Theory-Based Model and Prediction Analysis of Information Security Compliance Behavior in the Saudi Healthcare Sector

Alanazi, Sultan; Anbar, Mohammed; Ebad, Shouki A.; Karuppayah, Shankar; Al-Ani, Hadeer Akram

doi:10.3390/sym12091544

Cited by 17 publications

(11 citation statements)

References 33 publications

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“…Furthermore, factors that impact ISCB are also the determining factors in maintaining the confidentiality of EHRs, as described by Alanazi et al [17]. Such factors include psychological behaviors, religious beliefs, cultural beliefs, personality traits, cost of compliance, norms, technology awareness, and legal issues.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, they demonstrate that neutralization theory may be used to explain behavior that differs from anticipated norms and that it can also be used to predict the medical interns intention to breach hospital privacy rules in the health care sector. In the third study conducted by Alanazi et al [17], the effectiveness of the theory-based model and different information security compliance behavior (ISCB) predictions for health care professionals in the KSA government hospitals were explored. Moderating and uncommon variables (such as morality and religion) affected ISCBs, whereas demographic features (such as marital status, job experiences, and age) had no effect.…”

Section: Confidentiality Compliance Of Hcps and Driving Factors Of Da...mentioning

confidence: 99%

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Patient Confidentiality of Electronic Health Records: A Recent Review of the Saudi Literature

Almaghrabi

Bugis

2022

Dr. Sulaiman Al Habib Med J

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Background Health systems harbor lucrative data that can be targeted for illegal access, thus posing a serious privacy breach. In addition, patients could lose their lives or suffer permanent and irreversible harm due to such unauthorized access to health care data used in treatment. To ensure patient safety, the health care sector must integrate cybersecurity into its operations. Additionally, the health care industry must collaborate to tackle cybercrime and prevent unauthorized access to patient data. With the rapid transition from paper-based health records to electronic health records (EHRs), it is important to study, identify, and address the challenges that confront EHRs to protect patient confidentiality. Aim The main goal of this research was to create a clear picture of the role of EHRs in the health care system of Saudi Arabia regarding patient confidentiality. This work focused on the privacy and confidentiality challenges encountered in adopting EHRs in the health care system, and the advantages of using EHRs in terms of protecting patient confidentiality. Methods This project utilized a systematic literature review approach, and the methodology involved a careful critique of 11 recent articles. Results The confidentiality and privacy of patient data and information must be ensured, because the health care sector in Saudi Arabia is flawed with several security risks that may corrupt the integrity of patient data. The health care system is facing many cybercrimes whereby hackers can gain access to confidential data and patient information. Internal factors such as inexperienced medical personnel have also necessitated EHRs in Saudi Arabia. Health care workers who lack the appropriate skills in handling EHRs may cause breaches of patient data, which in turn may compromise the health and safety of the patients. Conclusion Confidentiality and privacy are critical components of a reliable EHR system. EHR confidentiality has a significant impact on maintaining patient safety and security, thus enhancing patient care in Saudi Arabia. Additionally, challenges such as hackers and data breaches have slowed the adoption process among health care companies in Saudi Arabia.

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Section: Discussionmentioning

confidence: 99%

Section: Confidentiality Compliance Of Hcps and Driving Factors Of Da...mentioning

confidence: 99%

Patient Confidentiality of Electronic Health Records: A Recent Review of the Saudi Literature

Almaghrabi

Bugis

2022

Dr. Sulaiman Al Habib Med J

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“…In contrast, punishments for peer pressures, sanctions, and top management supervision do not matter in this context. Likewise, [67] presented a framework based on eight behavioral theories constructs. They took nine influential variables and tested them with a survey of 433 employees.…”

Section: Intrinsic/extrinsic Motivations and Compliancementioning

confidence: 99%

“…PLS used for model testing 261 participants from a university Dimensions of moral intensity and organization criticality have significant effects on insiders' protection behaviors [27] Quantitative study. SEM used for model and hypothesis testing 206 correct responses were collected from the higher education sector PMT is the best predictor of employees' behavior towards ISPC in the higher education sector [67] Quantitative research design 433 employees participated in this study…”

Section: Authorsmentioning

confidence: 99%

Information Security Behavior and Information Security Policy Compliance: A Systematic Literature Review for Identifying the Transformation Process from Noncompliance to Compliance

et al. 2021

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A grave concern to an organization’s information security is employees’ behavior when they do not value information security policy compliance (ISPC). Most ISPC studies evaluate compliance and noncompliance behaviors separately. However, the literature lacks a comprehensive understanding of the factors that transform the employees’ behavior from noncompliance to compliance. Therefore, we conducted a systematic literature review (SLR), highlighting the studies done concerning information security behavior (ISB) towards ISPC in multiple settings: research frameworks, research designs, and research methodologies over the last decade. We found that ISPC research focused more on compliance behaviors than noncompliance behaviors. Value conflicts, security-related stress, and neutralization, among many other factors, provided significant evidence towards noncompliance. At the same time, internal/external and protection motivations proved positively significant towards compliance behaviors. Employees perceive internal and external motivations from their social circle, management behaviors, and organizational culture to adopt security-aware behaviors. Deterrence techniques, management behaviors, culture, and information security awareness play a vital role in transforming employees’ noncompliance into compliance behaviors. This SLR’s motivation is to synthesize the literature on ISPC and ISB, identifying the behavioral transformation process from noncompliance to compliance. This SLR contributes to information system security literature by providing a behavior transformation process model based on the existing ISPC literature.

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“…Predictive analytics can handle large data sets, for example, cohort data. With predictive analysis, it is possible to establish the general health of a community [1]- [3].…”

Section: Introductionmentioning

confidence: 99%

Predictive Analytics of Selected Datasets using DTREG Data Mining Tool

Megha¹

2020

CIML

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Predictive analytics is making a significant wave in healthcare Industry. Predictive analytics is an analytics offshoot which helps to make future predictions, resulting in more informed decisions. Data is central to accurate predictions. Several concepts like Data Mining, AI (Artificial Intelligence), Machine Learning and statistics need to work in tandem to ensure precise predictions. The main aim of the research work was to analyse the datasets of selected diseases using the DTREG data mining tool. Two datasets namely Alzheimer’s and Breast Cancer were taken from a public repository and analysed. Various algorithms namely single tree, decision tree, tree boost, support vector machine and neural network were studied. The results obtained were interpreted to understand which algorithm works best in each case. Also, the important predictors in each study were recorded. Interpretation of Alzheimer’s and breast cancer data using DTREG revealed neural network as the best algorithm. The significant predictors for Alzheimer’s were estimated as total intracranial blood volume, clinical dementia rating and age, and for breast cancer were uniformity of cell size, cell shape, benign and malignant and clump thickness. Data mining, artificial Intelligence and machine learning can thus be of very good help in determining the line of treatment to be followed by extracting knowledge from such suitable databases. Keyword : Terms—Algorithms, Alzheimer’s, Breast Cancer, DTREG

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Theory-Based Model and Prediction Analysis of Information Security Compliance Behavior in the Saudi Healthcare Sector

Cited by 17 publications

References 33 publications

Patient Confidentiality of Electronic Health Records: A Recent Review of the Saudi Literature

Patient Confidentiality of Electronic Health Records: A Recent Review of the Saudi Literature

Information Security Behavior and Information Security Policy Compliance: A Systematic Literature Review for Identifying the Transformation Process from Noncompliance to Compliance

Predictive Analytics of Selected Datasets using DTREG Data Mining Tool

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