Extreme Prototyping for a Community Health Worker Medical Application
- Author:
Jan Noel MOLON
1
Author Information
- Publication Type:Case Report
- From:Healthcare Informatics Research 2025;31(1):88-95
- CountryRepublic of Korea
- Language:English
-
Abstract:
Objectives:Noncommunicable diseases (NCDs) pose a significant burden, especially in low- and middle-income countries such as the Philippines. To tackle this issue, the Department of Health launched the Philippine Package of Essential Non-Communicable Disease Interventions (PhilPEN), which includes the use of the Noncommunicable Disease Risk Assessment Form. However, healthcare workers have encountered difficulties due to the form’s complexity and the lengthy process required. This study aimed to create a mobile medical app for community health workers by adapting the PhilPEN Noncommunicable Disease Risk Assessment Form using the extreme prototyping framework. The focus was on simplifying data collection and improving the usability of health technology solutions.
Methods:The study employed a qualitative research methodology, which included key informant interviews, linguistic validation, and cognitive debriefing. The extreme prototyping framework was utilized for app development, comprising static prototype, dynamic prototype, and service implementation phases. The app was developed with HTML5, CSS3, JavaScript, and Apache Cordova, adhering to World Health Organization (WHO) guidelines and PhilHealth Circular.
Results:The development process involved three prototype cycles, each consisting of multiple mini-cycles of feedback, system design, coding, and testing. Version 1.xx was aligned with WHO guidelines, Version 2.xx integrated the Department of Health NCD Risk Assessment Form, and Version 3.xx adapted to the updated form with expanded requirements.
Conclusions:The extreme prototyping framework was effectively applied in the development of a medical mobile app, facilitating the integration of health science and information technology. Future research should continue to validate the effectiveness of this approach and identify specific nuances related to health science applications.
