Evidence map›Paper›PMID 34652799›Full record

ArticleEuropean geriatric medicine2019

Development of the "chronic condition measurement guide": a new tool to measure chronic conditions in older people based on ICD-10 and ATC-codes.

Helle Gybel Juul-Larsen, Line Due Christensen, Ove Andersen, Thomas Bandholm, Susanne Kaae, Janne Petersen

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Article in European geriatric medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

9 citing papers in PubMed, 14 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

6 authors at 3 institutions in 1 country.

Helle Gybel Juul-LarsenClinical Research Centre, Optimed, Amager and Hvidovre Hospital, University of Copenhagen, Kettegaard Allé 30, 2650, Hvidovre, Copenhagen, Denmark. helle.juul-larsen@regionh.dk.
Line Due ChristensenClinical Research Centre, Optimed, Amager and Hvidovre Hospital, University of Copenhagen, Kettegaard Allé 30, 2650, Hvidovre, Copenhagen, Denmark.
Ove AndersenClinical Research Centre, Optimed, Amager and Hvidovre Hospital, University of Copenhagen, Kettegaard Allé 30, 2650, Hvidovre, Copenhagen, Denmark.
Thomas BandholmClinical Research Centre, Optimed, Amager and Hvidovre Hospital, University of Copenhagen, Kettegaard Allé 30, 2650, Hvidovre, Copenhagen, Denmark.
Susanne KaaeSocial and Clinical Pharmacy, Department of Pharmacy, Faculty of Health, University of Copenhagen, Copenhagen, Denmark.
Janne PetersenClinical Research Centre, Optimed, Amager and Hvidovre Hospital, University of Copenhagen, Kettegaard Allé 30, 2650, Hvidovre, Copenhagen, Denmark.
University of Copenhagen · DKHvidovre Hospital · DKFrederiksberg Hospital · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of the study was to develop a comprehensive open-source measurement guide of the most prevalent chronic conditions among persons aged 65+ based on registry data of both diagnoses and prescribed drugs [the chronic condition measurement guide (CCMG)]. Furthermore, to investigate proof of concept of the measurement guide, different years of history and in- and excluding data on prescribed drugs. Finally, to investigate the measurement guide with other measurement guides designed to identify chronic conditions in persons aged 65+.

methodsThe measurement guide was based on the 200 most prevalent chronic ICD10 codes in the Danish population 65+ years in 2015; the 200 most prevalent chronic ICD10 codes and causes of death in a cohort of 209,337 people who died of non-traumatic causes (January 2011-January 2016). Prescribed drugs were included in the measurement guide based on a literature review and specialist opinions.

resultsWe identified 83 different chronic conditions based on 1241 unique ICD-10 codes. Multimorbidity prevalence ranged from 10% (1-year history, excluding prescribing information) to 69% (15-year history, including prescribing information). We identified 95% of the persons with multimorbidity using the 29 most prevalent chronic conditions. Inclusion of these 29 conditions affected the prevalence of multimorbidity and 1-year mortality when the CCMG was compared with other measurement guides.

conclusionThe CCMG is easily implemented using registry data. When implementing the measurement guide 10 years of history and drug prescribing information should be used. Using the CCMG to study multimorbidity, we recommend using at least the 29 most prevalent chronic conditions.

Indexed as

Chronic conditionsMeasurementMultimorbidityPeople aged 65+

Identifiers

PMID34652799
OpenAlexW2940164067

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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.