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The mass exodus of the professional healthcare workforce has become a cankerworm for a developing nation like Nigeria, and this worsens the already depleted healthcare systems in underdeveloped nation. This study investigated the rationale behind medical workers' brain-drain syndrome and the quality healthcare delivery in the Nigerian public healthcare sector.

To stimulate an understanding of the effect of the phenomenon called brain drain, the study adopted a diagnostic research design to survey the public healthcare personnel in government hospitals. The study administered a battery of adapted research scales of different measures to confirm the variables of interest of this study on a probability sampling strategy. The study surveyed 450 public healthcare sector employees from four government hospitals to gather pertinent data. The study used a structural equation model (SEM) and artificial neural networks (ANNs) to analyse the collected data from the medical personnel of government hospitals.

The findings of this study are significant as postulated. The study discovered that poor quality worklife experienced by Nigerian medical personnel was attributed to the brain-drain effect and poor healthcare delivery. The study further demonstrated that job dissatisfaction suffered among the public healthcare workforce forced the workforce to migrate to the international labour market, and this same factor is a reason for poor healthcare delivery. Lastly, the study discovered that inadequate remuneration and pay discouraged Nigerian professionals and allied healthcare workers from being productive and ultimately pushed them to the global market.

Practically, this study has shown three major elements that caused the mass movement of Nigerian healthcare personnel to other countries of the world and that seems novel given the peculiarity of the Nigerian labour market. The study is original and novel as much study has not been put forward in the public healthcare sector in Nigeria concerning this phenomenon.

Facilities management (FM) professionals state that adopting FM will positively support core service delivery and ensure customer satisfaction. Evidences of such claim are important as it will enhance the rationale for institutionalising prudent FM service quality in hospitals in Ghana. This paper aims to assess the mediating effect of healthcare FM service quality on patients’ satisfaction and overall healthcare delivery.

This is a cross-sectional study involving adult patients at the Physician outpatient departments and Polyclinics of Komfo Anokye, Tamale and Cape Coast Teaching hospitals in Ghana. A questionnaire survey using a well-structured five-point likert scale based on the SERVQUAL dimensions and Healthcare core service dimensions rooted in the FM framework was used to collect data from 660 patients. Smart PLS was used to analyse the data of 622 valid questionnaires.

The study results revealed that FM service quality mediates the relationship between patients’ satisfaction and three of the constructs under core healthcare delivery. That is, (the quality of healthcare delivery, the quality of healthcare personnel and the adequacy of healthcare resources) – surprisingly, the fourth construct (the quality of administration process) was not supported.

There is no or at best very limited studies on the contribution of healthcare FM on patients satisfaction of core healthcare delivery in Ghana. Therefore, this study will enrich and contribute to knowledge in healthcare FM in general and that of a developing African country in particular.

The purpose of this study is to increase knowledge and understanding of the relationship between full-time-culture and the outcome for quality and safety of care.

The paper is a literature review with a qualitatively oriented thematic analysis concerning quality or safety outcomes for patients, or patients and staff when introducing a full-time culture.

Identified factors that could have a positive or negative impact on quality and patient safety when introducing full-time culture were length of shift, fatigue/burnout, autonomy/empowerment and system/structure. Working shifts over 12 h or more than 40 h a week is associated with increased adverse events and errors, lower quality patient care, less attention to safety concerns and more care left undone. Long shifts give healthcare personnel more flexibility and better quality-time off, but there is also an association between long shifts and fatigue or burnout. Having a choice and flexibility around shift patterns is a predictor of increased wellbeing and health.

A major challenge across healthcare services is having enough qualified personnel to handle the increasing number of patients. One of the measures to get enough qualified personnel for the expected tasks is to increase the number of full-time employees and move towards a full-time culture. It is argued that full-time culture will have a positive effect on work environment, efficiency and quality due to a better allocation of work tasks, predictable work schedule, reduced sick leave, and continuity in treatment and care. There is limited research on how the introduction of full-time culture will affect the quality and safety for patients and staff, and few studies have been focusing on the relationship between longer shift, work schedule, and quality and safety of care.

The purpose of this paper is to develop and test a multi-level healthcare service quality (HSQ) model in Jakarta, Indonesia.

The research used a quantitative research method. Data were collected via a survey with questionnaire. The respondents are 154 patients of a healthcare institution in Jakarta, Indonesia.

The research result shows a multi-level HSQ model. The HSQ model consists of three primary dimensions, namely, healthcare service outcome, healthcare service interaction, and healthcare service environment. Healthcare service outcome has three subdimensions, i.e. waiting time, medicine, and effectiveness. Healthcare service interaction has three dimensions, namely, soft interaction, medical personnel expertise, and hard interaction. Healthcare service environment has two dimensions, which are equipment condition and ambient condition.

This research was only conducted in one healthcare institution in Jakarta, Indonesia. The data collection using convenience sampling method as well as the use of small sample size caused the limitation of the research results in representing across the customer of the healthcare institution. This study can be replicated with larger sample size and involving more healthcare institutions in order to examine the stability of the HSQ model.

Healthcare institution’s managers can use the HSQ model to monitor, measure, and improve their service quality.

There is a lack of research that develops and tests HSQ model based on multi-level approach in the context of developing country. This paper has fulfilled the gap.

Indian healthcare system, especially in rural regions, faces several problems that prevent it from achieving universal and sustainable healthcare coverage. The purpose of this paper is to capture such problems through expert opinions and provide solution concepts that are derived from other similar scenarios.

Delphi study has been conducted with 38 experts from diverse areas related to the Indian healthcare sector. Nineteen theses were formulated based on the discussion with experts and were reconfirmed through intensive desktop research. Finally, theses were subjected to expert panel member’s evaluation.

The pool of arguments provided by the participating experts included 415 written statements explaining the (dis-)agreement with the theses. The experts achieved consensus in six theses with interquartile ranges smaller or equal to 20. The written arguments provided by experts were summarized into five different categories, namely interrelations/dependencies in healthcare, inequalities in healthcare, lack of proactive measures, importance of healthcare personnel and role of government in healthcare. Finally, a framework is proposed mapping the issues identified at different stages of the healthcare value chain. Problem-based cost allocation and hub-and-spoke model are discussed as potential solutions for the issues identified.

Lack of empirical and statistical data on the effective cost arising from the present issues suggests future research to determine these expenses and therefore examine the feasibility of applying the problem-based cost allocation framework discussed in this study.

Results show that merely targeting the supply side of healthcare falls short of the mark, especially in a country, such as India, with large socio-economic differentials. Healthcare system, hence, should be viewed from a market perspective, taking both forces of supply and demand into consideration.

This study intends to allow for a comprehensive approach to identify the issues in Indian healthcare system by reviewing the existing key studies in literature and validating it through empirical inputs from experts in the domain. Based on the validation, a framework is proposed mapping the issues identified at different stages of the healthcare value chain.

In this study, it is aimed to correctly weigh the criteria for the selection of qualified manager in a healthcare facility and to make the right selection among candidates with an objective method. In this study, in which the health manager selection was carried out with fuzzy Analytical Hierarchy Process (AHP) and MULTIMOORA methods, 8 candidates were evaluated according to 12 personnel selection criteria. Comparative matrices of qualified health manager selection criteria were presented to the expert opinion and analyzed with the fuzzy AHP method. According to the analysis result, among the 12 criteria; The “Crisis Management Skill” criterion is in the first place with 12.5% weight; The “Social Responsibility Awareness” criterion was found to be in the last place with 3.2% weight. The MULTIMOORA method was applied by analyzing the interview scores and criterion weightings of the candidates evaluated by the jury. According to the results of MULTIMOORA, Candidate 1 first place and Candidate 6 ranked last.

Healthcare provision is costly, and patient expectations are increasing. Lean implemented within healthcare settings is one possible solution for dealing with this issue, with much of the current research in this respect mostly focused on developed countries. The research examines the applicability of lean in the healthcare sector of a developing country, specifically Oman.

Interviews were conducted with 32 individuals representing four public sector hospitals, along with two major hospital suppliers and the Ministry of Health. The readiness of lean thinking was assessed against seven criteria. Data were then analyzed thematically.

The authors found that Oman's healthcare sector is strong on leadership support, understanding value and customer groups, ability to undertake an end-to-end process view and engaging in the required training for lean. Interviewees showed awareness of the challenges, including aligning lean with the strategic agenda of healthcare settings, aligning measurement and reward systems to lean thinking and matching demand and capacity levels. The authors conclude that Oman's healthcare sector is ready for widespread application of lean, and if executed successfully, will generate strong strategic and operational outcomes.

This paper provides evidence of the applicability of lean in a very different context to the one that has been generally reported in the literature. The authors propose that lean thinking can be applied in countries and regions with similar cultural contexts such as the Middle East.

The purpose of this study is to summarize the available pool of literature on service quality to identify different dimensions of service quality in the healthcare industry and understand how it is measured. The study attempts to explore the research gaps in the literature about different service quality dimensions and patient satisfaction.

A systematic literature review process was followed to achieve the objectives of the study. Various inclusion and exclusion criteria were used to select relevant research articles from 2000–2020 for the study, and a total of 100 research articles were selected.

The study identified 41 different dimensions of healthcare service quality measurement and classified these dimensions into four categories, namely servicescape, personnel, hospital administration and patients. It can be concluded that SERVQUAL is the most widely used service quality measurement tool.

The study identified that a majority of the researchers deduced a positive relationship between SERVQUAL dimensions and the quality of healthcare services. The findings of study will assist hospital executives in formulating effective strategies to ensure that patients receive superior quality healthcare services.

This paper seeks to argue that processes for selecting and appointing medically qualified personnel in some healthcare organizations may be limited, especially those that emphasize qualifications rather than expanding the criteria to include practice scope, person‐organization fit and capability to function within a healthcare team.

The paper is based on the authors' experiences and a literature review.

Selection based purely on academic merit, advanced clinical training, skills and professional achievements may not address other essential selection criteria. Medical personnel need to possess competencies such as ability to give high quality care and work constructively in a clinical team; communication skills; willingness to actively participate in quality and safety programs; teaching ability; management and leadership skills; and support institutional values and corporate aims. These attributes are often over‐looked and cannot be assumed from academic merit and achievements.

The study's conclusions are based on the authors' experiences and literature review. Future studies may wish to examine selection technique efficacy and outcomes empirically.

Better medical personnel selection and appointment processes are likely to reduce unnecessary costs associated with poorly‐made appointments, improve patient outcomes and may have a formative role encouraging medical personnel to take a broader view of their healthcare organization roles.

The authors challenge selection panel members to consider non‐traditional with normal selection criteria for medical appointments. Nine recommendations for enhancing selection processes are provided.

This study aims to evaluate the dynamics between healthcare resource capacity expansion and disease spread. Further, the study estimates the resources required to respond to a pandemic appropriately.

This study adopts a system dynamics simulation and scenario analysis to experiment with the modification of the susceptible exposed infected and recovered (SEIR) model. The experiments evaluate diagnostic capacity expansion to identify suitable expansion plans and timelines. Afterwards, two popularly used forecasting tools, artificial neural network (ANN) and auto-regressive integrated moving average (ARIMA), are used to estimate the requirement of beds for a period when infection data became available.

The results from the study reflect that aggressive testing with isolation and integration of quarantine can be effective strategies to prevent disease outbreaks. The findings demonstrate that decision-makers must rapidly expand the diagnostic capacity during the first two weeks of the outbreak to support aggressive testing and isolation. Further, results confirm a healthcare resource deficit of at least two months for Delhi in the absence of these strategies. Also, the study findings highlight the importance of capacity expansion timelines by simulating a range of contact rates and disease infectivity in the early phase of the outbreak when various parameters are unknown. Further, it has been reflected that forecasting tools can effectively estimate healthcare resource requirements when pandemic data is available.

The models developed in the present study can be utilised by policymakers to suitably design the response plan. The decisions regarding how much diagnostics capacity is needed and when to expand capacity to minimise infection spread have been demonstrated for Delhi city. Also, the study proposed a decision support system (DSS) to assist the decision-maker in short- and long-term planning during the disease outbreak.

The study estimated the resources required for adopting an aggressive testing strategy. Several experiments were performed to successfully validate the robustness of the simulation model. The modification of SEIR model with diagnostic capacity increment, quarantine and testing block has been attempted to provide a distinct perspective on the testing strategy. The prevention of outbreaks has been addressed systematically.