ArticlemHealth2025
Careful considerations for digital health innovation: developing Nanbar Health-a digital health solution empowering clinical decisions with data-driven insights.
Article in mHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
8 authors.
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Abstract
Background: Digital health tools have grown in their usage and popularity since the coronavirus disease 2019 (COVID-19) pandemic, when healthcare providers were required to find methods of monitoring and engaging with their patients while also practicing social distancing. The process of building any digital product is arduous and complicated, and successful deployment within a healthcare system involves navigating a complex landscape of regulations, cybersecurity requirements, and the unique considerations of each healthcare institution, in addition to managing general product maintenance and adapting to ongoing technological advancements. The aim of this study was to utilize stakeholder feedback to create an improved, modular, scalable, and disease agnostic digital health solution while also identifying common challenges and considerations for deploying health technology. Methods: Our large interdisciplinary team has been part of several digital health solutions that have been utilized in multiple areas of healthcare. Here, we discuss this journey, lessons learned and describe the recent culmination of this work in the development of Nanbar Health, a digital health solution that integrates patient-reported symptoms via a mobile application, biometrics collected from smartwatches and wearables, and electronic health record (EHR) data to build complex symptom networks and predictive algorithms, all with the goal of better understanding the disease experience of individuals living with various illnesses. Results: This article provides details about our previously built tools, methodology, challenges, insights, and the findings our team made during the development process, alongside considerations that should be made during the development and integration of any digital health solution. Conclusions: Nanbar Health is a comprehensive digital health tool developed over multiple years by an interdisciplinary team, utilizing user-centered design, longitudinal data, and predictive algorithms to better understand an individual's illness experiences. The development of such digital health solutions requires extensive planning, efficient multidisciplinary teamwork, and careful consideration of factors needed to build sustainable and modular mobile health (mHealth) apps. Future improvements should focus on developing disease-agnostic solutions, improving data capture strategies, and creating streamlined processes for EHR integration to enhance healthcare technology adoption and patient care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.