Screening for atrial fibrillation during influenza vaccinations by primary care nurses using a smartphone electrocardiograph (iECG): A feasibility study

Jessica Orchard, Nicole Lowres, S. Ben Freedman, Laila Ladak, William Lee, Nicholas Zwar, David Peiris, Yasith Kamaladasa, Jialin Li, Lis Neubeck

Research output: Contribution to journalArticleResearchpeer-review

25 Citations (Scopus)

Abstract

Background People with unknown atrial fibrillation (AF), who are often asymptomatic, have a substantially increased risk of stroke. Although recommended in European guidelines, AF screening is not routinely performed. Screening at the time of influenza vaccination presents an ideal opportunity to detect AF in large numbers in a primary care medical setting, with an existing annual recall system for patients aged ≥65 years. Design Cross-sectional pilot study of handheld smartphone electrocardiogram (iECG) screening to identify unknown AF. Methods General practices in Sydney, Australia, were recruited during the influenza-vaccination period of April-June 2015. Practice nurses screened patients aged ≥65 years with a 30-second iECG, which has a validated algorithm for detecting AF in real time. In order to confirm the accuracy of the algorithm, two research cardiologists reviewed de-identified iECGs. In order to explore barriers and enablers, semi-structured interviews were conducted with selected nurses, practice managers and general practitioners. Results Five general practices were recruited, and 973/2476 (39%) patients attending influenza vaccination were screened. Screening took an average of 5 minutes (range 1.5-10 minutes); however, abnormal iECGs required additional time. Newly identified AF was found in 8/973 patients (0.8%). The sensitivity of the iECG automated algorithm was 95% (95% confidence interval: 83-99%) and the specificity was 99% (95% confidence interval: 98-100%). Screening by practice nurses was well accepted by practice staff. Key enablers were the confidence and competence of nurses and a 'designated champion' to lead screening at the practice. Barriers were practice specific, and mainly related to staff time and funding. Conclusions Screening with iECG during influenza vaccination by primary care nurses is feasible and well accepted by practice staff. Addressing barriers is likely to increase uptake.

Original languageEnglish
Pages (from-to)13-20
Number of pages8
JournalEuropean Journal of Preventive Cardiology
Volume23
Issue number2_suppl
DOIs
Publication statusPublished - 1 Oct 2016
Externally publishedYes

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Feasibility Studies
Atrial Fibrillation
Human Influenza
Primary Health Care
Electrocardiography
Vaccination
Nurses
General Practice
Confidence Intervals
Mental Competency
General Practitioners
Smartphone
Cross-Sectional Studies
Stroke
Guidelines
Interviews
Research

Cite this

Orchard, Jessica ; Lowres, Nicole ; Freedman, S. Ben ; Ladak, Laila ; Lee, William ; Zwar, Nicholas ; Peiris, David ; Kamaladasa, Yasith ; Li, Jialin ; Neubeck, Lis. / Screening for atrial fibrillation during influenza vaccinations by primary care nurses using a smartphone electrocardiograph (iECG) : A feasibility study. In: European Journal of Preventive Cardiology. 2016 ; Vol. 23, No. 2_suppl. pp. 13-20.
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title = "Screening for atrial fibrillation during influenza vaccinations by primary care nurses using a smartphone electrocardiograph (iECG): A feasibility study",
abstract = "Background People with unknown atrial fibrillation (AF), who are often asymptomatic, have a substantially increased risk of stroke. Although recommended in European guidelines, AF screening is not routinely performed. Screening at the time of influenza vaccination presents an ideal opportunity to detect AF in large numbers in a primary care medical setting, with an existing annual recall system for patients aged ≥65 years. Design Cross-sectional pilot study of handheld smartphone electrocardiogram (iECG) screening to identify unknown AF. Methods General practices in Sydney, Australia, were recruited during the influenza-vaccination period of April-June 2015. Practice nurses screened patients aged ≥65 years with a 30-second iECG, which has a validated algorithm for detecting AF in real time. In order to confirm the accuracy of the algorithm, two research cardiologists reviewed de-identified iECGs. In order to explore barriers and enablers, semi-structured interviews were conducted with selected nurses, practice managers and general practitioners. Results Five general practices were recruited, and 973/2476 (39{\%}) patients attending influenza vaccination were screened. Screening took an average of 5 minutes (range 1.5-10 minutes); however, abnormal iECGs required additional time. Newly identified AF was found in 8/973 patients (0.8{\%}). The sensitivity of the iECG automated algorithm was 95{\%} (95{\%} confidence interval: 83-99{\%}) and the specificity was 99{\%} (95{\%} confidence interval: 98-100{\%}). Screening by practice nurses was well accepted by practice staff. Key enablers were the confidence and competence of nurses and a 'designated champion' to lead screening at the practice. Barriers were practice specific, and mainly related to staff time and funding. Conclusions Screening with iECG during influenza vaccination by primary care nurses is feasible and well accepted by practice staff. Addressing barriers is likely to increase uptake.",
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Screening for atrial fibrillation during influenza vaccinations by primary care nurses using a smartphone electrocardiograph (iECG) : A feasibility study. / Orchard, Jessica; Lowres, Nicole; Freedman, S. Ben; Ladak, Laila; Lee, William; Zwar, Nicholas; Peiris, David; Kamaladasa, Yasith; Li, Jialin; Neubeck, Lis.

In: European Journal of Preventive Cardiology, Vol. 23, No. 2_suppl, 01.10.2016, p. 13-20.

Research output: Contribution to journalArticleResearchpeer-review

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T1 - Screening for atrial fibrillation during influenza vaccinations by primary care nurses using a smartphone electrocardiograph (iECG)

T2 - A feasibility study

AU - Orchard, Jessica

AU - Lowres, Nicole

AU - Freedman, S. Ben

AU - Ladak, Laila

AU - Lee, William

AU - Zwar, Nicholas

AU - Peiris, David

AU - Kamaladasa, Yasith

AU - Li, Jialin

AU - Neubeck, Lis

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N2 - Background People with unknown atrial fibrillation (AF), who are often asymptomatic, have a substantially increased risk of stroke. Although recommended in European guidelines, AF screening is not routinely performed. Screening at the time of influenza vaccination presents an ideal opportunity to detect AF in large numbers in a primary care medical setting, with an existing annual recall system for patients aged ≥65 years. Design Cross-sectional pilot study of handheld smartphone electrocardiogram (iECG) screening to identify unknown AF. Methods General practices in Sydney, Australia, were recruited during the influenza-vaccination period of April-June 2015. Practice nurses screened patients aged ≥65 years with a 30-second iECG, which has a validated algorithm for detecting AF in real time. In order to confirm the accuracy of the algorithm, two research cardiologists reviewed de-identified iECGs. In order to explore barriers and enablers, semi-structured interviews were conducted with selected nurses, practice managers and general practitioners. Results Five general practices were recruited, and 973/2476 (39%) patients attending influenza vaccination were screened. Screening took an average of 5 minutes (range 1.5-10 minutes); however, abnormal iECGs required additional time. Newly identified AF was found in 8/973 patients (0.8%). The sensitivity of the iECG automated algorithm was 95% (95% confidence interval: 83-99%) and the specificity was 99% (95% confidence interval: 98-100%). Screening by practice nurses was well accepted by practice staff. Key enablers were the confidence and competence of nurses and a 'designated champion' to lead screening at the practice. Barriers were practice specific, and mainly related to staff time and funding. Conclusions Screening with iECG during influenza vaccination by primary care nurses is feasible and well accepted by practice staff. Addressing barriers is likely to increase uptake.

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