The Development of a Chatbot Technology to Disseminate Post-COVID-19 Information: Descriptive Implementation Study.

BACKGROUND: Post-COVID-19, or long COVID, has now affected millions of individuals, resulting in fatigue, neurocognitive symptoms, and an impact on daily life. The uncertainty of knowledge around this condition, including its overall prevalence, pathophysiology, and management, along with the growing numbers of affected individuals, has created an essential need for information and disease management. This has become even more critical in a time of abundant online misinformation and potential misleading of patients and health care professionals. OBJECTIVE: The RAFAEL platform is an ecosystem created to address the information about and management of post-COVID-19, integrating online information, webinars, and chatbot technology to answer a large number of individuals in a time- and resource-limited setting. This paper describes the development and deployment of the RAFAEL platform and chatbot in addressing post-COVID-19 in children and adults. METHODS: The RAFAEL study took place in Geneva, Switzerland. The RAFAEL platform and chatbot were made available online, and all users were considered participants of this study. The development phase started in December 2020 and included developing the concept, the backend, and the frontend, as well as beta testing. The specific strategy behind the RAFAEL chatbot balanced an accessible interactive approach with medical safety, aiming to relay correct and verified information for the management of post-COVID-19. Development was followed by deployment with the establishment of partnerships and communication strategies in the French-speaking world. The use of the chatbot and the answers provided were continuously monitored by community moderators and health care professionals, creating a safe fallback for users. RESULTS: To date, the RAFAEL chatbot has had 30,488 interactions, with an 79.6% (6417/8061) matching rate and a 73.2% (n=1795) positive feedback rate out of the 2451 users who provided feedback. Overall, 5807 unique users interacted with the chatbot, with 5.1 interactions per user, on average, and 8061 stories triggered. The use of the RAFAEL chatbot and platform was additionally driven by the monthly thematic webinars as well as communication campaigns, with an average of 250 participants at each webinar. User queries included questions about post-COVID-19 symptoms (n=5612, 69.2%), of which fatigue was the most predominant query (n=1255, 22.4%) in symptoms-related stories. Additional queries included questions about consultations (n=598, 7.4%), treatment (n=527, 6.5%), and general information (n=510, 6.3%). CONCLUSIONS: The RAFAEL chatbot is, to the best of our knowledge, the first chatbot developed to address post-COVID-19 in children and adults. Its innovation lies in the use of a scalable tool to disseminate verified information in a time- and resource-limited environment. Additionally, the use of machine learning could help professionals gain knowledge about a new condition, while concomitantly addressing patients' concerns. Lessons learned from the RAFAEL chatbot will further encourage a participative approach to learning and could potentially be applied to other chronic conditions.

An Intervention by a Patient-Designed Do-It-Yourself Mobile Device App Reduces HbA1c in Children and Adolescents with Type 1 Diabetes: A Randomized Double-Crossover Study.

BACKGROUND: Prevention of type 1 diabetes mellitus (T1DM)-related complications is dependent on metabolic control. The recommended glycated hemoglobin (HbA1c) values <7.5% (58.5 mmol/mol) are met only by a minority of diabetic children and especially adolescents. The aim of this study was to evaluate the impact of an intervention comprising the use of Webdia, a patient-designed app for smartphones, on metabolic control of T1DM in children. METHODS: Fifty-five patients with T1DM, 10-18 years of age, were included in this single-center, randomized double-crossover study. We tested an intervention consisting of using Webdia for 3 months with monthly feedback and adaptation of the treatment. Main outcome was modification of HbA1c. Secondary outcomes were the prevalence of hypoglycemia and quality of life (QoL). RESULTS: Of the 55 included patients, 33 completed the study, 9 dropped out, and 13 were excluded due to insufficient use of the app. The app was well accepted by the users who completed the study (46.4% rated the program as good and 39.3% as excellent). The intervention led to a reduction of HbA1c by 0.33%, compared to the control group in which HbA1c rose by 0.21% (P = 0.048) in patients with HbA1c values >8.0% (63.9 mmol/mol) at inclusion, without increasing the prevalence of hypoglycemia (8.52 ± 9.45 hypoglycemic events during last 2 weeks of intervention vs. 7.62 ± 6.37 observation, P = 0.680). QoL scores were not modified. CONCLUSIONS: The intervention resulted in a significant decrease in HbA1c, without increasing the prevalence of hypoglycemia in patients with initial HbA1c >8.0% (63.9 mmol/mol).

[InfoKids: changing the patients' journey paradigm in an Emergency Department]. / InfoKids : changement de paradigme du parcours patients dans un service d'urgences.

Nowadays, citizens are little supported to decide whether they should consult the Emergency Departments (ED) in case of illness or trauma. Moreover, once in the ED, they often must deal with overcrowding, long waiting times, the acute nature of the visits, administrative data management, and a lack of follow-up after the visit. To improve this situation, we have developed an e-health solution delivering a more patient-centered experience by connecting patients, caregivers, and administrative clerks through a web and mobile applications. This innovative system is intended to improve the entire emergency care process, facilitating the caregiver and administrative work and supporting patients before, during, and after their ED consultation.

De nos jours, les citoyens sont peu soutenus en cas de maladie ou de traumatisme pour décider si leur état de santé justifie une consultation aux urgences. Arrivés aux urgences, les patients doivent faire face à des délais d'attente, au stress engendré par une urgence médicale et au manque d'information concernant le suivi à domicile. Afin d'améliorer cette situation, nous avons développé une solution d'e-santé, composée d'applications web et mobiles, guidant le patient de manière personnalisée tout au long de son parcours et connectant patients, soignants et employés administratifs. Ce système novateur améliore l'ensemble du processus de soins d'urgence en facilitant le travail des soignants, des administratifs et en soutenant les patients avant, pendant et après leurs consultations aux urgences.

Connecting Parents to a Pediatric Emergency Department: Designing a Mobile App Based on Patient Centred Care Principles.

INTRODUCTION: Patient centred care fosters a holistic approach of care switching the focus from a disease perspective to a patient's experience perspective. Patient centred care is of particular importance in the context of paediatric emergency medicine. Indeed, parents entering a paediatric emergency department (PED) are usually under stress caused by their children's illness, the unfamiliar setting of the PED and delays of care. All these factors can deteriorate their experience as well as the relationships between healthcare providers, the patients and their parents. METHODS: We explore potential areas to improve the patient experience during his journey into PED. The dimensions of the picker's patient centred care are used to guide observations, conduct interviews and focus groups. The areas of improvement are then operationalized through their translation into app functionalities. RESULTS: Our novel application allows supporting users on 7 of the 8 dimensions of picker's patient centred care model. The app supports parents in their decision-making to consult a PED, it provides relevant medical information to avoid unrealistic expectations and accompany the family after discharge thanks to tailored information sheets about diagnostics. CONCLUSION: Our mobile app allows to make a big step toward the improvement of the patient-caregiver relationship. The direct benefits will be shared by patients and caregivers, as well as the institution.