Use of routine healthcare data in randomised implementation trials: a methodological mixed-methods systematic review.

BACKGROUND: Routine data are increasingly used in randomised controlled trials evaluating healthcare interventions. They can aid participant identification, outcome assessment, and intervention delivery. Randomised implementation trials evaluate the effect of implementation strategies on implementation outcomes. Implementation strategies, such as reminders, are used to increase the uptake of evidence-based interventions into practice, while implementation outcomes, such as adoption, are key measures of the implementation process. The use of routine data in effectiveness trials has been explored; however, there are no reviews on implementation trials. We therefore aimed to describe how routine data have been used in randomised implementation trials and the design characteristics of these trials. METHODS: We searched MEDLINE (Ovid) and Cochrane Central Register of Controlled Trials from Jan 2000 to Dec 2021 and manually searched protocols from trial registers. We included implementation trials and type II and type III hybrid effectiveness-implementation trials conducted using routine data. We extracted quantitative and qualitative data and narratively synthesised findings. RESULTS: From 4206 titles, we included 80 trials, of which 22.5% targeted implementation of evidence-based clinical guidelines. Multicomponent implementation strategies were more commonly evaluated (70.0%) than single strategies. Most trials assessed adoption as the primary outcome (65.0%). The majority of trials extracted data from electronic health records (EHRs) (62.5%), and 91.3% used routine data for outcome ascertainment. Reported reasons for using routine data were increasing efficiency, assessing outcomes, reducing research burden, improving quality of care, identifying study samples, confirming findings, and assessing representativeness. Data quality, the EHR system, research governance, and external factors such as government policy could act either as facilitators or barriers. CONCLUSIONS: Adherence to guidance on designing and reporting implementation studies, and specifically to harmonise the language used in describing implementation strategies and implementation outcomes, would aid identification of studies and data extraction. Routine healthcare data are widely used for participant identification, outcome assessment and intervention delivery. Researchers should familiarise themselves with the barriers and facilitators to using routine data, and efforts could be made to improve data quality to overcome some of the barriers. REGISTRATION: PROSPERO CRD42022292321.

The Impact of Point-of-Care Testing for Influenza on Antimicrobial Stewardship (PIAMS) in UK Primary Care: Protocol for a Mixed Methods Study.

BACKGROUND: Molecular point-of-care testing (POCT) used in primary care can inform whether a patient presenting with an acute respiratory infection has influenza. A confirmed clinical diagnosis, particularly early in the disease, could inform better antimicrobial stewardship. Social distancing and lockdowns during the COVID-19 pandemic have disturbed previous patterns of influenza infections in 2021. However, data from samples taken in the last quarter of 2022 suggest that influenza represents 36% of sentinel network positive virology, compared with 24% for respiratory syncytial virus. Problems with integration into the clinical workflow is a known barrier to incorporating technology into routine care. OBJECTIVE: This study aims to report the impact of POCT for influenza on antimicrobial prescribing in primary care. We will additionally describe severe outcomes of infection (hospitalization and mortality) and how POCT is integrated into primary care workflows. METHODS: The impact of POCT for influenza on antimicrobial stewardship (PIAMS) in UK primary care is an observational study being conducted between December 2022 and May 2023 and involving 10 practices that contribute data to the English sentinel network. Up to 1000 people who present to participating practices with respiratory symptoms will be swabbed and tested with a rapid molecular POCT analyzer in the practice. Antimicrobial prescribing and other study outcomes will be collected by linking information from the POCT analyzer with data from the patient's computerized medical record. We will collect data on how POCT is incorporated into practice using data flow diagrams, unified modeling language use case diagrams, and Business Process Modeling Notation. RESULTS: We will present the crude and adjusted odds of antimicrobial prescribing (all antibiotics and antivirals) given a POCT diagnosis of influenza, stratifying by whether individuals have a respiratory or other relevant diagnosis (eg, bronchiectasis). We will also present the rates of hospital referrals and deaths related to influenza infection in PIAMS study practices compared with a set of matched practices in the sentinel network and the rest of the network. We will describe any difference in implementation models in terms of staff involved and workflow. CONCLUSIONS: This study will generate data on the impact of POCT testing for influenza in primary care as well as help to inform about the feasibility of incorporating POCT into primary care workflows. It will inform the design of future larger studies about the effectiveness and cost-effectiveness of POCT to improve antimicrobial stewardship and any impact on severe outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46938.

Dual antithrombotic therapy and gastroprotection in atrial fibrillation: an observational primary care study.

BACKGROUND: Patients with both atrial fibrillation (AF) and cardiovascular disease (CVD) may receive dual antithrombotic therapy (DAT) with both an anticoagulant and ≥1 antiplatelet agents. Avoiding prolonged duration of DAT and use of gastroprotective therapies reduces bleeding risk. AIM: To describe the extent and duration of DAT and use of gastroprotection in a primary care cohort of patients with AF. DESIGN & SETTING: Observational study in 1.2 million people registered with GPs across four east London clinical commissioning groups (CCGs), covering prescribing from January 2020-June 2021. METHOD: In patients with AF, factors associated with DAT prescription, prolonged DAT prescription (>12 months), and gastroprotective prescription were characterised using logistic regression. RESULTS: There were 8881 patients with AF, of whom 4.7% (n = 416) were on DAT. Of these, 65.9% (n = 274) were prescribed DAT for >12 months and 84.4% (n = 351) were prescribed concomitant gastroprotection. Independent of all other factors, females with AF were less likely to receive DAT than males (odds ratio [OR] 0.61, 95% confidence interval [CI] = 0.49 to 0.77). Similarly, older (aged ≥75 years) individuals (OR 0.79, 95% CI = 0.63 to 0.98) were less likely to receive DAT than younger patients. Among those with AF on DAT, pre-existing CVD (OR 3.33, 95% CI = 1.71 to 6.47) and South Asian ethnicity (OR 2.70, 95% CI = 1.15 to 6.32) were associated with increased gastroprotection prescriptions. Gastroprotection prescription (OR 1.80, 95% CI = 1.01 to 3.22) was associated with prolonged DAT prescription. CONCLUSION: Almost two-thirds of patients with AF on DAT were prescribed prolonged durations of therapy. Prescription of gastroprotection therapies was suboptimal in one in six patients. Treatment decisions varied by sex, age, ethnic group, and comorbidity. Duration of DAT and gastroprotection in patients with AF requires improvement.

Effectiveness of clinical dashboards as audit and feedback or clinical decision support tools on medication use and test ordering: a systematic review of randomized controlled trials.

BACKGROUND: Clinical dashboards used as audit and feedback (A&F) or clinical decision support systems (CDSS) are increasingly adopted in healthcare. However, their effectiveness in changing the behavior of clinicians or patients is still unclear. This systematic review aims to investigate the effectiveness of clinical dashboards used as CDSS or A&F tools (as a standalone intervention or part of a multifaceted intervention) in primary care or hospital settings on medication prescription/adherence and test ordering. METHODS: Seven major databases were searched for relevant studies, from inception to August 2021. Two authors independently extracted data, assessed the risk of bias using the Cochrane RoB II scale, and evaluated the certainty of evidence using GRADE. Data on trial characteristics and intervention effect sizes were extracted. A narrative synthesis was performed to summarize the findings of the included trials. RESULTS: Eleven randomized trials were included. Eight trials evaluated clinical dashboards as standalone interventions and provided conflicting evidence on changes in antibiotic prescribing and no effects on statin prescribing compared to usual care. Dashboards increased medication adherence in patients with inflammatory arthritis but not in kidney transplant recipients. Three trials investigated dashboards as part of multicomponent interventions revealing decreased use of opioids for low back pain, increased proportion of patients receiving cardiovascular risk screening, and reduced antibiotic prescribing for upper respiratory tract infections. CONCLUSION: There is limited evidence that dashboards integrated into electronic medical record systems and used as feedback or decision support tools may be associated with improvements in medication use and test ordering.

Comparison of 2 Smart Watch Algorithms for Detection of Atrial Fibrillation and the Benefit of Clinician Interpretation: SMART WARS Study.

BACKGROUND: Smart watches and wearable technology capable of heart rhythm assessment have increased in use in the general population. The Apple Watch Series 4 (AW4) and KardiaBand (KB) are devices capable of obtaining single-lead electrocardiographic recordings, presenting a novel opportunity for the detection of paroxysmal arrhythmias. OBJECTIVES: The aim of this study was to assess the diagnostic utility of the AW4 and KB in an elderly outpatient population. METHODS: Consecutive recordings were taken from patients attending cardiology outpatient clinic from the AW4 and KB concurrently with 12-lead electrocardiography. Automated diagnoses and blinded single-lead electrocardiographic tracing interpretations by 2 cardiologists were analyzed. Analysis was also conducted to assess the effect of combined device and clinician interpretation. RESULTS: One hundred twenty-five patients were prospectively recruited (mean age 76 ± 7 years, 62% men). The accuracy of the automated rhythm assessment was higher with the KB than the AW4 (74% vs 65%). For the detection of atrial fibrillation, the sensitivity and negative predictive value of the KB were 89% and 97%, respectively, and of the AW4 were 19% and 82%, respectively. Using hybrid automated and clinician interpretation, the overall accuracy of the KB and AW4 was 91% and 87%, respectively. CONCLUSIONS: The KB automated algorithm outperformed the AW4 in its accuracy and sensitivity for detecting atrial fibrillation in the outpatient setting. Clinician assessment of the single-lead electrocardiogram improved accuracy. These findings suggest that although these devices' tracings are of sufficient quality, automated diagnosis alone is not sufficient for making clinical decisions about atrial fibrillation diagnosis and management.