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This paper aims to identify the reasons why cases of leakage of patient personal data often occur in the health sector. This paper also analyzes personal data protection regulations in the health sector from a comparative legal perspective between Indonesia, Singapore and the European Union (EU).

This type of research is legal research. The research approach used is the statute approach and conceptual approach. The focus of this study in this research is Indonesia with a comparative study in Singapore and the EU.

Cases of leakage of patient personal data in Indonesia often occur. In 2021, the data for 230,000 COVID-19 patients was leaked and sold on the Rapid Forums dark web forum. A patient’s personal data is a human right that must be protected. Compared to Singapore and the EU, Indonesia is a country that does not yet have a law on the protection of personal data. This condition causes cases of leakage of patients’ personal data to occur frequently.

This study analyzes the regulation and protection of patients’ personal data in Indonesia, Singapore and the EU to construct a regulatory design for the protection of patients’ personal data.

The results of this study are useful for constructing regulations governing the protection of patients’ personal data. The regulation is to protect the patient’s personal data like a patient’s human right.

The ideal regulatory design can prevent data breaches. Based on the results of comparative studies, in Singapore and the EU, cases of personal data leakage are rare because they have a regulatory framework regarding the protection of patients’ personal data.

Legal strategies that can be taken to prevent and overcome patient data breaches include the establishment of an Act on Personal Data Protection; the Personal Data Protection Commission; and management of patients’ personal data.

Innovation in a decentralized blockchain infrastructure can be used by medicine as a prerequisite for the exchange of patient data. Developments in the medical device industry that support the technology of the internet of things and wireless sensor networks also facilitate the examination of patient medical records that no longer require visits to the practice of doctors or hospitals which in some cases takes in a considerable time. Not to mention the consideration of traffic congestion and busy routine in the work. Patients can check their healthcare concerns using only sensors such as e-Health Sensor Shield Platform which then sends recording results through the transmission line to the data lakes. However, this patient’s medical record data is very confidential and may only be accessed by certain parties only. This required the design of the concept of security in the transmission of data so that the data does not leak to parties who are not eligible. This paper attempts to provide an overview of the concept of using encryption with an asymmetric key for securing data from sensors to data lakes before forwarding to a decentralized, interconnected blockchain infrastructure.

Ireland’s physicians have a legal and an ethical duty to protect confidential patient information. Most healthcare records in Ireland remain paper based, so the purpose of this paper is to: assess the protection afforded to paper records; log highest risk records; note the variations that occurred during the working week; and observe the varying protection that occurred when staff, students and public members were present.

A customised audit tool was created using Sphinx software. Data were collected for three months. All wards included in the study were visited once during four discrete time periods across the working week. The medical records trolley’s location was noted and total unattended medical records, total unattended nursing records, total unattended patient lists and when nursing personnel, medical students, public and a ward secretary were visibly present were recorded.

During 84 occasions when the authors visited wards, unattended medical records were identified on 33 per cent of occasions, 49 per cent were found during weekend visiting hours and just 4 per cent were found during morning rounds. The unattended medical records belonged to patients admitted to a medical specialty in 73 per cent of cases and a surgical specialty in 27 per cent. Medical records were found unattended in the nurses’ station with much greater frequency when the ward secretary was off duty. Unattended nursing records were identified on 67 per cent of occasions the authors visited the ward and were most commonly found unattended in groups of six or more.

This study is a timely reminder that confidential patient information is at risk from inappropriate disclosure in the hospital. There are few context-specific standards for data protection to guide healthcare professionals, particularly paper records. Nursing records are left unattended with twice the frequency of medical records and are found unattended in greater numbers than medical records. Protection is strongest when ward secretaries are on duty. Over-reliance on vigilant ward secretaries could represent a threat to confidential patient information.

While other studies identified data protection as an issue, this study assesses how data security varies inside and outside conventional working hours. It provides a rationale and an impetus for specific changes across the whole working week. By identifying the on-duty ward secretary’s favourable effect on medical record security, it highlights the need for alternative arrangements when the ward secretary is off duty. Data were collected prospectively in real time, giving a more accurate healthcare record security snapshot in each data collection point.

This study aims to assist organizations to protect the privacy of their users and the security of the data that they store and process. Users may be the customers of the organization (people using the offered services) or the employees (users who operate the systems of the organization). To be more specific, this paper proposes a privacy impact assessment (PIA) method that explicitly takes into account the organizational characteristics and employs a list of well-defined metrics as input, demonstrating its applicability to two hospital information systems with different characteristics.

This paper presents a PIA method that employs metrics and takes into account the peculiarities and other characteristics of the organization. The applicability of the method has been demonstrated on two Hospital Information Systems with different characteristics. The aim is to assist the organizations to estimate the criticality of potential privacy breaches and, thus, to select the appropriate security measures for the protection of the data that they collect, process and store.

The results of the proposed PIA method highlight the criticality of each privacy principle for every data set maintained by the organization. The method employed for the calculation of the criticality level, takes into account the consequences that the organization may experience in case of a security or privacy violation incident on a specific data set, the weighting of each privacy principle and the unique characteristics of each organization. So, the results of the proposed PIA method offer a strong indication of the security measures and privacy enforcement mechanisms that the organization should adopt to effectively protect its data.

The novelty of the method is that it handles security and privacy requirements simultaneously, as it uses the results of risk analysis together with those of a PIA. A further novelty of the method is that it introduces metrics for the quantification of the requirements and also that it takes into account the specific characteristics of the organization.

Designing digital artifacts is not a linear, straightforward process. This is particularly true when applying a user-centered design approach, or co-design, with users who are unable to participate in the design process. Although the reduced participation of a particular user group may harm the end result, the literature on solving this issue is sparse. In this article, proxy design is outlined as a method for involving a user group as proxy users to speak on behalf of a group that is difficult to reach. The article investigates the following research question: How can roleplaying be embedded in co-design to engage users as proxies on behalf of those who are unable to represent themselves?

The article presents a design ethnography spanning three years at a cancer rehabilitation clinic, where digital artifacts were designed to be used collaboratively by nurses and patients. The empirical data were analyzed using content analysis and consisted of 20 observation days at the clinic, six proxy design workshops, 21 telephone consultations between patients and nurses, and log data from the digital artifact.

The article shows that simulated consultations, with nurses roleplaying as proxies for patients ignited and initiated the design process and enabled an efficient in-depth understanding of patients. Moreover, the article reveals how proxy design as a method further expanded the design. The study findings illustrate: (1) proxy design as a method for initiating design, (2) proxy design as an embedded element in co-design and (3) six design guidelines that should be considered when engaging in proxy design.

The main contribution is the conceptualization of proxy design as a method that can ignite and initiate the co-design process when important users are unreachable, vulnerable or unable to represent themselves in the co-design process. More specifically, based on the empirical findings from a design ethnography that involved nurses as proxy users speaking on behalf of patients, the article shows that roleplaying in proxy design is a fitting way of initiating the design process, outlining proxy design as an embedded element of co-design.

Value creation based on artificial intelligence (AI) can significantly change global healthcare. Diagnostics, therapy and drug discovery start-ups are some key forces behind this change. This article aims to study the process of start-ups' value creation within healthcare.

A multiple case study method and a business model design approach were used to study nine European start-ups developing AI healthcare solutions. Obtained information was performed using within and cross-case analysis.

Three unique design elements were established, with 16 unique frames and three unifying design themes based on business models for AI healthcare start-ups.

Our in-depth framework focuses on the features of AI start-up business models in the healthcare industry. We contribute to the business model and business model innovation by systematically analyzing value creation, how it is delivered to customers, and communication with market participants, as well as design themes that combine start-ups and categorize them by specialization.

This paper has proposed a Fog architecture-based framework, which classifies dengue patients into uninfected, infected and severely infected using a data set built in 2010. The aim of this proposed framework is to developed a latency-aware system for classifying users into different categories based on their respective symptoms using Internet of Things (IoT) sensors and audio and video files.

To achieve the aforesaid aim, a smart framework is proposed, which consist of three components, namely, IoT layer, Fog infrastructure and cloud computing. The latency of the system is reduced by using network devices located in the Fog infrastructure. Data generated by IoT layer will first be processed by Fog layer devices which are in closer proximity of the user. Raw data and data generated will later be stored on cloud infrastructure, from where it will be sent to different entities such as user, hospital, doctor and government healthcare agencies.

Experimental evaluation proved the hypothesis that using the Fog infrastructure can achieve better response time for latency sensitive applications with the least effect on accuracy of the system.

The proposed Fog-based architecture can be used with IoT to directly link it with the Fog layer.

Healthcare policies around the globe are aimed at achieving patient-centeredness. The patient is understood as a prosumer of healthcare, wherein healthcare service co-production and value co-creation take center stage. The article endeavors to unpack the state of the literature on the innovations promoting the transition toward patient-centeredness, informing policy and management interventions fostering the reconceptualization of the patient as a prosumer of healthcare services.

A hybrid review methodology consisting of a bibliometric-interpretive review following the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol is used. The bibliometric component enabled us to objectively map the extant scientific knowledge into research streams, whereas the interpretive component facilitated the critical analysis of research streams.

Patient-centeredness relies on a bundle of innovations that are enacted through a cycle of patients' activation, empowerment, involvement and engagement, wherein the omission of any steps arrests the transition toward service co-production and value co-creation. Institutional, organizational and cognitive barriers should be overcome to boost the transition of patients from consumers to prosumers in a patient-centered model of healthcare.

The article delivers the state of the art of the scientific literature in the field of innovations aimed at sustaining the transition toward patient-centeredness and provides some food for thoughts to scholars and practitioners who wish to push forward service co-production and value co-creation in healthcare.

Nowadays, the digitized economy and technological advancements are increasing at a faster pace. One such technology that is gaining popularity in the healthcare sector is Artificial Intelligence (AI). AI has been debated much, searched so well due to the implications, issues and for its benefits in terms of ease, it will offer. The following research has focused on examining the ethical dilemmas associated with AI when it will be introduced in the healthcare sector.

A narrative review method focusing on content analysis has been used in the research. The authors have employed a deductive approach to determine the ethical facets of adopting AI in the healthcare sector. The current study is complemented by a review of related studies. The secondary data have been collected from authentic resources available on the Internet.

Patient privacy, biased results, patient safety and Human errors are some major ethical dilemmas that are likely to be faced once AI will be introduced in healthcare. The impact of ethical dilemmas can be minimized by continuous monitoring but cannot be eliminated in full if AI is introduced in healthcare. AI overall will increase the performance of the healthcare sector. However, we need to address some recommendations to mitigate the ethical potential issues that we could observe using AI. Technological change and AI can mimic the overall intellectual process of humans, which increases its credibility and also offers harm to humans.

Patient safety is the most crucial ethical concern because AI is a new technology and technology can lead to failure. Thus, we need to be certain that these new technological developments are ethically applied. The authors need to evaluate and assess the organizational and legal progress associated with the emergence of AI in the healthcare sector. It also highlights the importance of covering and protecting medical practitioners regarding the different secondary effects of this artificial medical progress. The research stresses the need of establishing partnerships between computer scientists and clinicians to effectively implement AI. Lastly, the research highly recommends training of IT specialists, healthcare and medical staff about healthcare ethics.

Competitive pressure and social influence for technology adoption have increased among developed, developing and emerging countries. The influence of social structure, organizational forces and political forces varies between public sector hospitals in countries where there are more social media restrictions. This study aims to explore how the use of social media can influence employee engagement and productivity in the workplaces of public sector hospitals.

The study follows a social constructivist approach to understand employee attitudes, motivation culture, political forces and the local context. Data were collected from health professionals of five public sector hospitals using a non-directive and semi-structured interview method.

The results show that the use of social media sites has increased collaboration, coordination and cooperation among health professionals, especially in critical situations. They are more socialized, connected and engaged, thus helping them to exchange useful knowledge using instant messaging apps. Conversely, there are no organizational polices and specific laws and too little support from management and senior doctors to drive the use of social networking sites in public hospitals. The use of social media has enhanced health professionals' engagement and productivity as they are able to share their expertise, knowledge and information with their colleagues and subordinates.

The results can guide policy-makers, researchers, hospitals, doctors and the Ministry of Health about the positive use of social networking sites in the workplace. The positive use of social networking sites in the workplace can enhance information, knowledge and coordination which may help to enhance employee engagement and productivity.

The present study has provided a social media health organization workplace (SMHOW) model which explains how individual and organizational contexts can influence the actual use of social media in healthcare organizations.