Modeling Cyber Attack Impacts on Patient Outcomes

模拟网络攻击对患者治疗结果的影响

• 批准号: 10606519
• 负责人: Christian Dameff
• 金额: $ 16.07万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2023-09-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10606519
• 关键词: Acceleration; Address; Alteplase; Antibiotics; Clinical; Clinical Research; Computer software; Creativeness; Data; Data Compromising; Dependence; Development; Diagnosis; Diagnostic; Discipline; Electronic Health Record; Event; Failure; Fostering; Foundations; Frequencies; Goals; Health; Health protection; Healthcare; Heart; Hospitals; Hypersensitivity; Infrastructure; Injections; Internet; Interruption; Ischemic Stroke; Knowledge; Knowledge acquisition; Laboratories; Life; Literature; Measures; Medical Device; Mentors; Methods; Mission; Modeling; Morbidity - disease rate; Myocardial Infarction; Outcome; Patient Care; Patient-Focused Outcomes; Patients; Persons; Preparation; Process; Proliferating; Public Health; Quality-Adjusted Life Years; Radiology Specialty; Research; Research Personnel; Risk; Scientific Advances and Accomplishments; Security; Sepsis; Services; Severities; Stroke; System; Technology; Testing; Theft; Therapeutic; Time; Training; United States National Institutes of Health; Work; X-Ray Computed Tomography; base; career; clinical care; computerized; connected care; cyber security; data integrity; data-driven model; digital; health care delivery; health care model; health data; improved; innovation; mortality; novel; patient population; patient privacy; patient safety; resilience; risk minimization; simulation; software systems; usability

ABSTRACT SUMMARY Over the last 25 years, healthcare has undergone significant digital transformation resulting in an increasing and near total dependence on technology to deliver clinical care. Despite this rapid acceleration of technology deployment, the protection of these systems from adversaries such as malicious hackers (a practice which constitutes the discipline of cybersecurity) has not matched the pace and ubiquity of technological advances. Cyber attacks on healthcare have been increasing in frequency and severity, resulting in many public examples of compromised clinical care, lost revenue, and breaches of protected health information. Furthermore, a vast majority of the nascent healthcare cybersecurity literature focuses on the protection of patient health data, and ignores the risks cyber attacks pose to patient safety and clinical outcomes. The long term goal is to understand the negative impacts of cyber attacks on patient outcomes including morbidity and mortality. The overall objective of this application is to identify which clinical workflows, medical devices, software systems, and other digitized hospital infrastructure present the greatest potential harm to patients when Integrity and Availability cyber attacks are used by malicious hackers. The central hypothesis is that data-driven models of cyber attacks on healthcare can identify processes and clinical workflows most vulnerable to negatively impacting patient outcomes. The rationale for this project is that its models will help create a foundational base of healthcare cybersecurity knowledge, without which targets in need of increased cybersecurity measures will remain unknown. The acquisition of this knowledge will change the healthcare security paradigm to include both a more holistic understanding of cybersecurity risks but also one that considers the patient safety and outcome impacts of cyber attacks. This project has two specific aims: (1) Develop healthcare cyber attack models where the integrity of patient data has been compromised; and (2) Develop healthcare cyber attack models where the availability of critical technical systems are impacted. The first aim will utilize microsimulation to model patient care in a hospital undergoing integrity cyber attacks that maliciously modify diagnostic and therapeutic data. The second aim will also utilize microsimulation but will model the care of patients in hospitals undergoing availability cyber attacks such as Ransomware which render certain technical systems inoperable. Both aims will model the care of patients presenting with stroke, myocardial infarction, and sepsis. The proposed research in this application is innovative, because it is the first known attempt to formally model the impacts cyber attacks have on patient outcomes. The proposed research is significant because it is expected to provide a strong theoretical foundation to justify further clinical studies of cyber attack patient outcome impacts, including empirical studies on real patient populations. Additionally, accurate and usable models of healthcare cyber attacks can give stakeholders the critical information they need to properly defend digital infrastructure from malicious hackers, minimizing risk to patient safety.

摘要摘要 在过去的25年中，医疗保健经历了重大的数字化转型，导致增加 几乎完全依赖于提供临床护理的技术。尽管技术的迅速加速 部署，保护这些系统免受恶意黑客等对手的保护（这种做法 构成网络安全的纪律）与技术进步的速度和无处不在。 网络对医疗保健的攻击的频率和严重程度一直在增加，导致许多公众 临床护理，收入损失和违反受保护的健康信息的示例。 此外，绝大多数新生的医疗保健网络安全文献侧重于保护 患者健康数据，忽略了网络攻击的风险对患者的安全性和临床结果构成构成。长 术语目标是了解网络攻击对患者结局的负面影响，包括发病率和 死亡。该应用程序的总体目的是确定哪些临床工作流程，医疗设备， 软件系统和其他数字化医院基础设施对患者造成了最大的潜在危害 恶意黑客使用完整性和可用性网络攻击时。中心假设是 数据驱动的网络攻击对医疗保健的模型可以识别过程和临床工作流程大多数 容易对患者的结果产生负面影响。该项目的理由是其模型将有所帮助 建立医疗保健网络安全知识的基础基础，没有需要增加的目标 网络安全措施将仍然未知。获取这些知识将改变医疗保健 安全范式既包括对网络安全风险的更全面的理解，又包括一个 考虑了患者的安全性和网络攻击的结果影响。该项目有两个具体的目标：（1） 开发医疗保健网络攻击模型，其中患者数据的完整性已被妥协； （2） 开发医疗保健网络攻击模型，其中关键技术系统的可用性受到影响。这 第一个目的将利用微仿真在接受完整性网络攻击的医院中对患者护理进行建模 恶意修改诊断和治疗数据。第二个目标还将利用微仿真，但将 模拟正在经历可用网络攻击的医院中患者的护理，例如勒索软件 某些无法操作的技术系统。这两个目标都将模拟出现中风的患者的护理， 心肌梗塞和败血症。本应用程序中拟议的研究具有创新性，因为它是第一个 已知的尝试正式建模网络攻击对患者结局的影响。拟议的研究 之所以重要，是因为预计将为进一步的临床研究提供强大的理论基础 网络攻击患者的结果影响，包括对实际患者人群的实证研究。此外， 准确且可用的医疗保健网络攻击模型可以为利益相关者提供关键信息 需要适当地捍卫数字基础设施免受恶意黑客的影响，从而最大程度地减少患者安全的风险。

项目成果

Design and Pilot Study of a High-Fidelity Medical Simulation of a Hospital-Wide Cybersecurity Attack.

全医院网络安全攻击的高保真医学模拟的设计和试点研究。

• DOI: 10.21203/rs.3.rs-3959502/v1
• 发表时间: 2024
• 期刊: Research square
• 作者: Marsh-Armstrong,Brennan;Pacheco,Fernanda;Dameff,Christian;Tully,Jeffrey
• 通讯作者: Tully,Jeffrey

Hacking Acute Care: A Qualitative Study on the Health Care Impacts of Ransomware Attacks Against Hospitals.

黑客急症护理：针对医院的勒索软件攻击对医疗保健影响的定性研究。

• DOI: 10.1016/j.annemergmed.2023.04.025
• 发表时间: 2024
• 期刊: Annals of emergency medicine
• 影响因子: 6.2
• 作者: vanBoven,LiselotteS;Kusters,RenskeWJ;Tin,Derrick;vanOsch,FritsHM;DeCauwer,Harald;Ketelings,Linsay;Rao,Madhura;Dameff,Christian;Barten,DennisG
• 通讯作者: Barten,DennisG

Ransomware Attack Associated With Disruptions at Adjacent Emergency Departments in the US.

• DOI: 10.1001/jamanetworkopen.2023.12270
• 发表时间: 2023-05-01
• 期刊: JAMA NETWORK OPEN
• 影响因子: 13.8
• 作者: Dameff, Christian;Tully, Jeffrey;Chan, Theodore C.;Castillo, Edward M.;Savage, Stefan;Maysent, Patricia;Hemmen, Thomas M.;Clay, Brian J.;Longhurst, Christopher A.
• 通讯作者: Longhurst, Christopher A.