promise of Clinical Decision Support (CDS) has always been to transform patient care and improve patient outcomes through the delivery of timely and appropriate recommendations that are patient specific and, more often than not, are appropriately actionable. However, the users of CDS-providers-are frequently bombarded with inappropriate and inapplicable CDS that often are not informational, not integrated into the workflow, not patient specific, and that may present out of date and irrelevant recommendations.
methodsThe integrated clinical prediction rule (iCPR) project was a randomized clinical trial (RCT) conducted to determine if a novel form of CDS, i.e., clinical prediction rules (CPRs), could be efficiently integrated into workflow and result in changes in outcomes (e.g., antibiotic ordering) when embedded within a commercial electronic health record (EHR). We use the lessons learned from the iCPR project to illustrate a framework for constructing usable, useful, and effective actionable CDS while employing off-the-shelf functionality in a production system. Innovations that make up the framework combine the following: (1) active and actionable decision support, (2) multiple rounds of usability testing with iterative development for user acceptance, (3) numerous context sensitive triggers, (4) dedicated training and support for users of the CDS tool for user adoption, and (5) support from clinical and administrative leadership. We define "context sensitive triggers" as being workflow events (i.e., context) that result in a CDS intervention. DISCUSSION: Success of the framework can be measured by CDS adoption (i.e., intervention is being used), acceptance (compliance with recommendations), and clinical outcomes (where appropriate). This framework may have broader implications for the deployment of Health Information Technology (HIT). RESULTS AND
conclusioniCPR was well adopted(57.4% of users) and accepted (42.7% of users). Usability testing identified and fixed many issues before the iCPR RCT. The level of leadership support and clinical guidance for iCPR was key in establishing a culture of acceptance for both the tool and its recommendations contributing to adoption and acceptance. The dedicated training and support lead to the majority of the residents reporting a high level of comfort with both iCPR tools strep pharyngitis (64.4 percent) and pneumonia (62.7 percent) as well as a high likelihood of using the tools in the future. A surprising framework addition resulted from usability testing: context sensitive triggers.
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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.