Laurie E Davies, David R Sinclair, Andrew Kingston, Gemma Frances Spiers, Barbara Hanratty
{"title":"是否有可能在初级保健中识别处于物质劣势的人群?利用临床实践研究数据库进行的可行性研究。","authors":"Laurie E Davies, David R Sinclair, Andrew Kingston, Gemma Frances Spiers, Barbara Hanratty","doi":"10.1136/jech-2024-222396","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Material disadvantage is associated with poor health, but commonly available area-based metrics provide a poor proxy for it. We investigate if a measure of material disadvantage could be constructed from UK primary care electronic health records.</p><p><strong>Methods: </strong>Using data from Clinical Practice Research Datalink Aurum (May 2022) linked to the 2019 English Index of Multiple Deprivation (IMD), we sought to (1) identify codes that signified material disadvantage, (2) aggregate these codes into a binary measure of material disadvantage and (3) compare the proportion of people with this binary measure against IMD quintiles for validation purposes.</p><p><strong>Results: </strong>We identified 491 codes related to benefits, employment, housing, income, environment, neglect, support services and transport. Participants with one or more of these codes were defined as being materially disadvantaged. Among 30,897,729 research-acceptable patients aged ≥18 with complete data, only 6.1% (n=1,894,225) were classified as disadvantaged using our binary measure, whereas 42.2% (n=13,038,085) belonged to the two most deprived IMD quintiles.</p><p><strong>Conclusion: </strong>Data in a major primary care research database do not currently contain a useful measure of individual-level material disadvantage. This represents an omission of one of the most important health determinants. Consideration should be given to creating codes for use by primary care practitioners.</p>","PeriodicalId":54839,"journal":{"name":"Journal of Epidemiology and Community Health","volume":" ","pages":"806-808"},"PeriodicalIF":4.9000,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11671866/pdf/","citationCount":"0","resultStr":"{\"title\":\"Is it possible to identify populations experiencing material disadvantage in primary care? A feasibility study using the Clinical Practice Research Database.\",\"authors\":\"Laurie E Davies, David R Sinclair, Andrew Kingston, Gemma Frances Spiers, Barbara Hanratty\",\"doi\":\"10.1136/jech-2024-222396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Material disadvantage is associated with poor health, but commonly available area-based metrics provide a poor proxy for it. We investigate if a measure of material disadvantage could be constructed from UK primary care electronic health records.</p><p><strong>Methods: </strong>Using data from Clinical Practice Research Datalink Aurum (May 2022) linked to the 2019 English Index of Multiple Deprivation (IMD), we sought to (1) identify codes that signified material disadvantage, (2) aggregate these codes into a binary measure of material disadvantage and (3) compare the proportion of people with this binary measure against IMD quintiles for validation purposes.</p><p><strong>Results: </strong>We identified 491 codes related to benefits, employment, housing, income, environment, neglect, support services and transport. Participants with one or more of these codes were defined as being materially disadvantaged. Among 30,897,729 research-acceptable patients aged ≥18 with complete data, only 6.1% (n=1,894,225) were classified as disadvantaged using our binary measure, whereas 42.2% (n=13,038,085) belonged to the two most deprived IMD quintiles.</p><p><strong>Conclusion: </strong>Data in a major primary care research database do not currently contain a useful measure of individual-level material disadvantage. This represents an omission of one of the most important health determinants. Consideration should be given to creating codes for use by primary care practitioners.</p>\",\"PeriodicalId\":54839,\"journal\":{\"name\":\"Journal of Epidemiology and Community Health\",\"volume\":\" \",\"pages\":\"806-808\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11671866/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Epidemiology and Community Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/jech-2024-222396\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Epidemiology and Community Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/jech-2024-222396","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Is it possible to identify populations experiencing material disadvantage in primary care? A feasibility study using the Clinical Practice Research Database.
Background: Material disadvantage is associated with poor health, but commonly available area-based metrics provide a poor proxy for it. We investigate if a measure of material disadvantage could be constructed from UK primary care electronic health records.
Methods: Using data from Clinical Practice Research Datalink Aurum (May 2022) linked to the 2019 English Index of Multiple Deprivation (IMD), we sought to (1) identify codes that signified material disadvantage, (2) aggregate these codes into a binary measure of material disadvantage and (3) compare the proportion of people with this binary measure against IMD quintiles for validation purposes.
Results: We identified 491 codes related to benefits, employment, housing, income, environment, neglect, support services and transport. Participants with one or more of these codes were defined as being materially disadvantaged. Among 30,897,729 research-acceptable patients aged ≥18 with complete data, only 6.1% (n=1,894,225) were classified as disadvantaged using our binary measure, whereas 42.2% (n=13,038,085) belonged to the two most deprived IMD quintiles.
Conclusion: Data in a major primary care research database do not currently contain a useful measure of individual-level material disadvantage. This represents an omission of one of the most important health determinants. Consideration should be given to creating codes for use by primary care practitioners.
期刊介绍:
The Journal of Epidemiology and Community Health is a leading international journal devoted to publication of original research and reviews covering applied, methodological and theoretical issues with emphasis on studies using multidisciplinary or integrative approaches. The journal aims to improve epidemiological knowledge and ultimately health worldwide.