Evidence map›Paper›PMID 39086849›Full record

ArticleSmart health (Amsterdam, Netherlands)2022

A comparative study on HIPAA technical safeguards assessment of android mHealth applications.

Md Raihan Mia, Hossain Shahriar, Maria Valero, Nazmus Sakib, Bilash Saha, Md Abdul Barek, Md Jobair Hossain Faruk, Ben Goodman, Rumi Ahmed Khan, Sheikh Iqbal Ahamed

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Smart health (Amsterdam, Netherlands), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Md Raihan MiaDepartment of Computer Science at Marquette University, WI, USA.
Hossain ShahriarDepartment of Information Technology at Kennesaw State University, GA, USA.
Maria ValeroDepartment of Information Technology at Kennesaw State University, GA, USA.
Nazmus SakibDepartment of Information Technology at Kennesaw State University, GA, USA.
Bilash SahaDepartment of Information Technology at Kennesaw State University, GA, USA.
Md Abdul BarekDepartment of Information Technology at Kennesaw State University, GA, USA.
Md Jobair Hossain FarukDepartment of Software Engineering and Game Development at Kennesaw State University, GA, USA.
Ben Goodman4A Security & Compliance, PA, USA.
Rumi Ahmed KhanDell Medical School at University of Texas, Austin, TX, USA.
Sheikh Iqbal AhamedDepartment of Computer Science at Marquette University, WI, USA.

Funding

A Framework for mHealth App Security and Privacy AnalysisR41GM146313 · NIGMS · UBITRIX INTERNATIONAL, INC. · PI AHAMED, SHEIKH IQBAL · 2021 to 2021
$256k
NIGMS NIH HHS R41 GM146313
6 · The paper itself

Abstract

Protecting personal health records is becoming increasingly important as more people use Mobile Health applications (mHealth apps) to improve their health outcomes. These mHealth apps enable consumers to monitor their health-related problems, store, manage, and share health records, medical conditions, treatment, and medication. With the increase of mHealth apps accessibility and usability, it is crucial to create, receive, maintain or transmit protected health information (PHI) on behalf of a covered entity or another business associate. The Health Insurance Portability and Accountability Act (HIPAA) provides guidelines to the app developers so that the apps must be compliant with required and addressable Technical Safeguards. However, most mobile app developers, including mHealth apps are not aware of HIPAA security and privacy regulations. Therefore, a research opportunity has emerged to develop an analytical framework to assist the developer to maintain a secure and HIPAA-compliant source code and raise awareness among consumers about the privacy and security of sensitive and personal health information. We proposed an Android source code analysis framework that evaluates twelve HIPAA Technical Safeguards to check whether a mHealth application is HIPAA compliant or not. The implemented meta-analysis and data-flow analysis algorithms efficiently identify the risk and safety features of mHealth apps that violate HIPAA regulations. Furthermore, we addressed API level checking for secure data communication mandated by recent CMS guidelines between third-party mobile health apps and EHR systems. Experimentally, a web-based tool has been developed for evaluating the efficacy of analysis techniques and algorithms. We have investigated 200 top popular Medical and Health & Fitness category Android apps collected from Google Play Store. We identified from the comparative analysis of the HIPAA rules assessment results that authorization to access sensitive resources, data encryption-decryption, and data transmission security is the most vulnerable features of the investigated apps. We provided recommendations to app developers about the most common mistake made at the time of app development and how to avoid these mistakes to implement secure and HIPAA-compliant apps. The proposed framework enables us to develop an IDE plugin for mHealth app developers and a web-based interface for mHealth app consumers.

Indexed as

AndroidData flow analysisHIPAA technical safeguardsMetadata analysismHealthPrivacySecurityStatic analysis

Identifiers

PMID39086849
PMCPMC11290549

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.