Evidence map›Paper›PMID 30772867›Full record

ArticleBMJ open2019

Patterns of high-risk prescribing and other factors in relation to receipt of a home medicines review: a prospective cohort investigation among adults aged 45 years and over in Australia.

Wei Du, Danijela Gnjidic, Sallie-Anne Pearson, Sarah N Hilmer, Andrew J McLachlan, Fiona Blyth, Rosalie Viney, Grace Joshy, Cathy Day, Emily Banks

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

4 citing papers in PubMed, 17 citations in OpenAlex.

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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

10 authors at 4 institutions in 1 country.

Wei DuResearch School of Population Health, Australian National University, Canberra, Sydney, Australia.ORCID 0000-0003-3622-2265
Danijela GnjidicSydney Pharmacy School and Centre for Education and Research on Ageing, University of Sydney and Concord Hospital, Sydney, New South Wales, Australia.
Sallie-Anne PearsonCentre for Big Data Research in Health, University of New South Wales, Sydney, New South Wales, Australia.
Sarah N HilmerKolling Institute of Medical Research, Sydney Medical School, Royal North Shore Hospital, University of Sydney, North Shore, Sydney, Australia.
Andrew J McLachlanSydney Pharmacy School and Centre for Education and Research on Ageing, University of Sydney and Concord Hospital, Sydney, New South Wales, Australia.
Fiona BlythCentre for Education and Research on Ageing, Sydney Medical School University of Sydney, Camperdown, Camperdown, Australia.
Rosalie VineyCentre for Health Economics Research Eval., University of Technology, Sydney, New South Wales, Australia.
Grace JoshyResearch School of Population Health, Australian National University, Canberra, Sydney, Australia.ORCID 0000-0002-0718-6368
Cathy DayResearch School of Population Health, Australian National University, Canberra, Sydney, Australia.
Emily BanksResearch School of Population Health, Australian National University, Canberra, Sydney, Australia.
Australian National University · AUThe University of Sydney · AUUniversity of Technology Sydney · AUUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo quantify the relationship between home medicines review (HMR) receipt in older adults and sociodemographic, medication-related and health factors.

designProspective cohort analysis. SETTINGS, PARTICIPANTS, MEASUREMENTS: Questionnaire data from a population-based cohort study of individuals aged ≥45 years, Sydney, Australia were linked with primary healthcare data, medication and hospitalisation data, to ascertain factors associated with HMR receipt during the period July 2009-June 2014. Medication-related factors included exposure to five and more medications (polypharmacy), narrow therapeutic index medicines, potentially inappropriate prescribing defined using Beers Criteria medicines, and anticholinergic and sedative drugs, defined using the Drug Burden Index (DBI). Poisson and Cox regression models were used to evaluate HMR receipt in relation to sociodemographic, behavioural and health characteristics, and time-varying factors including medication use and hospitalisations. PRIMARY OUTCOME: HMR receipt during the 5-year study period.

resultsOver 5 years of follow-up, 4.7% (n=6115) of 131 483 participants received at least one HMR. Five-year HMR receipt was: 1.5% in people using <5 medications at baseline, 6.8% with 5-9 medications, 12.7% with ≥10 medications, 8.8% using Narrow Therapeutic Index medicines, 6.8% using Beers Criteria potentially inappropriate medicines and 7.4% using DBI medicines. Age-sex stratified HRs for HMR receipt were 6.07 (95% CI: 5.58 to 6.59) and 12.46 (11.42 to 13.59) for concurrent use of 5-9 and ≥10 versus <5 medications, respectively. The age-sex adjusted rate ratio for HMR receipt was 2.65 (2.51 to 2.80) with poor versus good self-reported health; this association was attenuated substantially following additional adjustment for polypharmacy.

conclusionsHMR was common in individuals using multiple medications, a formal indication for general practitioner referral and, to a lesser extent, with poorer health and other markers of high-risk prescribing. Despite this, HMR use over a 5-year period was generally below 10%, even in high-risk groups, suggesting substantial potential for improvement in uptake and targeting.

Indexed as

Drug PrescriptionsHomes for the AgedPotentially Inappropriate Medication ListPractice Patterns, Physicians'AgedAged, 80 and overAustraliaDrug InteractionsFemaleHome Care ServicesHumansInappropriate PrescribingMaleMiddle AgedProspective Studiesageinghealth servicesquality use of medicines

Identifiers

PMID30772867
PMCPMC6398774
OpenAlexW2914695089

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.