ArticleApplied clinical informatics2020
Design and Usability of an Electronic Health Record-Integrated, Point-of-Care, Clinical Decision Support Tool for Modeling and Simulation of Antihemophilic Factors.
Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed, 11 citations in OpenAlex.
- Expanding access to veterinary clinical decision support in resource-limited settings: a scoping review of clinical decision support tools in medicine and antimicrobial stewardship.Frontiers in veterinary science · 2024Article
- Tracing the Progression of Sepsis in Critically Ill Children: Clinical Decision Support for Detection of Hematologic Dysfunction.Applied clinical informatics · 2022Article
- Human Factors and Organizational Issues in Health Informatics: Innovations and Opportunities.Yearbook of medical informatics · 2021Review
- Assessing Prescriber Behavior with a Clinical Decision Support Tool to Prevent Drug-Induced Long QT Syndrome.Applied clinical informatics · 2021Article
- The Effect of Electronic Health Record Usability Redesign on Annual Screening Rates in an Ambulatory Setting.Applied clinical informatics · 2020Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith the consequences of inadequate dosing ranging from increased bleeding risk to excessive drug costs and undesirable administration regimens, the antihemophilic factors are uniquely suited to dose individualization. However, existing options for individualization are limited and exist outside the flow of care. We developed clinical decision support (CDS) software that is integrated with our electronic health record (EHR) and designed to streamline the process for our hematology providers.
objectivesThe aim of this study is to develop and examine the usability of a CDS tool for antihemophilic factor dose individualization.
methodsOur development strategy was based on the features associated with successful CDS tools and driven by a formal requirements analysis. The back-end code was based on algorithms developed for manual individualization and unit tested with 23,000 simulated patient profiles created from the range of patient-derived pharmacokinetic parameter estimates defined in children and adults. A 296-item heuristic checklist was used to guide design of the front-end user interface. Content experts and end-users were recruited to participate in traditional usability testing under an institutional review board approved protocol.
resultsCDS software was developed to systematically walk the point-of-care clinician through dose individualization after seamlessly importing the requisite patient data from the EHR. Classical and population pharmacokinetic approaches were incorporated with clearly displayed estimates of reliability and uncertainty. Users can perform simulations for prophylaxis and acute bleeds by providing two of four therapeutic targets. Testers were highly satisfied with our CDS and quickly became proficient with the tool.
conclusionWith early and broad stakeholder engagement, we developed a CDS tool for hematology provider that affords seamless transition from patient assessment, to pharmacokinetic modeling and simulation, and subsequent dose selection.
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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.