Background Clinical guidelines recommend anticoagulation for patients with atrial fibrillation (AF) at high risk of stroke; however, studies report 40% of this population is not anticoagulated.
Objective To evaluate a population health intervention to increase anticoagulation use in high-risk patients with AF.
Methods We used machine learning algorithms to identify patients with AF from electronic health records at high risk of stroke (CHA2DS2-VASc risk score ≥2), and no anticoagulant prescriptions within 12 months. A clinical pharmacist in the anticoagulation service reviewed charts for algorithm-identified patients to assess appropriateness of initiating an anticoagulant. The pharmacist then contacted primary care providers of potentially undertreated patients and offered assistance with anticoagulation management. We used a stepped-wedge design, evaluating the proportion of potentially undertreated patients with AF started on anticoagulant therapy within 28 days for clinics randomised to intervention versus usual care.
Results Of 1727 algorithm-identified high-risk patients with AF in clinics at the time of randomisation to intervention, 432 (25%) lacked evidence of anticoagulant prescriptions in the prior year. After pharmacist review, only 17% (75 of 432) of algorithm-identified patients were considered potentially undertreated at the time their clinic was randomised to intervention. Over a third (155 of 432) were excluded because they had a single prior AF episode (transient or provoked by serious illness); 36 (8%) had documented refusal of anticoagulation, the remainder had other reasons for exclusion. The intervention did not increase new anticoagulant prescriptions (intervention: 4.1% vs usual care: 4.0%, p=0.86).
Conclusions Algorithms to identify underuse of anticoagulation among patients with AF in healthcare databases may not capture clinical subtleties or patient preferences and may overestimate the extent of undertreatment. Changing clinician behaviour remains challenging.
- electronic health records
- implementation research
- medical decision-making
- physician behaviour
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Presented at Early results were presented at the International Conference for Pharmacoepidemiology in Montreal, August 2017.
Contributors All authors contributed to the drafting and revision of this manuscript. SVW and MAF designed the study. S
VW, JRR, YJ and SD analysed the data.
Funding This project was funded by the Agency for Healthcare Research and Quality (R00HS022193).
Disclaimer The content is solely the responsibility of the authors and does not necessarily represent the official views of the Agency for Healthcare Research and Quality.
Competing interests SVW was supported by a grant from the Laura and John Arnold Foundation. She is a paid consultant to Aetion, a software company, and principal investigator on investigator-initiated grants from Novartis, Boehringer Ingelheim and J&J to BWH for unrelated work. During the conduct of this study, JRR was a paid consultant to Aetion, for unrelated work. MAF is Director of the National Resource Center for Academic Detailing, which is supported by AHRQ (Grant No R18HS023236).
Patient consent for publication Not required.
Ethics approval This study was approved by the BWH Institutional Review Board and BWH Primary Care Practice Based Research Network (PBRN) steering committee.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available upon reasonable request.
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