Evidence map›Paper›PMID 25103030›Full record

Observational studyAge and ageing2015

Much more medicine for the oldest old: trends in UK electronic clinical records.

David Melzer, Behrooz Tavakoly, Rachel E Winder, Jane A H Masoli, William E Henley, Alessandro Ble, Suzanne H Richards

2 registry-linked trialsOpen access · hybridAbstract readObservational Study
In one paragraph

Observational study in Age and ageing, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 4% 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.

NCT03786315 completednot on this mapstarted 2021, after this paper: background citation

Exploring 'VOLITION' in Context - a Study to Inform the Implementation of a New Intervention

TypeobservationalSponsorUniversity of ExeterRan2021 to 2022Enrolled72ConditionsDecision Making, Aged, Multimorbidity, General Practice
NCT04188470 nacompletednot on this mapstarted 2020, after this paper: background citation

Open Randomised Multicentric Controlled Trial to Evaluate the Impact of an Intervention to Improve Drug Appropriateness in Polymedicated Patients According to the Person-centered Care Model by a Multidisciplinary Team At Primary Care

TypeinterventionalSponsorFundacio d'Investigacio en Atencio Primaria Jordi Gol i GurinaRan2020 to 2024Enrolled208ConditionsMultiple Chronic Conditions, End Stage DiseaseArmsperson-centered care model
3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.

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  17. Gender Differences in Medication Use: A Drug Utilization Study Based on Real World Data.International journal of environmental research and public health · 2020
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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 1 institution in 1 country.

David MelzerEpidemiology and Public Health, University of Exeter Medical School, Barrack Road, Exeter EX2 5DW, UK.
Behrooz TavakolyEpidemiology and Public Health, University of Exeter Medical School, Barrack Road, Exeter EX2 5DW, UK.
Rachel E WinderEpidemiology and Public Health, University of Exeter Medical School, Smeall Building, St Luke's Campus, Exeter EX1 2LU, UK.
Jane A H MasoliEpidemiology and Public Health, University of Exeter Medical School, Barrack Road, Exeter EX2 5DW, UK.
William E HenleyHealth Statistics Group, University of Exeter Medical School, St Luke's Campus, Exeter EX1 2LU, UK.
Alessandro BleEpidemiology and Public Health, University of Exeter Medical School, Barrack Road, Exeter EX2 5DW, UK.
Suzanne H RichardsPrimary Care Research Group, University of Exeter Medical School, Smeall Building, St Luke's Campus, Exeter EX1 2LU, UK.
University of Exeter · GB

Funding

Department of Health DRF-2014-07-177
6 · The paper itself

Abstract

backgroundthe oldest old (85+) pose complex medical challenges. Both underdiagnosis and overdiagnosis are claimed in this group.

objectiveto estimate diagnosis, prescribing and hospital admission prevalence from 2003/4 to 2011/12, to monitor trends in medicalisation. DESIGN AND

settingobservational study of Clinical Practice Research Datalink (CPRD) electronic medical records from general practice populations (eligible; n = 27,109) with oversampling of the oldest old.

methodswe identified 18 common diseases and five geriatric syndromes (dizziness, incontinence, skin ulcers, falls and fractures) from Read codes. We counted medications prescribed ≥1 time in all quarters of studied years.

resultsthere were major increases in recorded prevalence of most conditions in the 85+ group, especially chronic kidney disease (stages 3-5: prevalence <1% rising to 36.4%). The proportions of the 85+ group with ≥3 conditions rose from 32.2 to 55.1% (27.1 to 35.1% in the 65-84 year group). Geriatric syndrome trends were less marked. In the 85+ age group the proportion receiving no chronically prescribed medications fell from 29.6 to 13.6%, while the proportion on ≥3 rose from 44.6 to 66.2%. The proportion of 85+ year olds with ≥1 hospital admissions per year rose from 27.6 to 35.4%.

conclusionsthere has been a dramatic increase in the medicalisation of the oldest old, evident in increased diagnosis (likely partly due to better record keeping) but also increased prescribing and hospitalisation. Diagnostic trends especially for chronic kidney disease may raise concerns about overdiagnosis. These findings provide new urgency to questions about the appropriateness of multiple diagnostic labelling.

Indexed as

AgedAged, 80 and overAge FactorsAgingDiagnostic Tests, RoutineDrug PrescriptionsElectronic Health RecordsFemaleGeriatricsHealth ResourcesHumansMalePatient AdmissionPolypharmacyPractice Patterns, Physicians'Predictive Value of Testsadmissionkidneyolder peopleoldestprescribingprevalence

Identifiers

PMID25103030
PMCPMC4255615
OpenAlexW2159995757

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.