Evidence map›Paper›PMID 40475296›Full record

ReviewDigital health

Data privacy in healthcare: Global challenges and solutions.

Andrew Kweku Conduah, Sebastian Ofoe, Dorothy Siaw-Marfo

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
–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

37 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. The FemTech revolution: Unlocking the potential of new technology for optimizing pregnancy outcomes in low- and middle-income countries and remote areas.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026
    Article
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  12. GEN-Guard: correcting generalization failures for deployable federated surgical AI.International journal of computer assisted radiology and surgery · 2026
    Article
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  17. Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026
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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

3 authors.

Andrew Kweku ConduahDepartment of Business Administration, Institute of Work, Employment & Society (IWES), University of Professional Studies (UPSA), Accra, Ghana.ORCID https://orcid.org/0000-0001-6716-0939
Sebastian OfoeJoshua Alabi Library, Department of Electronic Information Resources, University of Professional Studies, Accra (UPSA), Accra, Ghana.ORCID https://orcid.org/0000-0002-2519-4222
Dorothy Siaw-MarfoInstitute of Work, Employment & Society (IWES), University of Professional Studies (UPSA), Accra, Ghana.ORCID https://orcid.org/0000-0001-8231-0755

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study explores global frameworks for healthcare data privacy, focusing on the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Protection of Personal Information Act (POPIA). It examines the challenges of regional regulatory disparities, systemic vulnerabilities identified through major health data breach case studies, and the potential of advanced technologies to enhance privacy protections. Methods: A qualitative research approach was adopted, incorporating corpus construction and comparative analysis of legal and technical frameworks. The study also utilized case studies of significant health data breaches to identify vulnerabilities and evaluate the role of emerging technologies, such as artificial intelligence (AI) and machine learning (ML), in mitigating risks and enhancing regulatory compliance. Results: Findings indicate that GDPR, CCPA, and POPIA set high standards for data protection but reveal significant variability in enforcement and technological adoption across regions. Challenges include inconsistent definitions of sensitive data, semantic discrepancies, a lack of standardized protocols, and limited information technology infrastructure in certain jurisdictions. Advanced technologies like AI and ML promise to address these gaps by improving data harmonization and security. Conclusions: Addressing healthcare data privacy challenges requires harmonized global regulations, advanced technological tools, and international collaboration. Strengthening frameworks, enhancing information technology infrastructure, and employing semantic models and ontologies are essential for protecting sensitive data, ensuring compliance, and fostering public trust in digital healthcare systems.

Indexed as

California Consumer Privacy Act (CCPA)Data privacydata securityGeneral Data Protection Regulation (GDPR)healthcareProtection of Personal Information Act (POPIA)

Identifiers

PMID40475296
PMCPMC12138216

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.