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BackgroundThere has been growing international interest in performing remote consultations in primary care, particularly amidst the current COVID-19 pandemic. Despite this, the evidence surrounding the safety of remote consultations is inconclusive. The appropriateness of antibiotic prescribing in remote consultations is an important aspect of patient safety that needs to be addressed. ObjectiveThis study aimed to summarize evidence on the impact of remote consultation in primary care with regard to antibiotic prescribing. MethodsSearches were conducted in MEDLINE, Embase, HMIC, PsycINFO, and CINAHL for literature published since the databases’ inception to February 2020. Peer-reviewed studies conducted in primary health care settings were included. All remote consultation types were considered, and studies were required to report any quantitative measure of antibiotic prescribing to be included in this systematic review. Studies were excluded if there were no comparison groups (face-to-face consultations). ResultsIn total, 12 studies were identified. Of these, 4 studies reported higher antibiotic-prescribing rates, 5 studies reported lower antibiotic-prescribing rates, and 3 studies reported similar antibiotic-prescribing rates in remote consultations compared with face-to-face consultations. Guideline-concordant prescribing was not significantly different between remote and face-to-face consultations for patients with sinusitis, but conflicting results were found for patients with acute respiratory infections. Mixed evidence was found for follow-up visit rates after remote and face-to-face consultations. ConclusionsThere is insufficient evidence to confidently conclude that remote consulting has a significant impact on antibiotic prescribing in primary care. However, studies indicating higher prescribing rates in remote consultations than in face-to-face consultations are a concern. Further, well-conducted studies are needed to inform safe and appropriate implementation of remote consulting to ensure that there is no unintended impact on antimicrobial resistance.

BackgroundTobacco smoking remains the leading cause of preventable death and disease worldwide. Digital interventions delivered through smartphones offer a promising alternative to traditional methods, but little is known about their effectiveness. ObjectiveOur objective was to test the preliminary effectiveness of Quit Genius, a novel digital therapeutic intervention for smoking cessation. MethodsA 2-arm, single-blinded, parallel-group randomized controlled trial design was used. Participants were recruited via referrals from primary care practices and social media advertisements in the United Kingdom. A total of 556 adult smokers (aged 18 years or older) smoking at least 5 cigarettes a day for the past year were recruited. Of these, 530 were included for the final analysis. Participants were randomized to one of 2 interventions. Treatment consisted of a digital therapeutic intervention for smoking cessation consisting of a smartphone app delivering cognitive behavioral therapy content, one-to-one coaching, craving tools, and tracking capabilities. The control intervention was very brief advice along the Ask, Advise, Act model. All participants were offered nicotine replacement therapy for 3 months. Participants in a random half of each arm were pseudorandomly assigned a carbon monoxide device for biochemical verification. Outcomes were self-reported via phone or online. The primary outcome was self-reported 7-day point prevalence abstinence at 4 weeks post quit date. ResultsA total of 556 participants were randomized (treatment: n=277; control: n=279). The intention-to-treat analysis included 530 participants (n=265 in each arm; 11 excluded for randomization before trial registration and 15 for protocol violations at baseline visit). By the quit date (an average of 16 days after randomization), 89.1% (236/265) of those in the treatment arm were still actively engaged. At the time of the primary outcome, 74.0% (196/265) of participants were still engaging with the app. At 4 weeks post quit date, 44.5% (118/265) of participants in the treatment arm had not smoked in the preceding 7 days compared with 28.7% (76/265) in the control group (risk ratio 1.55, 95% CI 1.23-1.96; P

BackgroundGlobal trends in cardiovascular disease (CVD) exhibit considerable interregional and interethnic differences, which in turn affect long-term CVD risk across diverse populations. An in-depth understanding of the interplay between ethnicity, socioeconomic status, and CVD risk factors and mortality in a contemporaneous population is crucial to informing health policy and resource allocation aimed at mitigating long-term CVD risk. Generating bespoke large-scale and reliable data with sufficient numbers of events is expensive and time-consuming but can be circumvented through utilization and linkage of data routinely collected in electronic health records (EHR). ObjectiveWe aimed to characterize the burden of CVD risk factors across different ethnicities, age groups, and socioeconomic groups, and study CVD incidence and mortality by EHR linkage in London. MethodsThe proposed study will initially be a cross-sectional observational study unfolding into prospective CVD ascertainment through longitudinal follow-up involving linked data. The government-funded National Health System (NHS) Health Check program provides an opportunity for the systematic collation of CVD risk factors on a large scale. NHS Health Check data on approximately 200,000 individuals will be extracted from consenting general practices across London that use the Egton Medical Information Systems (EMIS) EHR software. Data will be analyzed using appropriate statistical techniques to (1) determine the cross-sectional burden of CVD risk factors and their prospective association with CVD outcomes, (2) validate existing prediction tools in diverse populations, and (3) develop bespoke risk prediction tools across diverse ethnic groups. ResultsEnrollment began in January 2019 and is ongoing with initial results to be published mid-2021. ConclusionsThere is an urgent need for more real-life population health studies based on analyses of routine health data available in EHRs. Findings from our study will help quantify, on a large scale, the contemporaneous burden of CVD risk factors by geography and ethnicity in a large multiethnic urban population. Such detailed understanding (especially interethnic and sociodemographic variations) of the burden of CVD risk and its determinants, including heredity, environment, diet, lifestyle, and socioeconomic factors, in a large population sample, will enable the development of tailored and dynamic (continuously learning from new data) risk prediction tools for diverse ethnic groups, and thereby enable the personalized provision of prevention strategies and care. We anticipate that this systematic approach of linking routinely collected data from EHRs to study CVD can be conducted in other settings as EHRs are being implemented worldwide. International Registered Report Identifier (IRRID)PRR1-10.2196/17548