Evidence map›Paper›PMID 29514335›Full record

ArticleMilitary medicine2018

Opioid Use Patterns Among Active Duty Service Members and Civilians: 2006-2014.

William Kazanis, Mary J Pugh, Claudina Tami, Joseph K Maddry, Vikhyat S Bebarta, Erin P Finley, Don D McGeary, David H Carnahan, Jennifer S Potter

Open access · hybridAbstract read
In one paragraph

Article in Military medicine, 2018. 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
2.2field-weighted citation impact, top 11% of its field
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, 23 citations in OpenAlex.

  1. Trial
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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

9 authors at 1 institution in 1 country.

William KazanisUniversity of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, TX 78229.
Mary J PughUniversity of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, TX 78229.
Claudina TamiUniversity of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, TX 78229.
Joseph K MaddryEn Route Care Research Center, 3698 Chambers Pass, Fort Sam Houston, San Antonio, TX 78234.
Vikhyat S BebartaUniversity of Colorado School of Medicine, Leprino Office Building, 12401 East 17th Avenue, Aurora, CO 80045.
Erin P FinleyUniversity of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, TX 78229.
Don D McGearyUniversity of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, TX 78229.
David H CarnahanDefense Health Agency, 7700 Arlington Boulevard, Falls Church, VA, 22042.
Jennifer S PotterUniversity of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, TX 78229.
South Texas Veterans Health Care System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Between 2001 and 2009, opioid analgesic prescriptions in the Military Health System quadrupled to 3.8 million. The sheer quantity of opioid analgesics available sets the stage for issues related to misuse, abuse, and diversion. To address this issue, the Department of Defense implemented several directives and clinical guidelines to improve access to appropriate pain care and safe opioid prescribing. Unfortunately, little has been done to characterize changing patterns of opioid use in active duty service members (ADSM), so little is known about how combat operations and military health care policy may have influenced this significant problem. We examined changes in opioid use for ADSM between 2006 and 2014, compared trends with the civilian population, and explored the potential role of military-specific factors in changes in opioid use in the Military Health System. Materials and Methods: After obtaining Institutional Review Board approval, administrative prescription records (Pharmacy Data Transaction Records) for non-deployed ADSM were used to determine the number of opioid prescriptions dispensed each year and the proportion of ADSM who received at least one prescription per month between 2006 and 2014. Based on the observation and the literature, we identified December 2011 as the demarcation point (the optimal point to identify the downturn in opioid use) and used it to compare opioid use trends before and after. We used an autoregressive forecast model to verify changes in opioid use patterns before and after 2011. Several interrupted time series models examined whether military system-level factors were associated with changes in opioid use. Results: Between 2006 and 2014, 1,516,979 ADSM filled 7,119,945 opioid prescriptions, either in military treatment facilities or purchased through TRICARE. Both active duty and civilian populations showed signs of decreasing use after 2011, but this change was much more pronounced among ADSM. The forecast model showed a significant difference after 2011 between the projected and actual proportion of ADSM filling an opioid prescription, confirming 2011 as a point of divergence in opioid use. Interrupted time series models showed that the deflection point was associated with significant decreases. A significant increase of 0.261% in opioid prescriptions was seen for every 1,000 wounded in action service members in a given month. Troops returning from Operation Enduring Freedom, Operation Iraqi Freedom, or Operation New Dawn did not appear to influence the rates of use. Even after accounting for returning troops from Operation Enduring Freedom/Operation Iraqi Freedom/Operation New Dawn and wounded in action counts, the deflection point was associated with a lower proportion of ADSM who filled an opioid prescription, leading to a decrease of 1.61% by the end of the observation period (December 2014). Conclusion: After December 2011, opioid use patterns significantly decreased in both civilian and ADSM populations, but more so in the military population. Many factors, such as numbers of those wounded in action and the structural organization of the Military Health System, may have caused the decline, although more than likely the decrease was influenced by many factors inside and outside of the military, including policy directives and cultural changes.

Indexed as

Analgesics, OpioidEpidemicsHumansMilitary PersonnelOpioid-Related DisordersUnited StatesAnalgesics, Opioid

Identifiers

PMID29514335
PMCPMC6927844
OpenAlexW2785170077

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.