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This literature review aims to assess the current research on healthcare job availability and skilled professionals. The objective of this research is to identify challenges caused by the imbalance between healthcare service demand and qualified professionals and propose potential solutions and future research directions.

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was employed as the guiding framework for conducting this review. A qualitative research design analyzed 38 peer-reviewed, evidence-based research works from 50 journal publications. Inclusion criteria focused on empirical studies, observational research and comprehensive reviews published within the last ten years. Thematic and discourse analysis categorized themes and factors explored in selected publications.

The findings highlight significant challenges in the healthcare sector regarding job availability and skilled professionals. Developed countries face understaffed healthcare facilities, resulting in increased workloads and compromised care. Developing countries experience high rates of unemployment among healthcare graduates due to limited resources and mentorship.

Improving educational infrastructure, expanding training opportunities and increasing healthcare investments are crucial for nurturing a skilled workforce. Implementing effective retention policies, fostering international collaborations and addressing socioeconomic determinants can create a sustainable job market.

The healthcare sector faces critical challenges in balancing job availability and skilled professionals. Strategic solutions are proposed to create a sustainable and equitable healthcare workforce. By implementing recommendations and conducting further research, access to quality healthcare and global public health outcomes can be improved.

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

Blockchain technology enhances information management in healthcare supply chains by securing healthcare information and providing medical resource traceability. However, there is no decision framework to support blockchain implementation for managing information, especially in emerging economies’ healthcare supply chains. This paper develops a hierarchical decision model for implementing blockchain technology for information management in emerging economies’ healthcare supply chains.

This study uses 20 health supply chain experts in Ghana to rank 17 decision criteria for implementing blockchain for healthcare information management using the best-worst method (BWM) multi-criteria decision technique.

The results show that “security” and “privacy,” “infrastructural facility” and “presence of training facilities” are the top three critical factors impacting blockchain adoption in the health supply chain for healthcare information management. Other sub-factors are prioritized.

To implement blockchain effectively to enhance information management in the healthcare supply chain, health institutions, blockchain technology providers and state authorities should concentrate on the highly critical factors extracted from the study.

This is the first study that develops a hierarchical decision model for implementing blockchain technology in emerging economies' health supply chains.

Coronavirus disease (COVID-19) has challenged leadership in hospitals worldwide. The experiences of leadership during the pandemic changed leadership significantly. This study aims to describe nurse leaders’ perceptions of what future leadership in hospital settings in the post-pandemic era needs to be like.

A qualitative descriptive study was used. A total of 20 nurse leaders from the Finnish central hospital were interviewed from June to October 2021. The data were analysed using inductive content analysis.

The analysis revealed five main categories describing nurse leaders’ perceptions of future leadership in hospital settings in the post-pandemic era: digitalisation and hybrid working culture, development of sustainable working conditions, moving smoothly to the post-pandemic era, dissolution of traditional regimes of organisation and flexibility in leadership.

In the post-pandemic era, the constantly changing demands and challenges currently facing healthcare systems have significantly increased the complexity of hospital organisations. This requires critical evaluation and change to traditional leadership. Enhancing flexibility and authenticity in leadership, strengthening competencies, implementing a wide range of digital resources and increasing the appeal of the nursing profession to build the next generation of nurses – all of these are needed to provide sustainability in future healthcare.

The results identify the critical points of leadership that need to be developed for future challenges and for maintaining a sufficient supply of qualified professionals. Acting on this information will enhance flexibility in organisations and lead to acceleration of changes and the development of new kinds of leadership in the future

The present research paper aims to examine the inter-relationship between organizational justice (Henceforth termed as OJ), psychological well-being at work (henceforth termed as PWBW) and organizational citizenship behavior (henceforth termed as OCB). More specifically, this paper attempts to critically analyze the mediating role of PWBW in the relationship between OJ and OCB. The study solely focuses on nurses working at private hospitals in Kerala, who are the largest group of healthcare personnel.

Data collected from 308 nursing employees were analyzed by using statistical package for the social sciences (SPSS) software.

The outcomes of the analysis demonstrate that significant correlations exist between all the three key variables and their dimensions. Moreover, it has been found that the relationship between OJ and OCB is partially mediated by PWBW.

In the present healthcare scenario, just after the Covid-19 pandemic, there is a paramount need for the well-being of healthcare staff in order to improve the functioning of the healthcare system.

The study enabled us to develop and provide an explanation as to how social exchange relationship works between OJ and OCB.

Healthcare organisations are often described as less innovative than other organisations, since organisational culture works against innovations. In this paper, the authors ask whether it has to be that way or whether is possible to nurture an innovative culture in a healthcare organisation. The aim of this paper is to describe and analyse nurturing an innovative culture within a healthcare organisation and how culture can support innovations in such a healthcare organisation.

Based on a qualitative case study of a healthcare unit that changed, within a few years, from having no innovations to repeatedly generating innovations, the authors describe important aspects of how innovative culture can be nurtured in healthcare. Data were analysed using inductive and deductive analysis steps.

The study shows that it is possible to nurture an innovative culture in a healthcare organisation. Relationships and competences beyond healthcare, empowering structures and signalling the importance of innovation work with resources all proved to be important. All are aspects that a manager can influence. In this case, the manager's role in nurturing innovative culture was very important.

This study highlights that an innovative culture can be nurtured in healthcare organisations and that managers can play a key role in such a process.

The paper describes and analyses an innovative culture in a healthcare unit and identifies important conditions and strategies for nurturing innovative culture in healthcare organisations.

This study explores how Lean was deployed in several hospitals in the Apulia region in Italy over 3.5 years.

An exploratory qualitative design was drawn up based on semi-structured interviews.

The drivers of Lean in hospitals were to increase patient satisfaction and improve workplace well-being by eliminating non-value-add waste. The participants highlighted three key elements of the pivotal implementation stages of Lean: introduction, spontaneous and informal dissemination and strategic level implementation and highlighted critical success and failure factors that emerged for each of these stages. During the introduction, training and coaching from an external consultant were among the most impactful factors in the success of pilot projects, while time constraints and the adoption of process analysis tools were the main barriers to implementation. The experiences of the Lean teams strongly influence the process of spontaneous dissemination aided by the celebration of project results and the commitment of the departmental hospital heads.

Lean culture can spread to allow many projects be conducted spontaneously, but the Lean paradigm can struggle to be adopted strategically. Lean in healthcare can fail because of the lack of alignment of Lean with leadership in healthcare and with their strategic vision, a lack of employees' project management skills and crucially the absence of a Lean steering committee.

The absence of managerial expertise and a will to support Lean implementation do not allow for systemic adoption of Lean. This is one of the first and largest long-term case studies on a Lean cross-regional multi-hospital application in healthcare.

Providing high-quality and cost-efficient care of older people is an important development priority for many health and social care systems in the world. This paper suggests a shift from acute, episodic and reactive hospital-centered care toward longitudinal, person-centered and proactive home-centered care. The purpose of this paper is to contribute to the knowledge of a comprehensive development strategy for designing and providing home-centered care of older people.

The study design is based on qualitative research with an inductive approach. The authors study development initiatives at the national, regional and local levels of the Swedish health and social care system. The data collection methods included interviews (n = 54), meeting observations (n = 25) and document studies (n = 59).

The authors describe findings related to policy actions and system changes, attempts to achieve collaboration, integration and coordination, new forms of care offerings, characteristics of work settings at home and differences in patients' roles and participation at home and in the hospital.

The authors suggest home-centered care as a solution for providing person-centered and integrated care of older people and give examples of how this can be achieved.

The authors outline five propositions for research and development related to national policies, service modularity as a solution for customized and coordinated care, developing human resources and infrastructure for home settings, expanding services that enable older people living at home and patient co-creation.

The COVID-19 pandemic significantly increased demand for medical and protective equipment by frontline health workers, as well as the general community, causing the supply chain to stretch beyond capacity, an issue further heightened by geographical and political lockdowns. Various 3D printing technologies were quickly utilised by businesses, institutions and individuals to manufacture a range of products on-demand, close to where they were needed. This study gathered data about 91 3D printed projects initiated prior to April 1, 2020, as the virus spread globally. It found that 60% of products were for personal protective equipment, of which 62% were 3D printed face shields. Fused filament fabrication was the most common 3D print technology used, and websites were the most popular means of centralising project information. The project data provides objective, quantitative insight balanced with qualitative critical review of the broad trends, opportunities and challenges that could be used by governments, health and medical bodies, manufacturing organisations and the 3D printing community to streamline the current response, as well as plan for future crises using a distributed, flexible manufacturing approach.

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and observe the important gaps in the literature that can inform a research agenda going forward.

A systematic literature strategy was utilized to identify and analyze scientific papers between 2012 and 2022. A total of 28 articles were identified and reviewed.

The outcomes reveal that while advances in machine learning have the potential to improve service access and delivery, there have been sporadic growth of literature in this area which is perhaps surprising given the immense potential of machine learning within the health sector. The findings further reveal that themes such as recordkeeping, drugs development and streamlining of treatment have primarily been focused on by the majority of authors in this area.

The search was limited to journal articles published in English, resulting in the exclusion of studies disseminated through alternative channels, such as conferences, and those published in languages other than English. Considering that scholars in developing nations may encounter less difficulty in disseminating their work through alternative channels and that numerous emerging nations employ languages other than English, it is plausible that certain research has been overlooked in the present investigation.

This review provides insights into future research avenues for theory, content and context on adoption of machine learning within the health sector.