Data-Driven and Artificial Intelligence (AI) Approach for Modelling and Analyzing Healthcare Security Practice: A Systematic Review

Data breaches in healthcare continue to grow exponentially, calling for a rethinking into better approaches of security measures towards mitigating the menace. Traditional approaches including technological measures, have significantly contributed to mitigating data breaches but what is still lacking is the development of the “human firewall,” which is the conscious care security practices of the insiders. As a result, the healthcare security practice analysis, modeling and incentivization project (HSPAMI) is geared towards analyzing healthcare staffs’ security practices in various scenarios including big data. The intention is to determine the gap between staffs’ security practices and required security practices for incentivization measures. To address the state-of-the art, a systematic review was conducted to pinpoint appropriate AI methods and data sources that can be used for effective studies. Out of about 130 articles, which were initially identified in the context of human-generated healthcare data for security measures in healthcare, 15 articles were found to meet the inclusion and exclusion criteria. A thorough assessment and analysis of the included article reveals that, KNN, Bayesian Network and Decision Trees (C4.5) algorithms were mostly applied on Electronic Health Records (EHR) Logs and Network logs with varying input features of healthcare staffs’ security practices. What was found challenging is the performance scores of these algorithms which were not sufficiently outlined in the existing studies

SecHealth: enhancing EHR security in digital health transformation.

In the contemporary wave of digital transformation, the implementation of electronic health records (EHRs) has become a pivotal undertaking for numerous nations. However, amidst this technological advancement, a critical facet deserving heightened attention is the security and privacy of these electronic health systems. Regrettably, this crucial concern often finds itself eclipsed by other aspects of digitalization. Consequently, these oversight lapses create vulnerabilities within the EHR framework, leaving them open and exposed to an array of malicious cyber intrusions. In response to this pressing issue, our study delves into a comprehensive evaluation of security measures within the ambit of African digital health strategies. Remarkably, among the number of approximately 42 nations that have embarked on digital health strategy formulation, a mere 2 countries have taken cognizance of the imperative to integrate robust security and privacy policies into their healthcare-oriented digital transformation initiatives. In light of this disconcerting revelation, we present an actionable roadmap that endeavours to fortify EHR security, aligning with the progressive "shift-left" paradigm. By advocating for the proactive integration of security measures from the inception of EHR development, we strive to curtail vulnerabilities and enhance the overall resilience of these systems. Our proposed roadmap stands as a clarion call for governments, healthcare authorities, and technology stakeholders to collectively prioritize security in tandem with digital health advancement, thereby fostering a safeguarded and privacy-respecting electronic healthcare landscape

HEALER2: a framework for secure data lake towards healthcare digital transformation efforts in low and middle-income countries.

Low and middle-income countries are vigorously digitizing their operations in the healthcare sector as steps in the digital transformation journey. However, some of the basic principles in information security are being skipped. This has a tendency to introduce fundamental vulnerabilities in the core foundation of their healthcare IT infrastructure. This paper, therefore, assessed e-health strategies in Africa and proposed a data lake framework for healthcare IT infrastructure which is deemed secure, privacy-preserving and economically efficient

Ethics & AI: A systematic review on ethical concerns and related strategies for designing with AI in healthcare

In modern life, the application of artificial intelligence (AI) has promoted the implementation of data-driven algorithms in high-stakes domains, such as healthcare. However, it is becoming increasingly challenging for humans to understand the working and reasoning of these complex and opaque algorithms. For AI to support essential decisions in these domains, specific ethical issues need to be addressed to prevent the misinterpretation of AI, which may have severe consequences for humans. However, little research has been published on guidelines that systematically addresses ethical issues when AI techniques are applied in healthcare. In this systematic literature review, we aimed to provide an overview of ethical concerns and related strategies that are currently identified when applying AI in healthcare. The review, which followed the PRISMA guidelines, revealed 12 main ethical issues: justice and fairness, freedom and autonomy, privacy, transparency, patient safety and cyber security, trust, beneficence, responsibility, solidarity, sustainability, dignity, and conflicts. In addition to these 12 main ethical issues, we derived 19 ethical sub-issues and associated strategies from the literature.</p

Models for providing improved care in residential care homes: a thematic literature review

This Annotated Bibliography is one output from a review of the available research evidence to support improved care in residential care homes as the needs of older people intensify. Key findings The review identified extremely little published evidence on residential care homes; the research base is almost exclusively related to provision of care in nursing homes. Much of this research is from the US or other non-UK sources. Although it could be argued that some findings are generalisable to the UK residential care context, a systematic process is required to identify which. The literature often makes no distinction between nursing and residential homes; use of generic terms such as ‘care home’ should be avoided. There is considerable international debate in the quality improvement literature about the relationship between quality of care and quality of life in nursing and residential homes. Measures of social care, as well as clinical care, are needed. The centrality of the resident’s voice in measuring quality of life must be recognised. Ethnic minority residents are almost entirely absent from the quality improvement literature. Some clinical areas, internationally identified as key in terms of quality e.g. palliative care, are absent in the general nursing and residential home quality improvement literature. Others such as mental health (dementia and depression), diabetes, and nutrition are present but not fully integrated. Considerable evidence points to a need for better management of medication in nursing homes. Pharmacist medication reviews have shown a positive effect in nursing homes. It is unclear how this evidence might relate to residential care. There is evidence that medical cover for nursing and residential care home residents is suboptimal. Care could be restructured to give a greater scope for proactive and preventive interventions. General practitioners' workload in care homes may be considered against quality-of-care measures. There is US literature on the relationship between nurse staffing and nursing care home quality, with quality measured through clinical-based outcomes for residents and organisational outcomes. Conclusions are difficult to draw however due to inconsistencies in the evidencebase. Hospital admission and early discharge to nursing homes research may not be generalisable to residential care. The quality of inter-institutional transfers and ensuring patient safety across settings is important. To date research has not considered transfer from residential to nursing home care. The literature on district nurse and therapist roles in care homes includes very little research on residential care. Partnership working between district nurses and care home staff appears largely to occur by default at present. There is even less research evidence on therapist input to care homes. Set against the context outlined above, the international literature provides evidence of a number of approaches to care improvement, primarily in nursing homes. These include little discussion of cost-effectiveness other than in telecare. Research is needed in the UK on care improvement in residential homes

Usability analysis of contending electronic health record systems

In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe