Atrial fibrillation self-screening, management and guideline recommended therapy (AF SELF SMART): improving AF screening in general practice by utilising self-screening stations in GP waiting rooms

Background

Opportunistic screening for silent atrial fibrillation (AF) is recommended to reduce stroke, but screening rates are sub-optimal in Australian general practice (<15%), with practitioners reporting time constraints being the main barrier. Previous AF screening interventions in general practice have not been able to exceed screening rates of ∼34% eligible patients which is sub-optimal for stroke prevention.

Purpose

To increase the proportion of patients screened for AF in general practice by implementing AF self-screening stations in waiting rooms.

Methods

We developed and tested an AF self-screening station using a single-lead ECG and app with automated ECG analysis. We also developed customised software which fully integrates the self-screening station with GP medical software and the practice workflow (Figure 1). The system: 1) automatically identifies eligible patients (aged ≥65 years, no AF diagnosis) from the practice appointment diary, and sends an SMS regarding self-screening prior to their appointment; 2) automatically creates individualised patient QR codes, which provided to the patient by the receptionist; 3) the patient then scans QR code and self-screens at station in waiting room; 4) the ECG and result are automatically imported into patient record before the GP consultation.

Results

Three general practices in New South Wales, Australia, were recruited. Each practice participated for approximately 3-months (between August 2020 and March 2021). During this period 825 patients completed AF self-screening, mean age 74.2 years and 45% male. When expressed as a proportion of the actual eligible patients attending the practice during the study period, the mean proportion screened in practices was 52% (range 38–65%). The device algorithm indicated “Possible AF” in 37/825 patients (4.5%); mean age 77.2 years 43% male.

Conclusion

An AF self-screening station placed in GP waiting rooms that is integrated with the practice software and workflow may achieve higher screening rates for AF in general practice than standard practice, and therefore contribute to greater reductions in stroke.

Funding Acknowledgement

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Investigator-lead grant from Bristol Myers Squibb and Pfizer

Patient self-screening stations for atrial fibrillation in general practice waiting rooms: process evaluation

Background

Our previous work has identified factors relevant to general practitioner (GP)-led screening for atrial fibrillation (AF) in Australian general practices, with GPs indicating significant time constraints. AF SELF SMART (Atrial fibrillation self-screening, management and guideline recommended therapy) allows for opportunistic patient self-screening using purpose-built screening stations located in GP waiting rooms (figure 1). It utilises a single-lead ECG, with results automatically imported into the patient medical record for review during the GP consultation. AF SELF SMART may increase screening rates, but acceptability by practice staff is unknown.

Purpose

Determine staff perspectives on opportunistic self-screening in practice waiting rooms, utilising AF SELF SMART.

Method

14 semi-structured interviews have been conducted with practice staff (GPs, receptionists and practice managers) across 3 practices participating in the AF SELF SMART pilot, with thematic analysis of results.

Results

Several themes were identified.

All staff acknowledged the importance of increasing screening for AF in the practice. GPs in particular placed a high value on AF screening for stroke prevention. GPs valued the increased information and accuracy provided by AF SELF SMART, as previously they checked patients for AF using manual methods, either routinely or as clinically indicated. There were differential impacts on workflow. GPs reported some small increase in workload but these were seen as being acceptable given the benefits of the program. Receptionists and Practice Managers reported significant interruptions to normal workflow associated with assisting patients. Receptionists routinely offered patients help with screening instead of patients screening independently. Staff perceived that patients were either unable to negotiate the self-screening process by themselves, or did not want to try. Given the increase in workload associated with assisting patients, and as screening was not receptionists' main priority, not all patients were offered self-screening during busy periods. Patient refusal was also identified as a factor limiting uptake.

Conclusion

While AF self-screening may increase screening rates, further process improvements are required to reduce impact on reception staff, and enhance the usability of the self-screening station for patients. Such improvements may increase acceptability and ongoing sustainability at a practice level.

Funding Acknowledgement

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Investigator initiated research grant from Bristol-Myers Squibb/Pfizer Alliance Figure 1. Self-screening station

223Atrial fibrillation screen, management and guideline recommended therapy (AF SMART II) in the rural primary care setting: eHealth tools to support all stages of screening

Funding Acknowledgements

National Heart Foundation of Australia: CVRN Grant and Vanguard Grant; investigator-initiated grant from Pfizer-BMS; AliveCor provided free devices

BACKGROUND

Internationally, most atrial fibrillation (AF) management guidelines recommend screening for AF in people aged ≥65 years, as well as treatment with oral anticoagulants (OAC) for those at high stroke risk ( CHA2DS2-VA ≥2). However, in practice, gaps remain in both screening and treatment. In Australian general practice in 2017, the estimated rate of AF screening was 11%, and only about 60% of diagnosed AF patients received guideline-based OAC. Our 2018 screening study using eHealth tools in metropolitan general practices increased screening to 16% of eligible patients, leading to further refinement of the eHealth tools.

PURPOSE

To investigate the impact of an AF screening program in rural general practices, using a suite of custom-designed eHealth tools designed to increase the proportion screened and treated for AF in accordance with guidelines.

METHODS

General practices (n = 8) in rural New South Wales, Australia participated in the study between September 2018 – June 2019. General practitioners (GPs) and practice nurses conducted opportunistic screening of eligible patients (i.e. aged ≥65 years without existing AF diagnosis) using a smartphone electrocardiogram during practice visits. Practices were also provided with 1) an electronic screening prompt (which appeared when an eligible patient’s file was opened); 2) electronic decision support based on ESC/Australian treatment guidelines; and 3) regular customised data reports aimed at quality improvement (Figure 1). A clinical audit tool was used to extract deidentified data from practices.

RESULTS

A total of 3,103 eligible patients (mean age 75.1 ± 6.8 years, 47% male) who attended the 8 practices during the study period were screened (median screening period 4.6 months). Practices screened a median of 35% of eligible patients (range 9-51% per practice), with 4/8 practices screening >40% of eligible patients. 36 (1.2%) new cases of AF were confirmed (mean age 77.0 years, 64% male, mean CHA2DS2-VA = 2.9). GPs (n = 22) screened 30% (range 1-182 per GP) of patients and nurses (n = 40) screened 70% (range 1-192 per nurse). OAC treatment rates of patients with AF with CHA2DS2-VA≥2 were 82% (screen-detected), 78% (clinically-detected during study period) and 75% (pre-existing AF), with no significant differences between groups.

CONCLUSIONS

In the rural general practice setting, an AF screening program supported by eHealth tools resulted in 35% of eligible people screened, which is substantially higher than the 16% achieved in our previous study. Half the practices screened 40-50% of eligible patients, suggesting this may represent a ‘ceiling’ of patients captured by opportunistic AF screening programs. OAC treatment rates were higher than previous studies at baseline and were trending upwards during the study. eHealth tools, particularly including customised data reports as part of an audit and feedback system, may be a valuable addition to future screening programs.

Abstract Figure 1 - screening process

P5319Evidence-practice gaps in the screening and management of cardiovascular risk factors in the Australian General Practice population

Background

Cardiovascular disease (CVD) is a major cause of death and disability in Australia affecting 1 in 6 of the Australian population. Studies a decade ago showed large evidence-practice gaps in the screening and management of CVD risk in Australian General Practice. A new risk-based screening and management guideline was launched in 2012.

Purpose

This study aimed to update the evidence to evaluate appropriate screening for, and management of, cardiovascular risk factors in Australian General Practice and explore practice and patient level predictors for appropriate screening and management.

Methods

Cross-sectional de-identified data from GP electronic health records were extracted for patients >18 years having attended at least once in the last 6 months and 3 times in the last 2 years (i.e. active patients). Practice-level data were also collected manually. The statistical cohort included Aboriginal and Torres Strait Islander people 35+ years and all others 45+ years, or any individual classified as “high CVD risk” regardless of age. High risk was defined as having either established CVD, pre-defined clinically high risk conditions or a calculated 5-year risk >15% using a Framingham based risk calculator. Appropriate screening was defined as having recorded/updated all essential risk factors for measurement of CVD risk within recommended time frames. Appropriate management was defined as: ≥1 BP lowering drug and a statin for people at high risk without CVD and the addition of an antiplatelet or anticoagulant agent for people with established CVD.

Results

Data were available on 110686 patients from 98 General Practices of which 55% were female, 1.4% of Aboriginal or Torres Strait Islander background, 14% current or ex-smoker and 15% with Diabetes. Forty-nine percent had complete and up to date screening information. Twenty-six percent were classified as high risk of which 11% had established CVD. Fifty-one per cent of those with established CVD were on appropriate treatment, vs 38% of those at high risk but without CVD. A greater proportion of males received appropriate screening (51.5% vs 47.5%). Females were less likely to receive recommended therapy (44.2% vs 55.1%) for secondary prevention but more likely for primary prevention (42% vs 35.5%). For those on BP lowering therapy, only 37% of those with CVD were reaching their target BP compared to 54% of those at high risk without established disease. 56% of those with CVD on lipid lowering therapy were reaching their targets compared to 45% of those at high risk without CVD.

Conclusion

Despite availability of a national guideline, gaps remain large for the management of CVD in Australian General Practice. Female primary prevention patients appear to receive better screening and treatment than their male counterparts, but this is reversed when they have established disease. Analysis of patient and practice level predictors for these gaps is currently underway.

Acknowledgement/Funding

National Health and Medical Research Council