ArticleApplied clinical informatics2023
Human-Centered Design of a Clinical Decision Support for Anemia Screening in Children with Inflammatory Bowel Disease.
Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 13 citations in OpenAlex.
- Effect of Artificial Intelligence Helpfulness and Uncertainty on Cognitive Interactions with Pharmacists: Randomized Controlled Trial.Journal of medical Internet research · 2025Trial
- End User Needs and Perspectives for a Digital Opioid Safety Tool in Adolescents and Young Adults With Inflammatory Bowel Disease: A Qualitative Human-Centered Design Study.JMIR formative research · 2026Article
- User-Centered Design in Real-Time: Utilization of an Insider Position to Inform Design and Adoption.Applied clinical informatics · 2025Article
- Iterative Development of a Clinical Decision Support Tool to Enhance Naloxone Coprescribing.Applied clinical informatics · 2025Article
- Realizing the Full Potential of Clinical Decision Support: Translating Usability Testing into Routine Practice in Health Care Operations.Applied clinical informatics · 2024Article
- Randomized Comparison of Electronic Health Record Alert Types in Eliciting Responses about Prognosis in Gynecologic Oncology Patients.Applied clinical informatics · 2024Article
- A Provider-Facing Decision Support Tool for Prostate Cancer Screening in Primary Care: A Pilot Study.Applied clinical informatics · 2024Article
- Addressing Alert Fatigue by Replacing a Burdensome Interruptive Alert with Passive Clinical Decision Support.Applied clinical informatics · 2024Article
- Behavioral Health Decision Support Systems and User Interface Design in the Emergency Department.Applied clinical informatics · 2023Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInflammatory bowel disease (IBD) commonly leads to iron deficiency anemia (IDA). Rates of screening and treatment of IDA are often low. A clinical decision support system (CDSS) embedded in an electronic health record could improve adherence to evidence-based care. Rates of CDSS adoption are often low due to poor usability and fit with work processes. One solution is to use human-centered design (HCD), which designs CDSS based on identified user needs and context of use and evaluates prototypes for usefulness and usability.
objectivesthis study aimed to use HCD to design a CDSS tool called the IBD Anemia Diagnosis Tool, IADx.
methodsInterviews with IBD practitioners informed creation of a process map of anemia care that was used by an interdisciplinary team that used HCD principles to create a prototype CDSS. The prototype was iteratively tested with "Think Aloud" usability evaluation with clinicians as well as semi-structured interviews, a survey, and observations. Feedback was coded and informed redesign.
resultsProcess mapping showed that IADx should function at in-person encounters and asynchronous laboratory review. Clinicians desired full automation of clinical information acquisition such as laboratory trends and analysis such as calculation of iron deficit, less automation of clinical decision selection such as laboratory ordering, and no automation of action implementation such as signing medication orders. Providers preferred an interruptive alert over a noninterruptive reminder.
conclusionProviders preferred an interruptive alert, perhaps due to the low likelihood of noticing a noninterruptive advisory. High levels of desire for automation of information acquisition and analysis with less automation of decision selection and action may be generalizable to other CDSSs designed for chronic disease management. This underlines the ways in which CDSSs have the potential to augment rather than replace provider cognitive work.
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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.