Evaluating Privacy Measures in Healthcare Apps Predominantly Used by Older Adults

• URL: http://arxiv.org/abs/2410.14607v1
• Date: Fri, 18 Oct 2024 17:01:14 GMT
• Title: Evaluating Privacy Measures in Healthcare Apps Predominantly Used by Older Adults
• Authors: Saka Suleiman, Sanchari Das,
• Abstract summary: rapid growth has also heightened concerns about the privacy of their health information. We evaluated 28 healthcare apps across multiple dimensions, including regulatory compliance, data handling practices, and privacy-focused usability. Our analysis revealed significant gaps in compliance with privacy standards to such, only 25% of apps explicitly state compliance with HIPAA, and only 18% mention. Surprisingly, 79% of these applications lack breach protocols, putting older adults at risk in the event of a data breach.
• Score: 2.7039386580759666
• License:
• Abstract: The widespread adoption of telehealth systems has led to a significant increase in the use of healthcare apps among older adults, but this rapid growth has also heightened concerns about the privacy of their health information. While HIPAA in the US and GDPR in the EU establish essential privacy protections for health information, limited research exists on the effectiveness of healthcare app privacy policies, particularly those used predominantly by older adults. To address this, we evaluated 28 healthcare apps across multiple dimensions, including regulatory compliance, data handling practices, and privacy-focused usability. To do this, we created a Privacy Risk Assessment Framework (PRAF) and used it to evaluate the privacy risks associated with these healthcare apps designed for older adults. Our analysis revealed significant gaps in compliance with privacy standards to such, only 25% of apps explicitly state compliance with HIPAA, and only 18% mention GDPR. Surprisingly, 79% of these applications lack breach protocols, putting older adults at risk in the event of a data breach.

Related papers

• A Global Medical Data Security and Privacy Preserving Standards Identification Framework for Electronic Healthcare Consumers [2.57177976232483]
  Different countries have varying standards for the security and privacy of medical data. This paper proposed a novel and comprehensive framework to standardize these rules globally.
  arXiv  Detail & Related papers  (2024-10-04T17:22:55Z)
• Privacy Checklist: Privacy Violation Detection Grounding on Contextual Integrity Theory [43.12744258781724]
  We formulate the privacy issue as a reasoning problem rather than simple pattern matching. We develop the first comprehensive checklist that covers social identities, private attributes, and existing privacy regulations.
  arXiv  Detail & Related papers  (2024-08-19T14:48:04Z)
• Collection, usage and privacy of mobility data in the enterprise and public administrations [55.2480439325792]
  Security measures such as anonymization are needed to protect individuals' privacy. Within our study, we conducted expert interviews to gain insights into practices in the field. We survey privacy-enhancing methods in use, which generally do not comply with state-of-the-art standards of differential privacy.
  arXiv  Detail & Related papers  (2024-07-04T08:29:27Z)
• A Qualitative Analysis Framework for mHealth Privacy Practices [0.0]
  This paper introduces a novel framework for the qualitative evaluation of privacy practices in mHealth apps. Our investigation encompasses an analysis of 152 leading mHealth apps on the Android platform. Our findings indicate persistent issues with negligence and misuse of sensitive user information.
  arXiv  Detail & Related papers  (2024-05-28T08:57:52Z)
• A Comprehensive Picture of Factors Affecting User Willingness to Use Mobile Health Applications [62.60524178293434]
  The aim of this paper is to investigate the factors that influence user acceptance of mHealth apps. Users' digital literacy has the strongest impact on their willingness to use them, followed by their online habit of sharing personal information. Users' demographic background, such as their country of residence, age, ethnicity, and education, has a significant moderating effect.
  arXiv  Detail & Related papers  (2023-05-10T08:11:21Z)
• Is It a Trap? A Large-scale Empirical Study And Comprehensive Assessment of Online Automated Privacy Policy Generators for Mobile Apps [15.181098379077344]
  Automated Privacy Policy Generators can create privacy policies for mobile apps. Nearly 20.1% of privacy policies could be generated by existing APPGs. App developers must carefully select and use the appropriate APPGs to avoid potential pitfalls.
  arXiv  Detail & Related papers  (2023-05-05T04:08:18Z)
• DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4 [80.36535668574804]
  We develop a novel GPT4-enabled de-identification framework (DeID-GPT") Our developed DeID-GPT showed the highest accuracy and remarkable reliability in masking private information from the unstructured medical text. This study is one of the earliest to utilize ChatGPT and GPT-4 for medical text data processing and de-identification.
  arXiv  Detail & Related papers  (2023-03-20T11:34:37Z)
• Privacy Explanations - A Means to End-User Trust [64.7066037969487]
  We looked into how explainability might help to tackle this problem. We created privacy explanations that aim to help to clarify to end users why and for what purposes specific data is required. Our findings reveal that privacy explanations can be an important step towards increasing trust in software systems.
  arXiv  Detail & Related papers  (2022-10-18T09:30:37Z)
• Associating eHealth Policies and National Data Privacy Regulations [1.713291434132985]
  This project aims to evaluate and highlight associations between systems' policies and privacy regulations. Using bias-corrected Cramer's V and Thiel's U tests we found weak zero associations between e-health systems' rules protections for data and personal privacy.
  arXiv  Detail & Related papers  (2022-02-27T21:22:48Z)
• On the Privacy of Mental Health Apps: An Empirical Investigation and its Implications for Apps Development [14.113922276394588]
  This paper reports an empirical study aimed at systematically identifying and understanding data privacy incorporated in mental health apps. We analyzed 27 top-ranked mental health apps from Google Play Store. The findings reveal important data privacy issues such as unnecessary permissions, insecure cryptography implementations, and leaks of personal data and credentials in logs and web requests.
  arXiv  Detail & Related papers  (2022-01-22T09:23:56Z)
• COVI White Paper [67.04578448931741]
  Contact tracing is an essential tool to change the course of the Covid-19 pandemic. We present an overview of the rationale, design, ethical considerations and privacy strategy of COVI,' a Covid-19 public peer-to-peer contact tracing and risk awareness mobile application developed in Canada.
  arXiv  Detail & Related papers  (2020-05-18T07:40:49Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.