ArticleJAMIA open2019
Improving the design of California's prescription drug monitoring program.
Article in JAMIA open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed, 13 citations in OpenAlex.
- How the presentation of patient information and decision-support advisories influences opioid prescribing behavior: A simulation study.Journal of the American Medical Informatics Association : JAMIA · 2020Trial
- A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements.Current opinion in anaesthesiology · 2025Review
- Opioid-related policy changes: Experiences and perspectives from people who use opioids to manage non-cancer chronic pain.Drug and alcohol review · 2023Article
- Barriers and facilitators related to healthcare practitioner use of real time prescription monitoring tools in Australia.Frontiers in public health · 2023Article
- Optimization of Prescription Drug Monitoring Program to Overcome Opioid Epidemic in West Virginia.Cureus · 2022Review
- Phenotyping as disciplinary practice: data infrastructure and the interprofessional conflict over drug use in California.Big data & society · 2021Article
- An interview study with medical scribes on how their work may alleviate clinician burnout through delegated health IT tasks.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- The Impact of a PDMP-EHR Data Integration Combined With Clinical Decision Support on Opioid and Benzodiazepine Prescribing Across Clinicians in a Metropolitan Area.Journal of addiction medicineArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe US CDC identified prescription drug monitoring programs (PDMPs) as a tool to address the contemporary opioid crisis, but few studies have investigated PDMP usability and effectiveness from the users' perspective. Even fewer have considered how practices differ across medical domains. In this study, we aimed to address these gaps, soliciting perspectives on PDMPs from providers contending with the opioid crisis: physicians working in emergency departments (EDs) and pain management clinics. We aimed to provide practical design recommendations to improve PDMP workflow integration, as well as controlled substance history retrieval, interpretation, and decision support.
methodsWe conducted 16 in-depth semi-structured interviews with practicing emergency and pain physicians regarding their procedures, problems, and proposed solutions surrounding their use of CURES, California's PDMP. We investigated design problems in CURES by combining users' feedback with our usability inspection, drawing upon an extensive body of design literature. Then, we generated alternatives using design methods.
resultsWe found CURES's design did not accommodate the unique information needs of different medical domains. Further, clinicians had trouble accessing CURES and retrieving patients' controlled substance histories, mainly due to usability problems that could be addressed with little technical adjustment. Additionally, CURES rendered patient histories in large, cluttered tables, devoid of overview or context, making interpretation difficult and precarious. Lastly, our interviewees had rarely noticed or used advanced features, such as decision support. DISCUSSION AND
conclusionUsability barriers inhibited adoption and effective use. We provide practical recommendations for improving opioid control by way of improving PDMP design, based on interviewees' suggestions and research-based design principles. Our findings have implications for other disciplines, including surgery and primary care.
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.