Rethinking the Meaning of Cloud Computing for Health Care: A Taxonomic Perspective and Future Research Directions

Gastroenterology in the Metaverse: The dawn of a new era?

2021 is known as the first Year of the Metaverse, and around the world, internet giants are eager to devote themselves to it. In this review, we will introduce the concept, current development, and application of the Metaverse and the use of the current basic technologies in the medical field, such as virtual reality and telemedicine. We also probe into the new model of gastroenterology in the future era of the Metaverse.

Electronic Medical Records for (Visceral) Medicine: An Overview of the Current Status and Prospects

Background

Electronic medical records (EMRs) offer key advantages over analog documentation in healthcare. In addition to providing details about current and past treatments, EMRs enable clear and traceable documentation regardless of the location. This supports evidence-based, multi-professional treatment and leads to more efficient healthcare. However, there are still several challenges regarding the use of EMRs. Understanding these challenges is essential to improve healthcare. The aim of this article is to provide an overview of the current state of EMRs in the field of visceral medicine, to describe the future prospects in this field, and to highlight some of the challenges that need to be faced.

Summary

The benefits of EMRs are manifold and particularly pronounced in the area of quality assurance and improvement of communication not only between different healthcare professionals but also between physicians and patients. Besides the danger of medical errors, the health consequences for the users (cognitive load) arise from poor usability or a system that does not fit into the real world. Involving users in the development of EMRs in the sense of participatory design can be helpful here. The use of EMRs in practice together with patients should be accompanied by training to ensure optimal outcomes in terms of shared decision-making.

Key Message

EMRs offer a variety of benefits. However, it is critical to consider user involvement, setting specificity, and user training during development, implementation, and use in order to minimize unintended consequences.

An Update for Taxonomy Designers

Taxonomies are classification systems that help researchers conceptualize phenomena based on their dimensions and characteristics. To address the problem of ‘ad-hoc’ taxonomy building, Nickerson et al. (2013) proposed a rigorous taxonomy development method for information systems researchers. Eight years on, however, the status quo of taxonomy research shows that the application of this method lacks consistency and transparency and that further guidance on taxonomy evaluation is needed. To fill these gaps, this study (1) advances existing methodological guidance and (2) extends this guidance with regards to taxonomy evaluation. Informed by insights gained from an analysis of 164 taxonomy articles published in information systems outlets, this study presents an extended taxonomy design process together with 26 operational taxonomy design recommendations. Representing an update for taxonomy designers, it contributes to the prescriptive knowledge on taxonomy design and seeks to augment both rigorous taxonomy building and evaluation.

A telediagnosis assistance system for multiple-lead electrocardiography

The diffusion of telemedicine opens-up a new perspective for the development of technologies furthered by Biomedical Engineering. In particular, herein we deal with those related to telediagnosis through multiple-lead electrocardiographic signals. This study focuses on the proof-of-concept of an internet-based telemedicine system as a use case that attests to the feasibility for the development, within the university environment, of techniques for remote processing of biomedical signals for adjustable detection of myocardial ischemia episodes. At each signal lead, QRS complexes are detected and delimited with the J-point marking. The same procedure to detect the complex is used to identify the respective T wave, then the area over the ST segment is applied to detect ischemia-related elevations. The entire system is designed on web-based telemedicine services using multiuser, remote access technologies, and database. The measurements for sensitivity and precision had their respective averages calculated at 11.79 and 24.21% for the leads of lower noise. The evaluations regarding the aspects of user friendliness and the usefulness of the application, resulted in 88.57 and 89.28% of broad or total acceptance, respectively. They are robust enough to enable scalability and can be offered by cloud computing, besides enabling the development of new biomedical signal processing techniques within the concept of distance services, using a modular architecture with collaborative bias.

Influential Factors of Knowledge Sharing of Multinational E-Health Service Based on 24HrKF

In order to solve the problem of cross-time and cross-regional medical collaboration and distributed knowledge sharing across patients and medical teams for 24 hours a day in the context of global resource allocation, a new 24HrKF e-health service model is proposed and a key knowledge model of 24HrKF e-health team knowledge sharing is established based on existing research results combined with 24HrKF distributed team characteristics. Finally, the questionnaire data of 338 multinational medical team members are used to verify the impact of key factors on the knowledge sharing of medical teams. The results shows that factors such as information and communication technology, the hospital's cultural characteristics, cross-cultural communication, medical knowledge and skills, and trust all have a significantly positive impact on knowledge sharing among team members especially information and communication technology and medical knowledge and skills. However, the degree of time-span separation across time zones has no significant effect on the knowledge sharing among team members.

Wireless monitoring and real-time adaptive predictive indicator of deterioration

To assist in the early warning of deterioration in hospitalised children we studied the feasibility of collecting continuous wireless physiological data using Lifetouch (ECG-derived heart and respiratory rate) and WristOx2 (pulse-oximetry and derived pulse rate) sensors. We compared our bedside paediatric early warning (PEW) score and a machine learning automated approach: a Real-time Adaptive Predictive Indicator of Deterioration (RAPID) to identify children experiencing significant clinical deterioration. 982 patients contributed 7,073,486 min during 1,263 monitoring sessions. The proportion of intended monitoring time was 93% for Lifetouch and 55% for WristOx2. Valid clinical data was 63% of intended monitoring time for Lifetouch and 50% WristOx2. 29 patients experienced 36 clinically significant deteriorations. The RAPID Index detected significant deterioration more frequently (77% to 97%) and earlier than the PEW score ≥ 9/26. High sensitivity and negative predictive value for the RAPID Index was associated with low specificity and low positive predictive value. We conclude that it is feasible to collect clinically valid physiological data wirelessly for 50% of intended monitoring time. The RAPID Index identified more deterioration, before the PEW score, but has a low specificity. By using the RAPID Index with a PEW system some life-threatening events may be averted.

Security and Privacy Requirements for Cloud Computing in Healthcare

Cloud computing promises essential improvements in healthcare delivery performance. However, its wide adoption in healthcare is yet to be seen, one main reason being patients’ concerns for security and privacy of their sensitive medical records. These concerns can be addressed through corresponding security and privacy requirements within the system engineering process. Despite a plethora of related research, security and privacy requirements for cloud systems and services have seldomly been investigated methodically so far, whereas their individual priorities to increase the system success probability have been neglected. Against this background, this study applies a systematic requirements engineering process: First, based on a systematic literature review, an extensive initial set of security and privacy requirements is elicited. Second, an online survey based on the best-worst scaling method is designed, conducted, and evaluated to determine priorities of security and privacy requirements.

Our results show that confidentiality and integrity of medical data are ranked at the top of the hierarchy of prioritized requirements, followed by control of data use and modification, patients’ anonymity, and patients’ control of access rights. Availability, fine-grained access control, revocation of access rights, flexible access, clinicians’ anonymity, as well as usability, scalability, and efficiency of the system complete the ranking. The level of agreement among patients is rather small, but statistically significant at the 0.01 level.

The main contribution of the present research comprises the study method and results highlighting the role of strong security and privacy and excluding any trade-offs with system usability. Enabling a richer understanding of patients’ security and privacy requirements for adopting cloud computing in healthcare, these are of particular importance to researchers and practitioners interested in supporting the process of security and privacy engineering for health-cloud solutions. It further represents a supplement that can support time-intensive negotiation meetings between the requirements engineers and patients.

Impact of industry 4.0 to create advancements in orthopaedics

Scientists and health professional are focusing on improving the medical sciences for the betterment of patients. The fourth industrial revolution, which is commonly known as Industry 4.0, is a significant advancement in the field of engineering. Industry 4.0 is opening a new opportunity for digital manufacturing with greater flexibility and operational performance. This development is also going to have a positive impact in the field of orthopaedics. The purpose of this paper is to present various advancements in orthopaedics by the implementation of Industry 4.0. To undertake this study, we have studied the available literature extensively on Industry 4.0, technologies of Industry 4.0 and their role in orthopaedics. Paper briefly explains about Industry 4.0, identifies and discusses the major technologies of Industry 4.0, which will support development in orthopaedics. Finally, from the available literature, the paper identifies twelve significant advancements of Industry 4.0 in orthopaedics. Industry 4.0 uses various types of digital manufacturing and information technologies to create orthopaedics implants, patient-specific tools, devices and innovative way of treatment. This revolution is to be useful to perform better spinal surgery, knee and hip replacement, and invasive surgeries.

Valuable Genomes: Taxonomy and Archetypes of Business Models in Direct-to-Consumer Genetic Testing

Background

Recent progress in genome data collection and analysis technologies has led to a surge of direct-to-consumer (DTC) genetic testing services. Owing to the clinical value and sensitivity of genomic data, as well as uncertainty and hearsay surrounding business practices of DTC genetic testing service providers, DTC genetic testing has faced significant criticism by researchers and practitioners. Research in this area has centered on ethical and legal implications of providing genetic tests directly to consumers, but we still lack a more profound understanding of how businesses in the DTC genetic testing markets work and provide value to different stakeholders.

Objective

The aim of this study was to address the lack of knowledge concerning business models of DTC genetic testing services by systematically identifying the salient properties of various DTC genetic testing service business models as well as discerning dominant business models in the market.

Methods

We employed a 3-phased research approach. In phase 1, we set up a database of 277 DTC genetic testing services. In phase 2, we drew on these data as well as conceptual models of DTC genetic testing services and iteratively developed a taxonomy of DTC genetic testing service business models. In phase 3, we used a 2-stage clustering method to cluster the 277 services that we identified during phase 1 and derived 6 dominant archetypes of DTC genetic testing service business models.

Results

The contributions of this research are 2-fold. First, we provided a first of its kind, systematically developed taxonomy of DTC genetic testing service business models consisting of 15 dimensions in 4 categories. Each dimension comprises 2 to 5 characteristics and captures relevant aspects of DTC genetic testing service business models. Second, we derived 6 archetypes of DTC genetic testing service business models named as follows: (1) low-cost DTC genomics for enthusiasts, (2) high-privacy DTC genomics for enthusiasts, (3) specific information tests, (4) simple health tests, (5) basic low-value DTC genomics, and (6) comprehensive tests and low data processing.

Conclusions

Our analysis paints a much more complex business landscape in the DTC genetic testing market than previously anticipated. This calls for further research on business models and their effects that underlie DTC genetic testing services and invites specific regulatory interventions to protect consumers and level the playing field.

An Ambulatory Blood Pressure Monitor Mobile Health System for Early Warning for Stroke Risk: Longitudinal Observational Study

BACKGROUND

Stroke, as a leading cause of death around the globe, has become a heavy burden on our society. Studies show that stroke can be predicted and prevented if a person's blood pressure (BP) status is appropriately monitored via an ambulatory blood pressure monitor (ABPM) system. However, currently there exists no efficient and user-friendly ABPM system to provide early warning for stroke risk in real-time. Moreover, most existing ABPM devices measure BP during the deflation of the cuff, which fails to reflect blood pressure accurately.

OBJECTIVE

In this study, we sought to develop a new ABPM mobile health (mHealth) system that was capable of monitoring blood pressure during inflation and could detect early stroke-risk signals in real-time.

METHODS

We designed an ABPM mHealth system that is based on mobile network infrastructure and mobile apps. The proposed system contains two major parts: a new ABPM device in which an inflation-type BP measurement algorithm is embedded, and an abnormal blood pressure data analysis algorithm for stroke-risk prediction services at our health data service center. For evaluation, the ABPM device was first tested using simulated signals and compared with the gold standard of a mercury sphygmomanometer. Then, the performance of our proposed mHealth system was evaluated in an observational study.

RESULTS

The results are presented in two main parts: the device test and the longitudinal observational studies of the presented system. The average measurement error of the new ABPM device with the inflation-type algorithm was less than 0.55 mmHg compared to a reference device using simulated signals. Moreover, the results of correlation coefficients and agreement analyses show that there is a strong linear correlation between our device and the standard mercury sphygmomanometer. In the case of the system observational study, we collected a data set with 88 features, including real-time data, user information, and user records. Our abnormal blood pressure data analysis algorithm achieved the best performance, with an area under the curve of 0.904 for the low risk level, 0.756 for the caution risk level, and 0.912 for the high-risk level. Our system enables a patient to be aware of their risk in real-time, which improves medication adherence with risk self-management.

CONCLUSIONS

To our knowledge, this device is the first ABPM device that measures blood pressure during the inflation process and has obtained a government medical license. Device tests and longitudinal observational studies were conducted in Peking University hospitals, and they showed the device's high accuracy for BP measurements, its efficiency in detecting early signs of stroke, and its efficiency at providing an early warning for stroke risk.