ArticleApplied clinical informatics2023
Pseudorandomized Testing of a Discharge Medication Alert to Reduce Free-Text Prescribing.
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 2 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
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.
- The Effect of Computerized Alerts on Prescribing and Patient Outcomes: A Systematic Review.Applied clinical informatics · 2025Pooled it
- Iterative Development of a Clinical Decision Support Tool to Enhance Naloxone Coprescribing.Applied clinical informatics · 2025Article
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 at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPseudorandomized testing can be applied to perform rigorous yet practical evaluations of clinical decision support tools. We apply this methodology to an interruptive alert aimed at reducing free-text prescriptions. Using free-text instead of structured computerized provider order entry elements can cause medication errors and inequity in care by bypassing medication-based clinical decision support tools and hindering automated translation of prescription instructions.
objectiveThe objective of this study is to evaluate the effectiveness of an interruptive alert at reducing free-text prescriptions via pseudorandomized testing using native electronic health records (EHR) functionality.
methodsTwo versions of an EHR alert triggered when a provider attempted to sign a discharge free-text prescription. The visible version displayed an interruptive alert to the user, and a silent version triggered in the background, serving as a control. Providers were assigned to the visible and silent arms based on even/odd EHR provider IDs. The proportion of encounters with a free-text prescription was calculated across the groups. Alert trigger rates were compared in process control charts. Free-text prescriptions were analyzed to identify prescribing patterns.
resultsOver the 28-week study period, 143 providers triggered 695 alerts (345 visible and 350 silent). The proportions of encounters with free-text prescriptions were 83% (266/320) and 90% (273/303) in the intervention and control groups, respectively (
conclusionAn interruptive alert was associated with a modest reduction in free-text prescriptions. Furthermore, the majority of these prescriptions could have been reproduced using structured order entry fields. Targeting user preference lists shows promise for future intervention.
Indexed as
Identifiers
What OpenQuestion holds
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.