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Record W4385080713 · doi:10.2196/47574

User-Centered Design and Evaluation of Clinical Decision Support to Improve Early Peanut Introduction: Formative Study

2023· article· en· W4385080713 on OpenAlexvenueno aff
Thinh H. Nguyen, Priscila Pereira Cunha, Annabelle Rowland, Evan Orenstein, Tricia Lee, Swaminathan Kandaswamy

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsnot available
FundersMorehouse School of MedicineEmory University
KeywordsSummative assessmentUsabilityFormative assessmentGuidelineMedicineClinical decision support systemMedical educationPeanut allergyTest (biology)Health careFamily medicinePediatricsPsychologyDecision support systemComputer scienceHuman–computer interactionAllergyArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Peanut allergy has recently become more prevalent. Peanut introduction recommendations have evolved from suggesting peanut avoidance until the age of 3 years to more recent guidelines encouraging early peanut introduction after the Learning Early about Peanut Allergy (LEAP) study in 2015. Guideline adherence is poor, leading to missed care opportunities. OBJECTIVE: In this study, we aimed to develop a user-centered clinical decision support (CDS) tool to improve implementation of the most recent early peanut introduction guidelines in the primary care clinic setting. METHODS: We edited the note template of the well-child check (WCC) visits at ages 4 and 6 months with CDS prompts and point-of-care education. Formative and summative usability testing were completed with pediatric residents in a simulated electronic health record (EHR). We estimated task completion rates and perceived usefulness of the CDS in summative testing, comparing a test EHR with and without the CDS. RESULTS: Formative usability testing with the residents provided qualitative data that led to improvements in the build for both the 4-month and 6-month WCC note templates. During summative usability testing, the CDS tool significantly improved discussion of early peanut introduction at the 4-month WCC visit compared to scenarios without the CDS tool (9/15, 60% with CDS and 0/15, 0% without CDS). All providers except one at the 4-month WCC scenario gave at least an adequate score for the ease of use of the CDS tool for the history of present illness and assessment and plan sections. During the summative usability testing with the 6-month WCC new build note template, providers more commonly provided comprehensive care once obtaining a patient history concerning for an immunoglobulin E-mediated peanut reaction by placing a referral to allergy/immunology (P=.48), prescribing an epinephrine auto-injector (P=.07), instructing on how to avoid peanut products (P<.001), and providing an emergency treatment plan (P=.003) with CDS guidance. All providers gave at least an adequate score for ease of use of the CDS tool in the after-visit summary. CONCLUSIONS: User-centered CDS improved application of early peanut introduction recommendations and comprehensive care for patients who have symptoms concerning for peanut allergy in a simulation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.106
metaresearch head score (Gemma)0.204
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.560

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1060.204
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.218
GPT teacher head0.533
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

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