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This study aims to investigate the adoption and use of electronic health record systems (EHRS) in Tanzanian public primary healthcare institutions. The study’s objectives include understanding the factors that affect EHRS adoption, identifying implementation challenges and evaluating the effect of EHRS usage on healthcare delivery. By addressing these research goals, the study aims to contribute insightful information on the current level of EHRS adoption in Tanzanian primary healthcare facilities and contribute to developing strategies to improve EHRS deployment and healthcare in the nation.

This study combined quantitative and qualitative data using a mixed-methods methodology. Both data types were collected and analysed concurrently using a concurrent triangulation approach. The study aimed to comprehend the variables that affect the adoption and use of EHRS in Tanzanian public primary healthcare institutions. Eleven regions spanning various geographic locations and urban–rural dynamics were chosen as research sites. A survey of 122 healthcare employees was conducted with a sample of 31 healthcare facilities. The questionnaire had closed-ended and open-ended questions to gather quantitative and qualitative data. Descriptive statistics and thematic analysis were used in data analysis. Throughout the investigation, ethical standards and confidentiality precautions were observed.

Several factors affect the adoption and use of EHRS. Perceived usefulness and use, support and training, interoperability, data security and privacy, business culture and leadership are all factors. Inadequate infrastructure, power interruptions, duplication of effort and a lack of data analytic expertise were among the difficulties. Among the effects were improvements in data management, service delivery and coordination, productivity and efficiency, medical supply inventory control, billing and revenue collection.

This study, which complements earlier research that has concentrated chiefly on specialised healthcare settings, gives new insights by investigating the adoption and utilisation of EHRS, especially in primary healthcare institutions. The findings give policymakers and healthcare professionals in Tanzania and other nations vital information to help them decide whether to embrace and use EHRS in primary healthcare.

This study investigates the pathways for adopting IoTs and BDA technologies to improve healthcare management.

The study relied on 445 healthcare professionals' perspectives to explore different causal pathways to IoTs and BDA adoption and usage for daily healthcare management. The Fussy-set Qualitative Comparative Analysis was adopted to explore the underlying pathways for healthcare management.

The empirical analysis revealed six different configural paths influencing the acceptance and use of IoTs and BDA for healthcare improvement. Two key user topologies from the six configural paths, digital literacy and ease of use and social influence and behavioural intentions, mostly affect the paths for using digital health technologies by healthcare physicians.

Despite this study's novel contributions, limitations include the fsQCA methodology, perceptual data and the context of the study. The fsQCA methodology is still evolving with different interpretations, although it reveals new insights and as such further studies are required to explain the configural paths of social phenomena. Additionally, future research should consider other constructs beyond the UTAUT and digital literacy to illustrate configural paths to healthcare technology acceptance and usage. Again, the views of healthcare professionals are perceptual data. Hence future research on operational data will support significant contributions towards pathways to accept and use emerging technologies for healthcare improvement. Lastly, this study is from a developing country perspective where emerging digital healthcare technology is still emerging to support healthcare management. Hence, more investigation from other cross-country analyses of configural paths for digital technology deployment in healthcare will enhance the conversation with IoTs and BDA for healthcare management.

Holistically, the acceptance and use of healthcare technologies and platforms is not solely on their capabilities, but a combination of distinct factors driven by users' perspectives. This offers healthcare administrators and institutions to essentially reflect on the distinct combinations of conditions favourable to health professionals who can use IoTs and BDA for healthcare improvement.

This study is among the few scholarly works to empirically investigate the configural paths to support healthcare improvement with emerging technologies. Using fsQCA is a unique contribution to existing information system literature for configural paths for healthcare improvement with emerging digital technologies.

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.

Norway, like other welfare states, seeks to leverage data to transform its pressured public healthcare system. While managers will be central to doing so, we lack knowledge about how specifically they would do so and what constraints and expectations they operate under. Public sources, like the Norwegian policy documents investigated here, provide important backdrops against which such managerial work emerges. This article therefore aims to analyze how key Norwegian policy documents construe data use in health management.

We analyzed five notable policy documents using a “practice-oriented” framework, considering these as arenas for “organizing visions” (OVs) about managerial use of data in healthcare organizations. This framework considers documents as not just texts that comment on a topic but as discursive tools that formulate, negotiate and shape issues of national importance, such as expectations about data use in health management.

The OVs we identify anticipate a bold future for health management, where data use is supported through interconnected information systems that provide relevant information on demand. These OVs are similar to discourse on “evidence-based management,” but differ in important ways. Managers are consistently framed as key stakeholders that can benefit from using secondary data, but this requires better data integration across the health system. Despite forward-looking OVs, we find considerable ambiguity regarding the practical, social and epistemic dimensions of data use in health management. Our analysis calls for a reframing, by moving away from the hype of “data-driven” health management toward an empirically-oriented, “data-centric” approach that recognizes the situated and relational nature of managerial work on secondary data.

By exploring OVs in the Norwegian health policy landscape, this study adds to our growing understanding of expectations towards healthcare managers' use of data. Given Norway's highly digitized health system, our analysis has relevance for health services in other countries.

This study aims to identify several perspectives that affect the adoption of blockchain technology in India (BCTA) and evaluate their impact. To study the sector’s influence on adoption and the impact of BCTA on the performance of the Indian healthcare supply chain (HSCP) using BCTA as a mediating variable.

In this study, we first developed a conceptual model based on Organizational Information Processing Theory and Technology-Organization-Environment, then formulated hypotheses. Based on this, a questionnaire was developed, and data were gathered from experts in the Indian healthcare industry who were familiar with blockchain technology. AMOS 19 was used to analyze data using structural equation modelling.

All the factors have a significant positive influence on BCTA. Healthcare supply chain factors influenced the adoption most dominantly, followed by technological, environmental, organizational and record-keeping unit factors. Both the public and private sectors of HSCP benefited significantly from BCTA.

This research work is fruitful for healthcare practitioners, top management, academicians and policymakers in assessing BCTA’s impact on the HSCP.

We have attempted to evaluate the possible BCTA impact on HSCP. BCTA as a mediating variable and considering different perspectives for a holistic view of adoption in the Indian context add to this work’s originality.

Purpose: This study investigates the role of telemedicine in sustaining healthcare systems in Europe, during the COVID-19 pandemic. It focusses on how telemedicine serves as a strategic response to modern healthcare challenges, emphasising its efficiency, accessibility, and patient-centred nature.

Need for the study: The need for this study arises from the escalating demands on healthcare systems, especially during the COVID-19 pandemic. It aims to understand the adoption of telemedicine practices across European Union (EU) countries and their impact on healthcare sustainability.

Methodology: This study employs hierarchical and K-Means clustering to analyse EU citizens’ attitudes towards teleconsultations during COVID-19. Principal component analysis (PCA) is used for data compression and insight extraction. Data is sourced from Eurofound’s 2020 and 2021 surveys, involving extensive participant responses across the EU.

Findings: The study’s findings reveal significant shifts towards digital healthcare solutions, such as an increase in online consultations and prescriptions. It identifies different patterns of telemedicine use across EU countries, influenced by socioeconomic and geographical factors. These findings offer insights into future healthcare policy and strategy development.

Practical implications: The findings provide valuable insights into the shifts in telemedicine adoption in the EU, highlighting the significance of economic and sociological factors in healthcare trends. This study stresses the importance of customising healthcare strategies to suit the unique needs and digital capabilities of different countries.

This paper aims to focus on the involvement of mental healthcare professionals in a co-design process of a digital healthcare platform. Many people with severe mental disorders need constant support and monitoring, and with long waiting lists and scarce resources in mental healthcare, there is a dire need for innovative digital solutions to counteract those issues. This paper elaborates on a co-design process of a digital platform and mobile app designed for people with mental disorders. The platform primarily considers two perspectives: i) the patients and ii) the healthcare professionals.

This paper is based on canonical action research, where the co-design involvement with 13 healthcare professionals is analyzed and their interactions with three primary scenarios are focused.

The main contribution of this paper is three co-design principles: i) clarity and information accessibility regarding the patient's side, ii) efficiency and flexibility when it comes to the healthcare professional's side and iii) a notification function in the mobile application.

The theoretical contribution is the conceptualization of the three co-design principles that others can use when designing digital platforms in healthcare in general and psychiatric care in particular. The practical contributions are firstly outlined through the co-design process itself, where scenarios to guide the work are used, and secondly, the improvements made in the digital platform derived from the results of the co-design process.

The aim of this paper is to analyse how technological innovations in performance measurement systems make it possible to overcome some of the challenges that public healthcare organizations face where management and control are concerned. The changes that could be applied to the performance measurement system of healthcare organisations were analysed together with an evaluation of the responses developed in order to achieve these changes.

The paper contains an in-depth case-study of a public university hospital which utilises an innovative information system.

The case-study highlights how technological innovations in performance measurement systems impact the management and monitoring information system in a public university hospital, through the implementation of a multidimensional management dashboard.

The limitation of this paper is that only one case-study is analysed, albeit in depth, while it would be interesting to consider more public university hospitals.

The paper highlights the fundamental role of middle management in change processes in the healthcare sector.

The case-study highlights how critical the active involvement of middle management is in performance measurement and management, and how this is achieved thanks to the adoption of a simple, clear method which ensures comprehensible communication of the objectives, as well as the measurement of performance by means of radar plots.

Data breaches in the US healthcare sector have more than tripled in the last decade across all states. However, to this day, no established framework ranks all states from most to least at risk for healthcare data breaches. This gap has led to a lack of proper risk identification and understanding of cyber environments at state levels.

Based on the security action cycle, the National Institute of Standards and Technology (NIST) cybersecurity framework, the risk-planning model, and the multicriteria decision-making (MCDM) literature, the paper offers an integrated multicriteria framework for prioritization in cybersecurity to address this lack and other prioritization issues in risk management in the field. The study used historical breach data between 2015 and 2021.

The findings showed that California, Texas, New York, Florida, Indiana, Pennsylvania, Massachusetts, Minnesota, Ohio, and Georgia are the states most at risk for healthcare data breaches.

The findings highlight each US state faces a different level of healthcare risk. The findings are informative for patients, crucial for privacy officers in understanding the nuances of their risk environment, and important for policy-makers who must grasp the grave disconnect between existing issues and legislative practices. Furthermore, the study suggests an association between positioning state risk and such factors as population and wealth, both avenues for future research.

Theoretically, the paper offers an integrated framework, whose basis in established security models in both academia and industry practice enables utilizing it in various prioritization scenarios in the field of cybersecurity. It further emphasizes the importance of risk identification and brings attention to different healthcare cybersecurity environments among the different US states.

The aim of this study is to explore how financial inclusion can impact healthcare access in developing countries using panel data for the period 2004–2022.

To check the impact of financial inclusion on healthcare access, the estimation techniques used are the fixed-effect model (FEM), two-stage least squares (2SLS) and the system generalized method of moments (GMM). The data were collected from different websites such as the World Development Indicators (WDI), the United Nations International Children's Emergency Fund (UNICEF) and the United Nations Educational, Scientific and Cultural Organization (UNESCO).

It is found in the study that financial inclusion has a significant positive effect on healthcare access, and it is also confirmed from previous literature results. The study found that if there are high financial services in the countries, healthcare sectors can be improved by timely facilities, care and funds. Proper development of financial services could be possible by conducting awareness initiatives, financial planning and implementing literacy programs to educate individuals, particularly in rural and underdeveloped areas. According to the results, trade openness and foreign direct investment have a positive impact on healthcare access, while urbanization has negatively influenced healthcare access.

The limitations of this study were restricted to only 29 developing countries. The main reason behind the lack of availability of data insurance data for developing countries was the limitation in generalizing the results.

The government and policymakers must check what are the best financial inclusion programs and policies that can be implemented to improve healthcare access. Previous literature does not show visibly the impact of financial inclusion’s dimensions on healthcare access.

This study presents a pioneering examination of financial inclusion and healthcare in 29 lower- and middle-income countries (developing countries). This study has used a comprehensive financial inclusion index of 29 developing countries to cover the overall impact of financial inclusion on healthcare in these countries.