Impact of an Atrial Fibrillation Decision Support Tool on thromboprophylaxis for atrial fibrillation

Eckman, Mark H.; Lip, Gregory Y.H.; Wise, R.; Speer, B. Bryce; Sullivan, Megan; Walker, Nita; Kissela, Brett M.; Flaherty, Matthew L.; Kleindorfer, Dawn; Baker, Pete; Ireton, Robert C.; Hoskins, Dave; Harnett, Brett; Aguilar, Carlos; Leonard, Anthony; Arduser, Lora; Steen, Dylan; Costea, Alexandru; Kues, John R.

doi:10.1016/j.ahj.2016.02.009

Cited by 48 publications

(45 citation statements)

References 36 publications

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“…This suggests that screening for AF alone is not enough, and that there may well be a place for a decision support tool to improve prescription practice. A number of programmes have been previously developed in order to increase evidence-based prescription of OACs, including electronic decision support tools, 19 targeted GP education programme, 20 and patient-focused education interventions. 21 The results of these programmes were generally positive, although they were also varied.…”

Section: Discussionmentioning

confidence: 99%

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

Orchard

Lowres

Freedman

et al. 2016

Eur J Prev Cardiolog

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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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Section: Discussionmentioning

confidence: 99%

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

Orchard

Lowres

Freedman

et al. 2016

Eur J Prev Cardiolog

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“…We have developed an AFDST that uses a decision analytic engine to generate patient-level recommendations for thromboprophylaxis. (7–10) Information required to calculate AF-related stroke risk using the CHA 2 DS 2 VASc(11), major hemorrhage using HAS-BLED(12), and intracerebral hemorrhage(12) rates are extracted from our EPIC® clinical data store (Clarity®) and are fed to the decision analytic engine. Stroke risk and bleeding risk (extracranial and intracerebral) are modified by appropriate measures of efficacy and relative hazards for each treatment based upon evidence in the published literature.…”

Section: Methodsmentioning

confidence: 99%

“…In a prior study of the AFDST , we found that clinicians made such changes in a total of roughly one third of patients. (7) However, the most common change was the addition of coronary artery disease as a diagnosis not captured on our query of the active problem lists. Although such changes may have affected the magnitude of the gain or loss with OAT, it was rare that they caused the AFDST recommendation to change.…”

Section: Limitationsmentioning

confidence: 99%

“…(7,8) Patient-level treatment recommendations are generated based upon projections for quality-adjusted life years (QALYs) calculated by a 29-state Markov decision analytic model. The previously described A trial F ibrillation D ecision S upport T ool ( AFDST) considered choices between OAT with warfarin, aspirin, or no antithrombotic therapy.…”

Section: Introductionmentioning

confidence: 99%

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Atrial fibrillation decision support tool: Population perspective

Eckman

Costea

Attari

et al. 2017

American Heart Journal

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Background Appropriate thromboprophylaxis for patients with atrial fibrillation or atrial flutter (AF) remains a national challenge. The recent availability of direct oral anticoagulants (DOACs) with comparable efficacy and improved safety compared with warfarin alters the balance between risk factors for stroke and benefit of anticoagulation. Our objective was to examine the impact of DOACs as an alternative to warfarin on the net benefit of oral anticoagulant therapy (OAT) in a real-world population of AF patients. Methods Retrospective cohort study of patients with paroxysmal or persistent nonvalvular AF. We updated an Atrial Fibrillation Decision Support Tool (AFDST) to include DOACs as treatment options. The tool generates patient–specific recommendations based upon individual patient risk factor profiles for stroke and major bleeding, using quality-adjusted life years (QALYs) calculated for each treatment strategy by a decision analytic model. The setting included inpatient and ambulatory sites in an academic health center in the mid-western United States. Study involved 5,121 adults with nonvalvular AF seen for any ambulatory visit or inpatient hospitalization over the 1-year period (January through December 2016). Outcome measure was net clinical benefit in QALYs. Results When DOACs are a therapeutic option, the AFDST recommends OAT for 4,134 (81%) patients, and no antithrombotic therapy or aspirin for 489 (9%). A strong recommendation for OAT could not be made in 498 (10%) patients. When warfarin is the only option, OAT is recommended for 3,228 (63%) patients, and no antithrombotic therapy or aspirin for 973 (19%). A strong recommendation for OAT could not be made in 920 (18%) patients. In total, 1,508 QALYs could be gained were treatment changed to that recommended by the AFDST. Conclusions Availability of DOACs increases the proportion of patients for whom oral anticoagulation therapy is recommended in a real-world cohort of AF patients and increased projected QALYs by more than 1,500 when all patients are receiving thromboprophylaxis as recommended by the AFDST compared with current treatment.

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“…For patients admitted to hospital, the level of venous thromboembolism prophylaxis and the proportion of prescribed prophylaxis increased from six to 24 hours after admission for clinicians allocated to venous thromboembolism reminder CDSS [12]. In another study, differences among physicians over the thromboprophylaxis treatment effect decreased with the help of CDSS providing treatment recommendation (p-value=0.02) [13]. In other studies, alert based CDSSs have been effective in physician behavior and progressive treatment improvement in anti-inflammatory drugs and lipid-lowering drugs, which has also been statistically significant [14][15][16].…”

Section: The Effect Of Cdss On Cardiovascular Diseasesmentioning

confidence: 98%

The effects of clinical decision support system for prescribing on patient outcomes and physician practice performance: A systematic review

Moghadam¹,

Velayati²,

Sadoughi³

et al. 2020

Preprint

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Background The clinical decision support systems(CDSSs) for prescription medications is one of the technologies aimed at improving physician practice behavior and patient outcomes by reducing drug prescription errors. This study was conducted to investigate the effect of various CDSSs on physician practice behavior and patient outcomes.Methods This systematic review was conducted by searching in PubMed, EMBASE, Web of Science, Scopus and Cochrane Library from January 2005 to November 2019. Two researchers independently evaluated the studies. Any discrepancies over the eligibility of the studies between the two researchers were then resolved by consulting a third researcher. Finally, data were extracted from the articles; however, we could not able to conduct meta-analysis due to the heterogeneity of the studies and the narrative form of the findings.Results Based on the inclusion criteria, 46 studies were considered eligible for the analysis in this review. The CDSS for prescription medications had been used for various diseases, namely cardiovascular diseases, hypertension, diabetes, gastrointestinal and respiratory diseases, AIDS, appendicitis, kidney disease, malaria, high blood potassium, mental disease. Meanwhile, other cases such as the concurrent prescription of multiple drugs for the patient and its effects on the above-mentioned outcomes were evaluated. The analysis shows that in some cases the application of CDSS provides positive effects on patient outcomes and physician practice behaviors. No significant difference was observed in comparison between some other cases and conventional methods. We think that this could be due to the disease type, the quantity and type of CDSS requirements that influence the comparison.Conclusions Our findings suggest that the positive effects of the CDSS are due to factors such as user-friendliness, compliance with clinical guidelines, patient and doctor cooperation, integration of electronic health records, CDSS and pharmaceutical systems, consideration of the views of physicians in assessing the importance of CDSS alerts and their real-time alerts in the prescription.Registration number on PROSPERO CRD42018079936.

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Impact of an Atrial Fibrillation Decision Support Tool on thromboprophylaxis for atrial fibrillation

Abstract: Among patients whose physicians reviewed recommendations of the decision support tool discordant therapy decreased significantly over 1 year. However, in nonstratified analyses, the intervention did not result in significant improvements in discordant antithrombotic therapy.

Cited by 48 publications

References 36 publications

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

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

Atrial fibrillation decision support tool: Population perspective

The effects of clinical decision support system for prescribing on patient outcomes and physician practice performance: A systematic review

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