Oral Anticoagulation in Atrial Fibrillation: Development and Evaluation of a Mobile Health Application to Support Shared Decision-Making.

BACKGROUND: Atrial fibrillation is responsible for one in four strokes, which may be prevented by oral anticoagulation, an underused therapy around the world. Considering the challenges imposed by this sort of treatment, mobile health support for shared decision-making may improve patients' knowledge and optimize the decisional process. OBJECTIVE: To develop and evaluate a mobile application to support shared decision about thromboembolic prophylaxis in atrial fibrillation. METHODS: We developed an application to be used during the clinical visit, including a video about atrial fibrillation, risk calculators, explanatory graphics and information on the drugs available for treatment. In the pilot phase, 30 patients interacted with the application, which was evaluated qualitatively and by a disease knowledge questionnaire and a decisional conflict scale. RESULTS: The number of correct answers in the questionnaire about the disease was significantly higher after the interaction with the application (from 4.7 ± 1.8 to 7.2 ± 1.0, p < 0.001). The decisional conflict scale, administered after selecting the therapy with the app support, resulted in an average of 11 ± 16/100 points, indicating a low decisional conflict. CONCLUSIONS: The use of a mobile application during medical visits on anticoagulation in atrial fibrillation improves disease knowledge, enabling a shared decision with low decisional conflict. Further studies are needed to confirm if this finding can be translated into clinical benefit.

Oral Anticoagulation in Atrial Fibrillation: Development and Evaluation of a Mobile Health Application to Support Shared Decision-Making / Anticoagulação Oral na Fibrilação Atrial: Desenvolvimento e Avaliação de um Aplicativo de Saúde Móvel para Suporte à Decisão Compartilhada

Abstract Background: Atrial fibrillation is responsible for one in four strokes, which may be prevented by oral anticoagulation, an underused therapy around the world. Considering the challenges imposed by this sort of treatment, mobile health support for shared decision-making may improve patients' knowledge and optimize the decisional process. Objective: To develop and evaluate a mobile application to support shared decision about thromboembolic prophylaxis in atrial fibrillation. Methods: We developed an application to be used during the clinical visit, including a video about atrial fibrillation, risk calculators, explanatory graphics and information on the drugs available for treatment. In the pilot phase, 30 patients interacted with the application, which was evaluated qualitatively and by a disease knowledge questionnaire and a decisional conflict scale. Results: The number of correct answers in the questionnaire about the disease was significantly higher after the interaction with the application (from 4.7 ± 1.8 to 7.2 ± 1.0, p < 0.001). The decisional conflict scale, administered after selecting the therapy with the app support, resulted in an average of 11 ± 16/100 points, indicating a low decisional conflict. Conclusions: The use of a mobile application during medical visits on anticoagulation in atrial fibrillation improves disease knowledge, enabling a shared decision with low decisional conflict. Further studies are needed to confirm if this finding can be translated into clinical benefit.

Resumo Fundamento: A fibrilação atrial é causa de um em cada quatro acidentes vasculares cerebrais, que podem ser prevenidos com anticoagulação oral, uma terapia subutilizada globalmente. Considerando os desafios desse tratamento, instrumentos de saúde móvel para suporte à decisão compartilhada podem melhorar o conhecimento do paciente e otimizar o processo decisório. Objetivo: Desenvolver e avaliar um aplicativo móvel para suporte à decisão compartilhada na profilaxia tromboembólica em fibrilação atrial. Métodos: Foi desenvolvido um aplicativo para ser usado durante a consulta médica, contendo um vídeo sobre fibrilação atrial, calculadoras de escores de risco, gráficos explicativos e orientações sobre os fármacos disponíveis para o tratamento. Durante o desenvolvimento, 30 pacientes interagiram com o aplicativo, que foi avaliado qualitativamente e pela aplicação de um questionário de conhecimento sobre a doença e de uma escala de conflito em tomadas de decisão. Resultados: O número de acertos no questionário de conhecimento sobre a doença teve um aumento significativo após a interação com o aplicativo (de 4,7 ± 1,8 para 7,2 ± 1,0, p < 0,001). A escala de conflito em tomadas de decisão, aplicada após a escolha da terapia com o suporte do aplicativo, resultou em uma média de 11 ± 16/100 pontos, indicando baixo conflito decisório. Conclusões: O uso de um aplicativo móvel durante a consulta sobre anticoagulação em fibrilação atrial melhora o conhecimento sobre a doença, permitindo uma escolha compartilhada com baixo conflito decisório. Mais estudos são necessários para verificar se isso se traduz em benefício clínico.

Processes and Recommendations for Creating mHealth Apps for Low-Income Populations.

BACKGROUND: Mobile health (mHealth) apps have shown to improve health indicators, but concerns remain about the inclusion of populations from low- and medium-income countries (LMIC) in these new technologies. Atrial fibrillation (AF) is a chronic condition with a challenging management. Previous studies have shown socioeconomic differences in the prescription of anticoagulant treatment and shared decision strategies are encouraged to achieve better outcomes. mHealth can aid both doctors and patients in this matter. OBJECTIVE: We describe the development of an mHealth app (aFib) idealized to aid shared decision between doctor and patient about anticoagulation prophylaxis in AF in a low-income and low-literacy population in Brazil. On the basis of our research, we suggest the processes to be followed when developing mHealth apps in this context. METHODS: A multidisciplinary team collected information about the target population and its needs and detected the best opportunity to insert the app in their current health care. Literature about the subject was reviewed and important data were selected to be delivered through good navigability, easy terminology, and friendly design. The app was evaluated in a multimethod setting. RESULTS: The steps suggested to develop an mHealth app target to LMIC are: (1) characterize the problem and the target user, (2) review the literature, (3) translate information to knowledge, (4) protect information, and (5) evaluate usability and efficacy. CONCLUSIONS: We expect that these recommendations can guide the development of new mHealth apps in LMIC, on a scientific basis.