Evidence map›Paper›PMID 25015470›Full record

ArticleBMJ open2014

Examining different measures of multimorbidity, using a large prospective cross-sectional study in Australian general practice.

Christopher Harrison, Helena Britt, Graeme Miller, Joan Henderson

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 187 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
187citing papers in PubMed, 10 pooled it
–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

187 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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127 more citing papers are in PubMed but not listed here.

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

4 authors.

Christopher HarrisonFamily Medicine Research Centre, School of Public Health, University of Sydney, Sydney, Australia.
Helena BrittFamily Medicine Research Centre, School of Public Health, University of Sydney, Sydney, Australia.
Graeme MillerFamily Medicine Research Centre, School of Public Health, University of Sydney, Sydney, Australia.
Joan HendersonFamily Medicine Research Centre, School of Public Health, University of Sydney, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPrevalence estimates of multimorbidity vary widely due to inconsistent definitions and measurement methods. This study examines the independent effects on prevalence estimates of how 'disease entity' is defined-as a single chronic condition or chapters/domains in the International Classification of Primary Care (V.2; ICPC-2), International Classification of Disease (10th revision; ICD-10) or the Cumulative Illness Rating Scale (CIRS), the number of disease entities required for multimorbidity, and the number of chronic conditions studied.

designNational prospective cross-sectional study.

settingAustralian general practice.

participants8707 random consenting deidentified patient encounters with 290 randomly selected general practitioners.

main outcome measuresPrevalence estimates of multimorbidity using different definitions.

resultsData classified to ICPC-2 chapters, ICD-10 chapters or CIRS domains produce similar multimorbidity prevalence estimates. When multimorbidity was defined as two or more (2+) disease entities: counting individual chronic conditions and groups of chronic conditions produced similar estimates; the 12 most prevalent chronic conditions identified about 80% of those identified using all chronic conditions. When multimorbidity was defined as 3+ disease entities: counting individual chronic conditions produced significantly higher estimates than counting groups of chronic conditions; the 12 most prevalent chronic conditions identified only two-thirds of patients identified using all chronic conditions.

conclusionsMultimorbidity defined as 2+ disease entities can be measured using different definitions of disease entity with as few as 12 prevalent chronic conditions, but lacks specificity to be useful, especially in older people. Multimorbidity, defined as 3+, requires more measurement conformity and inclusion of all chronic conditions, but provides greater specificity than the 2+ definition. The proposed concept of "complex multimorbidity", the co-occurrence of three or more chronic conditions affecting three or more different body systems within one person without defining an index chronic condition, may be useful in identifying high-need individuals.

Indexed as

General PracticeAgedAged, 80 and overAge FactorsAustraliaChronic DiseaseComorbidityCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceProspective StudiesRetrospective StudiesComorbidityGeneral practiceMultimorbidity

Identifiers

PMID25015470
PMCPMC4120329

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LicenceCC BY-NC
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Registered trials

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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.