Healthcare Sector Research Articles

Revealing the hidden wealth in healthcare: an empirical study of intellectual capital disclosure in leading global hospitals

Purpose Under the lens of stakeholder theory, this study aims to explore the dissemination of intellectual capital (IC) information within the healthcare sector. Specifically, the primary objective is to investigate the extent of IC disclosure (ICD) among leading global hospitals and its underlying determinants. Design/methodology/approach This study conducts a manual content analysis of the official websites of 175 leading global hospitals, selected based on The World’s Best Hospitals 2022, and uses a linear regression model to test the research hypotheses. Findings The empirical results underscore an adequate dissemination of IC information by leading global hospitals through their official websites. Moreover, they reveal a positive association between hospital complexity, public status, and online visibility with the extent of IC information disclosed. Originality/value This study represents a pioneering contribution to the examination of determinants influencing online ICD within a global hospital context. It significantly enhances the existing literature on ICD and offers valuable practical implications.

Assessing the Dynamic Capabilities and Sustainable Performance in Public Hospital Supply Chains Management

In the volatility, uncertainty, complexity, and ambiguity (VUCA) era, unexpected disasters are rising. The Coronavirus disease 2019 (COVID-19) pandemic severely disrupted healthcare supply chains, with resource shortages significantly impacting the sustainable provision of public healthcare services. This highlighted the importance of supply chain management for public healthcare sustainability operations. An online survey was conducted among 127 public hospital employees and managers, adopting the SEM-PLS method to identify critical dynamic capabilities of supply chain management capabilities and their effect on sustainable development. The results indicate that strategic formulation capabilities, leadership, and digital technology competence significantly enhance the sustainable performance of public hospitals. This finding enriches the literature on sustainable supply chain management in the healthcare sector and provides policymakers and healthcare administrators with decision-making support.

Narratives of growth of formative technological innovation systems based on a knowledge perspective: the case of medical devices

Purpose This study aims to analyze the narratives of growth during the initial stages of development of the medical device technological innovation system (TIS). This paper used micro/nanofluidic-based point-of-care testing (mnPOCT), a breakthrough technology in the health-care sector. Design/methodology/approach This study presents a framework that includes measures of knowledge breadth and sharing mechanisms based on cognitive and actor-based networks. The framework integrates bibliometric, network and statistics-based approaches with a focus on the first decade of mnPOCT development. Findings In addition to the typical patterns of technological emergence, the mnPOCT sector exhibits distinctive characteristics. This paper observed significant scientific content and a high geographic concentration. Although small- and medium-sized enterprises, particularly startups, detonate knowledge development, large companies play a subtle yet impactful role as innovation mediators. Interfirm alliances are sparse, reflecting the complementarities between startups and large firms throughout the innovation value chain. These alliances show a significant correlation with SME knowledge creation. Research limitations/implications This study provides researchers and practitioners with guidelines for assessing the dynamics of the growth of technologies in the earliest stages of growth through knowledge and implications for research strategy toward the development and deployment of effective system interventions. Originality/value The study of formative TISs presents challenges because of the nascent characteristics and uncertainties surrounding emerging technologies. Current discussions on the narratives of growth of emerging TISs are limited to broad descriptions, which hinder understanding of these formative stages. This study offers a unique approach to assessing the initial stages of technological evolution. Moreover, it contributes to the existing literature by providing guidelines for managing new technologies for R&D researchers and practitioners.

Exploring the Landscape of Explainable Artificial Intelligence (XAI): A Systematic Review of Techniques and Applications

Artificial intelligence (AI) encompasses the development of systems that perform tasks typically requiring human intelligence, such as reasoning and learning. Despite its widespread use, AI often raises trust issues due to the opacity of its decision-making processes. This challenge has led to the development of explainable artificial intelligence (XAI), which aims to enhance user understanding and trust by providing clear explanations of AI decisions and processes. This paper reviews existing XAI research, focusing on its application in the healthcare sector, particularly in medical and medicinal contexts. Our analysis is organized around key properties of XAI—understandability, comprehensibility, transparency, interpretability, and explainability—providing a comprehensive overview of XAI techniques and their practical implications.

Triggerpunkt-Behandlungs-Tool zur Selbsttherapie von Myogelosen im Berufsumfeld – eine Anwendungsbeobachtung

Trigger point treatment tool for self-therapy of myogelosis in the professional environment – An observational study Aim: There is a large number of occupations where workplace-associated movement patterns and/or forced postures lead to muscle tension in the shoulders and back. These tensions have a direct detrimental impact on the quality of life and capacity for work of those affected. In the medium to long term, they also promote the development of structural degeneration of the musculoskeletal system. If employees in the healthcare sector are affected, this impairs high-quality patient care. The trigger point self-treatment tool “TensionTerminator” (ErgoPhysion, Innsbruck, Austria) was developed for the self-therapy of such tension conditions in the workplace. The use of this device was evaluated as part of an application observation in six departments at Vienna General Hospital (AKH). Methods: Six departments at Vienna General Hospital from the areas of surgery, laboratory medicine, internal medicine and radiology were each provided with a “TensionTerminator” device for independent use for 4 months between May 2023 and March 2024. A contact person in each department was trained in the use of the device and how to handle the documentation. As part of the observation, users were asked to independently enter their user ID, the duration of use and their subjective assessment of the effect (“better”/”worse”/”no change”) in a list each time they used the device. Results: During the test period, a total of 430 uses by 145 users were documented in the six departments, i.e. an average of almost 3 uses per person. The average application duration was 6.5 minutes. In 85.1% of all uses, the patient’s condition after use was described as “better”, and in 14% of all cases as “no change”. One of the 430 uses received a negative rating (“worse”). Conclusion: The trigger point self-treatment tool “TensionTerminator” has proven to be an effective device against workplace-associated muscle tension. It was received very well in the hospital setting and was used regularly. Keywords: workplace health promotion – back pain – myogelosis – myofascial trigger points

Digital Health Technology on Patient Recovery and Nurse Performance in Indonesia

This study investigates the impact of digital health technology, nurse competence, patient safety protocols, and organizational support on patient recovery and nurse performance within the Indonesian healthcare sector. Utilizing a quantitative approach, data were collected from 120 healthcare professionals through structured questionnaires and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS 3). The findings reveal that digital health technology, nurse competence, and patient safety protocols positively influence patient recovery, while organizational support and digital health technology significantly enhance nurse performance. Organizational support and patient safety protocols emerged as the strongest predictors of nurse performance and patient recovery, respectively. These results suggest that a comprehensive approach integrating technological, safety, and support factors can substantially improve healthcare outcomes. This study offers practical recommendations for healthcare administrators and policymakers to enhance healthcare quality through strategic investments in digital tools, training, safety protocols, and supportive work environments.

Synthetic Data, Common Data Models and Federation: Holy Trinity or unholy mess?

The healthcare sector's adoption of data and digital technologies is hindered by stringent data privacy regulations. Synthetic data, common data models (CDMs) and federated data ecosystems present promising solutions to these challenges. This workshop explored the potential of synthetic data to revolutionise health research, education and innovation (REI). By discussing applications, benefits, and ethical implications, the workshop addressed the role of synthetic data in enhancing data interoperability, scalability, and privacy preservation within healthcare REI systems. It also examined the relationship between synthetic data and CDMs, such as the Observational Medical Outcomes Partnership (OMOP) CDM, and the potential of federated data ecosystems to enable collaborative analysis while maintaining data ownership and control. The workshop delved into specific use cases to assess the feasibility, benefits, and limitations of synthetic data in various healthcare contexts. Through case studies and discussions, participants explored and developed best practices for effective utilisation. Ultimately, the workshop aimed to explore whether the combination of synthetic data, CDMs, and federation could facilitate privacy-preserving data sharing, seamless data integration, and scalable analysis across distributed data sources. By addressing privacy, interoperability, and scalability challenges, these approaches can drive innovation and insights within the healthcare sector.

An XGBoost Approach to Predictive Modelling of Rift Valley Fever Outbreaks in Kenya Using Climatic Factors

Reports of Rift Valley fever (RVF), a highly climate-sensitive zoonotic disease, have been rather frequent in Kenya. Although multiple empirical analyses have shown that machine learning methods outperform time series models in forecasting time series data, there is limited evidence of their application in predicting disease outbreaks in Africa. In recent times, the literature has reported several applications of machine learning in facilitating intelligent decision-making within the healthcare sector and public health. However, there is a scarcity of information regarding the utilization of the XGBoost model for predicting disease outbreaks. Within the provinces of Kenya, the incidence of Rift Valley fever was more prominent in the Rift Valley (26.80%) and Eastern (20.60%) regions. This study investigated the correlation between the occurrence of RVF (rapid vegetation failure) and several climatic variables, including humidity, clay content, elevation, slope, and rainfall. The correlation matrix revealed a modest linear dependence between different climatic variables and RVF cases, with the highest correlation, a mere 0.02903, observed for rainfall. The XGBoost model was trained using these climate variables and achieved outstanding performance measures including an AUC of 0.8908, accuracy of 99.74%, precision of 99.75%, and recall of 99.99%. The analysis of feature importance revealed that rainfall was the most significant predictor. These findings align with previous studies demonstrating the significance of weather conditions in RVF outbreaks. The study’s results indicate that incorporating advanced machine learning models that consider several climatic variables can significantly enhance the prediction and management of RVF incidence.

Paper waste and carbon emissions from oral contraceptive leaflets.

Oral contraceptives (OC) are the most used form of contraception among women in the U.S. and Europe. Like other medications, their packaging must include patient information leaflets. This study quantifies the environmental impact of paper waste generated by these leaflets. We conducted an observational analysis, measuring the weight of leaflets, pills, and packaging components across various OC brands. Significant variations in leaflet weights were observed. On average, leaflets accounted for 55% of the package weight, while pills and blister dispensers represented only 32%. The mean weight of OC leaflets was 12.3 ± 5.5 grams (4.7-21.9 grams), leading to an estimated annual paper waste of 6,118.4 tons, 5,763.5 tons of carbon dioxide equivalent emissions, and the use of approximately 146,841 trees for production. Standardizing leaflet weight to the lightest reported can reduce annual waste by 3780.5 tons of paper. This study highlights the substantial environmental cost of the waste generated from OC leaflets and proposes practical strategies to mitigate waste, including electronic leaflets and standardized packaging. Targeting these materials presents a significant opportunity to enhance sustainability, aligning with global efforts to reduce greenhouse gas emissions from the healthcare sector.

A comprehensive survey of cybercrimes in India over the last decade

Since the 1990s, the integration of technology into daily life has led to the creation of an extensive network of interconnected devices, transforming how individuals and organizations operate. However, this digital transformation has also spurred the rise of cybercrime, criminal activities perpetrated through networks or computer systems. Cybercrime has become a global concern, presenting significant challenges to security systems. Although advancements in digital technology have enhanced efficiency, they have also opened new avenues for exploitation by cybercriminals, highlighting the urgent need for advanced cybersecurity measures. The escalating number of cyberattacks and associated risks in the past decade highlights the critical importance of protecting sensitive data and safeguarding information systems. Cybercrimes range from financial fraud and phishing scams to identity theft and online harassment, posing substantial risks to both individuals and organizations. In response, governments, law enforcement agencies, and cybersecurity units have intensified their efforts to address these threats. In recent years, India has experienced a significant surge in cybercrime incidents, with a notable increase in cases involving ransomware, data breaches, and social engineering attacks. The growing penetration of internet services, the expansion of e-commerce, and the rapid adoption of digital payment systems have made individuals and organizations more vulnerable to cyber threats. Key areas affected include banking, healthcare, and government sectors, which are frequently targeted due to the sensitive nature of the data they handle. To combat these risks, there is an increasing focus on public awareness, cybersecurity education, and robust regulatory frameworks. This paper provides an in-depth analysis of cybercrime, with a focus on developing innovative prevention strategies, strengthening internal security protocols, and classifying key cybercrime terminologies to better understand their implications for digital infrastructure.

Hospitality in Healthcare: Leveraging Employee e-WOM

ABSTRACT Providing hospitality services to patients to enhance their overall healing process has gained importance in the healthcare industry. It is not only just about getting healed but also the experience involved. This entails quality hospitality services in addition to medical services. Given that a happy employee provides better services, the role of job satisfaction of employees providing these services thus becomes important. Drawing from service quality frameworks, this article aims to identify enablers and deterrents of job satisfaction and validate with practitioners pulling out latent aspects that need to be focused on integrating hospitality in healthcare. We explored these aspects using a three-pronged approach. Initially, we identified the key themes influencing job satisfaction by applying data mining techniques to 13,000 employee reviews from companies recognized as Great Place to Work, sourced from Glassdoor. 1 Second, we validated the identified theme from experts through 24 focused group discussions comprising HR practitioners, thereby gaining interesting insights about certain important overlooked aspects. Third, we include literature support for each of the identified themes, stating their importance to the healthcare sector. The study provides a rubric of enablers and deterrents to job satisfaction, which can help the sector enhance employee satisfaction.

Quantum Cryptography for Secure Communications and the Enhancement of U.S. Cybersecurity in the Quantum Age

This paper explores the critical role of quantum cryptography in enhancing U.S. cybersecurity, focusing on its potential to counteract the growing threats posed by quantum computing. As quantum computers advance, classical encryption methods like RSA and AES face unprecedented vulnerabilities. Quantum Key Distribution (QKD) offers a groundbreaking solution by leveraging quantum mechanics to secure data transmission. The paper evaluates current implementations and future challenges of quantum cryptography, emphasizing its importance for government, military, financial, and healthcare sectors in safeguarding sensitive communications in the quantum age.

Architecting Resilience : A Framework for Secure and Compliant Healthcare IT Infrastructures

Healthcare information technology (IT) systems face unique challenges in maintaining data security and regulatory compliance while supporting critical patient care functions. This article provides a comprehensive analysis of the complex interplay between data protection measures and compliance requirements in the healthcare sector. We examine key components of data security, including encryption, data integrity measures, and secure transfer protocols, with a specific focus on their application to sensitive patient information. The impact of regulations such as HIPAA on system design and maintenance is explored, offering insights into the alignment of IT practices with evolving standards. Through a review of current literature and industry best practices, we present strategies for risk management, employee training, and the implementation of technical controls that address both security and compliance needs. Emerging trends, including cloud computing, the Internet of Medical Things (IoMT), and artificial intelligence in healthcare security, are discussed to provide a forward-looking perspective. This article contributes to the ongoing dialogue on balancing innovation with security in healthcare IT, offering practical recommendations for healthcare organizations to enhance their data protection measures while ensuring regulatory compliance.

Evolving trends, limitations, and ethical considerations in AI-driven conversational interfaces: assessing ChatGPT's impact on healthcare, financial services, and educational sectors

ABSTRACT This study presents a comprehensive bibliometric analysis of ChatGPT's impact on three critical sectors: healthcare, financial services, and education, covering the period from 2022 to 2024. The research aimed to explore the evolving trends, limitations, and ethical considerations associated with the deployment of ChatGPT and similar AI-driven conversational interfaces. The findings reveal that while ChatGPT offers significant potential in enhancing efficiency and decision-making processes, it also faces substantial challenges in data privacy, integration with existing systems, and the need for improved emotional intelligence. The study highlights the inherent biases in AI models, raising concerns about the accuracy and fairness of AI-driven outputs. Ethical considerations, including data privacy, transparency, accountability, and equity in AI applications, are identified as crucial areas requiring urgent attention and development. Additionally, the research underscores the importance of developing robust regulatory frameworks and ethical guidelines to govern AI deployment in these sectors. Successful integration of ChatGPT and similar technologies depends on addressing these challenges and ethical considerations through collaborative efforts among AI developers, industry professionals, policymakers, and ethicists. Future research should focus on improving AI's data security, emotional intelligence, bias reduction, human-AI collaboration, and assessing long-term impacts across diverse settings.

Unveiling the Nexus: Organizational Integrity Culture, Integrity Management Practices, and Ethical Performance in the Private Healthcare Sector

Unveiling the Nexus: Organizational Integrity Culture, Integrity Management Practices, and Ethical Performance in the Private Healthcare Sector

From Routine to Crisis: The Impact of COVID‐19 Pandemic on Antibiotic Consumption in Iran

ABSTRACTBackground and AimsThe COVID‐19 pandemic has significantly impacted the healthcare sector, influencing patients, providers, and the overall system. This study evaluates how the pandemic affected antibiotic prescriptions among 44 million Iranians insured by the Social Security Organization (SSO).MethodsIn this quasi‐experimental study, we utilized monthly aggregated data on antibiotic prescriptions per 1000 individuals insured by the SSO. We employed a single‐group interrupted time series analysis (ITSA) over a period of 72 months, from March 20, 2016 to February 19, 2020 for the pre‐pandemic phase, and from February 20, 2020 to March 20, 2022, for the during‐pandemic period. Additionally, we conducted a multiple‐group ITSA to assess the differential impact of the pandemic on antibiotic consumption between the direct (SSO‐owned medical centers) and indirect (other private or public centers contracted by the SSO) sectors.ResultsThe study revealed a 30% reduction in the monthly average antibiotic consumption rate when comparing the during‐pandemic period to pre‐pandemic usage across the total sector. The results from the single‐group ITSA indicated that the mean antibiotic consumption per 1000 individuals at baseline was 1664. Following the onset of the pandemic, there was a significant reduction in antibiotic prescriptions, dropping to 484 per 1000 individuals (p ≤ 0.001) in the first month. However, during the pandemic period, antibiotic prescriptions exhibited insignificant monthly increases, averaging 10.7 per 1000 insured individuals. The multiple‐group ITSA revealed that both sectors experienced a decline in antibiotic prescriptions after the outbreak of COVID‐19. Notably, the indirect sector demonstrated a greater reduction, with a decrease of 187 prescriptions per 1000 insured individuals in the first month following the pandemic's onset.ConclusionsOur study found a significant reduction in antibiotic consumption. Further research is needed to compare antibiotic use between hospitals and outpatient centers, as well as among COVID‐19 and non‐COVID‐19 patients.

Sustainable leadership: empowering green organizational citizenship behaviour through employee green value in the Indian healthcare sector

Purpose Leadership is crucial for promoting employees’ environmental behaviour, essential for implementing sustainability initiatives. Academics and practitioners emphasize the need for integrated top-to-bottom actions to address environmental issues effectively. Thus, the purpose of this study is to investigate how Environment-Specific Servant Leadership (ESSL), via Employee Green Value (EGV), promotes Green Organizational Citizenship Behaviour (GOCB). Design/methodology/approach The present study adopted a quantitative cross-sectional approach. Additionally, a total of 333 data points were collected from employees working in various hospitals in Ranchi, India. The data and hypothesized relationships were analysed using PLS-SEM with SmartPLS 4.0 software. Findings The present results indicate that ESSL has a notable direct effect on employees’ GOCB. Moreover, EGV was identified as a partial mediator in the relationship between ESSL and GOCB. Practical implications The findings imply that leaders who prioritize sustainability and exhibit environmentally responsible behaviour, along with employees who value and prioritize green initiatives, can create a workplace that value pro-environmental practices. In this workplace employees are also likely to demonstrate green organizational citizenship behaviour, therefore promoting sustainable practices and outcomes. Originality/value This study provides valuable insight into the individual psychological mechanisms that drive voluntary participation in environmental protection and conservation efforts. Furthermore, the study also highlighted the relationship between ESSL, EGV and GOCB in terms of their work environment as well as highlighting the potential for organizations to create a more sustainable and socially responsible workplace.

Development of health care expenditures in Finland up to 2040

Abstract Background Increasing health care expenditures are threatening public health by complicating the supply of adequate health services. Exploration of possible future developments of the expenditures is needed to understand how to prepare for future or to change an unwanted course of development. We provided projections by health care sectors taking into account demographic and other developments. Methods We used national data on the realized expenditures per capita by age group, sex and health care sectors from 2017 to 2020, and official forecasts of the population in Finland up to 2040. Future per capita expenditures were projected with Bayesian linear regression models incorporating a priori dependency structure for the slope parameters of the age groups such that the time trends of adjacent groups would be more similar than other groups. These projections were then combined with the population forecasts to estimate the total expenditures. Results The greatest increase (164%) was estimated for the total costs of the primary outpatient healthcare: from 2153 to 5677 million euros in 2020-2040, such that 7% of the growth was attributed to demographic developments. The estimated growths were 68% for the primary inpatient healthcare, 14% for the specialised somatic healthcare, and 52% for the urgent and emergency health services, of which 91%, 98% and 21% were attributed to demographic developments, respectively. Conclusions Notable increases in expenditures are expected in all considered health care sectors, but there are great differences in the proportions of the growth attributed to demographic developments. Due to the limited role of demographic changes, it is worth focusing on controlling the impacts of other developments by, e.g., improving the population health and the efficiency of the health care system. Key messages • Notable increases are expected in health care expenditures up to 2040. • Impacts of demographic changes varies markedly between health care sectors.

6.Y.2. AI and health care: what are the capabilities and limitations?

Abstract With the rapid advancement of artificial intelligence (AI) technologies and their implementation in health care, there is a critical need to explore the different applications and implications of AI. This workshop seeks to look at different aspects of AI, both potential applications for AI technology in health, public opinions of use of AI in health care, and the reality of implementing AI in different contexts. Understanding health care approaches to AI from different countries is a unique opportunity for shared learning of innovations across various sectors of health care and patient engagement in order to most effectively engage this emerging field. AI, in whichever form it may be incorporated into health care, has the opportunity to impart meaningful, innovative change, but understanding this new technology comes with important questions. This session will dive into research on AI in various areas of health care by 1) looking at different ways AI is being harnessed in health care; 2) discussing lessons which can be learned and adapted from other countries; 3) discussing promising solutions and approaches to implementing AI in health care; 4) discussing the limitations or concerns of integrating AI in health care. The panel will be composed of 1 moderator and 2 panelists. Panelists are experts in their fields, established researchers and practitioners, and alumni of the Harkness Fellowship from Germany and the United Kingdom. A moderator will briefly frame the discussion for the audience and introduce the speakers and their presentations before leading an interactive, engaging question and answer portion. The coherence of this panel lays in its theme of leveraging AI to enhance healthcare delivery and understanding ways we can work across countries to foster ethical, equitable AI technologies that revolutionize healthcare practices with the ultimate goal of improving patient outcomes and health system efficiencies. Dr. Saira Ghafur from the U.K. will begin by presenting her research on evidence-based reasons for implementing AI in health care and Dr. Benedikt Simon from Germany will close out by discussing his work in AI in Germany and the challenges that have prevented robust integration. Each panelist will speak for roughly 8-10 minutes, with about 5 minutes reserved for moderator and audience questions. Key messages • Sharing cross-country experiences and research enables us to better understand how AI can impact health care. • In weighing both the benefits and challenges or limitations of implementing AI, we can best understand effective approaches to utilizing AI in health care.

Timing of Palliative Care, End-of-Life Quality Indicators, and Health Resource Utilization

Despite research supporting the benefits of early palliative care, timely initiation by gynecologic oncology patients is reportedly low, which may limit the effectiveness of palliative care. To investigate the association of the timing of palliative care initiation with the aggressiveness of end-of-life care using established quality indicators among patients with ovarian cancer. This population-based retrospective cohort study of ovarian cancer decedents used linked administrative health care data to identify palliative care provision across all health care sectors and health care professionals (specialist and nonspecialist) and end-of-life quality indicators in Ontario, Canada, from 2006 to 2018. Data analyses were performed July 12, 2024. The primary outcome was the associations between the timing of palliative care and end-of-life quality indicators, including emergency department use, hospital or intensive care unit admission in the last 30 days of life, chemotherapy in last 14 days of life, death in the hospital, and a composite measure of aggressive care. Late palliative care was defined as 3 months or less prior to death. There were 8297 ovarian cancer decedents. Their mean (SD) age at death was 69.6 (13.1) years, and their mean (SD) oncologic survival was 2.8 (3.9) years. Among 3958 patients with known cancer stage, 3495 (88.3%) presented with stage III or IV disease. One-third of patients (2667 [32.1%]) received late palliative care in the final 3 months of life. Results of multivariable regression analysis indicated that any palliative care initiated earlier than 3 months before death was associated with lower rates of aggressive end-of-life care (odds ratio [OR], 0.47 [95% CI, 0.37-0.60]), death in hospital (OR, 0.54 [95% CI, 0.45-0.65]), and intensive care unit admission (OR, 0.46 [95% CI, 0.27-0.76]). Specialist palliative consultation from 3 months up to 6 monts before death was associated with decreased likelihood of late chemotherapy (OR, 0.46 [95% CI, 0.24-0.88]). Findings from this cohort study suggested that early palliative care may be associated with less-aggressive end-of-life care than late palliative care. Implementation strategies for early palliative care initiation are needed to optimize care quality and health resource utilization at the end of life.