Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK census
Objectives To address the lack of individual-level socioeconomic information in electronic healthcare records, we linked the 2011 census of England and Wales to patient records from a large mental healthcare provider. This paper describes the linkage process and methods for mitigating bias due to no...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2024-01-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/14/1/e073582.full |
| _version_ | 1797295867900723200 |
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| author | Robert Stewart Amelia Jewell Matthew Hotopf Jayati Das-Munshi Megan Pritchard Craig Morgan Natasha Chilman Michael Dewey Lukasz Cybulski Rosanna Hildersley Rachel Huck Milena Wuerth |
| author_facet | Robert Stewart Amelia Jewell Matthew Hotopf Jayati Das-Munshi Megan Pritchard Craig Morgan Natasha Chilman Michael Dewey Lukasz Cybulski Rosanna Hildersley Rachel Huck Milena Wuerth |
| author_sort | Robert Stewart |
| collection | DOAJ |
| description | Objectives To address the lack of individual-level socioeconomic information in electronic healthcare records, we linked the 2011 census of England and Wales to patient records from a large mental healthcare provider. This paper describes the linkage process and methods for mitigating bias due to non-matching.Setting South London and Maudsley NHS Foundation Trust (SLaM), a mental healthcare provider in Southeast London.Design Clinical records from SLaM were supplied to the Office of National Statistics for linkage to the census through a deterministic matching algorithm. We examined clinical (International Classification of Disease-10 diagnosis, history of hospitalisation, frequency of service contact) and socio-demographic (age, gender, ethnicity, deprivation) information recorded in Clinical Record Interactive Search (CRIS) as predictors of linkage success with the 2011 census. To assess and adjust for potential biases caused by non-matching, we evaluated inverse probability weighting for mortality associations.Participants Individuals of all ages in contact with SLaM up until December 2019 (N=459 374).Outcome measures Likelihood of mental health records’ linkage to census.Results 220 864 (50.4%) records from CRIS linked to the 2011 census. Young adults (prevalence ratio (PR) 0.80, 95% CI 0.80 to 0.81), individuals living in more deprived areas (PR 0.78, 95% CI 0.78 to 0.79) and minority ethnic groups (eg, Black African, PR 0.67, 0.66 to 0.68) were less likely to match to census. After implementing inverse probability weighting, we observed little change in the strength of association between clinical/demographic characteristics and mortality (eg, presence of any psychiatric disorder: unweighted PR 2.66, 95% CI 2.52 to 2.80; weighted PR 2.70, 95% CI 2.56 to 2.84).Conclusions Lower response rates to the 2011 census among people with psychiatric disorders may have contributed to lower match rates, a potential concern as the census informs service planning and allocation of resources. Due to its size and unique characteristics, the linked data set will enable novel investigations into the relationship between socioeconomic factors and psychiatric disorders. |
| first_indexed | 2024-03-07T21:55:11Z |
| format | Article |
| id | doaj.art-66a531b3be6d4a38a271e682d8cf4bb8 |
| institution | Directory Open Access Journal |
| issn | 2044-6055 |
| language | English |
| last_indexed | 2024-03-07T21:55:11Z |
| publishDate | 2024-01-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj.art-66a531b3be6d4a38a271e682d8cf4bb82024-02-24T18:10:08ZengBMJ Publishing GroupBMJ Open2044-60552024-01-0114110.1136/bmjopen-2023-073582Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK censusRobert Stewart0Amelia Jewell1Matthew Hotopf2Jayati Das-Munshi3Megan Pritchard4Craig Morgan5Natasha Chilman6Michael Dewey7Lukasz Cybulski8Rosanna Hildersley9Rachel Huck10Milena Wuerth11Department of Psychological Medicine, King’s College London, Institute of Psychiatry Psychology and Neuroscience, London, UKSouth London & Maudsley NHS Foundation Trust, London, UKDepartment of Psychological Medicine, King’s College London, Institute of Psychiatry Psychology and Neuroscience, London, UKDepartment of Psychological Medicine, King’s College London, Institute of Psychiatry Psychology and Neuroscience, London, UKUniversity of East Anglia Norwich Medical School, Norwich, UKHealth Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UKDepartment of Psychological Medicine, King’s College London, Institute of Psychiatry Psychology and Neuroscience, London, UKHealth Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UKDepartment of Psychological Medicine, King’s College London, Institute of Psychiatry Psychology and Neuroscience, London, UKDepartment of Psychological Medicine, King’s College London, Institute of Psychiatry Psychology and Neuroscience, London, UKOffice for National Statistics, London, UKDepartment of Psychological Medicine, King’s College London, Institute of Psychiatry Psychology and Neuroscience, London, UKObjectives To address the lack of individual-level socioeconomic information in electronic healthcare records, we linked the 2011 census of England and Wales to patient records from a large mental healthcare provider. This paper describes the linkage process and methods for mitigating bias due to non-matching.Setting South London and Maudsley NHS Foundation Trust (SLaM), a mental healthcare provider in Southeast London.Design Clinical records from SLaM were supplied to the Office of National Statistics for linkage to the census through a deterministic matching algorithm. We examined clinical (International Classification of Disease-10 diagnosis, history of hospitalisation, frequency of service contact) and socio-demographic (age, gender, ethnicity, deprivation) information recorded in Clinical Record Interactive Search (CRIS) as predictors of linkage success with the 2011 census. To assess and adjust for potential biases caused by non-matching, we evaluated inverse probability weighting for mortality associations.Participants Individuals of all ages in contact with SLaM up until December 2019 (N=459 374).Outcome measures Likelihood of mental health records’ linkage to census.Results 220 864 (50.4%) records from CRIS linked to the 2011 census. Young adults (prevalence ratio (PR) 0.80, 95% CI 0.80 to 0.81), individuals living in more deprived areas (PR 0.78, 95% CI 0.78 to 0.79) and minority ethnic groups (eg, Black African, PR 0.67, 0.66 to 0.68) were less likely to match to census. After implementing inverse probability weighting, we observed little change in the strength of association between clinical/demographic characteristics and mortality (eg, presence of any psychiatric disorder: unweighted PR 2.66, 95% CI 2.52 to 2.80; weighted PR 2.70, 95% CI 2.56 to 2.84).Conclusions Lower response rates to the 2011 census among people with psychiatric disorders may have contributed to lower match rates, a potential concern as the census informs service planning and allocation of resources. Due to its size and unique characteristics, the linked data set will enable novel investigations into the relationship between socioeconomic factors and psychiatric disorders.https://bmjopen.bmj.com/content/14/1/e073582.full |
| spellingShingle | Robert Stewart Amelia Jewell Matthew Hotopf Jayati Das-Munshi Megan Pritchard Craig Morgan Natasha Chilman Michael Dewey Lukasz Cybulski Rosanna Hildersley Rachel Huck Milena Wuerth Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK census BMJ Open |
| title | Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK census |
| title_full | Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK census |
| title_fullStr | Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK census |
| title_full_unstemmed | Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK census |
| title_short | Improving our understanding of the social determinants of mental health: a data linkage study of mental health records and the 2011 UK census |
| title_sort | improving our understanding of the social determinants of mental health a data linkage study of mental health records and the 2011 uk census |
| url | https://bmjopen.bmj.com/content/14/1/e073582.full |
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