Evidence map›Paper›PMID 31420823›Full record

ArticleJournal of general internal medicine2019

Prescribing Associated with High-Risk Opioid Exposures Among Non-cancer Chronic Users of Opioid Analgesics: a Social Network Analysis.

Keiki Hinami, Michael J Ray, Kruti Doshi, Maria Torres, Steven Aks, John J Shannon, William E Trick

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Keiki HinamiDepartment of Medicine, Cook County Health, Chicago, IL, USA. khinami@cookcountyhhs.org.
Michael J RayDepartment of Medicine, Cook County Health, Chicago, IL, USA.
Kruti DoshiDepartment of Medicine, Cook County Health, Chicago, IL, USA.
Maria TorresDepartment of Anesthesiology, Division of Pain Management, Cook County Health , Chicago, IL, USA.
Steven AksDepartment of Emergency Medicine, Division of Medical Toxicology, Cook County Health , Chicago, IL, USA.
John J ShannonDepartment of Medicine, Cook County Health, Chicago, IL, USA.
William E TrickDepartment of Medicine, Cook County Health, Chicago, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe continued rise in fatalities from opioid analgesics despite a steady decline in the number of individual prescriptions directing ≥ 90 morphine milligram equivalents (MME)/day may be explained by patient exposures to redundant prescriptions from multiple prescribers.

objectivesWe evaluated prescribers' specialty and social network characteristics associated with high-risk opioid exposures resulting from single-prescriber high-daily dose prescriptions or multi-prescriber discoordination.

designRetrospective cohort study.

participantsA cohort of prescribers with opioid analgesic prescription claims for non-cancer chronic opioid users in an Illinois Medicaid managed care program in 2015-2016. MAIN MEASURES: Per prescriber rates of single-prescriber high-daily-dose prescriptions or multi-prescriber discoordination. KEY

resultsFor 2280 beneficiaries, 36,798 opioid prescription claims were submitted by 3532 prescribers. Compared to 3% of prescriptions (involving 6% of prescribers and 7% of beneficiaries) that directed ≥ 90 MME/day, discoordination accounted for a greater share of high-risk exposures-13% of prescriptions (involving 23% of prescribers and 24% of beneficiaries). The following specialties were at highest risk of discoordinated prescribing compared to internal medicine: dental (incident rate ratio (95% confidence interval) 5.9 (4.6, 7.5)), emergency medicine (4.7 (3.8, 5.8)), and surgical subspecialties (4.2 (3.0, 5.8)). Social network analysis identified 2 small interconnected prescriber communities of high-volume pain management specialists, and 3 sparsely connected groups of predominantly low-volume primary care or emergency medicine clinicians. Using multivariate models, we found that the sparsely connected sociometric positions were a risk factor for high-risk exposures.

conclusionLow-volume prescribers in the social network's periphery were at greater risk of intended or discoordinated prescribing than interconnected high-volume prescribers. Interventions addressing discoordination among low-volume opioid prescribers in non-integrated practices should be a priority. Demands for enhanced functionality and integration of Prescription Drug Monitoring Programs or referrals to specialized multidisciplinary pain management centers are potential policy implications.

Indexed as

Analgesics, OpioidEmergency MedicineHumansOpioid-Related DisordersPractice Patterns, Physicians'Prescription Drug Monitoring ProgramsPrimary Health CareRetrospective StudiesSocial NetworkingAnalgesics, Opioidcare discoordinationepidemiologyharm reductionMedicaidopioid analgesic prescribingsocial network analysis

Identifiers

PMID31420823
PMCPMC6848735

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.