Healthcare Management System Research Articles

A cost-effectiveness analysis of three surgical options for treating displaced femoral neck fractures in active older patients in Japan: A full economic evaluation.

For older patients with displaced femoral neck fractures, in which primary osteosynthesis is usually not indicated, there are three primary prosthetic options-bipolar hemiarthroplasty (BHA), single-bearing total hip arthroplasty (SB-THA), and dual-mobility THA (DM-THA). However, the optimal choice for managing displaced femoral neck fractures remains controversial. Accordingly, this study aimed to evaluate the cost-effectiveness of BHA, SB-THA, and DM-THA in active older patients with displaced femoral neck fractures. A decision tree combined with a Markov model was employed to analyze the cost and quality-adjusted life years (QALYs) of BHA, SB-THA, and DM-THA for the management in the Japanese healthcare system. By simulating the five-year trajectory of a 75-year-old woman treated for a displaced femoral neck fracture, the cost-effectiveness of the three surgical options was evaluated. One-way sensitivity analysis and probabilistic sensitivity analysis (PSA) were used to assess parameter uncertainty. Additionally, two scenario analyses were conducted for other settings. The treatment was considered to be cost-effective when the incremental cost-effectiveness ratio (ICER) was below the 5,000,000 yen/QALY threshold. Compared with BHA, SB-THA exhibited higher costs but greater health benefits, resulting in an ICER of 1,499,440 yen/QALY. DM-THA offered additional health benefits compared with SB-THA, with an ICER of 4,145,777 yen/QALY. One-way sensitivity analysis revealed some influential parameters. PSA indicated that the probability of DM-THA, SB-THA, and BHA being cost-effective was 40.1%, 38.5%, and 21.4%, respectively. SB-THA was more cost-effective than BHA in patients aged 65-85 years, while DM-THA was more cost-effective than SB-THA in patients aged 65-75 years. The results suggest that SB-THA is a cost-effective alternative to BHA for displaced femoral neck fractures in active older patients, whereas DM-THA is more cost-effective than SB-THA in relatively younger patients. It is, therefore, recommended that orthopedic surgeons select the most appropriate surgical option based on the individual patient's physiological age.

Managing no-shows in healthcare: insights from an urban Health District in Northern Italy

Abstract Background Non-attendance at healthcare appointments, known as no-show, poses significant challenges to healthcare systems, disrupting patient care continuity, exacerbating waiting times, and straining resources. Addressing this issue is crucial for optimizing health care delivery and containing costs. This study explores the phenomenon of patient no-shows and aims to identify factors associated in a densely populated healthcare district in Turin, Northern Italy. Methods Data were extracted from the healthcare management system covering outpatient care appointments in the health district in 2022 and 2023. The analysis included various patient and service-related variables. Missing information on key variables were managed with listwise deletion. Descriptive statistics provided an overview of missed appointment rates, while multivariate analysis explored various patient and service-related variables. Results A 5.1% (n = 6198) no-show rate was observed out of 120,405 records. The total cost incurred due to missed appointment fees amounted to €127,244. Several factors were associated with a significantly increased likelihood of no-show (p < 0.05), including initial visit (OR = 1.11), deferred priority (OR = 1.22), non-exempt status from healthcare co-payments (OR = 1.36), exemption based on income (OR = 1.82), age under 18 (OR = 2.46) and under 65 (OR = 2.32), male gender (OR = 1.17), residency outside the Piedmont Region (OR = 1.31) and outside Italy (OR = 2.46), and longer waiting time (OR = 1.01). Conclusions This study sheds light on the widespread issue of patient no-shows and its economic implications. It provides clear direction for implementing tailored interventions in healthcare settings. As a response to these findings, a telephone recall project was launched. Its efficacy will be evaluated in subsequent assessments to determine if it can effectively alleviate the burden of no-shows, thus enhancing healthcare efficiency and ensuring continuity of care for patients. Key messages • The no-show phenomenon has important implications both organizationally and economically. • The magnitude and major determinants of patient no-shows must be recognized to guide the deployment of tailored interventions in a real-world setting.

Integration of Health Care Modules in Current Health Care Management Systems in India

Health care beyond worldwide boundaries is a critical problem, particularly when the population differs in terms of geographic position, culture, habits, socioeconomic background, medical strategy, and variations in disease burden over time. For countries like India, with a significant percentage of high-end medical experts as well as support and other health care systems, the development and integration of comprehensive and functionally versatile health care management systems are among the most important clinical problems addressed. The central dogma of a country that facilitates adopting a conglomeration will create a dedicated population to provide tailor-made health care in health shield, health protection, and health care delivery; a nation that takes care of a nation. Until now, it has given us E-Health, and offerings have been fine-tuned in research literature. In India, the health care domain is currently breaking the boundaries of knowledge workers in clinical and research domains working with the help of these workhorses (Fletcher-Brown et al. 2021). Many e-governance and public health reform programs in India are under consideration, and many of them are under implementation. This research focuses more on the integration of health care technology relevant to the paper topic within clinical setups, passive provision, and utilization of services for administrative purposes technologically implemented (Das et al. 2023).

Optimizing data management in healthcare: Lessons from clinical trials and beyond

This study comprehensively explores the optimization of data management in healthcare by drawing on lessons learned from clinical trials and extending these insights to broader healthcare contexts. The study's purpose is to examine the challenges, strategies, and technological innovations that are essential for effective data management in modern healthcare systems. Utilizing a detailed literature review, the study identifies key methodologies from clinical trials that have successfully enhanced data integrity, accuracy, and security, such as the implementation of electronic data capture (EDC) systems and rigorous data governance frameworks. These methods are crucial in managing the increasing volume and complexity of healthcare data. The study's findings reveal that big data analytics and artificial intelligence (AI) are pivotal in transforming healthcare data management, enabling personalized and precise patient care. However, these technologies also introduce challenges related to data security, interoperability, and ethical considerations, particularly concerning patient privacy and the transparency of AI-driven decision-making processes. In conclusion, the study emphasizes the need for continuous innovation and improvement in healthcare data management practices. Recommendations include the integration of blockchain technology, cloud computing, and real-time data from wearable devices to address existing challenges and enhance data management capabilities. The study advocates for a balanced approach that prioritizes patient privacy, ethical governance, and regulatory compliance to ensure that technological advancements contribute positively to patient outcomes and healthcare efficiency.

Adaptive Mobility and Reliability-based Routing Protocol for Smart Healthcare Management Systems in Vehicular Ad‐hoc Networks

Ambulances enable digital and widespread remote care for older people in the healthcare sector. The Vehicular Ad Hoc Network (VANET) is critical for allowing the digital and Intelligent Transportation System (ITS) for the smart healthcare world. Enhancing the dependability and flexibility of an adaptive routing algorithm improves vehicular communications' Quality of Service (QoS) effectiveness. An essential concern in vehicular technology is enabling drivers to make reliable judgments. Developing an effective routing system that ensures a suitable QoS takes time and effort. The vehicular network ecosystem is characterized by limited mobility, fast vehicle speeds, and constantly changing configurations. This study makes four distinct contributions. Initially, it presents adaptive routing protocols, capable of recognizing changes in the network environment, aware of the mobility of nodes, and dependable in delivering data packets. The experimental configuration is implemented inside a discrete Network Simulator (NS-3) scenario to enhance the QoS. Mobility-aware routing algorithms can provide ITS with satisfactory mobility, vital dependability, high Packet Delivery Ratio (PDR), high throughput, and low End-to-End (E2E) Delay. The proposed method has an average throughput of 664.3 kbps, a delay of 151.3 ms, and a packet delivery ratio (PDR) of 94.23%.

Factors Influencing ICT Usage in the Healthcare Management System at Government Hospitals in Tanzania: A Case of Kilwa Road Police Hospital

This study assesses the factors influencing Information and Communication Technology (ICT) usage in healthcare management systems at government hospitals in Tanzania, with a specific focus on Kilwa Road Police Hospital. The study aims to: examine the extent to which ICT infrastructure availability influences ICT usage in healthcare management systems; determine the influence of staff awareness on ICT usage at Kilwa Road Police Hospital; and investigate the influence of management support on ICT usage in healthcare management systems at the hospital. The study was guided by the Technology Acceptance Model (TAM) and Resource-Based Theory (RBT) and employed a descriptive research design. Systematic sampling was used to select 162 respondents from a target population of 272 staff members. Data was collected through questionnaires and analysed using both descriptive and inferential statistics. Descriptive statistics included frequencies and percentages, while inferential statistics utilized multiple regression analysis. The findings reveal that the availability of necessary hardware and software is significantly and positively related to the effective utilization of ICT in healthcare management systems at Kilwa Road Police Hospital. Additionally, the level of staff awareness was identified as a crucial factor influencing ICT usage. The relationship between hardware and software availability and ICT utilization was statistically significant (p < 0.05), highlighting its importance in enhancing healthcare management systems. Furthermore, management support was found to play a significant role in ICT usage for healthcare management at Kilwa Road Police Hospital. The study concludes that ICT infrastructure, staff awareness, and management support are critical factors influencing ICT usage in healthcare management systems at Kilwa Road Police Hospital. It recommends that the hospital's management ensure the continuous availability of ICT infrastructure to sustain effective healthcare management systems.

An empirical study of job crafting and employees’ loyalty in the Nigerian healthcare system

Many factors have contributed to the continuous departure of workers from the Nigerian healthcare system since the COVID-19 outbreak. Therefore, this study aimed at examining the effect of job crafting on the loyalty of healthcare workers in public hospitals in Lagos, Nigeria. The study population was 11,084, comprising all the doctors and nurses in public hospitals in Lagos, with a sample size of 725 using the Morgan Sample Size Determination table. We collected primary data using a well-structured questionnaire and conducted analysis using structural equation modeling. The findings revealed a significant positive relationship between job creation and healthcare workers' loyalty in the public healthcare system. This implies that job creation influences health care workers' loyalty. This study suggests that the management of the public healthcare system should encourage and support job crafting while also building and encouraging positive relationships among healthcare workers to ensure their loyalty and effective service delivery.

Risk factor analysis of medical litigation outcomes in obstetrics and gynecology: A retrospective cohort study of 344 claims in Japan

AimMedical errors are critical in obstetrics and gynecology (OB/GYN) and contribute to high litigation risks. However, few studies have examined system and diagnostic errors as potential preventable problems. This study aimed to enhance medical safety and reduce litigation by identifying and addressing key contributory factors. MethodsWe retrospectively searched the national Japanese malpractice claims database for OB/GYN cases between 1961 and 2017. We evaluated provider characteristics and background information of the patients (plaintiffs). The main outcome was litigation (acceptance or rejection) in the final judgment. Using multivariable logistic regression models, we assessed the associations between medical malpractice variables (system and diagnostic errors, facility size, situation, place, time, and clinical outcomes) and litigation outcomes (acceptance). ResultsOverall, 344 malpractice claims were analyzed. Among these, 277 (80.5 %) were obstetric, and 67 (19.5 %) were gynecological. Of the obstetric cases, 193 were perinatal, and 84 were maternal. Malpractice claims were accepted (OB-GYN losses) in 185 cases (53.8 %). In multivariable analyses, system errors (odds ratio 97.4, 95 % confidence interval 35.2–270.0), diagnostic errors (odds ratio 4.5, 95 % confidence interval 1.8–11.3), and clinic (odds ratio 2.7, 95 % confidence interval 1.2–4.8) had a significant statistical association with accepted claims. ConclusionSystem errors, diagnostic errors, and clinics were significantly associated with acceptance claims. These findings underscore the necessity of addressing modifiable factors at the physician level and within the healthcare management system to enhance patient safety and reduce litigation risks, thereby ensuring a safer and more reliable healthcare environment for patients and medical professionals.

Healing the Whole: An International Review of the Collaborative Care Model between Primary Care and Psychiatry.

The collaborative care model (CCM) was created to improve the delivery of mental health care and is reported to improve access, enhance treatment outcomes, and reduce healthcare costs. To understand the impacts of the CCM on symptom management, diverse populations, and sustainability in healthcare systems, a systematic review was conducted. Several databases were searched for articles assessing the CCM. The inclusion criteria limited the studies to those (1) published between January 2008 and January 2024; (2) written in the English language; (3) analyzing adult patients; (4) analyzing symptom improvement in major depressive disorder, generalized anxiety disorder, or post-traumatic stress disorder; and (5) fitting the given definition of a CCM. We identified 9743 articles. Due to missing information or duplication, 4702 were excluded. The remaining articles were screened, yielding 468 articles for full-text analysis, of which 16 articles met the inclusion criteria. Of these articles, five primarily focused on individual patient outcomes, five focused on specific populations, and six reviewed system impacts; eleven articles studied US populations and five studied international populations. An analysis revealed that in 12 of the final articles, the CCM led to a statistically significant improvement in anxiety and depression symptoms with viable implementation and sustainability strategies. The CCM is an effective method for improving patient symptoms and can be potentially affordable in healthcare systems.

Characteristics of U.S. Baccalaureate Health Informatics Programs.

Health informatics (HI) is a growing field of study, yet sparse data are available on the characteristics of undergraduate HI programs in the United States. The lack of a central location for U.S. HI undergraduate program data has led to a gap in information to support current efforts to promote academic standards in the field and attract potential students. The objective of this study was to perform an environment scan of colleges and universities within the United States and Puerto Rico to identify undergraduate programs in HI including majors, minors, and undergraduate-level certificates. Potential institutions offering HI programs were identified from the National Center for Education Statistics (NCES), the Commission for Accreditation of Health Informatics and Health Information Management Education (CAHIIM), the Association of University Programs in Health Administration (AUPHA), the Healthcare Information and Management Systems Society (HIMSS), and the American Health Information Management Association (AHIMA). Publicly available materials for these institutions were reviewed, and data were captured for identified HI programs including geographic location; college or school in which the program was offered; type of degree (if applicable); program title; total credits to complete the program; delivery format; and source of data. A total of 83 HI programs were identified from 60 institutions and 26 states. The primary finding of this environment scan was that inconsistencies exist among U.S. HI undergraduate programs including variations in offering college/school, title of program, number of credits required, delivery formats, CIP codes, and the type of information published on university/college websites. This environment scan was a first step in exploring the characteristics of undergraduate HI programs within the United States. Further research is needed on the curricular similarities and differences among the programs, the administrative methods of these interdisciplinary programs, and the information most needed by current and potential undergraduate students.

Assessment of sustainable healthcare management policies and practices in Oman: A comprehensive analysis using an ai-based literature review

Health Vision 2050 Oman is a strategic plan to establish Oman as a regional leader and a research base for world-class health research. The vision emphasises prioritising health research to allocate and plan available resources appropriately. A sustainable healthcare management system is a holistic approach that seeks to balance economic, social, and environmental concerns to ensure the long-term viability and efficacy of healthcare services. There are numerous obstacles to implementing a sustainable healthcare management system in Oman. For example, assessing patient safety culture in primary healthcare settings in Muscat has revealed patient safety concerns throughout the healthcare system. It is critical to address these difficulties to improve the quality and safety of healthcare services, both of which are essential for sustainable healthcare management. The primary goal of this study is to identify the sustainable healthcare areas and policies required for Oman's Healthcare Management System. This research undertakes a comprehensive literature review using artificial intelligence (AI) to analyse Oman's sustainable healthcare management policies and practices. This study uses two AI tools, Scite.ai and SciSpace, to discover areas and policies related to Oman's sustainable healthcare management system. The study highlighted environmental sustainability, public health initiatives, infrastructure development, waste management, and community engagement and education. Furthermore, a variety of interconnected policies are discernible within each domain. This study provides significant data about Oman's sustainable healthcare practices and can guide policymakers and healthcare sector stakeholders. This study contributes significantly to creating sustainable healthcare management strategies and establishing resilient healthcare systems in Oman by focusing on critical domains and policies.

Primary healthcare in the aftermath of the COVID-19 pandemic: a qualitative interview study in Sweden

ObjectiveTo explore how primary healthcare workers in Sweden experienced and perceived the long-term impact of the pandemic on their work.DesignThis is a descriptive qualitative study with individual semistructured interviews conducted...

Enhancing Citizen Health Literacy Through Digital Technology.

Contemporary society faces significant public health challenges with prevalent unhealthy behaviors and environmental risks leading non-communicable diseases. This study assesses health awareness campaigns'to effectiveness in a specific Taiwanese municipality, focusing on the impact of a health care management system. Objectives include enhancing public health literacy and evaluating community health promotion. The proposed system includes a personalized assistant app, personnel education, and events covering topics like hypertension, diabetes, diet, exercise, and chronic disease prevention. In summary, the research advocates for effective public health interventions, integrating digital technologies, personalized health management, and community engagement to promote health literacy and healthier lifestyles.

Healthcare and the Internet of Medical Things: Applications, Trends, Key Challenges, and Proposed Resolutions

In recent years, the Internet of medical things (IoMT) has become a significant technological advancement in the healthcare sector. This systematic review aims to identify and summarize the various applications, key challenges, and proposed technical solutions within this domain, based on a comprehensive analysis of the existing literature. This review highlights diverse applications of the IoMT, including mobile health (mHealth) applications, remote biomarker detection, hybrid RFID-IoT solutions for scrub distribution in operating rooms, IoT-based disease prediction using machine learning, and the efficient sharing of personal health records through searchable symmetric encryption, blockchain, and IPFS. Other notable applications include remote healthcare management systems, non-invasive real-time blood glucose measurement devices, distributed ledger technology (DLT) platforms, ultra-wideband (UWB) radar systems, IoT-based pulse oximeters, accident and emergency informatics (A&EI), and integrated wearable smart patches. The key challenges identified include privacy protection, sustainable power sources, sensor intelligence, human adaptation to sensors, data speed, device reliability, and storage efficiency. The proposed mitigations encompass network control, cryptography, edge-fog computing, and blockchain, alongside rigorous risk planning. The review also identifies trends and advancements in the IoMT architecture, remote monitoring innovations, the integration of machine learning and AI, and enhanced security measures. This review makes several novel contributions compared to the existing literature, including (1) a comprehensive categorization of IoMT applications, extending beyond the traditional use cases to include emerging technologies such as UWB radar systems and DLT platforms; (2) an in-depth analysis of the integration of machine learning and AI in IoMT, highlighting innovative approaches in disease prediction and remote monitoring; (3) a detailed examination of privacy and security measures, proposing advanced cryptographic solutions and blockchain implementations to enhance data protection; and (4) the identification of future research directions, providing a roadmap for addressing current limitations and advancing the scientific understanding of IoMT in healthcare. By addressing current limitations and suggesting future research directions, this work aims to advance scientific understanding of the IoMT in healthcare.

Machine Learning for Evaluating Hospital Mobility: An Italian Case Study

This study delves into hospital mobility within the Italian regions of Apulia and Emilia-Romagna, interpreting it as an indicator of perceived service quality. Utilizing logistic regression alongside other machine learning techniques, we analyze the impact of structural, operational, and clinical variables on patient perceptions of quality, thus influencing their healthcare choices. The analysis of mobility trends has uncovered significant regional differences, emphasizing how the regional context shapes perceived service quality. To further enhance the analysis, SHAP (SHapley Additive exPlanations) values have been integrated into the logistic regression model. These values quantify the specific contributions of each variable to the perceived quality of service, significantly improving the interpretability and fairness of evaluations. A methodological innovation of this study is the use of these SHAP impact scores as weights in the data envelopment analysis (DEA), facilitating a comparative efficiency analysis of healthcare facilities that is both weighted and normative. The combination of logistic regression and SHAP-weighted DEA provides a deeper understanding of perceived quality dynamics and offers essential insights for optimizing the distribution of healthcare resources. This approach underscores the importance of data-driven strategies to develop more equitable, efficient, and patient-centered healthcare systems. This research significantly contributes to the understanding of perceived quality dynamics within the healthcare context and promotes further investigations to enhance service accessibility and quality, leveraging machine learning as a tool to increase the efficiency of healthcare services across diverse regional settings. These findings are pivotal for policymakers and healthcare system managers aiming to reduce regional disparities and promote a more responsive and personalized healthcare service.

Valuation of knowledge, attitude, practices of tuberculosis among the health care workers from Islamabad Pakistan

BackgroundTuberculosis (TB) as a foremost infectious disease adds massive burden to morbidity and mortality rate, despite of well-structured TB control programs around the globe. Inappropriate health care management system and poor implementation on standard in relevance to TB, remain some reasons causative to TB prevalence and its rising antimicrobial resistance. Health Care Workers (HCWs) laboring as a part of TB control system, are the vital warriors in achieving the goals of TB End Strategy by 2035. Their performance is influenced by their knowledge, attitude, and practices (KAP) toward this infectious disease. This study aimed to signify the role of KAP score of health care Workers in the better control and prevention of TB in the Islamabad Capital Territory (ICT), Pakistan. MethodsA cross-sectional study on Knowledge, Attitude and Practice study of Tuberculosis (TB) among health care Workers, was done in ICT, which is the capital of Pakistan. The KAP of TB was collected for the 306 Health Care Workers from all the Islamabad TB referring health facilities which refer the TB patients for testing to the National Reference Laboratory, Islamabad Pakistan. Eligible health care workers were requested to respond on KAP questionnaire after informed consent. KAP questionnaire comprised of knowledge, attitude, and practices section including demographic information. All the data was analyzed using IBM SPSS statistics 21. One Way Analysis of Variance (ANOVA) was applied to calculate KAP mean score against different variables. On the significant data sets of ANOVA output, Tukey's Multiple Comparison Test was applied for pairwise comparison. Pearson correlation coefficient was utilized to explore the association between two qualitative variables. The non-parametric tests were applied to evaluate difference of KAP score in relation to demographic covariates individually. ResultsFrom June to July 2023, we conducted TB KAP study among Health Care Workers of ICT, Pakistan. The average age was 33 years (range 26–30 years). Majority of the recruited subjects were not being trained for dealing with TB infection. The results demonstrated that Health Care Workers working were lacking their knowledge about mode of TB transmission, best diagnostic technique, and contraction of TB infections. The mean knowledge, attitude and practices mean scores were 15.05 (SD = 3.96), 83.68 (SD = 15.74) and 6.31 (SD = 2.21), respectively. Mean knowledge score of Health Care Workers were significantly related to their educational level and occupation while no significant association was declared with working experience as TB staff. Pearson coefficient of attitude score with knowledge of Health Care Workers was of weak level (0.28). Practice mean score was correlated to knowledge mean score at a moderate level (r = 0.40). On the other hand, practice score was r = 0.29 with attitude mean score had shown weak level correlation. A number of demographic factors were strongly linked to each of the mean score of knowledge, attitude, and practices. ConclusionThese findings highlighted the significant involvement of education, profession, and professional trainings in the better knowledge, attitude, and practices of the TB related health care Workers. For a better management system of infectious diseases like TB, a well-trained and professionally competent staff of Health Care Workers is important so as to achieve the goal of TB-End strategy by 2035 from Pakistan, which is the 5th highest burden country for TB.

A blockchain-based solution for enhancing the efficiency and security of healthcare knowledge management systems in the era of industry 4.0

A blockchain-based solution for enhancing the efficiency and security of healthcare knowledge management systems in the era of industry 4.0

Analisis Pelaksanaan Rujukan Pasien Rawat Jalan Peserta BPJS Kesehatan di Puskesmas Mataram

The referral system is a healthcare management system that carries out the transfer of mutually accountable responsibilities for a specific medical case or health problem either vertically, meaning from a less capable unit to a more capable unit, or horizontally, meaning among units of similar capabilities. The referral system regulates the flow of where someone with a particular health problem should seek examination for their health issues. The purpose of this research is to analyze the Implementation of Outpatient Referral for Participants of the Health Social Security Agency (BPJS Kesehatan) at Mataram Community Health Center. The method used in this research employs a qualitative descriptive approach to gain an overview of the analysis of outpatient referral implementation for BPJS Kesehatan participants at Mataram Community Health Center. Descriptive means that the data collected are in the form of words, images, and not numerical values. The findings of the research indicate that the implementation of outpatient referral at the Community Health Center shows that it has not fully run smoothly. Patient knowledge varies, with some understanding and others not understanding. The facilities and infrastructure are still lacking, some diseases diagnosed under code 144 are still referred, many referrals are initiated by the patients themselves, and there are outpatient referrals from outside healthcare facilities.

Cognitive analytics enabled responsible artificial intelligence for business model innovation: A multilayer perceptron neural networks estimation

Cognitive analytics employs and analyses complex and heterogeneous data sources generating deeper insights that mimic the natural intelligence of the human brain. Cognitive analytics-enabled Artificial Intelligence (AI) that promotes Business Model Innovation (BMI) for the efficiency of the healthcare system is a nascent and undertheorized domain. Within the healthcare management systems, stakeholders’ engagement with AI, particularly with responsible AI, to optimize BMI and improve business performance is bounded by several caveats. Using the Technology Acceptance Model (TAM) and Social Network Theory (SNT) as our conceptual foci, we empirically examine through the Multilayer Perceptron Neural Network the extent to which responsible AI leads to Business Model Innovation (BMI) through the stakeholders’ engagement. Our contributions are novel which demonstrate that cognitive analytics-enabled responsible AI is central to innovation, and healthcare stakeholders exhibit a robust propensity to reorientate and innovate their existing BMI to achieve improved business performance. It has significant implications for innovation, AI and cognitive analytics literature.

Developing guidelines for ethical response to infectious disease outbreaks in Islamic Republic of Iran

Background: Ethical considerations are important in pandemic preparedness and response, however, there is a noticeable scarcity of ethical codes that are tailored to disease outbreaks and health emergencies. Aim: To document the development of guidelines for ethical management of infectious disease outbreaks in Islamic Republic of Iran, as a model for low- and middle-income countries. Methods: We conducted a non-systematic scoping review on PubMed and Google Scholar for drafting the guidelines for ethical management of infectious disease outbreaks in Islamic Republic of Iran. The draft was discussed and revised following consultations with different groups of experts and the Medical Ethics Council of the Iranian Academy of Medical Sciences. Results: The joint assembly of the National Clinical Ethics Committee and the Supreme Council of Medical Ethics endorsed and introduced the revised document as official guidelines for ethical response to infectious disease outbreaks in Islamic Republic of Iran. The guidelines were based on a set of core values and principles: human dignity, liberty, maximizing benefits and minimizing risks, and justice and transparency. In 3 distinct sections, the document provides ethical guidance for healthcare system management and leadership; provision of health services; and for education, research and use of technology during health emergencies. Conclusion: The guidelines have been very useful in responding ethically to the COVID-19 pandemic, there may be a need to adapt some of the recommendations for optimum benefits in specific contexts. It is necessary to create awareness of the existence of the document and educate healthcare professionals about its importance so they can apply the recommendations in their practice.