Polypharmacy in primary care: A population-based retrospective cohort study of electronic health records.

BACKGROUND: Polypharmacy, prescription of multiple medications to a patient, is a major challenge for health systems. There have been no peer-reviewed studies of polypharmacy prevalence and medication cost at a population level in England. AIMS: To determine prevalence and medication cost of polypharmacy, by patient characteristics. Design and setting: Retrospective cohort study of North West London electronic health records. METHOD: We quantified prevalence and direct cost of polypharmacy (five or more regular medications), stratified by demographics and frailty. We fitted a mixed-effects logistic regression for polypharmacy. RESULTS: Of 1.7 million adults, 167,665 (9.4%) were on polypharmacy. Age and socio-economic deprivation were associated with polypharmacy (OR 9.24 95% CI 8.99 to 9.50, age 65-74 compared with 18-44; OR 0.68 95% CI 0.65 to 0.71, least deprived compared with most). Polypharmacy prevalence increased with frailty (OR 1.53 95% CI 1.53 to 1.54 per frailty component, for White women). Men had higher odds of polypharmacy than women at average frailty (OR 1.26 95% CI 1.24 to 1.28) and with additional frailty components (OR 1.10 95% CI 1.09 to 1.10). Black people had lower odds of polypharmacy at average frailty (OR 0.82 95% CI 0.79 to 0.85, compared with White), but along with other ethnicities, saw greater odds increases with increasing frailty (OR 1.02 95% CI 1.01 to 1.03). Annual medication cost 8.2 times more for those on polypharmacy compared with not (£370.89 and £45.31). CONCLUSION: Demographic characteristics are associated with polypharmacy, after adjusting for frailty. Further research should explore why, to reduce health inequities and optimise cost associated with polypharmacy.

Uptake of COVID-19 vaccines and association with hospitalisation due to COVID-19 in pregnancy: Retrospective cohort study.

OBJECTIVES: To determine demographic and clinical characteristics associated with uptake of COVID-19 vaccines among pregnant women, and quantify the relationship between vaccine uptake and admission to hospital for COVID-19. BACKGROUND: Pregnant women are at increased risk of severe adverse outcomes from COVID-19. Since April 2021, COVID-19 vaccines were recommended for pregnant women in the UK. Despite this, evidence shows vaccine uptake is low. However, this evidence has been based only on women admitted to hospital, or on qualitative or survey-based studies. METHODS: Retrospective cohort study including all pregnancies ending between 18 June 2021 and 22 August 2022, among adult women registered with a Northwest London general practice. Statistical analyses were mixed-effects multiple logistic regression models. We conducted a nested case-control analysis to quantify the relationship between vaccine uptake by end of pregnancy and hospitalisation for COVID-19 during pregnancy. RESULTS: Our study included 47,046 pregnancies among 39,213 women. In 26,724 (57%) pregnancies, women had at least one dose of vaccine by the end of pregnancy. Uptake was lowest in pregnant women aged 18-24 (33%; reference group), Black women compared with White (37%; OR 0.55, 95% CI: 0.51 to 0.60), and women in more deprived areas (50%; reference group). Women with chronic conditions were more likely to receive the vaccine than women without (Asthma OR 1.21, 95% CI: 1.13 to 1.29). Patterns were similar for the second dose. Women admitted to hospital were much less likely to be vaccinated (22%) than those not admitted (57%, OR 0.22, 95% CI: 0.15 to 0.31). CONCLUSIONS: Women who received the COVID-19 vaccine were less likely to be hospitalised for COVID-19 during pregnancy. COVID-19 vaccine uptake among pregnant women is suboptimal, particularly in younger women, Black women, and women in more deprived areas. Interventions should focus on increasing uptake in these groups to improve health outcomes and reduce health inequalities.

Characteristics associated with influenza vaccination uptake in pregnancy: a retrospective cohort study.

BACKGROUND: Pregnant women are at increased risk from influenza, yet maternal influenza vaccination levels remain suboptimal. AIM: To estimate associations between sociodemographic and health characteristics and seasonal influenza vaccination uptake among pregnant women, and to understand trends over time to inform interventions to improve vaccine coverage. DESIGN AND SETTING: Retrospective cohort study using linked electronic health records of women in North West London with a pregnancy overlapping an influenza season between September 2010 and February 2020. METHOD: A multivariable mixed-effects logistic regression model was used to identify associations between characteristics of interest and the primary outcome of influenza vaccination. RESULTS: In total, 451 954 pregnancies, among 260 744 women, were included. In 85 376 (18.9%) pregnancies women were vaccinated against seasonal influenza. Uptake increased from 8.4% in 2010/11 to 26.4% in 2017/18, dropping again to 21.1% in 2019/20. Uptake was lowest among women aged 15-19 years (11.9%; reference category) or ≥40 years (15.2%; odds ratio [OR] 1.17, 95% confidence interval [CI] = 1.10 to 1.24); of Black (14.1%; OR 0.55, 95% CI = 0.53 to 0.57) or unknown ethnicity (9.9%; OR 0.42, 95% CI = 0.39 to 0.46); who lived in more deprived areas (OR least versus most deprived [reference category] 1.16, 95% CI = 1.11 to 1.21); or with no known risk factors for severe influenza. CONCLUSION: Seasonal influenza vaccine uptake in pregnant women increased in the decade before the COVID-19 pandemic, but remained suboptimal. Targeted approaches are recommended to reducing inequalities in access to vaccination and should focus on women of Black ethnicity, younger and older women, and women living in deprived areas.

Factors associated with accessing long-term adult social care in people aged 75 and over: a retrospective cohort study.

BACKGROUND: An ageing population and limited resources have put strain on state provision of adult social care (ASC) in England. With social care needs predicted to double over the next 20 years, there is a need for new approaches to inform service planning and development, including through predictive models of demand. OBJECTIVE: Describe risk factors for long-term ASC in two inner London boroughs and develop a risk prediction model for long-term ASC. METHODS: Pseudonymised person-level data from an integrated care dataset were analysed. We used multivariable logistic regression to model associations of demographic factors, and baseline aspects of health status and health service use, with accessing long-term ASC over 12 months. RESULTS: The cohort comprised 13,394 residents, aged ≥75 years with no prior history of ASC at baseline. Of these, 1.7% became ASC clients over 12 months. Residents were more likely to access ASC if they were older or living in areas with high socioeconomic deprivation. Those with preexisting mental health or neurological conditions, or more intense prior health service use during the baseline period, were also more likely to access ASC. A prognostic model derived from risk factors had limited predictive power. CONCLUSIONS: Our findings reinforce evidence on known risk factors for residents aged 75 or over, yet even with linked routinely collected health and social care data, it was not possible to make accurate predictions of long-term ASC use for individuals. We propose that a paradigm shift towards more relational, personalised approaches, is needed.