Effectiveness Of Health Care Services Research Articles

Evaluation of an electronic prescription platform: Clinicians’ feedback on three distinct services aiming to facilitate clinical decision and safer e-prescription

BackgroundHealth Care Professionals (HCPs) are the main end-users of digital clinical tools such as electronic prescription systems. For this reason, it is of high importance to include HCPs throughout the design, development and evaluation of a newly introduced system to ensure its usefulness, as well as confirm that it tends to their needs and can be integrated in their everyday clinical practice. MethodsIn the context of the PrescIT project, an electronic prescription platform with three services was developed (i.e., Prescription Check, Prescription Suggestion, Therapeutic Prescription Monitoring). To allow an iterative process of discovery through user feedback, design and implementation, a two-phase evaluation was carried out, with the participation of HCPs from three hospitals in Northern Greece. The two-phase evaluation included presentations of the platform, followed by think-aloud sessions, individual platform testing and the collection of qualitative as well as quantitative feedback, through standard questionnaires (e.g., SUS, PSSUQ). ResultsTwenty one HCPs (8 in the first, 18 in the second phase, and five present in both) participated in the two-phase evaluation. HCPs comprised clinicians varying in their specialty and one pharmacist. Clinicians' feedback during the first evaluation phase already deemed usability as “excellent” (with SUS scores ranging from 75 to 95/100, showing a mean value of 86.6 and SD of 9.2) but also provided additional user requirements, which further shaped and improved the services. In the second evaluation phase, clinicians explored the system's usability, and identified the services' strengths and weaknesses. Clinicians perceived the platform as useful, as it provides information on potential adverse drug reactions, drug-to-drug interactions and suggests medications that are compatible with patients' comorbidities and current medication. ConclusionsThe developed PrescIT platform aims to increase overall safety and effectiveness of healthcare services. Therefore, including clinicians in a two-phase evaluation confirmed that the introduced system is useful, tends to the users’ needs, does not create fatigue and can be integrated in their everyday clinical practice to support clinical decision and e-prescribing.

Performance Evaluation of Hospitals under Data Uncertainty: An Uncertain Common-Weights Data Envelopment Analysis.

In the context of healthcare systems, the performance evaluation of hospitals plays a crucial role in assessing the quality of healthcare systems and facilitating informed decision-making processes. However, the presence of data uncertainty poses significant challenges to accurate performance measurement. This paper presents a novel uncertain common-weights data envelopment analysis (UCWDEA) approach for evaluating the performance of hospitals under uncertain environments. The proposed UCWDEA approach addresses the limitations of traditional data envelopment analysis (DEA) models by incorporating the uncertainty theory (UT) to model the inherent uncertainty in input and output data. Also, by utilizing a common set of weights (CSW) technique, the UCWDEA method provides a more robust and reliable assessment of hospital performance. The main advantages of the proposed UCWDEA approach can be succinctly summarized as follows. Firstly, it allows for the comparison of all hospitals on a consistent basis to calculate a realistic efficiency score, rather than an overly optimistic efficiency score. Secondly, the uncertain common-weights DEA approach exhibits linearity, enhancing its applicability. Thirdly, it possesses the capability to extend its utility under various other prevalent uncertainty distributions. Moreover, it enhances the discriminatory power of results, facilitates the ranking of hospitals in the presence of data uncertainty, and aids in identifying the sensitivity and stability levels of hospitals towards data uncertainty. Notably, in order to showcase the pragmatic application and efficacy of the uncertain common-weights DEA model, a genuine dataset has been utilized to evaluate the efficiency of 20 public hospitals in Tehran, all of which are affiliated with the Iran University of Medical Sciences. The results of the experiment demonstrate the efficacy of the UCWDEA approach in assessing and ranking hospitals amidst uncertain conditions. In summary, the research outcomes can offer policymakers valuable insights regarding hospital performance amidst data uncertainty. Additionally, it can provide practical recommendations on optimizing resource allocation, benchmarking performance, and formulating effective policies to augment the overall efficiency and effectiveness of healthcare services.

Utilization of repeat services in the outpatient department of Dewi Sartika general hospital, Kendari City, 2023

The reutilization of services in outpatient clinics of hospitals plays a crucial role in enhancing the quality and effectiveness of healthcare services. This study aims to analyze the factors associated with service reutilization in hospital outpatient clinics using a cross-sectional design and quantitative approach. Data were collected through questionnaires from 100 respondents at Dewi Sartika General Hospital in Kendari, Southeast Sulawesi, during October-November 2023, using accidental sampling techniques. The analysis results indicate that factors such as service quality, family encouragement, facilities, location, and patient attitudes are significantly associated with service reutilization in outpatient clinics. Univariate analysis was used to describe sample and variable characteristics, while bivariate analysis involved correlation testing to evaluate the relationships among variables. The conclusion of this study highlights the importance of enhancing communication, education, and family support in influencing patient decisions to reuse the same services at the hospital. The development of family support programs, patient empowerment, family-friendly policies, and periodic program evaluations are crucial steps in improving patient experiences and healthcare outcomes. Recommendations include critical steps such as enhancing communication, education, and family support, as well as developing structured family support programs, empowering patients, implementing family-friendly policies, and conducting regular program evaluations. It is expected that the implementation of these recommendations will improve patient experience, enhance adherence to treatment, and overall improve healthcare outcomes.

The use of Electronic Medical Record (EMR) in hospitals during the COVID-19 pandemic in Indonesia: a systematic literature review

Purpose: Electronic medical records (EMR) are information technology-based systems that store and manage patient medical data. EMR are beneficial for improving healthcare services' efficiency, effectiveness, and security. The COVID-19 pandemic has driven the adoption of EMR, but there are still challenges, such as the surge in patient numbers and problems with EMR filling. This study aimed to investigate the use of EMR in hospitals during the COVID-19 pandemic in Indonesia. 
 Method: This study was a systematic literature review using the PRISMA diagram. Article search was conducted based on the PICO model eligibility criteria. The articles used were retrieved from 3 databases: Google Scholar, ResearchGate, and Cerdika. The researcher limited the publication year of the journals to 2020-2021, when the COVID-19 pandemic was ongoing, and added the keyword "COVID-19" to the journals published in 2022-2023. 
 Results: The results of the study showed that the COVID-19 pandemic has had a significant impact and the need for the implementation of EMR due to its various benefits, such as improving the efficiency and effectiveness of healthcare services, facilitating access to patient health information, increasing collaboration among healthcare workers, accelerating the process of clinical decision-making, and improving the security and accuracy of health data. However, implementing EMR during the COVID-19 pandemic has only sometimes been smooth. Some challenges include suboptimal infrastructure, untrained human resources, and inadequate policies. 
 Conclusion: To overcome these challenges, efforts from various parties, including the government, hospitals, and healthcare workers, are needed.

Morbidity and mortality profile of neonates: a five-year retrospective study in a tertiary care neonatal unit in Kolkata

Background: Neonatal mortality and morbidity pattern reflects a nation's efficiency and effectiveness of health care services. There is a paucity of reliable data in India on this, while India Newborn Action Plan (INAP) targets single digit neonatal mortality by 2030. Aim was to identify the morbidity and mortality profile of neonates admitted to a tertiary neonatal care unit. Methods: This retrospective descriptive study was conducted at a tertiary care neonatal unit in Kolkata. Data of neonates admitted in this unit were extracted from admission, discharge, and death registers, compiled, and analyzed from January 2015 to December 2019. Neonates brought dead to the unit were excluded. Results: A total of 10301 neonates were admitted during the study period of which 75.05% were inborn. Most of them were male (55.46%) and only 0.70% had differential sexual disorders. A total of 709 deaths were recorded during the study period equating to a rate of 6.9 deaths per 100 neonatal admissions. The major cause of admission was neonatal hyperbilirubinemia (19.30%) followed by congenital anomalies (11.15%), respiratory distress syndrome (10.58%), prematurity (9.72%), and birth weight <1800 grams. (9.51%), perinatal asphyxia (8.11%) and maternal sickness (8.09%). Among congenital anomalies, anomalies related to the gastrointestinal system were most frequent (30.81%). Congenital anomalies (29.9%) were the leading cause of neonatal mortality followed by perinatal asphyxia (17.07%). Conclusions: The commonest causes of neonatal morbidity and mortality were congenital anomalies. Thus, special focus has to be given to the management of congenital malformation in tertiary care units.

A Study on the Effectiveness and Efficiency of Public or Private Hospitals within Pakistan

Hospitals play a very important role in human lives. People are in search of quality and timely healthcare facilities. This paper talks about the efficiency and effectiveness of healthcare services. One needs to identify the factors and mechanisms to enhance the performance of government and private hospitals. This study aims to find the important variables that were required to find the best solution for public and private hospitals in Pakistan. The major contributions of the paper are as follows. The paper first deliberates on the need for technical excellence as compared to interpersonal excellence for hospital management. It also performs a qualitative review of the literature on the important variables for determining the effectiveness and efficiencies of the hospital. Then, the paper presents a public survey about the effectiveness and efficiency of public and private hospitals using different questionnaires. These questionnaires were filled by the relatives of patients or patients themselves when they visited hospitals. On this dataset, the paper applies a machine learning algorithm i.e., random forest, to predict which hospital type is suitable for them while considering the variables. These variables include; the services of the hospital, admission process, treatment, doctor's behavior, timely treatment, and knowledge of the staff about SOPs. The data was split into 75 % training and 25 % testing dataset. Python’s Library SK-learn was used for implementation. The accuracy of the classifier on the test dataset is 96.91 %. The paper then determines the variables that are contributing the most to the measure of effectiveness and efficiencies of hospitals. The algorithm also ranks these features that can be used to improve a hospital's performance. It also provides a benchmark to the patients in the selection of hospitals for healthcare facilities.

Artificial Intelligence and Decision-Making in Healthcare: A Thematic Analysis of a Systematic Review of Reviews.

The use of artificial intelligence (AI), which can emulate human intelligence and enhance clinical results, has grown in healthcare decision-making due to the digitalization effects and the COVID-19 pandemic. The purpose of this study was to determine the scope of applications of AI tools in the decision-making process in healthcare service delivery networks. This study used a qualitative method to conduct a systematic review of the existing reviews. Review articles published between 2000 and 2024 in English-language were searched in PubMed, Scopus, ProQuest, and Cochrane databases. The CASP (Critical Appraisal Skills Programme) Checklist for Systematic Reviews was used to evaluate the quality of the articles. Based on the eligibility criteria, the final articles were selected and the data extraction was done independently by 2 authors. Finally, the thematic analysis approach was used to analyze the data extracted from the selected articles. Of the 14 219 identified records, 18 review articles were eligible and included in the analysis, which covered the findings of 669 other articles. The quality assessment score of all reviewed articles was high. And, the thematic analysis of the data identified 3 main themes including clinical decision-making, organizational decision-making, and shared decision-making; which originated from 8 subthemes. This study revealed that AI tools have been applied in various aspects of healthcare decision-making. The use of AI can improve the quality, efficiency, and effectiveness of healthcare services by providing accurate, timely, and personalized information to support decision-making. Further research is needed to explore the best practices and standards for implementing AI in healthcare decision-making.

Assessing the Big Data Adoption Readiness Role in Healthcare between Technology Impact Factors and Intention to Adopt Big Data

Big data is quickly becoming a new area where administrative work can be improved. Even so, it is still in the early stages of being used in hospitals in countries with less technology. Therefore, there is an inadequate grasp of the evaluation of big data adoption preparedness in the healthcare sector as data-point-determined insights become crucially useful in healthcare institutions in underdeveloped nations. This process, called “digital transformation,” has a lot of benefits; for example, it helps healthcare organizations to create more efficient processes, offer different services, give better care, make more money, and cut costs. This paper aims to suggest and assess a conceptual framework that focuses on technological factors and can assist in determining the readiness of healthcare institutions in developing nations to utilize big data. Although the study can offer valuable perspectives on the advantages that can arise from adopting big data in the healthcare sector, it is important to highlight that leveraging big data analytics in healthcare has the potential to enhance the efficiency and effectiveness of healthcare services. This, in turn, can indirectly contribute to sustainability objectives by optimizing the allocation of resources, minimizing waste, and improving patient outcomes. A total of 328 healthcare workers from Malaysia were subjected to experimental testing of the model. The collected data were evaluated using the Smart PLS 3 program and the structural equation model (SEM). The study’s findings supported our hypotheses. The results showed that technological factors affected the participants’ perception of their readiness for big data, which ultimately influenced their interest in utilizing it. By concentrating on big data preparedness in the healthcare industry and ambition to utilize big data, this research provides an important theoretical contribution. Employees who are “big data ready” would benefit from the study’s results, as, through their recognition, said employees are more likely to increase the desire to use big data in Malaysia’s healthcare sectors.

Implementation of Ventilator Associated Pneumonia (VAP) Prevention in Health Care and Its Effectiveness: Literature Review

Background: The incidence of HAIs in developed countries is estimated at around 1/100 hospitalized patients, while in developing countries it is around 10/100 patients. Patients receiving mechanical ventilation accounted for 86% of HAI cases. As many as 9-27% of patients with ventilator installation have the possibility of suffering from VAP.
 Objectives: This study aims to describe the implementation of VAP prevention and its effectiveness in health care services.
 Research Metodes: This type of research is literature study through the search engines ScienceDirect, Google Scholar, and PubMed.
 Results: Of the thirteen articles obtained, there were six articles discussing the implementation of VAP prevention in health services, six articles discussing the effectiveness of VAP prevention in health services, and one article discussing both.
 Conclusion: Prevention of VAP in health services is carried out through surveillance and bundles. This prevention is very effective in reducing VAP cases in health care facilities if the implementation is optimal

Perceived Stress and Anxiety of Healthcare Providers Before and After a Hospital Accreditation Program in Ahvaz City, Iran

Background: Evaluation and accreditation of hospitals have essential roles in improving the quality, safety, and effectiveness of healthcare services. Nevertheless, this process may cause stress and anxiety among hospital staff. This study aims to determine and compare employees’ anxiety levels and perceived stress before and after the accreditation program in private hospitals in Ahvaz City, Iran. Methods: This research was a quantitative, observational, and longitudinal study. A total of 456 employees of Ahvaz private hospitals were recruited by convenience sampling. The state-trait anxiety inventory (STAI) and the perceived stress scale-14 (PSS-14) were used to measure the level of anxiety and stress among hospital employees one month before and one month after implementing the hospital accreditation program. The data were analyzed in SPSS software, version 22 using descriptive and inferential statistics, such as the paired t-test, Pearson, and Spearman correlation coefficients. The significance level was set at P<0.05. Results: The findings showed a significant difference between perceived stress and anxiety before and after implementing the accreditation program (P<0.05). There was a significant relationship between the employees’ perceived stress levels and their age, gender, and work experience. The subjects’ state-trait anxiety was also significantly associated with their sex, work experience, and organizational position (P<0.05). Conclusion: Although the accreditation program usually improves the quality of healthcare, the employees experienced more stress and anxiety before the implementation of this program than after its completion, which can negatively affect the quality of care. Therefore, policymakers and managers should pay great attention to prevent stress and anxiety among healthcare providers while implementing the accreditation program.

The antecedents of patient satisfaction: Evidence from super-specialty hospitals in Tiruchirappalli in India

ABSTRACT This study explores the determinants of patient satisfaction in the healthcare industry in a developing country. The effect of healthcare services, supportive services, and auxiliary services were conceptualized in three models. After checking the measurement properties of the survey instrument, the hypotheses were tested using the data collected from 748 in-patients from five super specialty hospitals in Tiruchirappalli in southern India. The physicians’ services, intensive care unit (ICU) services, operation theatre (OT) services, and outpatient department (OPD) services had a significant positive influence on patient satisfaction. The results also suggest supportive services, including nurse, technical, and administrative services, played an essential role in increasing patient satisfaction. Finally, patients were satisfied with the registration process, transportation, and housekeeping services, including cleanliness in the hospitals. The results did not find support for pharmacy services, emergency services, and hospital security impacting patient satisfaction. The findings provide recommendations for the administrators of healthcare units to improve patient satisfaction.

The Italian registry for patients with Prader–Willi syndrome

BackgroundPrader–Willi syndrome (PWS) is a rare and complex genetic disease, with numerous implications on metabolic, endocrine, neuropsychomotor systems, and with behavioural and intellectual disorders. Rare disease patient registries are important scientific tools (1) to collect clinical and epidemiologic data, (2) to assess the clinical management including the diagnostic delay, (3) to improve patients’ care and (4) to foster research to identify new therapeutic solutions. The European Union has recommended the implementation and use of registries and databases. The main aims of this paper are to describe the process of setting up the Italian PWS register, and to illustrate our preliminary results.Materials and methodsThe Italian PWS registry was established in 2019 with the aims (1) to describe the natural history of the disease, (2) to determine clinical effectiveness of health care services, (3) to measure and monitor quality of care of patients. Information from six different variables are included and collected into this registry: demographics, diagnosis and genetics, patient status, therapy, quality of life and mortality.ResultsA total of 165 patients (50.3% female vs 49.7% male) were included into Italian PWS registry in 2019–2020 period. Average age at genetic diagnosis was 4.6 years; 45.4% of patients was less than 17 years old aged, while the 54.6% was in adult age (> 18 years old). Sixty-one percent of subjects had interstitial deletion of the proximal long arm of paternal chromosome 15, while 36.4% had uniparental maternal disomy for chromosome 15. Three patients presented an imprinting centre defect and one had a de novo translocation involving chromosome 15. A positive methylation test was demonstrated in the remaining 11 individuals but the underlying genetic defect was not identified. Compulsive food-seeking and hyperphagia was present in 63.6% of patients (prevalently in adults); 54.5% of patients developed morbid obesity. Altered glucose metabolism was present in 33.3% of patients. Central hypothyroidism was reported in 20% of patients; 94.7% of children and adolescents and 13.3% of adult patients is undergoing GH treatment.ConclusionsThe analyses of these six variables allowed to highlight important clinical aspects and natural history of PWS useful to inform future actions to be taken by national health care services and health professionals.

ESPO AND HEALTH SCIENCES SECTION SYMPOSIUM: INCLUDING DIVERSE STAKEHOLDERS IN HEALTH INTERVENTION DESIGN: LESSONS LEARNED FOR ADVANCING HEALTH EQUITY

Abstract The COVID-19 pandemic exposed persistent disparities in the effectiveness of healthcare services and long-term care among the older adult population. For example, significant gaps disproportionately affected older adults living in rural areas, racial and ethnic minorities, individuals with cognitive impairments, and those from low socioeconomic backgrounds. To improve health equity, research is needed to design, implement, and disseminate health interventions that address the heterogeneity of older adults and caregivers. Reflecting on lessons learned from including underrepresented key stakeholder groups in intervention research may reveal strategies to design health interventions that are more accessible and effective for diverse populations of older adults and their caregivers. This symposium highlights five studies that included diverse populations of older adults and/or caregivers in the design of health interventions. Dr. Schiaffino will share how disparities in co-morbid cancer and dementia across racial, ethnic, and age groups will inform improvements to care delivery processes for this population. Ms. Crane will discuss barriers to designing exergame interventions that are accessible to older adults with multiple chronic conditions and functional limitations. Dr. Díaz-Santos will describe results of piloting and refining a social connection intervention to reduce loneliness among Latinx older adults at risk for dementia. Dr. del Pino will highlight strategies to improve implementation of a screening intervention for at-risk drinking among African American older adults living with HIV. Mr. Cotton will present results of tailoring a crisis intervention to improve cultural fit for African American caregivers of people with dementia.

Comparing the Effectiveness of 2 Cardiac Rehabilitation Exercise Therapy Programs

Cardiovascular diseases are among the leading causes of morbidity and mortality in Canada, highlighting the critical role of disease prevention and risk reduction programs. Cardiac rehabilitation (CR) is a key component of comprehensive cardiovascular care. Currently, more than 200 CR programs are established across the country, varying in duration, number of in-person supervised exercise sessions, and recommendations for exercise frequency at-home. In an increasingly cost-conscious healthcare environment, the effectiveness of healthcare services must be consistently reevaluated. This study evaluates the impact of 2 CR programs implemented by the Northern Alberta Cardiac Rehabilitation Program, by comparing peak metabolic equivalents achieved by study participants in each program. We hypothesize that our “hybrid” CR program, which is structured as an 8-week program with weekly in-person exercise sessions and a prescribed home exercise program, has patient outcomes similar to those of our “traditional” CR program, which required biweekly in-person exercise sessions over the course of 5 weeks. The results of this study may have implications for evaluating how to minimize barriers to both rehabilitation participation and long-term effectiveness of CR programs. The results may help inform the structuring and funding of future rehabilitation programs.

Briefs in Assessing the Adequacy of Health Care Facilities’ Fixed Assets

This work considers some procedures to assess the adequacy of fixed assets for Health Care facilities activity. In terms of effectiveness, equitable distribution examines whether limited resources are directed toward improving the health of the population in the delivery of health care services. Assessing the adequacy of health care resources examines the extent to which resources are used to provide health system outcomes and/or achieve health system goals. The results of such an assessment: on the one hand can prevent waste of limited health care resources, and another hand to increase effectiveness of health care services.

A prospective interoperable distributed e-Health system with loose coupling in improving healthcare services for developing countries

A loosely coupled distributed system enables interoperability in healthcare structures and can be used to create flexible architecture. The key limitation in adopting electronic health (e-Health) services in developing countries is the health data interoperability problem. Most developing countries are being confronted with the utilization of e-Health systems for their health care services. This study aims to develop a prospective e-Health system for developing countries to improve the effectiveness of health care services. This paper presents an enhanced e-Health framework using distributed memory and heterogeneous data handling mechanisms with loose coupling. The distributed e-Health has been designed using e-Health standards that are compatible with health level 7 (HL7) and can facilitate interoperability among health information systems. The Message Passing Interface (MPI) has been implemented to store regular backups of heterogeneous health data. The HL7 standards can also handle security threats. Data interchange from one e-Health system server to another has been conducted based on the experimental results. The distributed database has been made accessible from a remote server by using loosely coupled technology. It also provided the e-Health data recovery features and handled an extensive database through a distributed environment. According to the study, the developed system can deliver a low-cost service to the intended developing-country community effectively. • Entails distributed technology into the e-Health system and keep track of the health records of different organizations independently for developing countries. • Providing potential interoperability among health information systems using health level 7 (HL7) based e-Health standard. • Employs a decentralized, distributed database to address the challenges of a centralized database in sustaining e-Health care. • Using the message passing interface (MPI) regular backups of heterogeneous health data has been performed to avoid system failure.

BOSS: A new QoS aware blockchain assisted framework for secure and smart healthcare as a service

AbstractThe latest epidemic of COVID‐19 has significantly impacted both human capital and the global economy, contributing to pandemics and severe global crises. Research into the creation and propagation of the disease is desperately needed. The Internet of Things, cloud computing, and artificial intelligence offer modern technology for real‐time processing for multiple applications such as healthcare applications, transport, traffic control, and so on blockchain is an evolving technology that will dramatically boost transaction protection in finance, supply chain, and other transaction networks. A stable and latency‐sensitive Quality of Service framework for COVID‐19 is the need of an hour. The purpose of this paper is to combine Fog computing and Artificial Intelligence with smart health to establish a reliable platform for early‐stage detection of COVID‐19 infection. A new ensemble‐based classifier is proposed to detect COVID‐19 patients. This research offers a blockchain platform to analyse how the unrelated cases of the COVID‐19 virus can be tracked and identified using peer‐to‐peer, time stamping, and the shared storage advantages of blockchain. In addition to growing patient loyalty, this would effectively enhance the consistency, flexibility, productivity, performance, and effectiveness of healthcare services. The idea of blockchain is used to establish security for the whole framework. Different implementations measure the efficiency of the suggested system. The performance of the proposed framework is evaluated in terms of delay, network usages, RAM usages, and energy consumption. On the other hand, the classifier is evaluated in terms of classifier accuracy, recall, precision, kappa static, and root mean square error. The result shows the performance of the proposed framework and classifier is always better than the traditional frameworks and classifiers.

Revisiting the relationship between contact and physician attitudes toward patients with opioid use disorder

IntroductionPrior research suggests that some physicians hold negative attitudes toward patients who misuse opioids and that this serves as a barrier which limits the availability and effectiveness of health care services. Interventions which improve physicians’ attitudes have thus garnered attention, many of which have focused on increasing contact between physicians and patients who misuse opioids. However, drawing on recent literature on intergroup contact, the current paper argues that contact may not have uniformly positive effects on prejudice. MethodsWe surveyed 408 board-certified physicians in the state of Ohio where many opioid overdose deaths have been concentrated. We used regression to test for interactions between contact and three focal variables, bias, burnout, and stress, on physician willingness to work with patients who misuse opioids. ResultsThe negative relationships between bias, physician burnout, and stress induced by working with patients who misuse opioids and physicians’ willingness to work with this patient population are each exacerbated when contact with patients who misuse opioids is high. ConclusionsAlthough intervention studies have shown promise for the role that increased contact may have in reducing stigma toward patients who misuse opioids, these interventions may not be appropriate for physicians who are experiencing strain or who hold preexisting negative attitudes toward this patient population. Future interventions may need to target bias, burnout, and stress, in addition to facilitating contact, to increase physician willingness to work with these patients.

Organizational hindrances to Healthcare 4.0 adoption: An multi‐criteria decision analysis framework

AbstractDue to the latest developments in the healthcare sector, the efficiency and effectiveness of healthcare services are being improved. This investigation aims to shortlist the organizational hindrances that influence the adoption of Healthcare 4.0 technologies and model the mutual relationship between them using the DEMATEL methodology. In addition, this study offers a cause‐effect relationship between the barriers and helps to identify the most important challenges to the adoption of Healthcare 4.0 technologies. By reviewing the literature and consulting experts in the case domain, 10 hindrances were identified. The findings of the study highlighted three causal factors namely ‘Lack of vision and commitment from the top management’, ‘Hierarchical structure’, and ‘Lack of skilled workforce’ as critical ones that have the significant causality intensity; whereas, ‘Lack of R&D facilities’ was found be the least significant barrier which belongs to the effect category. It may be noted that the causal factors need to be addressed by the top management of the healthcare organizations for the successful adoption of Health 4.0. Further, the elimination of the causal factors identified by this study would help in reducing the cost of the treatment and enhance the patients' experience. In addition, this research aims to guide managers/decision‐makers of healthcare organizations to deduce policies for the adoption of the latest technologies in the case sector.

Integration of human factors/ergonomics in healthcare systems: A giant leap in safety as a key strategy during Covid-19.

In this article, we present a model for integrating Human Factors/Ergonomics (HFE) into healthcare systems to make them more robust and resilient. We believe that to increase the impact of HFE during and after the Covid‐19 pandemic this integration should be carried out simultaneously at all levels (micro, meso, and macro) of the healthcare system. This new model recognizes the interrelationship between HFE and other system characteristics such as capacity, coverage, robustness, integrity, and resilience. We hope that the model will serve as a reference for a giant leap to design and improve the safety and effectiveness of healthcare services from a holistic (systems) perspective.