The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort
Introduction Multimorbidity, the co-existence of two or more health conditions, is a growing challenge. It may be measured using health service administrative data via the emerging consensus measure by Barnett. However, the original Barnett was developed using Scottish-specific primary care coding,...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Swansea University
2018-09-01
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| Series: | International Journal of Population Data Science |
| Online Access: | https://ijpds.org/article/view/909 |
| _version_ | 1797430970882719744 |
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| author | Marjorie Johnston Corri Black Stewart Mercer Gordon Prescott Jessica Butler |
| author_facet | Marjorie Johnston Corri Black Stewart Mercer Gordon Prescott Jessica Butler |
| author_sort | Marjorie Johnston |
| collection | DOAJ |
| description | Introduction
Multimorbidity, the co-existence of two or more health conditions, is a growing challenge. It may be measured using health service administrative data via the emerging consensus measure by Barnett. However, the original Barnett was developed using Scottish-specific primary care coding, which restricts its application in other health systems.
Objectives and Approach
The aim was to create and test International Classification of Disease (ICD) coding algorithms for all 40 Barnett conditions.
We evaluated this new measure by:
• Assessing the prevalence of secondary care multimorbidity in 2001
• Assessing the association between multimorbidity and mortality rate over 15 years
Participants of the Aberdeen Children of the 1950s cohort (ACONF) were linked to their secondary-care healthcare records and mortality records. Multimorbidity was defined as the presence of two or more of the 40 conditions. The association between multimorbidity and mortality was assessed using Cox proportional hazards regression with adjustment for key covariates.
Results
We combined results of a review of the coding literature with codes used commonly by the National Health Service in Scotland, to apply ICD codes to each Barnett condition.
The ACONF were aged 45 to 51 years in 2001. Of 8,094 members who were alive and linked to Scottish administrative data, 246 (3%) had multimorbidity. There were 629 deaths by 2016 with 83 occurring in the multimorbidity group.
Relative to those without multimorbidity, those with multimorbidity in 2001 had a mortality hazard ratio (HR) of 5.9 (95% CI 4.6-7.4) over 15 years follow-up. This was unchanged when adjusted for age, gender, social class at birth, cognition at age 7, secondary school type and educational attainment (HR 6.2, 95% CI 4.4-8.5).
Conclusion/Implications
We have created a new version of the influential Barnett measure using ICD codes, which allows for its wider application across health systems. We found that this measure of multimorbidity was associated with greatly increased mortality, indicating it could help predict poor outcome using administrative records. |
| first_indexed | 2024-03-09T09:35:10Z |
| format | Article |
| id | doaj.art-c8904b7d4e7141b1b51d59286ef6547f |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T09:35:10Z |
| publishDate | 2018-09-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-c8904b7d4e7141b1b51d59286ef6547f2023-12-02T02:22:09ZengSwansea UniversityInternational Journal of Population Data Science2399-49082018-09-013410.23889/ijpds.v3i4.909909The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohortMarjorie Johnston0Corri Black1Stewart Mercer2Gordon Prescott3Jessica Butler4University of AberdeenUniversity of AberdeenUniversity of GlasgowUniversity of AberdeenUniversity of AberdeenIntroduction Multimorbidity, the co-existence of two or more health conditions, is a growing challenge. It may be measured using health service administrative data via the emerging consensus measure by Barnett. However, the original Barnett was developed using Scottish-specific primary care coding, which restricts its application in other health systems. Objectives and Approach The aim was to create and test International Classification of Disease (ICD) coding algorithms for all 40 Barnett conditions. We evaluated this new measure by: • Assessing the prevalence of secondary care multimorbidity in 2001 • Assessing the association between multimorbidity and mortality rate over 15 years Participants of the Aberdeen Children of the 1950s cohort (ACONF) were linked to their secondary-care healthcare records and mortality records. Multimorbidity was defined as the presence of two or more of the 40 conditions. The association between multimorbidity and mortality was assessed using Cox proportional hazards regression with adjustment for key covariates. Results We combined results of a review of the coding literature with codes used commonly by the National Health Service in Scotland, to apply ICD codes to each Barnett condition. The ACONF were aged 45 to 51 years in 2001. Of 8,094 members who were alive and linked to Scottish administrative data, 246 (3%) had multimorbidity. There were 629 deaths by 2016 with 83 occurring in the multimorbidity group. Relative to those without multimorbidity, those with multimorbidity in 2001 had a mortality hazard ratio (HR) of 5.9 (95% CI 4.6-7.4) over 15 years follow-up. This was unchanged when adjusted for age, gender, social class at birth, cognition at age 7, secondary school type and educational attainment (HR 6.2, 95% CI 4.4-8.5). Conclusion/Implications We have created a new version of the influential Barnett measure using ICD codes, which allows for its wider application across health systems. We found that this measure of multimorbidity was associated with greatly increased mortality, indicating it could help predict poor outcome using administrative records.https://ijpds.org/article/view/909 |
| spellingShingle | Marjorie Johnston Corri Black Stewart Mercer Gordon Prescott Jessica Butler The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort International Journal of Population Data Science |
| title | The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort |
| title_full | The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort |
| title_fullStr | The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort |
| title_full_unstemmed | The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort |
| title_short | The prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort |
| title_sort | prevalence of multimorbidity measured by linked healthcare data and its association with mortality in a large longitudinal cohort |
| url | https://ijpds.org/article/view/909 |
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