Observational studyInternal and emergency medicine2016
Variation in opioid prescribing patterns between ED providers.
Observational study in Internal and emergency medicine, 2016. 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
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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, 17 citations in OpenAlex.
- Article
- Positive Toxicology Results Are Not Associated with Emergency Physicians' Opioid Prescribing Behavior.The western journal of emergency medicine · 2021Article
- Variation in opioid analgesia administration and discharge prescribing for emergency department patients with suspected urolithiasis.The American journal of emergency medicine · 2020Article
- Emergency department provider and facility variation in opioid prescriptions for discharged patients.The American journal of emergency medicine · 2019Article
- Discharge prescription patterns of opioid and nonopioid analgesics after common surgical procedures.Pain reports · 2018Article
- We have to "think" before prescribing an opioid in Italian Emergency Department?Internal and emergency medicine · 2017Article
- Global prescription "opioi-demic:" what about provider prescribing behaviors?Internal and emergency medicine · 2016Article
- A Call for Better Opioid Prescribing Training and Education.The western journal of emergency medicine · 2016Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abuse of opioid prescription drugs has become an epidemic across the developed world. Despite the fact that emergency physicians overall account for a small proportion of total opioids prescribed, the number of prescriptions has risen dramatically in the past decade and, to some degree, contributes to the available supply of opioids in the community, some of which are diverted for non-medical use. Since successfully reducing opioid prescribing on the individual level first requires knowledge of current prescribing patterns, we sought to determine to what extent variation exists in opioid prescribing patterns at our institution. This was a single-institution observational study at a community hospital with an annual ED volume of 47,000 visits. We determined the number of prescriptions written by each provider, both total number and accounting for the number of patients seen. Our primary outcome measure was the level of variation at the physician level for number of prescriptions written per patient. We also identified the mean number of pills written per prescription. We analyzed data from November 13, 2014 through July 31, 2015 for 21 full-time providers. There were a total of 2211 prescriptions for opioids written over this time period for a total of 17,382 patients seen. On a per-patient basis, the rate of opioid prescriptions written per patient during this period was 127 per 1000 visits (95 % CI 122-132). There was a variation on the individual provider level, with rates ranging from 33 per to 332 per 1000 visits. There was also substantial variation by provider in the number of pills written per prescription with coefficient of variation (standard deviation divided by mean) averaged over different opioids ranging from 16 to 40 %. There was significant variation in opioid prescribing patterns at the individual physician level, even when accounting for the number of patients seen.
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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.