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Assessing the Food and Drug Administration’s Risk-Based Framework for Software Precertification With Top Health Apps in the United States: Quality Improvement Study

BACKGROUND: As the development of mobile health apps continues to accelerate, the need to implement a framework that can standardize the categorization of these apps to allow for efficient yet robust regulation is growing. However, regulators and researchers are faced with numerous challenges, as ap...

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Autores principales: Alon, Noy, Stern, Ariel Dora, Torous, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652687/
https://www.ncbi.nlm.nih.gov/pubmed/32927429
http://dx.doi.org/10.2196/20482
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author Alon, Noy
Stern, Ariel Dora
Torous, John
author_facet Alon, Noy
Stern, Ariel Dora
Torous, John
author_sort Alon, Noy
collection PubMed
description BACKGROUND: As the development of mobile health apps continues to accelerate, the need to implement a framework that can standardize the categorization of these apps to allow for efficient yet robust regulation is growing. However, regulators and researchers are faced with numerous challenges, as apps have a wide variety of features, constant updates, and fluid use cases for consumers. As past regulatory efforts have failed to match the rapid innovation of these apps, the US Food and Drug Administration (FDA) has proposed that the Software Precertification (Pre-Cert) Program and a new risk-based framework could be the solution. OBJECTIVE: This study aims to determine whether the risk-based framework proposed by the FDA’s Pre-Cert Program could standardize categorization of top health apps in the United States. METHODS: In this quality improvement study during summer 2019, the top 10 apps for 6 disease conditions (addiction, anxiety, depression, diabetes, high blood pressure, and schizophrenia) in Apple iTunes and Android Google Play Store in the United States were classified using the FDA’s risk-based framework. Data on the presence of well-defined app features, user engagement methods, popularity metrics, medical claims, and scientific backing were collected. RESULTS: The FDA’s risk-based framework classifies an app’s risk by the disease condition it targets and what information that app provides. Of the 120 apps tested, 95 apps were categorized as targeting a nonserious health condition, whereas only 7 were categorized as targeting a serious condition and 18 were categorized as targeting a critical condition. As the majority of apps targeted a nonserious condition, their risk categorization was largely determined by the information they provided. The apps that were assessed as not requiring FDA review were more likely to be associated with the integration of external devices than those assessed as requiring FDA review (15/58, 26% vs 5/62, 8%; P=.03) and health information collection (24/58, 41% vs 9/62, 15%; P=.008). Apps exempt from the review were less likely to offer health information (25/58, 43% vs 45/62, 72%; P<.001), to connect users with professional care (7/58, 12% vs 14/62, 23%; P=.04), and to include an intervention (8/58, 14% vs 35/62, 55%; P<.001). CONCLUSIONS: The FDA’s risk-based framework has the potential to improve the efficiency of the regulatory review process for health apps. However, we were unable to identify a standard measure that differentiated apps requiring regulatory review from those that would not. Apps exempt from the review also carried concerns regarding privacy and data security. Before the framework is used to assess the need for a formal review of digital health tools, further research and regulatory guidance are needed to ensure that the Pre-Cert Program operates in the greatest interest of public health.
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spelling pubmed-76526872020-11-13 Assessing the Food and Drug Administration’s Risk-Based Framework for Software Precertification With Top Health Apps in the United States: Quality Improvement Study Alon, Noy Stern, Ariel Dora Torous, John JMIR Mhealth Uhealth Original Paper BACKGROUND: As the development of mobile health apps continues to accelerate, the need to implement a framework that can standardize the categorization of these apps to allow for efficient yet robust regulation is growing. However, regulators and researchers are faced with numerous challenges, as apps have a wide variety of features, constant updates, and fluid use cases for consumers. As past regulatory efforts have failed to match the rapid innovation of these apps, the US Food and Drug Administration (FDA) has proposed that the Software Precertification (Pre-Cert) Program and a new risk-based framework could be the solution. OBJECTIVE: This study aims to determine whether the risk-based framework proposed by the FDA’s Pre-Cert Program could standardize categorization of top health apps in the United States. METHODS: In this quality improvement study during summer 2019, the top 10 apps for 6 disease conditions (addiction, anxiety, depression, diabetes, high blood pressure, and schizophrenia) in Apple iTunes and Android Google Play Store in the United States were classified using the FDA’s risk-based framework. Data on the presence of well-defined app features, user engagement methods, popularity metrics, medical claims, and scientific backing were collected. RESULTS: The FDA’s risk-based framework classifies an app’s risk by the disease condition it targets and what information that app provides. Of the 120 apps tested, 95 apps were categorized as targeting a nonserious health condition, whereas only 7 were categorized as targeting a serious condition and 18 were categorized as targeting a critical condition. As the majority of apps targeted a nonserious condition, their risk categorization was largely determined by the information they provided. The apps that were assessed as not requiring FDA review were more likely to be associated with the integration of external devices than those assessed as requiring FDA review (15/58, 26% vs 5/62, 8%; P=.03) and health information collection (24/58, 41% vs 9/62, 15%; P=.008). Apps exempt from the review were less likely to offer health information (25/58, 43% vs 45/62, 72%; P<.001), to connect users with professional care (7/58, 12% vs 14/62, 23%; P=.04), and to include an intervention (8/58, 14% vs 35/62, 55%; P<.001). CONCLUSIONS: The FDA’s risk-based framework has the potential to improve the efficiency of the regulatory review process for health apps. However, we were unable to identify a standard measure that differentiated apps requiring regulatory review from those that would not. Apps exempt from the review also carried concerns regarding privacy and data security. Before the framework is used to assess the need for a formal review of digital health tools, further research and regulatory guidance are needed to ensure that the Pre-Cert Program operates in the greatest interest of public health. JMIR Publications 2020-10-26 /pmc/articles/PMC7652687/ /pubmed/32927429 http://dx.doi.org/10.2196/20482 Text en ©Noy Alon, Ariel Dora Stern, John Torous. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 26.10.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Alon, Noy
Stern, Ariel Dora
Torous, John
Assessing the Food and Drug Administration’s Risk-Based Framework for Software Precertification With Top Health Apps in the United States: Quality Improvement Study
title Assessing the Food and Drug Administration’s Risk-Based Framework for Software Precertification With Top Health Apps in the United States: Quality Improvement Study
title_full Assessing the Food and Drug Administration’s Risk-Based Framework for Software Precertification With Top Health Apps in the United States: Quality Improvement Study
title_fullStr Assessing the Food and Drug Administration’s Risk-Based Framework for Software Precertification With Top Health Apps in the United States: Quality Improvement Study
title_full_unstemmed Assessing the Food and Drug Administration’s Risk-Based Framework for Software Precertification With Top Health Apps in the United States: Quality Improvement Study
title_short Assessing the Food and Drug Administration’s Risk-Based Framework for Software Precertification With Top Health Apps in the United States: Quality Improvement Study
title_sort assessing the food and drug administration’s risk-based framework for software precertification with top health apps in the united states: quality improvement study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652687/
https://www.ncbi.nlm.nih.gov/pubmed/32927429
http://dx.doi.org/10.2196/20482
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