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The purpose of this study was to better understand the state of the healthcare facility management (FM) workforce and trends and how it compares to the nonhealthcare industries.

A survey was developed, based on relevant literature, regarding respondents’ gender, race, age, educational attainment and job tenure. The survey was sent electronically via Qualtrics^® system in February 2021 to members of the International Facility Management Association membership; 3,557 individuals completed the survey by April 2021, for a 29% response rate. Only data from 1,407 US respondents working in facility operations were included in this study. Of the 1,407 respondents included in this study, 89 worked in the healthcare industry. The majority of respondents not working in healthcare industry (1,318) were employed in government, education or banking and investment.

The demographics of facility managers in the healthcare industry are similar to the demographics of facility managers in other industries: the majority of the FM workforce is male, middle-aged, white, college educated and employed in-house. While healthcare and nonhealthcare facility managers have similar responsibilities across job levels, compensation for entry-level FM roles in the healthcare industry is significantly lower than for entry-level FM roles in other industries. This low pay in healthcare FM, compared to other industries, may exacerbate ongoing challenges related to talent recruitment and retention and justify pay banding increases to improve attraction of top talent into healthcare FM. Both healthcare and nonhealthcare industries hire new college graduates for entry-level FM jobs, but the healthcare industry is more likely to hire individuals who majored in liberal arts compared to other industries more likely to hire individuals who majored in subjects related to the built environment such as FM and engineering. To compensate for low entry-level pay, healthcare organizations may be focusing recruitment efforts on liberal arts students who have little to no training in the built environment because they have lower pay expectations. Older healthcare facility professionals also have shorter job tenures with their current employers than do older facility professionals in other industries; this trend appears to be recent and not be related to pay or the COVID-19 pandemic. A surge of senior-level FM retirements may be creating advancement opportunities for older entry- and mid-level FM personnel in healthcare; if this situation is a factor, research should be conducted to understand its implications for recruiting and developing healthcare FM talent.

Only data from US respondents who were working in healthcare facility operations at the time of the study were included in the data analysis.

Healthcare organizations can use the study’s findings to help address FM workforce challenges unique to their industry staff recruitment, retention and succession planning.

By following the “employee-centric” approach, this study aims at identifying the impact of high-performance work systems (HPWS) on specific employee attitudinal outcomes such as work engagement, job satisfaction and affective commitment in the Indian healthcare industry.

The target population for this study includes the nurses working in large private multi-specialty tertiary care hospitals in India. Partial Least Squares Structural Equation Modelling (PLS-SEM) techniques are used on a sample of 152 nurses working in two large specialty hospitals.

In the Indian healthcare industry context, the nurse's perception of HPWS has shown a significant positive effect on their attitudinal variables such as work engagement, job satisfaction and affective commitment. When checked for mediation of work engagement and job satisfaction variables in HPWS – affective commitment relationship, nurse's job satisfaction partially mediated the relationship, but nurse's work engagement has shown no mediation effect.

This is one of the pioneering studies conducted in the Indian healthcare industry context, especially on the nurse's sample in identifying the impact of high-performance work systems on their attitudinal outcomes. Underscoring the paucity of HPWS research in the Indian healthcare industry, this study's findings will be an addition to the HPWS literature and also to the nursing research in the Indian healthcare settings.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.

At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.

Along with technology-based ecosystems, healthcare start-ups are expanding multi-fold. On the other hand, underlying uncertainties pose several challenges for these health-tech enterprises at macro-meso-micro level, influencing their business circumstances and profitability. The current study aims to comprehend the macro-, meso- and micro-level barriers that make it difficult for enterprises to set up healthcare technology start-ups. The study also observed the perceived effect of these challenges on firms' performance and cost structure over time. Using the theory of behaviour under uncertainty, the study revealed multiple systemic, sector-related, human and implementation barriers that hinder business growth and lead to uncertainties for health-tech start-ups.

Using a grounded theory approach, the study collected the views of 51 health tech start-ups in the UK using an online participants pool. The data was collected using qualitative data techniques in the form of open-ended essays, and a content analysis using thematic coding process was conducted. The questions centered around the different institutional uncertainties or barriers while setting up or running a healthcare start-up.

The study revealed several macro-, meso- and micro-level barriers these technology-based enterprises perceive in the healthcare industry. These are recognised as systemic barriers, such as lack of funding and procedural issues; sector-related barriers, such as market-related impediments; human barriers, including psychological barriers and resistance to new technology; and implementation barriers, such as operational and personnel issues.

The study used qualitative, open-ended essay techniques to collect the data. Future studies may use a mixed-methods approach to provide holistic insights. The study is conducted in a single developed country, the UK. Future work may expand these findings by comparing developed market challenges with those of emerging markets and by assessing the viewpoints of healthcare start-ups.

This research will assist the healthcare sector and government understand health tech start-up hurdles and uncertainty. Policymakers must assist start-ups and encourage entrepreneurial innovation. Regulating and enabling policies will help. The paper examines start-ups' macro, meso and micro uncertainties. Policymakers promoting sector entrepreneurship must consider these barriers while designing policy guidelines.

The study contributes to the existing literature on technology start-ups, particularly in the healthcare industry, and identifies significant barriers these start-ups face. The study synthesizes research on health-tech start-up uncertainty and bridges the gap between theory and practice by applying empirical findings.

This study aims to focus on the supply chain (SC) cost drivers of healthcare industries in the USA, as SC costs have increased 40% over the last decade. The second-most significant expense, the SC, accounts for 38% of total expenses in a typical hospital, while most other industries can operate within 10% of their operating cost. This makes healthcare centers supply-chain-sensitive organizations with limited facilities for high-quality healthcare services. As the cost drivers of healthcare SC are almost unknown to managers, their jobs become more complex.

Guided by pragmatism and positivism paradigms, a cross-sectional study has been designed using quantitative and deductive approaches. Both primary and secondary data were used. Primary data were collected from health centers across the country, and secondary data were from healthcare-related databases. This study examined the attributes that explain the most significant variation in each contributing factor. With multiple regression analysis for predicting cost and Student's t-tests for the significance of contributing factors, the authors of this study examined different theories, including the market-based view and five-forces, network and transaction cost analysis.

This study revealed that supply, materials and services represent the most significant expenses in primary care. Supply-chain cost breakdown results in four critical factors: facility, inventory, information and transportation.

This study examined the data from primary and secondary care institutions. Tertiary and quaternary care systems were not included. Although tertiary and quaternary care systems represent a small portion of the healthcare system, future research should address the supply chain costs of highly specialized organizations.

This study suggests methods that can help to improve supply chain operations in healthcare organizations worldwide.

This study presents an empirically proven methodology for testing the statistical significance of the primary factors contributing to healthcare supply chain costs. The results of this study may lead to positive policy changes to improve healthcare organizations' efficiency and increase access to high-quality healthcare.

The purpose of this study is to capture patients' and employees' perception of quality of care in the Indian private hospitals and to find the possible perceptual gaps between both the groups.

Authors have referred to the Victorian patient satisfaction monitoring (VPSM) scale and studied the responses of 327 patients and 327 employees collected from six private Indian tertiary care hospitals. SPSS v26 software was used to conduct the data reliability test, descriptive analysis and Mann–Whitney U test.

Authors have found significant differences in perceptions of quality of care between the patients and employees in the Indian hospitals. Employees have high positive perceptions towards the provided medical care whereas the patients have less favourable perceptions for many quality indicators.

This study findings help the healthcare managers, practitioners and healthcare workers of the Indian hospitals to understand the perceptions of both the employees and the patients towards healthcare quality elements and help to reduce the existing perceptual gap in the process of providing quality healthcare services.

To the best of authors knowledge, this is one of the pioneering studies conducted in Indian healthcare industry to capture and compare the perceptions of both the employees' and the patients' perceptions of various quality of care elements. This study highlighted the existing perceptual gap between the employees and the patients on various healthcare quality elements and indicated the critical areas for improvement to provide high quality healthcare services.

This research aimed to create inventive principles in managing quality and innovation systems that can be used as a guide for the development of effective innovation projects in hospitals.

Total quality and innovation management in healthcare (TQIM-H) framework and theory of inventive problem-solving (TRIZ) were integrated with results from in-depth interviews with 30 healthcare experts, resulting in TQIM-H inventive principle. The developed inventive principle was validated using 50 effective innovation projects from one of the largest healthcare conglomerates in Southeast Asia.

The TQIM-H inventive principle consisted of 7 dimensions and 72 procedures for creating innovation in hospitals under the medical quality framework. The principle effectively helps innovators develop innovative solutions that still strictly comply with medical guidelines.

Innovation is recognized as a critical factor that helps organizations adapt to global changes and increases the potential for competition, especially in hospitals. However, creating innovation in hospitals has a lower success rate than in other industries because, in general, ineffective innovation development strategies are used and the created innovation is not aligned with regulations and restrictions regarding healthcare quality in the healthcare system.

Recently, blockchain technology (BT) has resolved healthcare data management challenges. It helps healthcare providers automate medical records and mining to aid in data sharing and making more accurate diagnoses. This paper attempts to identify the critical success factors (CSFs) for successfully implementing BT in healthcare.

The paper is methodologically structured in four phases. The first phase leads to identifying success factors by reviewing the extant literature. In the second phase, expert opinions were solicited to authenticate the critical success factors required to implement BT in the healthcare sector. Decision Making Trial and Evaluation Laboratory (DEMATEL) method was employed to find the cause-and-effect relationship among the third phase’s critical success factors. In phase 4, the authors resort to validating the final results and findings.

Based on the analysis, 21 CSFs were identified and grouped under six dimensions. After applying the DEMATEL technique, nine factors belong to the causal group, and the remaining 12 factors fall under the effect group. The top three influencing factors of blockchain technology implementation in the healthcare ecosystem are data transparency, track and traceability and government support, whereas; implementation cost was the least influential.

This study provides a roadmap and may facilitate healthcare professionals to overcome contemporary challenges with the help of BT.

A direct correlation exists between waste disposal, disease spread and public health. This article systematically reviewed healthcare waste and its implication for public health. This review identified and described the associations and impact of waste disposal on public health.

This paper systematically reviewed the literature on waste disposal and its implications for public health by searching Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA), PubMed, Web of Science, Scopus and ScienceDirect databases. Of a total of 1,583 studies, 59 articles were selected and reviewed.

The review revealed the spread of infectious diseases and environmental degradation as the most typical implications of improper waste disposal to public health. The impact of waste includes infectious diseases such as cholera, Hepatitis B, respiratory problems, food and metal poisoning, skin infections, and bacteremia, and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife.

Infectious diseases such as cholera, hepatitis B, respiratory problems, food and metal poisoning, skin infections, bacteremia and environmental degradation such as land, water, and air pollution, flooding, drainage obstruction, climate change, and harm to marine and wildlife are some of the public impacts of improper waste disposal.

Healthcare industry waste is a significant waste that can harm the environment and public health if not properly collected, stored, treated, managed and disposed of. There is a need for knowledge and skills applicable to proper healthcare waste disposal and management. Policies must be developed to implement appropriate waste management to prevent public health threats.