Inequalities in cancer screening participation between adults with and without severe mental illness: results from a cross-sectional analysis of primary care data on English Screening Programmes.

BACKGROUND: People with severe mental illness (SMI) are 2.5 times more likely to die prematurely from cancer in England. Lower participation in screening may be a contributing factor. METHODS: Clinical Practice Research Datalink data for 1.71 million, 1.34 million and 2.50 million adults were assessed (using multivariate logistic regression) for possible associations between SMI and participation in bowel, breast and cervical screening, respectively. RESULTS: Screening participation was lower among adults with SMI, than without, for bowel (42.11% vs. 58.89%), breast (48.33% vs. 60.44%) and cervical screening (64.15% vs. 69.72%; all p < 0.001). Participation was lowest in those with schizophrenia (bowel, breast, cervical: 33.50%, 42.02%, 54.88%), then other psychoses (41.97%, 45.57%, 61.98%), then bipolar disorder (49.94%, 54.35%, 69.69%; all p-values < 0.001, except cervical screening in bipolar disorder; p-value > 0.05). Participation was lowest among people with SMI who live in the most deprived quintile of areas (bowel, breast, cervical: 36.17%, 40.23%, 61.47%), or are of a Black ethnicity (34.68%, 38.68%, 64.80%). Higher levels of deprivation and diversity, associated with SMI, did not explain the lower participation in screening. CONCLUSIONS: In England, participation in cancer screening is low among people with SMI. Support should be targeted to ethnically diverse and socioeconomically deprived areas, where SMI prevalence is greatest.

The incidence rate of planned and emergency physical health hospital admissions in people diagnosed with severe mental illness: a cohort study.

BACKGROUND: People with severe mental illness (SMI) have more physical health conditions than the general population, resulting in higher rates of hospitalisations and mortality. In this study, we aimed to determine the rate of emergency and planned physical health hospitalisations in those with SMI, compared to matched comparators, and to investigate how these rates differ by SMI diagnosis. METHODS: We used Clinical Practice Research DataLink Gold and Aurum databases to identify 20,668 patients in England diagnosed with SMI between January 2000 and March 2016, with linked hospital records in Hospital Episode Statistics. Patients were matched with up to four patients without SMI. Primary outcomes were emergency and planned physical health admissions. Avoidable (ambulatory care sensitive) admissions and emergency admissions for accidents, injuries and substance misuse were secondary outcomes. We performed negative binomial regression, adjusted for clinical and demographic variables, stratified by SMI diagnosis. RESULTS: Emergency physical health (aIRR:2.33; 95% CI 2.22-2.46) and avoidable (aIRR:2.88; 95% CI 2.60-3.19) admissions were higher in patients with SMI than comparators. Emergency admission rates did not differ by SMI diagnosis. Planned physical health admissions were lower in schizophrenia (aIRR:0.80; 95% CI 0.72-0.90) and higher in bipolar disorder (aIRR:1.33; 95% CI 1.24-1.43). Accident, injury and substance misuse emergency admissions were particularly high in the year after SMI diagnosis (aIRR: 6.18; 95% CI 5.46-6.98). CONCLUSION: We found twice the incidence of emergency physical health admissions in patients with SMI compared to those without SMI. Avoidable admissions were particularly elevated, suggesting interventions in community settings could reduce hospitalisations. Importantly, we found underutilisation of planned inpatient care in patients with schizophrenia. Interventions are required to ensure appropriate healthcare use, and optimal diagnosis and treatment of physical health conditions in people with SMI, to reduce the mortality gap due to physical illness.

The impact of comorbid severe mental illness and common chronic physical health conditions on hospitalisation: A systematic review and meta-analysis.

BACKGROUND: People with severe mental illness (SMI) are at higher risk of physical health conditions compared to the general population, however, the impact of specific underlying health conditions on the use of secondary care by people with SMI is unknown. We investigated hospital use in people managed in the community with SMI and five common physical long-term conditions: cardiovascular diseases, COPD, cancers, diabetes and liver disease. METHODS: We performed a systematic review and meta-analysis (Prospero: CRD42020176251) using terms for SMI, physical health conditions and hospitalisation. We included observational studies in adults under the age of 75 with a diagnosis of SMI who were managed in the community and had one of the physical conditions of interest. The primary outcomes were hospital use for all causes, physical health causes and related to the physical condition under study. We performed random-effects meta-analyses, stratified by physical condition. RESULTS: We identified 5,129 studies, of which 50 were included: focusing on diabetes (n = 21), cardiovascular disease (n = 19), COPD (n = 4), cancer (n = 3), liver disease (n = 1), and multiple physical health conditions (n = 2). The pooled odds ratio (pOR) of any hospital use in patients with diabetes and SMI was 1.28 (95%CI:1.15-1.44) compared to patients with diabetes alone and pooled hazard ratio was 1.19 (95%CI:1.08-1.31). The risk of 30-day readmissions was raised in patients with SMI and diabetes (pOR: 1.18, 95%CI:1.08-1.29), SMI and cardiovascular disease (pOR: 1.27, 95%CI:1.06-1.53) and SMI and COPD (pOR:1.18, 95%CI: 1.14-1.22) compared to patients with those conditions but no SMI. CONCLUSION: People with SMI and five physical conditions are at higher risk of hospitalisation compared to people with that physical condition alone. Further research is warranted into the combined effects of SMI and physical conditions on longer-term hospital use to better target interventions aimed at reducing inappropriate hospital use and improving disease management and outcomes.

Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data.

BACKGROUND: People with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI. METHODS AND FINDINGS: We performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; while 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions. CONCLUSIONS: In this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.