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Trends in ransomware attacks on US hospitals, clinics, and other health care delivery organizations, 2016-2021.
Open accessAbstract
Importance: Anecdotal evidence suggests that health care delivery organizations face a growing threat from ransomware attacks that are designed to disrupt care delivery and may consequently threaten patient outcomes. Objective: To quantify the frequency and characteristics of ransomware attacks on health care delivery organizations. Design, Setting, and Participants: This cohort study used data from the Tracking Healthcare Ransomware Events and Traits database to examine the number and characteristics of ransomware attacks on health care delivery organizations from 2016 to 2021. Logistic and negative binomial regression quantified changes over time in the characteristics of ransomware attacks that affected health care delivery organizations. Main Outcomes and Measures: Date of ransomware attack, public reporting of ransomware attacks, personal health information (PHI) exposure, status of encrypted/stolen data following the attack, type of health care delivery organization affected, and operational disruption during the ransomware attack. Results: From January 2016 to December 2021, 374 ransomware attacks on US health care delivery organizations exposed the PHI of nearly 42 million patients. From 2016 to 2021, the annual number of ransomware attacks more than doubled from 43 to 91. Almost half (166 [44.4%]) of ransomware attacks disrupted the delivery of health care, with common disruptions including electronic system downtime (156 [41.7%]), cancellations of scheduled care (38 [10.2%]), and ambulance diversion (16 [4.3%]). From 2016 to 2021, ransomware attacks on health care delivery organizations increasingly affected large organizations with multiple facilities (annual marginal effect [ME], 0.08; 95% CI, 0.05-0.10; P < .001), exposed the PHI of more patients (ME, 66 385.8; 95% CI, 3400.5-129 371.2; P = .04), were less likely to be restored from data backups (ME, -0.04; 95% CI, -0.06 to -0.01; P = .002), were more likely to exceed mandatory reporting timelines (ME, 0.06; 95% CI, 0.03-0.08; P < .001), and increasingly were associated with delays or cancellations of scheduled care (ME, 0.02; 95% CI, 0-0.05; P = .02). Conclusions and Relevance: This cohort study of ransomware attacks documented growth in their frequency and sophistication. Ransomware attacks disrupt care delivery and jeopardize information integrity. Current monitoring/reporting efforts provide limited information and could be expanded to potentially yield a more complete view of how this growing form of cybercrime affects the delivery of health care.
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“Ransomware cyberattacks on healthcare delivery organizations (HDOs) are increasing in frequency and sophistication (1).”
From Ransomware Cyberattack Associated With Cardiac Arrest Incidence and Outcomes at Untargeted, Adjacent Hospitals (2024) · cites this paper as [1]
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Cites
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Gordon, W. J., Wright, A. T., Aiyagari, R. M., Corbo, L., Glynn, R. J., Kadakia, J., Kufahl, J., Mazzone, C., Noga, J., Parkulo, M. A., et al. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.0393 · Cited by 81
Temporal trends and characteristics of reportable health data breaches, 2010-2017
McCoy, T. H., & Perlis, R. H. (2018) · JAMA · doi:10.1001/jama.2018.9222 · Cited by 62
Health Information Technology for Economic and Clinical Health Act
(2011) · NASN School Nurse · doi:10.1177/1942602x10390377 · Cited by 52
Hospital risk of data breaches
Bai, G., Jiang, J. (., & Flasher, R. (2017) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2017.0336 · Cited by 51
Data breach locations, types, and associated characteristics among US hospitals.
Gabriel, M. H., Noblin, A. M., Rutherford, A. E., Walden, A., & Cortelyou-Ward, K. H. (2018) · PubMed · Cited by 45
Types of Information Compromised in Breaches of Protected Health Information
Jiang, J. (., & Bai, G. (2020) · Annals of Internal Medicine · doi:10.7326/m19-1759 · Cited by 21
Your Money or Your Patient's Life? Ransomware and Electronic Health Records
Cohen, I. G., Hoffman, S., & Adashi, E. Y. (2017) · Annals of Internal Medicine · doi:10.7326/m17-1312 · Cited by 14
Beyond Security Patches—Fundamental Incentive Problems in Health Care Cybersecurity
Kanter, G. P., Kufahl, J., & Cohen, I. G. (2021) · JAMA Health Forum · doi:10.1001/jamahealthforum.2021.2969 · Cited by 4
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Jahed, F., Rosenzweig, C., Grün, K., Werner, P., Ostermann, M., Akdeniz, E. E., Gilbert, S., & Freyer, O. (2026) · Journal of Medical Internet Research · doi:10.2196/103202
Ojo, A., Yusuff, A., Ogunniran, A. E., Adeniji, Y. J., Matope, E. M., & Olawade, D. B. (2026) · Intelligent Hospital · doi:10.1016/j.inhs.2026.100110
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Mushedhe, A., & Ijiga, O. M. (2026) · International Journal of Innovative Science and Research Technology (IJISRT) · doi:10.38124/ijisrt/26oct623
“Neprash et al. (2022) documented 374 ransomware attacks affecting United States healthcare delivery organizations between 2016 and 2021, with approximately 42 million patients' personal health information exposed and substantial disruption to healthcare operations.”
Metadata
- Authors
- Neprash, H. T., McGlave, C. C., Cross, D. A., Virnig, B. A., Puskarich, M. A., Huling, J. D., Rozenshtein, A. Z., & Nikpay, S. S.
- Affiliations
- University of Minnesota (US)
- University of Florida Health (US)
- Corresponding author
- Neprash, Hannah T.
- ORCID
- Venue
- JAMA Health Forum
- Publisher
- American Medical Association (AMA)
- Published
- 2022-12-29
- Volume
- 3
- Issue
- 12
- Pages
- e224873
- ISSN
- 2689-0186 (ISSN-L)
- PMC
- PMC9856685
- OpenAlex
- W4313325293
- Cited by
- 154
- References
- 8
- Citations by year
- 2026: 49 · 2025: 43 · 2024: 43 · 2023: 19
- FWCI
- 25.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JAMA Health Forum (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Thoreau and American Literature
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Physical Sciences › Computer Science › Software › Advanced Malware Detection Techniques
- Keywords
- ransomware, health care delivery organization, hospitals, clinics, operational disruption, mandatory reporting, ransom negotiation, ransom payments, ambulance diversion, patient safety
- MeSH terms
- Delivery of Health Care, Health Facilities, Hospitals, Humans, Organizations, Cohort Studies
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