A Smart Chatbot for Interactive Management in Beta Thalassemia Patients

Alma Mohammed Alturaiki; Haneen Reda Banjar; Ahmed Salleh Barefah; Salwa Abdulrahman Alnajjar; Salwa Hindawi

doi:10.1155/2022/9734518

A Smart Chatbot for Interactive Management in Beta Thalassemia Patients

Int J Telemed Appl. 2022 May 11:2022:9734518. doi: 10.1155/2022/9734518. eCollection 2022.

Authors

Alma Mohammed Alturaiki¹, Haneen Reda Banjar^{2

3}, Ahmed Salleh Barefah^{4

5}, Salwa Abdulrahman Alnajjar^{4

5}, Salwa Hindawi^{4

6}

Affiliations

¹ King Abdulaziz and His Companions Foundation for Giftedness and Creativity (Mawhiba), Saudi Arabia.
² Computer Science Department, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia.
³ Centre of Artificial intelligence in Precision Medicines, King Abdulaziz University, Jeddah, Saudi Arabia.
⁴ Hematology Department, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
⁵ Hematology Research Unit, King Fahd Medical Research Centre, King Abdulaziz University, Jeddah, Saudi Arabia.
⁶ Saudi Friends of Thalassemia and Sickle Cell Anaemia Society, Jeddah, Saudi Arabia.

Abstract

Background: β-thalassemia is an inherited blood disorder that affects the production of hemoglobin molecules owing to the reduction or absence of beta chains. Transfusion therapy has had a key role in extending the lifespan of β-thalassemia patients. This life-saving therapy is linked to numerous assessments and complications that now comprise most thalassemia management considerations. Consequently, many patients do not receive adequate information about the required assessments, as indicated by evidence-based medical guidelines. Patients with β-thalassemia may benefit from chatbots that follow up on their condition and that provide the required assessment information. Self-management will hopefully have a positive impact on health outcomes.

Objectives: This study aims to develop a chatbot that can assist in the management of β-thalassemia by providing the assessment information required to monitor patients' statuses.

Methods: The chatbot operated as a messaging system. A question/answer system was created based on knowledge pertaining to β-thalassemia assembled from experts, medical guidelines, and articles. Recommendations regarding the patient's follow-up assessment are made based on the answers.

Results: A prototype was implemented to demonstrate how the chatbots could dynamically and flexibly provide the assessment information required to follow up on and monitor patients. A small sample of adults with β-thalassemia used the chatbot to examine the system's usability and perceived utility. A system usability scale and utility scale were implemented to complete a post-test survey. The chatbots were considered by 34 patients, of whom the majority (72%) found them easy to use, while more than 90% of patients considered their use beneficial. Most of the participants agreed that the chatbots could improve their knowledge about their β-thalassemia assessments.

Conclusion: Our findings suggest that chatbots can be beneficial to the development of recommended tests and management related to the assessment of β-thalassemia.