Antibiotic prescribing in remote versus face-to-face consultations for acute respiratory infections in primary care in England: an observational study using target maximum likelihood estimation.

Background: The COVID-19 pandemic has led to an ongoing increase in the use of remote consultations in general practice in England. Although the evidence is limited, there are concerns that the increase in remote consultations could lead to more antibiotic prescribing. Methods: In this cohort study, we used patient-level primary care data from the Clinical Practice Research Datalink to estimate the association between consultation mode (remote versus face-to-face) and antibiotic prescribing in England for acute respiratory infections (ARI) between April 2021 and March 2022. Eligibility criteria were applied at both practice-level and patient-level. 400 practices in England were sampled at random and then 600,000 patients were randomly sampled from the eligible patients (whose sex was recorded). Consultations for acute respiratory infections were identified. All antibiotic prescriptions were included, with the exception of antituberculosis drugs and antileprotic drugs, as identified through chapter 5.1 of the British National Formulary. The CPRD Aurum data was linked to the COVID-19 ONS infection survey by region. All analyses were done at the individual level. Repeated consultations from the same patient within 7 days were grouped together. We used targeted maximum likelihood estimation, a causal machine learning method with adjustment for infection type and patient-level, clinician-level and practice-level factors. Findings: There were 45,997 ARI consultations (34,555 unique patients) within the study period, of which 28,127 were remote and 17,870 were face-to-face. For children, 48% of consultations were remote and, for adults, 66% were remote. For children, 42% of remote and 43% of face-to-face consultations led to an antibiotic prescription; the equivalent values for adults were 52% and 42%, respectively. After adjustment with TMLE, adults with a remote consultation had 23% (odds ratio [OR] 1.23, 95% CI: 1.18-1.29) higher chance of being prescribed antibiotics than if they had been seen face-to-face. We found no significant association between consultation mode and antibiotic prescribing in children (OR 1.04 95% CI: 0.98-1.11). Interpretation: The higher rates of antibiotic prescribing in remote consultations for adults are cause for concern. We see no significant difference in antibiotic prescribing between consultation mode for children. These findings should inform antimicrobial stewardship activities for health-care professionals and policy makers. Future research should examine differences in guideline-compliance between remote and face-to-face consultations to understand the factors driving antibiotic prescribing in different consultation modes. Funding: None.

Consultation Rate and Mode by Deprivation in English General Practice From 2018 to 2022: Population-Based Study.

BACKGROUND: The COVID-19 pandemic has had a significant impact on primary care service delivery with an increased use of remote consultations. With general practice delivering record numbers of appointments and rising concerns around access, funding, and staffing in the UK National Health Service, we assessed contemporary trends in consultation rate and modes (ie, face-to-face versus remote). OBJECTIVE: This paper describes trends in consultation rates in general practice in England for key demographics before and during the COVID-19 pandemic. We explore the use of remote and face-to-face consultations with regard to socioeconomic deprivation to understand the possible effect of changes in consultation modes on health inequalities. METHODS: We did a retrospective analysis of 9,429,919 consultations by general practitioners, nurses, or other health care professionals between March 2018 and February 2022 for patients registered at 397 general practices in England. We used routine electronic health records from Clinical Practice Research Datalink Aurum with linkage to national data sets. Negative binomial models were used to predict consultation rates and modes (ie, remote versus face-to-face) by age, sex, and socioeconomic deprivation over time. RESULTS: Overall consultation rates increased by 15% from 4.92 in 2018-2019 to 5.66 in 2021-2022 with some fluctuation during the start of the COVID-19 pandemic. The breakdown into face-to-face and remote consultations shows that the pandemic precipitated a rapid increase in remote consultations across all groups, but the extent varies by age. Consultation rates increased with increasing levels of deprivation. Socioeconomic differences in consultation rates, adjusted for sex and age, halved during the pandemic (from 0.36 to 0.18, indicating more consultations in the most deprived), effectively narrowing relative differences between deprivation quintiles. This trend remains when stratified by sex, but the difference across deprivation quintiles is smaller for men. The most deprived saw a relatively larger increase in remote and decrease in face-to-face consultation rates compared to the least deprived. CONCLUSIONS: The substantial increases in consultation rates observed in this study imply an increased pressure on general practice. The narrowing of consultation rates between deprivation quintiles is cause for concern, given ample evidence that health needs are greater in more deprived areas.

Piloting of a minimum data set for older people living in care homes in England: protocol for a longitudinal, mixed-methods study.

INTRODUCTION: Health and care data are routinely collected about care home residents in England, yet there is no way to collate these data to inform benchmarking and improvement. The Developing research resources And minimum data set for Care Homes' Adoption and use study has developed a prototype minimum data set (MDS) for piloting. METHODS AND ANALYSIS: A mixed-methods longitudinal pilot study will be conducted in 60 care homes (approximately 960 residents) in 3 regions of England, using resident data from cloud-based digital care home records at two-time points. These will be linked to resident and care home level data held within routine National Health Service and social care data sets. Two rounds of focus groups with care home staff (n=8-10 per region) and additional interviews with external stakeholders (n=3 per region) will explore implementation and the perceived utility of the MDS. Data will be assessed for completeness and timeliness of completion. Descriptive statistics, including percentage floor and ceiling effects, will establish data quality. For validated scales, construct validity will be assessed by hypothesis testing and exploratory factor analysis will establish structural validity. Internal consistency will be established using Cronbach's alpha. Longitudinal analysis of the pilot data will demonstrate the value of the MDS to each region. Qualitative data will be analysed inductively using thematic analysis to understand the complexities of implementing an MDS in care homes for older people. ETHICS AND DISSEMINATION: The study has received ethical approval from the London Queen's Square Research Ethics Committee (22/LO/0250). Informed consent is required for participation. Findings will be disseminated to: academics working on data use and integration in social care, care sector organisations, policy makers and commissioners. Findings will be published in peer-reviewed journals. Partner NIHR Applied Research Collaborations, the National Care Forum and the British Geriatrics Society will disseminate policy briefs.

A Comparison of Ordered Categorical versus Discrete Choices within a Stated Preference Survey of Whole-Blood Donors.

HIGHLIGHTS: This article compares the relative preferences from stated preference (SP) questions requiring ordered categorical versus discrete choice responses. The approaches were contrasted for blood donation service characteristics that offer opportunities to donate blood.The estimates of relative preferences for alternative blood donation service characteristics were similar between the 2 forms of SP approach.This study illustrates how SP survey questions can be formulated to provide responses on an ordered categorical scale and to estimate marginal rates of substitution between different attributes, which can be compared with those derived from discrete choice experiment (DCE) choices.The article highlights the potential value of considering alternative choice framings rather than relying solely on DCEs.

Stated versus revealed preferences: An approach to reduce bias.

Stated preference (SP) survey responses may not predict actual behavior, leading to hypothetical bias. We developed an approach that harnesses large-scale routine data to help SP surveys provide more accurate estimates of revealed preferences (RPs), within a study which elicited preferences for alternative changes to the blood service in England. The SP survey responses were used to predict the mean number of annual whole blood donations. Ex ante, the iterative survey design estimated hypothetical bias by contrasting pilot SP survey responses (N = 1254), with individually linked data on RPs, to inform the main SP survey design (N = 25,187). Ex post, the analysis recognized mediation of the relationship between SP and RP when blood donation is deferred. The pilot survey reported that donors' intended donation frequency of 3.2 (men) and 2.6 (women) times per year, exceeded their actual frequency by 41% and 30% respectively. Choice scenario attributes for the main SP survey were then modified, and over-prediction subsequently decreased to 34% for men and 16% for women. The mediating effect of deferrals explained 29% (men) and 86% (women) of the residual discrepancy between SP and RP. Future studies can use this approach to reduce hypothetical bias, and provide more accurate predictions for decision-making.