ArticleJournal of general internal medicine2025
The Rise of Clinical Decision Support Algorithms in Pain Management 2009-2024.
Article in Journal of general internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Evaluating the validity and performance of a modifiable prediction model to predict new long-term opioid use in prescription drug monitoring programs.JAMIA open · 2026Article
- Understanding pharmaceutical industry coalitions: a case study of Mallinckrodt.Humanities & social sciences communications · 2026Article
- Vigilant Algorithms and the Contagion of Risk in Automated Opioid Risk Assessment.Sociology of health & illness · 2026Article
- Purdue's development of abuse-deterrent formulation opioids as a response to market competition: An industry documents analysis.SSM. Qualitative research in health · 2026Article
- Centralized daily drug management in clinical trial institutions and specific implementation plans.Frontiers in drug safety and regulation · 2025Review
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.
Funding
Abstract
This paper examines the rise of clinical decision support algorithms used to assess risk in pain management and the opioid industry's influence on their development and implementation. To understand this influence, we conducted a qualitative study of documents related to the development of a tool that relied on artificial intelligence (AI) to suggest modifications in opioid prescribing, called NarxCare. The study began with keyword searches of the Opioid Industry Document Archive (OIDA), which contained over 3 million documents at the time of the study, to examine the pharmaceutical industry's role in shaping the digital transformation of opioid prescribing. Our findings highlight industry-driven investments, educational campaigns, corporate policy activities, and the reliance on proprietary data that facilitated the widespread implementation of NarxCare. The increasing reliance on NarxCare raises concerns about its limited transparency, unknown reliability, and potential bias which may disproportionately affect certain patient groups based on race, socioeconomic status, or health conditions. This paper argues that the promotion of technologies like NarxCare allows the pharmaceutical industry to reinforce the narrative that opioids can be effective when prescribed responsibly, using advanced, data-driven strategies. Marketed as tools that assist clinicians in making more informed prescribing decisions, NarxCare contributes to the portrayal of the industry as a responsible actor in the regulation and distribution of opioids. Shifting attention to individual risk factors rather than systemic challenges enables the pharmaceutical industry to sidestep its role in the opioid crisis and evade scrutiny for its influence over regulation, the sponsorship of education and research, lobbying, supply chain control, and public health narratives. While NarxCare aims to improve prescribing safety, it requires critical evaluation in terms of effectiveness, ethical considerations, and the continued influence of the pharmaceutical industry in its design and implementation.
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.