Noncommunicable diseases (NCDs), also known as chronic diseases, represent a major global health challenge, responsible for two-thirds of all deaths worldwide. These diseases place a particularly heavy burden on low- and middle-income countries (LMICs), including the Philippines. In this country, cardiovascular and cerebrovascular diseases are the primary causes of death. The most frequently reimbursed procedures by the Philippine Health Insurance Corporation (PhilHealth) pertain to complications arising from these NCDs. Economically, the impact is substantial, with losses amounting to 4.8% of the gross domestic product in 2017 [1–3].

To address this concern, the Department of Health (DOH) implemented the Philippine Package of Essential Non-Communicable Disease Interventions (PhilPEN) through Administrative Order (AO) No. 2012–0029. This initiative, adapted from the World Health Organization (WHO) guidelines, targets the management of NCDs in low-resource settings. The PhilPEN intervention protocol mandates that healthcare workers and volunteers use the Noncommunicable Disease Risk Assessment Form to gather patient data, evaluate risk factors, stratify cardiovascular risk, and, if necessary, refer patients for specialized consultation [3–7]. Despite these efforts, the program’s adoption has been sluggish, hindered by several factors, including the cumbersome nature of the multiple forms, the time-consuming process, and the overwhelming patient volume [8].

To address these challenges, information technology (IT) solutions, particularly mobile applications (apps), are emerging as potential aids in healthcare delivery, especially in LMICs such as the Philippines. This country not only has a growing mobile market but also a rising consumer interest in mobile apps [9–17]. However, the development of medical mobile apps, which integrate IT and health science disciplines, faces challenges due to the absence of clearly established frameworks (Table 1). This study aims to explore an alternative method for collecting NCD data using a mobile app. This app is based on the PhilPEN Protocol and was developed through extreme prototyping, an iterative software development framework that is well-suited to the unique requirements of health science [18–21].

The study utilized the software prototyping model (Figure 1) as the framework for developing a mobile health app designed to replicate the Noncommunicable Disease Risk Assessment Form. This model divides a large project into smaller, manageable segments, facilitating modifications during development, reducing both risk and cost, and incorporating end-user input for immediate feedback. This approach significantly enhances the likelihood of user acceptance [18,22,23]. The conceptual framework was derived from Komatineni’s “Reshaping IT Project Delivery through Extreme Prototyping” (Figure 2). It is structured into three phases: the static prototype-extended static prototype phase, the dynamic prototype (also known as the extreme prototype or user-interface) phase, and the service implementation phase [21].

The study employed a qualitative research methodology, which included several key components. A semi-structured interview was conducted with the Muntinlupa City Health Officer (CHO) to establish the foundational concepts for the mobile medical app. Linguistic validation was carried out at the Sentro ng Wikang Filipino (SWF) of UP Manila and UP Diliman. Additionally, cognitive debriefing was performed with the head community health worker of the barangay, who met specific criteria: (1) completion of training for NCD intervention, (2) utilization of the NCD Risk Assessment Form, (3) proficiency in using a smartphone and web browser, and (4) provision of written consent. The mobile medical app was designed and developed using HTML5, CSS3, and JavaScript—essential technologies for creating web content. It was subsequently ported to Android using Apache Cordova, a framework that enables the development of cross-platform native applications using web technologies [24–27].

The static prototype was designed using HTML5 and structured with CSS3, followed by the integration of a logical data model to enhance the prototype. The dynamic prototype required recoding and adjustments to the user interface, along with the implementation of field validation, computation functions, and a functional risk stratification routine.

The development of the PhilPEN Risk Stratification mobile medical app involved three prototype cycles. Each cycle included multiple mini-cycles consisting of feedback/requirement definition, system design, coding/testing, and then returning to feedback/requirement definition (Figure 3). Version 1.xx of the app was based on the WHO Prevention of Cardiovascular Disease 2007 [4] and PhilHealth Circular No.0020 s. 2013 24 [3] (Supplement A). This version was designed assuming the absence of facilities for necessary laboratory work and anticipated only 128 possible outcomes. A static prototype of this version was presented to the CHO, who noted the absence of laboratory data entry points. Subsequently, the DOH NCD Risk Assessment Form, translated into Filipino and adapted to include local nuances, was provided.

Version 2.xx of the app was developed based on the information and resources provided by the CHO. It supports two types of patient data entries: those without laboratory values, which have 128 possible outcomes, and those with laboratory results, featuring 640 possible outcomes (Supplement B). The app features a local language interface to enhance acceptance among the target user population. Concurrently, an extended static prototype and a dynamic prototype were developed. This process included recoding and adjusting the user interface, implementing field validation and computation functions, and establishing a functional risk stratification routine with 640 possible outcomes.

Upon presentation of Version 2.xx to the CHO, the DOH issued an updated NCD Risk Assessment Form (Supplement C). This new form requires more patient data and places a strong emphasis on risk screening, documenting associated factors, and streamlining the process for physicians to stratify patients’ risk profiles. Consequently, these expanded requirements necessitated an update to the app.

Version 3.xx of the app was developed based on feedback from the updated NCD Risk Assessment Form. During the development process, code refactoring and bug fixes that were identified internally were not included in the reported results. [1]

This study aimed to apply design theory to the development of a mobile app intended to support data collection for healthcare delivery. Specifically, it focused on creating a mobile medical app for community health workers based on the PhilPEN NCD Risk Assessment Form, utilizing extreme prototyping. The analysis suggests that the extreme prototyping framework is not only applicable to general mobile app development but also effectively bridges the gap between health science and information technology in the context of medical mobile apps.

The prototyping framework served development well, primarily by clarifying previously ambiguous objectives. Initially, both the CHO and the head physician at the health center supported the idea of an IT-based solution. However, they were unable to provide specific details on its implementation beyond presenting the PhilPEN NCD Risk Assessment Form. Prototyping can begin with just a rudimentary understanding of the core business issue [18,23,28], enabling the creation of a preliminary system, as demonstrated by the extended static prototype for the PhilPEN mobile medical app (Figure 4).

Breaking down the medical mobile app into smaller components using the prototyping methodology made development more manageable, given the limited resources available [18,19,28]. The use of extreme prototyping further streamlined the process by enabling parallel progression; each component could independently undergo cycles of feedback, requirement definition, system design, and coding/testing. Crucially, end-user involvement, a key aspect of the prototyping methodology, enhanced the development process by securing stakeholder buy-in and facilitating open communication throughout the iteration cycles [18,28].

The level of interaction facilitated addressing the challenges associated with the prototyping approach, including the informal approval process, the risk of inadequate checks and balances, and the possibility of changing requirements [18]. The foundation of this approach was strengthened by WHO initiatives, complemented by insights from the CHO regarding DOH nuances, which enabled the developer to manage expectations and address potential shortcomings effectively. The hypothesized benefits of the prototype, such as reduced inherent project risks and costs, appear to have been realized. This success can be attributed to the cooperation among the involved parties and their early participation, which contributed significantly to the potential successful conclusion of the project.

The significant value of this methodology in the development of medical mobile apps may explain its popularity among researchers like Prabhakaran et al. [29] and Rudin et al. [30] when creating their own applications. Although their discussions primarily concentrated on the health science aspect, the methodology’s influence is evident. This formal documentation of prototyping in the development of mobile medical apps likely provides the first detailed insight into their creation process. It bridges the gap between conceptualization and actualization in mobile medical application development, offering a repeatable methodology for future innovation and design.

While the development process was limited yet relatively complete, the effectiveness of this approach in integrating two distinct disciplines can only be fully validated through further research. The next logical step involves ‘barangay’ health workers using the app with actual patients to validate its accurate representation of the NCD Risk Assessment Form, assess its usability in their work environment, and refine it through additional prototype iterations. Future research on mobile medical app development using extreme prototyping could confirm the utility and advantages of applying system development methodologies in this emerging field. The prototyping process, based on scientific principles, should be replicable for those interested in developing similar applications. These future studies could also clarify which processes are truly applicable to health science and pinpoint any unique nuances that need consideration. Overall, this study has established a foundation for a systematic and evidence-based approach to developing medical mobile apps, effectively bridging the gap between conceptualization and actualization in this interdisciplinary field.