Methods used to construct disability indicators in linked administrative datasets: a systematic scoping review.
Background: In this scoping review, we aimed to examine evidence on methods used to construct disability indicators in linked administrative datasets and describe the approaches used to assess the validity of the indicators. Methods: Medline (Ovid) and Embase (Ovid) were searched for studies publish...
| Published in: | Population Health Metrics Vol. 23; no. 1; pp. 1 - 17 |
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| Main Authors: | , , , , |
| Format: | research systematic review tables/charts Journal Article |
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BioMed Central
6/6/2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=185783370&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 185783370 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14787954 1CZQ jtl: Population Health Metrics issn: 14787954 maglogo: N pubinfo: dt: 6/6/2025 vid: 23 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 185783370 185783370 185783370 10.1186/s12963-025-00386-w 185783370 ppf: 1 ppct: 16 formats: tig: atl: Methods used to construct disability indicators in linked administrative datasets: a systematic scoping review. aug: au: Aitken, Zoe Walmsley, Sarah M Bishop, Glenda Badji, Samia Fortune, Nicola affil: https://ror.org/01ej9dk98 Melbourne School of Population and Global Health, The University of Melbourne, 3010, Melbourne, VIC, Australia sug: subj: Disability Evaluation Health Status Indicators Routinely Collected Health Data Validation Studies Human Scoping Review Medline Embase Descriptive Statistics Confidence Intervals Algorithms Construct Validity Funding Source ab: Background: In this scoping review, we aimed to examine evidence on methods used to construct disability indicators in linked administrative datasets and describe the approaches used to assess the validity of the indicators. Methods: Medline (Ovid) and Embase (Ovid) were searched for studies published between January 2010 and June 2023. Original, peer-reviewed studies that aimed to construct a disability indicator using linked administrative data sources were included. Studies identifying any types of disability were included, but not those which defined the target population in terms of specific health conditions. We produced a narrative synthesis of findings related to disability indicator construction methods and validation approaches. Results: Thirty-six relevant studies were included, with 30 of those identifying a cohort of people with intellectual and/or developmental disability. Health data sources were most commonly used for indicator construction, with 33 of the studies using at least one health data source. Disability and education sector data sources were also commonly used. Diagnostic codes were used for disability identification in 34 of the 36 studies; 16 used diagnostic codes alone and 18 used diagnostic codes along with other information. A subgroup of 19 studies had a primary aim to create a disability cohort or estimate disability prevalence. Thirteen of these 19 studies compared their estimated prevalence rates with previously published estimates. Only five studies conducted testing to investigate the extent to which their derived disability indicator captured the intended target population. Discussion: We found a paucity of evidence on methods for identifying a target population of people with diverse disabilities. In the existing literature, diagnostic information is relied upon heavily for disability identification, likely due to a lack of other types of disability-relevant information in administrative data sources. Use of derived disability indicators within linked data holds potential to advance research regarding people with disability. It is crucial, however, to conduct and report validation testing to understand the strengths and limitations of the indicators and inform their use for specific purposes. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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