Clustering by multiple long-term conditions and social care needs: a cross-sectional study among 10 026 older adults in England.

BACKGROUND   : People with multiple long-term conditions (MLTC) face health and social care challenges. This study aimed to classify people by MLTC and social care needs (SCN) into distinct clusters and quantify the association between derived clusters and care outcomes. METHODS : A cross-sectional study was conducted using the English Longitudinal Study of Ageing, including people with up to 10 MLTC. Self-reported SCN was assessed through 13 measures of difficulty with activities of daily living, 10 measures of mobility difficulties and whether health status was limiting earning capability. Latent class analysis was performed to identify clusters. Multivariable logistic regression quantified associations between derived MLTC/SCN clusters, all-cause mortality and nursing home admission. RESULTS: Our study included 9171 people at baseline with a mean age of 66.3 years; 44.5% were men. Nearly 70.8% had two or more MLTC, the most frequent being hypertension, arthritis and cardiovascular disease. We identified five distinct clusters classified as high SCN/MLTC through to low SCN/MLTC clusters. The high SCN/MLTC included mainly women aged 70-79 years who were white and educated to the upper secondary level. This cluster was significantly associated with higher nursing home admission (OR=8.71; 95% CI: 4.22 to 18). We found no association between clusters and all-cause mortality. CONCLUSIONS: We have highlighted those at risk of worse care outcomes, including nursing home admission. Distinct clusters of individuals with shared sociodemographic characteristics can help identify at-risk individuals with MLTC and SCN at primary care level

Exploring patient views of empathic optimistic communication for osteoarthritis in primary care: A qualitative interview study using vignettes

BACKGROUND: Osteoarthritis (OA) causes pain and disability. An empathic optimistic consultation approach can improve patient quality of life, satisfaction with care, and reduce pain. However, expressing empathic optimism may be overlooked in busy primary care consultations and there is limited understanding of patients' views about this approach. AIM: To explore patients' perspectives on clinician communication of empathy and optimism in primary care OA consultations. DESIGN & SETTING: Vignette study with qualitative semi-structured interviews. SETTING: Purposefully sampled patients (n=33) aged 45+ with hip/knee OA from Wessex GP practices. METHOD: Fifteen participants watched two filmed OA consultations with a GP, and eighteen participants read two case vignettes. In both formats, one GP depicted an empathic optimistic approach and one GP had a 'neutral' approach. Semi-structured interviews were conducted with all participants and analysed using thematic analysis. RESULTS: Patients recognised that empathic communication enhanced interactions, helping to engender a sense of trust in their clinician. They felt it was acceptable for GPs to convey optimism only if it was realistic, personalised and embedded within an empathic consultation. Discussing patients' experiences and views with them, and conveying an accurate understanding of these experiences improves the credibility of optimistic messages. CONCLUSION: Patients value communication with empathy and optimism, but it requires a fine balance to ensure messages remain realistic and trustworthy. Increased use of a realistic optimistic approach within an empathic consultation could enhance consultations for OA and other chronic conditions, and improve patient outcomes. Digital training to help GPs implement these findings is being developed

Understanding social care need through primary care big data: a rapid scoping review

Background A more comprehensive understanding and measurement of adult social care need could contribute to efforts to develop more effective, holistic personalised care, particularly for those with Multiple Long Term Conditions. Progress in this area faces the challenge of a lack of clarity in the literature relating to how social care need is assessed and coded within variables included in primary care databases. Aim To explore how social care need is assessed and coded within variables included in primary care databases. Design & setting An exploratory rapid scoping review of peer-reviewed articles and grey literature. Method Articles were screened and extracted onto a charting sheet and findings were summarised descriptively. Articles were included if published in English, related to primary care and social care using data from national primary care databases. Results The search yielded 4,010 articles. Twenty-seven were included. Six articles used the term ‘social care need’, although related terminology was identified including ‘need factors’, ‘social support’ and ‘social care support’. Articles mainly focused on specific components of social care need, including levels of social care usage/service utilisation and costs incurred to social care, primary care and other providers in addressing needs. A limited range of database variables were found measuring social care need. Conclusion Further research is needed on how social care need has been defined in a UK context and captured in primary care big databases. There is potential scope to broaden the definition of social care need, which captures social service needs and wider social needs

Association between race and COVID-19 outcomes among 2.6 million children in England

Importance Although children mainly experience mild COVID-19 disease, hospitalization rates are increasing, with limited understanding of underlying factors. There is an established association between race and severe COVID-19 outcomes in adults in England; however, whether a similar association exists in children is unclear. Objective To investigate the association between race and childhood COVID-19 testing and hospital outcomes. Design, Setting, Participants In this cohort study, children (0-18 years of age) from participating family practices in England were identified in the QResearch database between January 24 and November 30, 2020. The QResearch database has individually linked patients with national SARS-CoV-2 testing, hospital admission, and mortality data. Exposures The main characteristic of interest is self-reported race. Other exposures were age, sex, deprivation level, geographic region, household size, and comorbidities (asthma; diabetes; and cardiac, neurologic, and hematologic conditions). Main Outcomes and Measures The primary outcome was hospital admission with confirmed COVID-19. Secondary outcomes were SARS-CoV-2–positive test result and any hospital attendance with confirmed COVID-19 and intensive care admission. Results Of 2 576 353 children (mean [SD] age, 9.23 [5.24] years; 48.8% female), 410 726 (15.9%) were tested for SARS-CoV-2 and 26 322 (6.4%) tested positive. A total of 1853 children (0.07%) with confirmed COVID-19 attended hospital, 343 (0.01%) were admitted to the hospital, and 73 (0.002%) required intensive care. Testing varied across race. White children had the highest proportion of SARS-CoV-2 tests (223 701/1 311 041 [17.1%]), whereas Asian children (33 213/243 545 [13.6%]), Black children (7727/93 620 [8.3%]), and children of mixed or other races (18 971/147 529 [12.9%]) had lower proportions. Compared with White children, Asian children were more likely to have COVID-19 hospital admissions (adjusted odds ratio [OR], 1.62; 95% CI, 1.12-2.36), whereas Black children (adjusted OR, 1.44; 95% CI, 0.90-2.31) and children of mixed or other races (adjusted OR, 1.40; 95% CI, 0.93-2.10) had comparable hospital admissions. Asian children were more likely to be admitted to intensive care (adjusted OR, 2.11; 95% CI, 1.07-4.14), and Black children (adjusted OR, 2.31; 95% CI, 1.08-4.94) and children of mixed or other races (adjusted OR, 2.14; 95% CI, 1.25-3.65) had longer hospital admissions (≥36 hours). Conclusions and Relevance In this large population-based study exploring the association between race and childhood COVID-19 testing and hospital outcomes, several race-specific disparities were observed in severe COVID-19 outcomes. However, ascertainment bias and residual confounding in this cohort study should be considered before drawing any further conclusions. Overall, findings of this study have important public health implications internationally

Using Primary Care Data to Report Real-World Pancreatic Cancer Survival and Symptomatology.

Pancreatic cancer is the 10th most common cancer diagnosed; despite recent advances in many areas of oncology, survival remains poor, in part owing to late diagnosis. Whilst primary care data are used widely for epidemiology and pharmacovigilance, they are less used for observing survival. In this study we extracted a pancreatic cancer cohort from a nationally representative English primary care database of electronic health records (EHRs) and reported on their symptom and mortality data. A total of 11, 649 cases were identified within the Oxford Royal College of General Practitioners (RCGP) Clinical Informatics Digital Hub network. All-cause mortality data was recorded for 4623 (39.69%). Mean age at recording of cancer diagnosis was 71.4 years (SD 12.0 years). 1-year and 5-year survival was 22.06% and 3.27% respectively. Within a multivariate model, age had a significant impact on survival; those diagnosed under the age of 60 had the longest survival, as compared to those age 60 - 79 (HR: 1.36, 95% CI: 1.20 - 1.54, p < 0.001) and 80+ (HR: 2.13, 95% CI: 1.86 - 2.44, p < 0.01). Symptomatology was examined; at any time point abdominal pain was the most commonly reported symptom present in 5271 cases (45.2%), but within the 12 months preceding diagnosis jaundice was the most common feature, present in 2587 patients (22.2%). Future studies clarifying other contributing factors on survival outcomes and patterns of symptomatology are needed; primary care EHRs provide an opportunity to evaluate real-world cancer patient cohort data