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Worldwide, healthcare systems struggle to sustain the delivery of services at a time of increasing demand, limited resources and growing expectations from users, coupled with dealing with the aftermath of the Covid-19 pandemic and the threat of other outbreaks. There has never been a more important time to sustain innovation and improvements. Using an illustrative case, the authors assess the application of two existing frameworks to identify the key propositions and dimensions required to deliver sustainable services.

This illustrative case study focuses on a service provided by a chronic disease, multidisciplinary community healthcare team in the UK. Experienced-based interviews were conducted with health professionals, patients and relatives to provide a rich account of a care pathway design. A high-level process map is used to visualise the key touch points.

The authors identify all seven propositions of the SERVICE framework being present along with additional dimensions relating to sustaining innovation and improvement.

This research is limited to a chronic disease care pathway. However, the authors believe the results could be applicable to other medical conditions, which are supported by a similar multi-disciplinary service delivery model.

The authors provide a sustainable public service operations SERVICES framework for health professionals and managers to consider when (re)designing care pathways.

This research contributes to the emerging discipline of public service operations research by empirically testing for the first time the SERVICE framework within healthcare. The authors have included additional factors associated with innovation and improvement and recommended further development of the framework to include factors, such as economic sustainability, highly relevant to the context of universal healthcare systems.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

Highlights that one service industry in the USA ‐ health care ‐ has accepted high inherent rates of variation into its process designs. Notes that, increasingly, health care industry leaders recognize that elimination of unnecessary variation is a necessary, but not a sufficient, condition for producing quality professional services at reasonable costs. Using the innovation model of Boynton et al. (1993), identifies continuous improvement, rather than mass production, as the key step in the rationalization of what has been a craft industry and the ultimate objective of delivering health care in a mass customization mode. Claims, however, that it is not sufficient, because high levels of inherent variation will continue to exist and must be managed, even in the best of all possible worlds. Reviews the health care experience (in the context of that model) to suggest how service operations managers and researchers should conceptualize variation, and then discusses what that conceptualization of variation implies about how operations management should treat variation in its modelling and decision making.

Configuring strategies to ensure a health service provider’s resilience when extreme disruptions occur is not simple. Optimal configuration in such circumstances is rare. Therefore, this research has relied on the dynamic capability view (DCV) to develop a decision-support framework for configuring resilience strategies that will mitigate the worst challenges and improve the performance of health service providers during “extreme” disruptive events.

The research adopted a multi-study, multi-method approach comprising interviews, quality function deployment (QFD), and fuzzy set qualitative comparative analysis (fsQCA).

The findings reveal that, during a crisis, standalone resilience strategies are not enough. To guarantee performance, healthcare services require a combination of resilience strategies and a negation of challenges.

This research extends our current knowledge of healthcare operational management by offering optimal configurations of resilience strategies to manage performance during extreme disruptions. Thus, it offers strategic insights into how health-service managers can be more resilient during a crisis.

As social media platforms become increasingly popular among service firms, many US hospitals have been using social media as a means to improve their patients’ experiences. However, little research has explored the implications of social media use within a hospital context. The purpose of this paper is to investigate a hospital’s customer engagement through social media and its association with customers’ experiential quality. Also, this study examines the role of a hospital’s service characteristics, which could shape the nature of the interactions between patients and the hospital.

Data from 669 hospitals with complete experiential quality and demographic data were collected from multiple sources of secondary data, including the rankings of social media friendly hospitals, the Hospital Compare database, the Center for Medicare and Medicaid (CMS) cost report, the CMS impact file, the Healthcare Information and Management Systems Society Analytics database and the Dartmouth Atlas of Health Care. Specifically, the authors designed the instrumental variable estimate to address the endogeneity issue.

The empirical results suggest a positive association between a hospital’s social media engagement and experiential quality. For hospitals with a high level of service sophistication, the association between online engagement and experiential quality becomes more salient. For hospitals offering various services, offline engagement is a critical predictor of experiential quality.

A hospital with more complex services should make efforts to engage customers through social media for better patient experiences. The sample is selected from databases in the US, and the databases are cross-sectional in nature.

Not all hospitals may be better off improving the patient experience by engaging customers through social media. Therefore, practitioners should exercise caution in applying the study’s results to other contexts and in making causal inferences.

The current study delineates customer engagement through social media into online and offline customer engagement. This study is based on the theory of customer engagement and reflects the development of mobile technology. Moreover, this research may be considered as pioneering in that it considers the key characteristics of a hospital’s service operations (i.e., service complexity) when discovering the link between customers’ engagement through a hospital’s social media and experiential quality.

This paper seeks to concentrate on the question whether any parallels can be found between the industrial sector and health care services with respect to the developments that have taken place in the area of Supply Chain Management. Starting from an analysis of existing literature, it is intended that different modes of Supply Chain integration will be discussed. Also, in doing so, it is intended that the lessons learned from the studies presented in this special issue will be summarized and placed into the perspective of future research that can be considered as necessary.

This paper adopted an exploratory, qualitative approach based on an analysis of existing literature in the area of Supply Chain Management in Health Services. Additionally, material from the case studies presented in this special issue is used to assess the current body of knowledge regarding Supply Chain Management in Health Services.

Starting from a classification of existing research, five main research areas with respect to Supply Chain Management in a health care setting are defined. Additionally, it is concluded that next to studies with a mono‐disciplinary focus, an interdisciplinary focus on Supply Chain Management issues in health services seems to be necessary.

This paper contributes to both the supply chain management literature and literature in the area of healthcare management by identifying some important research areas which are linked to both fields. This paper helps both academics and managers to gain a better understanding of the complexity of supply chain management in health services.

The purpose of this paper is to present a business process reengineering (BPR) framework of process and data integration with patient journey as the basis for process evaluation and the improvement of patient-flow.

A BPR framework is developed using a mixed-method research design, which incorporated a case study to demonstrate a healthcare scenario with associated processes and data elements, using process models based on event-driven process chain methodology as well as patient and data models, based on unitary structuring technique. The framework includes key processes including patient booking and rebooking, and associated inputs, outputs, and control parameters. In this case, the framework is demonstrated through application to computed tomography (CT) services in a hospital to improve patient-flow, with numerical simulation of CT data collected over time.

The framework supports flexible patient scheduling and the associated planning of healthcare operations and logistics – this in turn helps to improve patient-flow. Furthermore, mathematical modelling and simulation precisely reveal the impact of booking and rebooking on the performance of the CT department.

This innovative framework has potential value for other services, within and beyond the hospital setting.

The proposed framework of process modelling, data, and patient journey addresses the lack of a holistic approach to monitoring and evaluating service performance in hospital settings. Patient journey modelling is an integral part of process and data models that can be implemented in an integrated system environment such as an enterprise resource planning system for real-time monitoring of patient-flow under dynamic conditions.

Researchers recommend a reorganization of the medical profession into larger groups with a multispecialty mix. We analyze whether there is evidence for the superiority of these models and if this organizational transformation is underway.

We summarize the evidence on scale and scope economies in physician group practice, and then review the trends in physician group size and specialty mix to conduct survivorship tests of the most efficient models.

The distribution of physician groups exhibits two interesting tails. In the lower tail, a large percentage of physicians continue to practice in small, physician-owned practices. In the upper tail, there is a small but rapidly growing percentage of large groups that have been organized primarily by non-physician owners.

While our analysis includes no original data, it does collate all known surveys of physician practice characteristics and group practice formation to provide a consistent picture of physician organization.

Our review suggests that scale and scope economies in physician practice are limited. This may explain why most physicians have retained their small practices.

Larger, multispecialty groups have been primarily organized by non-physician owners in vertically integrated arrangements. There is little evidence supporting the efficiencies of such models and some concern they may pose anticompetitive threats.

This is the first comprehensive review of the scale and scope economies of physician practice in nearly two decades. The research results do not appear to have changed much; nor has much changed in physician practice organization.

This paper introduces a systems‐based methodology for conducting analysis of organizational structure for health care operations. Increasingly, health care organizations must operate in turbulent environments characterized by rapid change, high levels of uncertainty, and increasing levels of complexity. A fundamental issue for effective performance in these environments is the development and maintenance of organizational structures that simultaneously provide both operational stability and agile response to environmental turbulence. Drawing from systems science, a systems‐based methodology for structural analysis of healthcare operations is developed. This methodology identifies operational deficiencies stemming from inadequate organizational structure and suggests focal areas for structural modification. The results from an application of the methodology in a health care organization are examined. Implications and limitations for use of the methodology by health care professionals are provided.

This paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.

An adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.

The results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.

The findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.

This study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.