Does a screening checklist for complex health and social care needs have potential clinical usefulness for predicting unplanned hospital readmissions in intensive care survivors: development and prospective cohort study.

OBJECTIVES: Intensive care (ICU) survivors are at high risk of long-term physical and psychosocial problems. Unplanned hospital readmission rates are high, but the best way to triage patients for interventions is uncertain. We aimed to develop and evaluate a screening checklist to help predict subsequent readmissions or deaths. DESIGN: A checklist for complex health and social care needs (CHSCNs) was developed based on previous research, comprising six items: multimorbidity; polypharmacy; frequent previous hospitalisations; mental health issues; fragile social circumstances and impaired activities of daily living. Patients were considered to have CHSCNs if two or more were present. We prospectively screened all ICU discharges for CHSCNs for 12 months. SETTING: ICU, Royal Infirmary, Edinburgh, UK. PARTICIPANTS: ICU survivors over a 12-month period (1 June 2018 and 31 May 2019). INTERVENTIONS: None. OUTCOME MEASURE: Readmission or death in the community within 3 months postindex hospital discharge. RESULTS: Of 1174 ICU survivors, 937 were discharged alive from the hospital. Of these 253 (27%) were classified as having CHSCNs. In total 28% (266/937) patients were readmitted (N=238) or died (N=28) within 3 months. Among CHSCNs patients 45% (n=115) patients were readmitted (N=105) or died (N=10). Patients without CHSCNs had a 22% readmission (N=133) or death (N=18) rate. The checklist had: sensitivity 43% (95% CI 37% to 49%), specificity 79% (95% CI 76% to 82%), positive predictive value 45% (95% CI 41% to 51%), and negative predictive value 78% (95% CI 76% to 80%). Relative risk of readmission/death for patients with CHSCNs was 2.06 (95% CI 1.69 to 2.50), indicating a pretest to post-test probability change of 28%-45%. The checklist demonstrated high inter-rater reliability (percentage agreement ≥87% for all domains; overall kappa, 0.84). CONCLUSIONS: Early evaluation of a screening checklist for CHSCNs at ICU discharge suggests potential clinical usefulness, but this requires further evaluation as part of a care pathway.

Ethnic and social inequalities in COVID-19 outcomes in Scotland: protocol for early pandemic evaluation and enhanced surveillance of COVID-19 (EAVE II).

INTRODUCTION: Evidence from previous pandemics, and the current COVID-19 pandemic, has found that risk of infection/severity of disease is disproportionately higher for ethnic minority groups, and those in lower socioeconomic positions. It is imperative that interventions to prevent the spread of COVID-19 are targeted towards high-risk populations. We will investigate the associations between social characteristics (such as ethnicity, occupation and socioeconomic position) and COVID-19 outcomes and the extent to which characteristics/risk factors might explain observed relationships in Scotland.The primary objective of this study is to describe the epidemiology of COVID-19 by social factors. Secondary objectives are to (1) examine receipt of treatment and prevention of COVID-19 by social factors; (2) quantify ethnic/social differences in adverse COVID-19 outcomes; (3) explore potential mediators of relationships between social factors and SARS-CoV-2 infection/COVID-19 prognosis; (4) examine whether occupational COVID-19 differences differ by other social factors and (5) assess quality of ethnicity coding within National Health Service datasets. METHODS AND ANALYSIS: We will use a national cohort comprising the adult population of Scotland who completed the 2011 Census and were living in Scotland on 31 March 2020 (~4.3 million people). Census data will be linked to the Early Assessment of Vaccine and Anti-Viral Effectiveness II cohort consisting of primary/secondary care, laboratory data and death records. Sensitivity/specificity and positive/negative predictive values will be used to assess coding quality of ethnicity. Descriptive statistics will be used to examine differences in treatment and prevention of COVID-19. Poisson/Cox regression analyses and mediation techniques will examine ethnic and social differences, and drivers of inequalities in COVID-19. Effect modification (on additive and multiplicative scales) between key variables (such as ethnicity and occupation) will be assessed. ETHICS AND DISSEMINATION: Ethical approval was obtained from the National Research Ethics Committee, South East Scotland 02. We will present findings of this study at international conferences, in peer-reviewed journals and to policy-makers.