Evidence map›Paper›PMID 37147416›Full record

ReviewDrugs & aging2023

Identifying Residents Who May Benefit from an Analgesic Review: Applying Analgesic Indicators in Residential Aged Care Services.

Laura A Dowd, Amanda J Cross, Shin J Liau, Agathe D Jadczak, Renuka Visvanathan, Felicity C Veal, J Simon Bell

Open access · hybridAbstract readReview
In one paragraph

Review in Drugs & aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
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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

7 authors at 4 institutions in 1 country.

Laura A DowdCentre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia. laura.dowd@monash.edu.ORCID 0000-0002-2228-5508
Amanda J CrossCentre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia.
Shin J LiauCentre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia.
Agathe D JadczakNational Health and Medical Research Council (NHMRC) Centre of Research Excellence in Frailty and Healthy Ageing, Adelaide, SA, Australia.
Renuka VisvanathanNational Health and Medical Research Council (NHMRC) Centre of Research Excellence in Frailty and Healthy Ageing, Adelaide, SA, Australia.
Felicity C VealUnit for Medication Outcomes Research and Education (UMORE), School of Pharmacy and Pharmacology, University of Tasmania, Hobart, TAS, Australia.
J Simon BellCentre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, VIC, Australia.
National Health and Medical Research Council · AUMonash University · AUQueen Elizabeth Hospital · AUUniversity of Tasmania · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEnsuring safe and effective analgesic use in residential aged care services is important because older adults are susceptible to analgesic-related adverse drug events (ADEs).

objectiveThe aim of this study was to identify the proportion and characteristics of residents of aged care services who may benefit from analgesic review based on indicators in the 2021 Society for Post-Acute and Long-Term Care Medicine (AMDA) Pain Management Guideline.

methodsCross-sectional analyses of baseline data from the Frailty in Residential Sector over Time (FIRST) study (N = 550 residents) across 12 South Australian residential aged care services in 2019 were conducted. Indicators included the proportion of residents who received > 3000 mg/day of acetaminophen (paracetamol), regular opioids without a documented clinical rationale, opioid doses > 60 mg morphine equivalents (MME)/day, more than one long-acting opioid concurrently, and a pro re nata (PRN) opioid on more than two occasions in the previous 7 days. Logistic regression was performed to investigate factors associated with residents who may benefit from analgesic review.

resultsOf 381 (69.3%) residents charted regular acetaminophen, 176 (46.2%) were charted > 3000 mg/day. Of 165 (30%) residents charted regular opioids, only 2 (1.2%) had no prespecified potentially painful conditions in their medical record and 31 (18.8%) received > 60 MME/day. Of 153 (27.8%) residents charted long-acting opioids, 8 (5.2%) received more than one long-acting opioid concurrently. Of 212 (38.5%) residents charted PRN opioids, 10 (4.7%) received more than two administrations in the previous 7 days. Overall, 196 (35.6%) of 550 residents were identified as potentially benefiting from analgesic review. Females (odds ratio [OR] 1.87, 95% confidence interval [CI] 1.20-2.91) and residents with prior fracture (OR 1.62, 95% CI 1.12-2.33) were more likely to be identified. Observed pain (OR 0.50, 95% CI 0.29-0.88) was associated with a lower likelihood of being identified compared with residents with no observed pain. Overall, 43 (7.8%) residents were identified based on opioid-related indicators.

conclusionsUp to one in three residents may benefit from a review of their analgesic regimen, including 1 in 13 who may benefit from a specific review of their opioid regimen. Analgesic indicators represent a new approach to target analgesic stewardship interventions.

Indexed as

AcetaminophenAnalgesics, OpioidAgedAnalgesicsAustraliaCross-Sectional StudiesEndrinFemaleHumansMorphinePainAcetaminophenAnalgesicsAnalgesics, OpioidEndrinMMEMorphine

Identifiers

PMID37147416
PMCPMC10198878
OpenAlexW4372333313

What OpenQuestion holds

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LicenceCC BY-NC
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.