A systematic review of emerging information technologies for sustainable data-centric health-care

Advanced technique for firmware security analysis through heterogeneous data fusion and knowledge mapping

As the core component of a device, firmware's security directly affects the stability of the entire system and the security of user data. In order to provide a more comprehensive and accurate data foundation and improve the accuracy of firmware security analysis, this article conducts research on advanced technologies for firmware security analysis through heterogeneous data fusion and knowledge mapping. Firstly, preprocess the firmware security analysis knowledge graph data using cleaning, segmentation, classification, and other processing methods. Secondly, calculate the firmware security status value under heterogeneous information based on the processed data; Again, based on the calculation results of firmware security status values, extract knowledge graph features for firmware security analysis and annotate relationship description entries; Finally, based on knowledge mapping technology, ontology integration and ontology mapping knowledge fusion were carried out to achieve more effective organization and representation of firmware security analysis knowledge, and the research on the construction technology of firmware security analysis knowledge graph was completed. The experimental results show that after applying the proposed method for firmware security analysis, the loss function index value and F1 index value are both very high, and the prediction accuracy of knowledge graph evolution is very close to 100%, with good operational effect.

Pooled prevalence and associated factors of ECG abnormality among type 2 diabetic patients in the last ten years: Systematic review and meta-analysis

BACKGROUND

Type 2 diabetes mellitus is a global epidemic affecting millions of individuals worldwide. It is considered a chronic metabolic disorder of impaired glucose homeostasis, associated with various long-term complications and poor prognosis of cardiovascular performance. Therefore, this systematic review aimed to determine the pooled prevalence of ECG abnormality among type 2 diabetic patients both in the hospital setting and the general population based on the existing literature.

METHODS

This systematic review has been conducted on the ECG abnormality of patients with Type 2 diabetes. Following the establishment of eligibility criteria, a literature search was conducted using three databases and two search engines. Included articles were then screened, critically appraised, and data extracted independently by two reviewers, and any disagreements were handled by the involvement of a third party. The quality of the included studies had been assessed using the New Castle Ottawa quality assessment scale tool. Pooled prevalence and sensitivity were determined by random effect analysis. Heterogeneity was assessed by Higgins's I2, and its presence was alleviated by using sub-group analysis.

RESULT

Following the identification of 32, 785 studies, 33 publications were eligible for the review with a sample size of 31, 449. The pooled prevalence of ECG abnormality among Type 2 diabetic patients was 31% (95% CI: 25, 36%). It was 26% (95% CI: 1, 51%), and 31% (95% CI: 24, 37%) in the hospital and general/ community population, respectively. Body mass index (AOR =  5.90; 95%CI: 4.96, 7.03), duration of diabetic mellitus (AOR = 9.21; 95%CI: 9.12, 9.31), and being hypertensive (AOR = 5.17; 95%CI: 4.90, 5.46), were significantly associated factors with ECG abnormality among patients with Type 2 diabetic mellitus.

CONCLUSION

The pooled prevalence of ECG abnormality among Type 2 diabetic mellitus patients was high, while its magnitude was higher among patients attending hospital settings than in the community. Duration of diabetic mellitus, high body mass index and presence of hypertension were significant factors in this review. Moreover, we advise more longitudinal researches to determine the incidence of ECG abnormality among patients with diabetes considering time duration and sex differences.

ETHICAL CONSIDERATION

Since our study was on the review of secondary data, ethical issues are not necessary.

A qualitative reflexive thematic analysis of innovation and regulation in hearing health care

BACKGROUND

The hearing health sector is an example of a health sector that is experiencing a period of rapid innovation driven by digital technologies. These innovations will impact the types of interventions and services available to support the communication of deaf and hard-of-hearing individuals. This study explored the perceptions of informed participants on the topic of innovation and regulation within hearing healthcare in Australia and the United Kingdom (UK).

METHODS

Participants (N = 29, Australia [n = 16], UK [n = 13]) were purposively sampled and joined one of two online workshops. Participants included adults with hearing loss and family members, hearing health professionals, academics/researchers, representatives of hearing device manufacturers, regulators and policymakers. Workshop data were analysed using reflexive thematic analysis.

RESULTS

Participants conceptualised the hearing health sector as a network of organisations and individuals with different roles, knowledge and interests, in a state of flux driven by innovation and regulation. Innovation and regulation were perceived as mechanisms to ensure quality and mitigate risk within a holistic approach to care. Innovations encompassed technological as well as non-technological innovations of potential benefit to consumers. Participants agreed it was essential for innovation and regulation to be congruent with societal values. Critical to ethical congruence was the involvement of consumers throughout both innovation and regulation stages, and the use of innovation and regulation to tackle stigma and reduce health disparities. Participants expressed the desire for accessible and inclusive innovation in the context of fair, transparent and trustworthy commercial practices.

CONCLUSIONS

This study explored how stakeholders within the hearing health sector understand and make sense of innovation and the role of regulation. Overall, and despite reservations relating to health care professionals' changing roles and responsibilities, innovation and regulation were conceptualised as beneficial when situated in the context of holistic, whole-person, models of care. The results of this study will inform considerations to support the development and implementation of innovations and regulation within the hearing sector and across other health sectors influenced by technological advances.

Continuously monitoring the human machine? - A cross-sectional study to assess the acceptance of wearables in Germany

Background: Wearables have the potential to transform healthcare by enabling early detection and monitoring of chronic diseases. This study aimed to assess wearables' acceptance, usage, and reasons for non-use. Methods: Anonymous questionnaires were used to collect data in Germany on wearable ownership, usage behaviour, acceptance of health monitoring, and willingness to share data. Results: Out of 643 respondents, 550 participants provided wearable acceptance data. The average age was 36.6 years, with 51.3% female and 39.6% residing in rural areas. Overall, 33.8% reported wearing a wearable, primarily smartwatches or fitness wristbands. Men (63.3%) and women (57.8%) expressed willingness to wear a sensor for health monitoring, and 61.5% were open to sharing data with healthcare providers. Concerns included data security, privacy, and perceived lack of need. Conclusion: The study highlights the acceptance and potential of wearables, particularly for health monitoring and data sharing with healthcare providers. Addressing data security and privacy concerns could enhance the adoption of innovative wearables, such as implants, for early detection and monitoring of chronic diseases.

Business intelligence and the leverage of information in healthcare organizations from a managerial perspective: a systematic literature review and research agenda

PURPOSE

Business intelligence (BI) systems and tools are deemed to be a transformative source with the potential to contribute to reshaping the way different healthcare organizations' (HCOs) services are offered and managed. However, this emerging field of research still appears underdeveloped and fragmented. Hence, this paper aims to reconciling, analyzing and synthesizing different strands of managerial-oriented literature on BI in HCOs and to enhance both theoretical and applied future contributions.

DESIGN/METHODOLOGY/APPROACH

A literature-based framework was developed to establish and guide a three-stage state-of-the-art systematic literature review (SLR). The SLR was undertaken adopting a hybrid methodology that combines a bibliometric and a content analysis.

FINDINGS

In total, 34 peer-review articles were included. Results revealed significant heterogeneity in theoretical basis and methodological strategies. Nonetheless, the knowledge structure of this research's stream seems to be primarily composed of five clusters of interconnected topics: (1) decision-making, relevant capabilities and value creation; (2) user satisfaction and quality; (3) process management, organizational change and financial effectiveness; (4) decision-support information, dashboard and key performance indicators; and (5) performance management and organizational effectiveness.

ORIGINALITY/VALUE

To the authors' knowledge, this is the first SLR providing a business and management-related state-of-the-art on the topic. Besides, the paper offers an original framework disentangling future research directions from each emerged cluster into issues pertaining to BI implementation, utilization and impact in HCOs. The paper also discusses the need of future contributions to explore possible integrations of BI with emerging data-driven technologies (e.g. artificial intelligence) in HCOs, as the role of BI in addressing sustainability challenges.

QDS-COVID: A visual analytics system for interactive exploration of millions of COVID-19 healthcare records in Brazil

COVID-19 is responsible for the deaths of millions of people around the world. The scientific community has devoted its knowledge to finding ways that reduce the impact and understand the pandemic. In this work, the focus is on analyzing electronic health records for one of the largest public healthcare systems globally, the Brazilian public healthcare system called Sistema Único de Saúde (SUS). SUS collected more than 42 million flu records in a year of the pandemic and made this data publicly available. It is crucial, in this context, to apply analysis techniques that can lead to the optimization of the health care resources in SUS. We propose QDS-COVID, a visual analytics prototype for creating insights over SUS records. The prototype relies on a state-of-the-art datacube structure that supports slicing and dicing exploration of charts and Choropleth maps for all states and municipalities in Brazil. A set of analysis questions drives the development of the prototype and the construction of case studies that demonstrate the potential of the approach. The results include comparisons against other studies and feedback from a medical expert.