Multimorbidity clusters among people with serious mental illness: a representative primary and secondary data linkage cohort study

Ma, Ruimin; Romano, Eugenia; Ashworth, Mark; Yadegarfar, Mohammad E; Dregan, Alexandru; Ronaldson, Amy; Oliveira, Claire de; Jacobs, Rowena; Stewart, Robert; Stubbs, Brendon

doi:10.1017/s003329172200109x

Cited by 4 publications

(4 citation statements)

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“…Of the 42 full-text articles, 23 articles were excluded due to lack of relevant outcomes, not including analysis on the association between severe mental illness and physical multimorbidity, and mental health diagnoses were not obtained. This left 19 articles to be included in the systematic review 25–41…”

Section: Resultsmentioning

confidence: 99%

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Relationship between severe mental illness and physical multimorbidity: a meta-analysis and call for action

Pizzol,

Trott,

Butler

et al. 2023

BMJ Ment Health

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BackgroundPeople with severe mental illness (SMI) have a higher prevalence of several chronic physical health conditions, and the prevalence of physical multimorbidity is expected to rise. The aim of this study was to assess the strength of the association between SMI and physical multimorbidity.Study selection and analysisWe systematically searched PubMed/Medline, Scopus, Embase, Web of Science, PsycINFO and the behavioural sciences collection databases, from inception to 31 January 2023, for studies that investigated the association between SMI and physical multimorbidity. Humans of any age either clinically diagnosed and/or currently receiving treatment for SMI, specified as schizophrenia (and related psychotic disorders), bipolar disorder and psychotic depression, were eligible. Data from studies selected for inclusion were converted into ORs, with a subsequent meta-analysis conducted.FindingsWe included 19 studies with a total of 194 123 patients with SMI with different diagnoses and drawn from the general population. The pooled OR for physical multimorbidity in people with versus without SMI was 1.84 (95% CI 1.33 to 2.54), with the analysis indicating a high level of heterogeneity (98.38%). The other 15 studies included in the systematic review for which it was not possible to conduct a meta-analysis showed strong associations between SMI and physical multimorbidity.ConclusionsThe current evidence highlights the link between SMI and physical multimorbidity. A multidisciplinary approach is now urgent to develop the best models of services tailored to patients with SMI with physical multimorbidities to improve physical, mental and social outcomes.PROSPERO registration numberCRD42023395165.

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Section: Resultsmentioning

confidence: 99%

“…This left 19 articles to be included in the systematic review. [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41] Descriptive data…”

Section: Literature Searchmentioning

confidence: 99%

Relationship between severe mental illness and physical multimorbidity: a meta-analysis and call for action

Pizzol,

Trott,

Butler

et al. 2023

BMJ Ment Health

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“…Read codes 45 were used to identify patients who had a pain diagnosis or were on any pain medications and treatments: 1. A pain medication code list developed as part of a project described in Ma et al 46 focused on analgesics (obtained from dm+d, a dictionary of medicines and devices 47 ) used in the treatment of 35 long-term conditions. These 35 conditions were obtained from Barnett et al, 48 a cross-sectional study on multimorbidities in patients registered with 314 medical practices in Scotland as of March 2007.…”

Section: Recorded Painmentioning

confidence: 99%

Distributions of recorded pain in mental health records: a natural language processing based study

Chaturvedi,

Stewart,

Ashworth

et al. 2024

BMJ Open

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ObjectiveThe objective of this study is to determine demographic and diagnostic distributions of physical pain recorded in clinical notes of a mental health electronic health records database by using natural language processing and examine the overlap in recorded physical pain between primary and secondary care.Design, setting and participantsThe data were extracted from an anonymised version of the electronic health records of a large secondary mental healthcare provider serving a catchment of 1.3 million residents in south London. These included patients under active referral, aged 18+ at the index date of 1 July 2018 and having at least one clinical document (≥30 characters) between 1 July 2017 and 1 July 2019. This cohort was compared with linked primary care records from one of the four local government areas.OutcomeThe primary outcome of interest was the presence of recorded physical pain within the clinical notes of the patients, not including psychological or metaphorical pain.ResultsA total of 27 211 patients were retrieved. Of these, 52% (14,202) had narrative text containing relevant mentions of physical pain. Older patients (OR 1.17, 95% CI 1.15 to 1.19), females (OR 1.42, 95% CI 1.35 to 1.49), Asians (OR 1.30, 95% CI 1.16 to 1.45) or black (OR 1.49, 95% CI 1.40 to 1.59) ethnicities, living in deprived neighbourhoods (OR 1.64, 95% CI 1.55 to 1.73) showed higher odds of recorded pain. Patients with severe mental illnesses were found to be less likely to report pain (OR 0.43, 95% CI 0.41 to 0.46, p<0.001). 17% of the cohort from secondary care also had records from primary care.ConclusionThe findings of this study show sociodemographic and diagnostic differences in recorded pain. Specifically, lower documentation across certain groups indicates the need for better screening protocols and training on recognising varied pain presentations. Additionally, targeting improved detection of pain for minority and disadvantaged groups by care providers can promote health equity.

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“…1. Pain medications code list -developed as part of a project described in [41], which focused on analgesics (obtained from dm+d (a dictionary of medicines and devices [42]) used in the treatment of 35 long-term conditions. These 35 conditions were obtained from [43], a cross-sectional study on multimorbidities in patients registered with 314 medical practices in Scotland as of March 2007.…”

Section: Recorded Painmentioning

confidence: 99%

Distributions of Recorded Pain in Mental Health Records: A Natural Language Processing Based Study

Chaturvedi,

Stewart,

Ashworth

et al. 2023

Preprint

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Objective The objective of this study is to determine demographic and diagnostic distributions of physical pain recorded in the clinical notes of a mental health electronic health records database by utilising natural language processing and to examine the level of overlap in recorded physical pain between primary and secondary care. Design, Setting and Participants The data were extracted from an anonymised version of the electronic health records from a large mental community and secondary healthcare provider serving a catchment of 1.3M residents in south London. These included patients under active referral and aged 18+ at the index date of July 1, 2018, and had at least one clinical document (>=30 characters) associated with their record between July 1, 2017 and July 1, 2019. This cohort was compared to linked primary care records from one of the four catchment boroughs. Outcome The primary outcome of interest was the presence or absence of recorded physical pain within the clinical notes of the patients. This does not include mental, psychological or metaphorical pain. Results A total of 27,211 patients were retrieved based on the extraction criteria. Of these, 52% (14,202) had narrative text containing relevant mentions of physical pain. Patients who were older (OR 1.17, 95% CI 1.15-1.19), female (OR 1.42, 95% CI 1.35-1.49), of Asian (OR 1.30, 95% CI 1.16-1.45) or Black (OR 1.49, 95% CI 1.40-1.59) ethnicities, and living in deprived neighbourhoods (OR 1.64, 95% CI 1.55-1.73) showed higher odds of recorded pain. Patients with an SMI diagnosis were found to be less likely to report pain (OR 0.43, 95% CI 0.41-0.46, p<0.001). When comparing the overlap between primary and secondary care, 17% of the CRIS cohort also had records within LDN, and 31% of these had recorded pain in both records. Conclusion The findings of this study show the sociodemographic and diagnostic differences in recorded pain, and have significant implications for the assessment and management of physical pain in patients with mental health disorders.

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Multimorbidity clusters among people with serious mental illness: a representative primary and secondary data linkage cohort study

Cited by 4 publications

References 84 publications

Relationship between severe mental illness and physical multimorbidity: a meta-analysis and call for action

Relationship between severe mental illness and physical multimorbidity: a meta-analysis and call for action

Distributions of recorded pain in mental health records: a natural language processing based study

Distributions of Recorded Pain in Mental Health Records: A Natural Language Processing Based Study

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