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Information systems (IS) research in general and health IS studies, in particular, are prone to a positivity bias – largely focusing on upside gains rather than the potential misuse practices. This paper aims to explore failures in health IS use and shortcomings in data privacy and cybersecurity and to provide an explanatory model for health record misuse.

This research is based on four data sets that we collected through a longitudinal project studying digital health (implementation, use and evaluation), interviews with experts (cybersecurity and digital health) and healthcare stakeholders (health professionals and managers). We applied qualitative analysis to explain health records misuse from a sociotechnical perspective.

We propose a contextualized model of “health records misuse” with two overarching dimensions: data misfit and improper data processing. We explain sub-categories of data misfit: availability misfit, meaning misfit and place misfit, as well as sub-categories of improper data processing: improper interaction and improper use-related actions. Our findings demonstrate how health records misuse can emerge in sociotechnical health systems and impact health service delivery and patient safety.

Through contextualizing system misuse in healthcare, this research advances the understanding of ineffective use and failures in health data protection practices. Our proposed theoretical model provides explanations for unique patterns of IS misuse in healthcare, where data protection failures are consequential for healthcare organizations and patient safety.

Today, e-government (electronic government) applications have extended to the frontiers of health-care delivery. E-Nabız contains personal health records of health services received, whether public or private. The use of the application by patients and physicians has provided efficiency and cost advantages. The success of e-Nabız depends on the level of technology acceptance of health-care service providers and recipients. While there is a large research literature on the technology acceptance of service recipients in health-care services, there is a limited number of studies on physicians providing services. This study aims to determine the level of influence of trust and privacy variables in addition to performance expectancy, effort expectancy, social influence and facilitating factors in the unified theory of acceptance and use of technology (UTAUT) model on the intention and behavior of using e-Nabız application.

The population of the study consisted of general practitioners and specialist physicians actively working in any health facility in Turkey. Data were collected cross-sectionally from 236 physicians on a voluntary basis through a questionnaire. The response rate of data collection was calculated as 47.20%. Data were collected cross-sectionally from 236 physicians through a questionnaire. Descriptive statistics, correlation analysis and structural equation modeling were used to analyze the data.

The study found that performance expectancy, effort expectancy, trust and perceived privacy had a significant effect on physicians’ behavioral intentions to adopt the e-Nabız system. In addition, facilitating conditions and behavioral intention were determinants of usage behavior (p < 0.05). However, no significant relationship was found between social influence and behavioral intention (p > 0.05).

This study confirms that the UTAUT model provides an appropriate framework for predicting factors influencing physicians’ behaviors and intention to use e-Nabız. In addition, the empirical findings show that trust and perceived privacy, which are additionally considered in the model, are also influential.

This qualitative case study aims to identify and analyse the factors influencing the implementation and effectiveness of electronic health record systems (EHRS) in primary health-care (PHC) facilities in Tanzania. This study aims to explore ways to optimize the use of EHRS for better health-care service delivery.

The study uses a qualitative case study design. Data were collected through interviews and focus groups conducted with health-care workers and information and communication technology officers at the PHC facilities in Tanzania. Purposive sampling and data source triangulation were used to address potential biases and limitations associated with the study’s small sample size.

This study identifies several key findings related to the implementation and effectiveness of EHRS in Tanzanian PHC facilities. The primary obstacles include inadequate technical infrastructure, poor internet connectivity and insufficient financial resources. The study suggests a comprehensive strategy for improving EHRS, emphasizing patient and health-care professional involvement in system design, investments in technical infrastructure and connectivity, data quality and accuracy and ongoing technical support and training.

This research contributes to the existing body of knowledge by offering a nuanced understanding of the Tanzanian health-care context. It emphasizes the need for tailored solutions and strategies specific to the region’s challenges and opportunities. The study’s originality lies in its focus on EHRS in the Tanzanian context, providing valuable insights for future initiatives. A key policy implication underscores the importance of a supportive regulatory framework, dedicated resources and consistent stakeholder communication for successful EHRS implementation.

Due to its ability to support well-informed decision-making, business intelligence (BI) has grown in popularity among executives across a range of industries. However, given the volume of data collected in health-care organizations, there is a lack of exploration concerning its implementation. Consequently, this research paper aims to investigate the key factors affecting the acceptance and use of BI in healthcare organizations.

Leveraging the theoretical lens of the “unified theory of acceptance and use of technology” (UTAUT), a study framework was proposed and integrated with three context-related factors, including “rational decision-making culture” (RDC), “perceived threat to professional autonomy” (PTA) and “medical–legal risk” (MLR). The variables in the study framework were categorized as follows: information systems (IS) perspective; organizational perspective; and user perspective. In Jordan, 434 healthcare professionals participated in a cross-sectional online survey that was used to collect data.

The findings of the “structural equation modeling” revealed that professionals’ behavioral intentions toward using BI systems were significantly affected by performance expectancy, social influence, facilitating conditions, MLR, RDC and PTA. Also, an insignificant effect of PTA on PE was found based on the results of statistical analysis. These variables explained 68% of the variance (R²) in the individuals’ intentions to use BI-based health-care systems.

To promote the acceptance and use of BI technology in health-care settings, developers, designers, service providers and decision-makers will find this study to have a number of practical implications. Additionally, it will support the development of effective strategies and BI-based health-care systems based on these study results, attracting the interest of many users.

To the best of the author’s knowledge, this is one of the first studies that integrates the UTAUT model with three contextual factors (RDC, PTA and MLR) in addition to examining the suggested framework in a developing nation (Jordan). This study is one of the few in which the users’ acceptance behavior of BI systems was investigated in a health-care setting. More specifically, to the best of the author’s knowledge, this is the first study that reveals the critical antecedents of individuals’ intention to accept BI for health-care purposes in the Jordanian context.

This research paper aimed to study the legal structure of top-performing health governance systems and compare them with the Indonesian health social security system to identify the main differences and provide recommendations for Indonesian and other developing countries’ health policymakers and administrators.

Using formative research with a conceptual approach and statute approach as method in this study. Data was gathered using the document study technique, which studies various documents, especially legal documents related to health law, linked to legal purpose theories. Moreover, the World Health Organization ranking was considered to choose the two countries (France and Singapore) with a high social health security system for comparative analysis. All data collected has been analyzed using a qualitative and theoretical basis. Content analysis was performed by analyzing the legal documents, and the regulatory framework of all three countries was deeply analyzed to draw conclusions and recommendations.

Indonesia has specific laws to implement a social security system in the health sector. However, the lack of the best medical facilities and infrastructure and weak implementation of existing laws were identified as major reasons behind the poor health security system compared to comparative countries. Also, as a developing nation Indonesian Government face budgetary pressures and huge population challenges to meet required standards. Thus, the financing approaches used by Singapore and France may help developing countries meet these challenges effectively. Therefore, there is a dire need to strengthen the social health security system all over the country with amendments to laws and ensure the implementation of prevailing laws and regulations.

Providing understanding related to the social security health system in Indonesia along with a detailed description of the sound social health security system in France and Singapore will further provide an avenue for the researchers to critically analyze this line of study to devise some valuable suggestions further and to draw loopholes in the system.

A comparative approach for legal studies in the health sector is rare. So, this research advanced the social security health system-related literature and legal studies on the health sector by using this comparative approach to develop policy insights and future research directions, which will further help the field to grow.

The main objective of the study is to address the lack of sustainability assessments of smart connected health systems in the academic literature by presenting an assessment model to determine the alignment of these systems with the 17 Sustainable Development Goals (SDGs) proposed in the 2030 Agenda.

An evaluation model based on decision analysis is proposed that includes three phases: alignment framework, information gathering and assessment. This model measures the alignment of the connected health system with each of the 17 SDGs, identifying the goals and criteria associated with each SDG that the system achieves to satisfy.

The analysis reveals that the system has achieved more than 24% of the targets among the 17 SDGs. In addition, it identifies four sustainability challenges that the system potentially addresses in relation to the SDGs, providing valuable guidance for researchers and practitioners interested in sustainable health technology development.

The study's results have significant implications for policymakers and stakeholders in the health and technology sectors.

The originality of this study lies in its comprehensive approach to assessing the sustainability of connected health systems in the context of the SDGs, filling an important gap in the existing literature.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.

This study investigated two key aspects: (1) how a hospital bundles limited resources for preventive care performance and (2) how to develop IS capabilities to enhance preventive care performance.

A case study method was adopted to examine how a hospital integrates its limited resources which leads to the need for resource bundles and an understanding of IS capabilities development to understand how they contribute to the delivery of preventive care in a Malaysian hospital.

This research proposes a comprehensive framework outlining resource-bundling and IS capabilities development to improve preventive care.

We acknowledge that the problem of transferring and generalizing results has been a common criticism of a single case study. However, our objective was to enhance the reader’s understanding by including compelling, detailed narratives demonstrating how our research results offer practical examples that can be generalized theoretically. The findings also apply to similar-sized public hospitals in Malaysia and other developing countries, facing challenges like resource constraints, HIS adoption levels, healthcare workforce shortages, cultural and linguistic diversity, bureaucratic hurdles, and specific patient demographics and health issues. Further, lessons from this context can be usefully applied to non-healthcare service sector domains.

This study provides a succinct strategy for enhancing preventive care in Malaysian public hospitals, focusing on system integration and alignment with hospital strategy, workforce diversity through recruitment and mentorship, and continuous training for health equity and inclusivity. This approach aims to improve resource efficiency, communication, cultural competence, and healthcare outcomes.

Efficiently using limited resources through HIS investment is essential to improve preventive care and reduce chronic diseases, which cause approximately nine million deaths annually in Southeast Asia, according to WHO. This issue has significantly impacted the socioeconomic development of developing countries.

This research refines resource orchestration theory with new mechanisms for resource mobilization, extends IS literature by identifying how strategic bundling forms specialized healthcare IS capabilities, enriches preventive care literature through actionable resource-bundling activities, and adds to HIS literature by advocating for an integrated, preventive care focus from the alignment of HIS design, people and institutional policies to address concerns raised by other research regarding the utilization of HIS in improving the quality of preventive care.

This article seeks to discuss trust within the context of public health crises using an autopoietic systems perspective that positions communication as one of its core concepts. This article will explore trust studies conducted during public health crises in this Millennium (from SARS to COVID-19 pandemics), including their problems; briefly summarize Luhmann's concept of Vertrauen; and use this concept to analyze trust issues during the COVID-19 pandemic.

This article will explore trust studies conducted during public health crises from SARS to COVID-19 pandemics, including their problems. The perspective used is an explication of Niklas Luhmann's theory regarding Vertrauen which was derived as a framework for reading empirical facts on trust issues during the COVID-19 pandemic. The research design and exploration stages were inspired by the theory of autopoiesis systems by Niklas Luhmann.

From a systems perspective, the COVID-19 pandemic has highlighted the extraordinary complexity of the linkages between social systems. Trust will continue to evolve dynamically as new variants emerge in society. Consequently, the pandemic has provided the momentum necessary for maximally exploring the concept of trust. Indonesia thus experienced significant obstacles when making and implementing disaster mitigation policies. Owing to the lack of a trust system, greater emphasis was given to control and power. There has been little preparedness to create and reinforce public trust, and this in turn has stifled efforts to stop the spread of COVID-19.

This study of trust, communication and public health crises has provided space to reflect on the development of trust within the social system. This study shows that trust can prove to be a very important factor in resolving a crisis. However, the complexity of the interrelationships of the social system can affect the quality of trust. The context of Indonesia's social system which is very complex due to population density and the dynamics of the development of its social system which is very diverse as an archipelagic country has contributed to the originality of the study of trust in times of crisis in a growing contemporary society.

Efficiency and quality are primary factors for the survival of health systems. The evaluation of the efficiency of the healthcare system is a crucial component of promoting long-term health policy actions. Healthcare capacity indicators provide a basis for evaluating and comparing the performance of different healthcare organizations. Intrinsic quality indicators are Donabedian (1980)’s structural and process elements of quality of healthcare. This study aims to integrate capacity and intrinsic quality indicators of healthcare while measuring the efficiency of provinces by using radial and non-radial efficiency measurement techniques.

Efficiency analysis performed in Turkey from 2015 to 2020 by performing input-oriented radial, nonradial, and super-efficiency estimates for 81 provinces of Turkey by incorporating capacity and intrinsic quality indicators into the different model specifications.

Radial and nonradial efficiency results have an increasing trend over the study years obtained from the efficiency models showing high average scores obtained from the models that include intrinsic quality of care indicators. Statistically significant mean rank differences are observed between different radial efficiency models for all study years (p < 0.001). Negative and moderate level correlations were observed between radial efficiency results and quality of care indicators (r < 0.70).

Under long-term centralized health policies, increases in efficiency result in decreased intrinsic quality of care indicators. A better synthesis of health system capacity and intrinsic healthcare quality indicators is necessary to generate evidence-based health systems.