ArticleFrontiers in pharmacology2016
Design and Testing of an EHR-Integrated, Busulfan Pharmacokinetic Decision Support Tool for the Point-of-Care Clinician.
Article in Frontiers in pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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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
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of applied usability metrics within usability evaluation methods for hospital electronic healthcare record systems: Metrics and Evaluation Methods for eHealth Systems.Journal of evaluation in clinical practice · 2021Pooled it
- Population Pharmacokinetics and Optimal Sampling Strategy for Model-Based Precision Dosing of Melphalan in Patients Undergoing Hematopoietic Stem Cell Transplantation.Clinical pharmacokinetics · 2018Trial
- The Coming of Age of Model-Informed Precision Therapeutics for Children.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2025Article
- Development of a Human Factors-Based Guideline to Support the Design, Evaluation, and Continuous Improvement of Clinical Decision Support.Mayo Clinic proceedings. Digital health · 2025Article
- What Are the Current Approaches to Optimising Antimicrobial Dosing in the Intensive Care Unit?Pharmaceutics · 2020Review
- Design and Usability of an Electronic Health Record-Integrated, Point-of-Care, Clinical Decision Support Tool for Modeling and Simulation of Antihemophilic Factors.Applied clinical informatics · 2020Article
- What Does it Take to Make Model-Informed Precision Dosing Common Practice? Report from the 1st Asian Symposium on Precision Dosing.The AAPS journal · 2019Article
- Precision dosing to avoid adverse drug reactions.Therapeutic advances in drug safety · 2019Article
- Precision medicine technology hype or reality? The example of computer-guided dosing.F1000Research · 2019Article
- Precision Dosing: Public Health Need, Proposed Framework, and Anticipated Impact.Clinical and translational science · 2017Review
- Genomics and Precision Medicine to Direct Statin Use in the Young.Progress in pediatric cardiology · 2009Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBusulfan demonstrates a narrow therapeutic index for which clinicians routinely employ therapeutic drug monitoring (TDM). However, operationalizing TDM can be fraught with inefficiency. We developed and tested software encoding a clinical decision support tool (DST) that is embedded into our electronic health record (EHR) and designed to streamline the TDM process for our oncology partners.
methodsOur development strategy was modeled based on the features associated with successful DSTs. An initial Requirements Analysis was performed to characterize tasks, information flow, user needs, and system requirements to enable push/pull from the EHR. Back-end development was coded based on the algorithm used when manually performing busulfan TDM. The code was independently validated in MATLAB using 10,000 simulated patient profiles. A 296-item heuristic checklist was used to guide design of the front-end user interface. Content experts and end-users (n = 28) were recruited to participate in traditional usability testing under an IRB approved protocol.
resultsDecision support software was developed to systematically walk the point-of-care clinician through the TDM process. The system is accessed through the EHR which transparently imports all of the requisite patient data. Data are visually inspected and then curve fit using a model-dependent approach. Quantitative goodness-of-fit are converted to single tachometer where "green" alerts the user that the model is strong, "yellow" signals caution and "red" indicates that there may be a problem with the fitting. Override features are embedded to permit application of a model-independent approach where appropriate. Simulations are performed to target a desired exposure or dose as entered by the clinician and the DST pushes the user approved recommendation back into the EHR. Usability testers were highly satisfied with our DST and quickly became proficient with the software.
conclusionsWith early and broad stake-holder engagement we developed a clinical DST for the non-pharmacologist. This tools affords our clinicians the ability to seamlessly transition from patient assessment, to pharmacokinetic modeling and simulation, and subsequent prescription order entry.
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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.