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Further investigation is needed of network effectiveness in healthcare and how it is influenced by unpredictable events like COVID-19. Based on Provan and Milward’s (2001) framework, this study investigates the effectiveness criteria of healthcare networks and their potential contribution to network effectiveness during the pandemic’s challenges.

This research employs an explanatory case study in a local area of Italy’s Lombardy Region and analyzes network effectiveness at the network level based on network member perceptions.

Network effectiveness refers to the network’s ability to address patient needs, guaranteeing services through network members' coordinated efforts and a central coordinator that facilitates their interaction. Members’ capacity to strengthen their roles played a crucial part in sustaining network effectiveness when COVID-19 revised other members’ priorities and threatened achievement of network goals.

This study’s findings equip healthcare managers and policymakers with knowledge about network effectiveness criteria at the network level, offering suggestions for managerial practices and network design to address exogenous shocks.

This study identifies factors that influence network effectiveness criteria and provides insight into how network members can contribute to sustaining effectiveness during crises.

Value-based healthcare suggested using patient-reported information to complement the information available in the medical records and administrative healthcare data to provide insights into patients' perceptions of satisfaction, experience and self-reported outcomes. However, little attention has been devoted to questions about factors fostering the use of patient-reported information to create value at the system level.

Action research design is carried out to elicit possible triggers using the case of patient-reported experience and outcome data for breast cancer women along their clinical pathway in the clinical breast network of Tuscany (Italy).

The case shows that communication and engagement of multi-stakeholder representation are needed for making information actionable in a multi-level, multispecialty care pathway organized in a clinical network; moreover, political and managerial support from higher level governance is a stimulus for legitimizing the use for quality improvement. At the organizational level, an external facilitator disclosing and discussing real-world uses of collected data is a trigger to link measures to action. Also, clinical champion(s) and clear goals are key success factors. Nonetheless, resource munificent and dedicated information support tools together with education and learning routines are enabling factors.

Current literature focuses on key factors that impact performance information use often considering unidimensional performance and internal sources of information. The use of patient/user-reported information is not yet well-studied especially in supporting quality improvement in multi-stakeholder governance. The work appears relevant for the implications it carries, especially for policymakers and public sector managers when confronting the gap in patient-reported measures for quality improvement.

This paper aims to identify the key issues that healthcare knowledge-intensive organizations (KIPOs) should focus on to define themselves as socioenvironmentally and governance responsible for integrating environmental, social, and governance (ESG) logic into their business strategy. At the same time, this provides an understanding of how healthcare KIPOs contribute to achieving the Sustainable Development Goals of the 2030 Agenda.

Taking a cue from the model developed by the World Economic Forum, an “ESG Processing Map” was constructed to identify qualitative disclosures that a healthcare company should consider when implementing sustainability logic. The aspects investigated were processed, considering national and international standards, frameworks and disclosures. The social network analysis technique was used to systemize and combine the outcomes of these processes and analyze their consistency with sustainable development.

Through the “ESG Processing Map,” 13 areas of action and 27 topics specific to the health sector were defined on which to intervene in sustainability in order to concretely help HCOs to place specific corrective and improvement actions over time concerning socioenvironmental and governance aspects.

The paper provides contribute, on the one hand, to enriching and updating the academic literature on ESG logic in a still underexplored field and, on the other hand, to provide these types of organizations with a “compass” to guide and orient their business strategies towards sustainability.

Understanding the outcomes of co-creation (CC) in healthcare is increasingly gaining multidisciplinary scientific interest. Although more and more service management scholars have pointed out the benefits of cross-fertilization between the various research fields, the literature on this topic is still scattered and poorly integrated. This study aims to summarize and integrate multiple strands of extant knowledge CC by identifying the outcomes of health CC and the determinants of these outcomes and their relationships.

A structured literature review was conducted per PRISMA guidelines. A total of 4,189 records were retrieved from the six databases; 1,983 articles were screened, with 161 included in the qualitative thematic analysis.

This study advances a comprehensive framework for healthcare CC based on a thorough analysis of the outcomes and their determinants, that is, antecedents, management activities and institutional context. Extant research rarely evaluates outcomes from a multidimensional and systemic perspective. Less attention has been paid to the relationship among the CC process elements.

This study offers an agenda to guide future studies on healthcare CC. Highlighting some areas of integration among different disciplines further advances service literature.

The framework offers an operational guide to better shape managerial endeavors to facilitate CC, provide direction and assess multiple outcomes.

This is the first extensive attempt to synthesize and integrate multidisciplinary knowledge on CC outcomes in healthcare settings by adopting a systematic perspective on the overall process.

The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.

Potential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.

The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.

Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.

At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

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.

The paper contributes to the discussion on valuation in organization studies and strategic management literature. The nascent literature on valuation practices has examined established markets where producers and consumers are known and rivalry in the market is a given. Furthermore, previous research has operated with a narrow meaning of value as either a financial profit or a subjective consumer preference. Such a narrow view on value is problematic and insufficient for studying the interlacing of innovation and value creation in emerging technoscientific business domains.

The authors present an empirical study about value creation in an emerging technoscience business domain formed around personalized medicine and digital health data.

The results of this analysis show that in a technoscientific domain, valuation of innovations is multiple and malleable, entails pursuing attractiveness in collaboration and partnerships and is performative, and due to emphatic future orientation, values are indefinite and promissory.

As research implications, this study shows that valuation practices in an emerging technoscience business domain focus on defining the potential economic value in the future and attracting partners as probable future beneficiaries. Commercial value upon innovation in an embryonic business milieu is created and situated in valuation practices that constitute the prospective market, the prevalent economic discourse, and rationale. This is in contrast to an established market, where valuation practices are determined at the intersection of customer preferences and competitive arenas where suppliers, producers, service providers and new entrants to the market present value propositions.

The study findings extend discussion on valuation from established business domains to emerging technoscience business domains which are in a “pre-competition” phase where suppliers, customers, producers and their collaborative and competitive relations are not yet established.

As managerial implications, this study provides insights into health innovation stakeholders, including stakeholders in the public, private and academic sectors, about the ecosystem dynamics in a technoscientific innovation. Such insight is useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To business managers, the findings of this study about valuation practices are useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To policy makers, this study provides an in-depth analysis of an overall business ecosystem in an emerging technoscience business that can be propelled to increase the financial investments in the field. As a policy implication, this study provides insights into the various dimensions of valuation in technoscience business to policy makers, who make governance decisions to guide and control the development of medical innovation using digital health data.

This study's results expand previous theorizing on valuation by showing that in technoscientific innovation all types of value created – scientific, clinical, social or economic – are predominantly promissory. This study complements the nascent theorizing on value creation and valuation practices of technoscientific innovation.

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

The outbreak of the COVID-19 pandemic has significantly impacted healthcare systems, presenting unforeseen challenges that necessitated the implementation of change management strategies to adapt to the new contextual conditions. This study aims to analyze organizational changes within the total hip replacement (THR) surgery pathway at multiple levels, including macro, meso and micro. It employs data triangulation from various sources to gauge the complexity of the change process and comprehend how multi-level decision-making influenced an unexpected shift.

A multicentric, single in-depth case study was conducted using a mixed-methods approach. Data sources included patient-reported outcome measures specific to the THR pathway and carefully structured in-depth interviews administered to managers and clinicians in two healthcare organizations serving the same population.

Decisions made at the macro level resulted in an overall reduction in surgical activities. Organizational changes at the meso level led to a complete cessation or partial reorganization of activities. Micro-level actions for change and adaptation revealed diverse and fragmented change management strategies.

Organizations with segmented structures may require a robust and structured department for coordinating change management responses to prevent the entire system from becoming stuck in the absorptive phase of change. However, it is important to recognize that absorptive solutions can serve as a starting point for genuine innovations in change management.

The utilization of data triangulation enables the authors to visualize how specific changes implemented in response to the pandemic have influenced the observed outcomes. From a managerial perspective, it provides insights into how future innovations could be introduced.

The build-up of large-scale COVID-19 testing required an unprecedented effort of coordination within decentralized healthcare systems around the world. The aim of the study was to elucidate the challenges of vertical policy coordination between non-political actors at the national and regional levels regarding this policy issue, using Sweden as our case.

Interviews with key actors at the national and regional levels were analyzed using an adapted version of a conceptualization by Adam et al. (2019), depicting barriers to vertical policy coordination.

Our results show that the main issues in the Swedish context were related to parallel sovereignty and a vagueness regarding responsibilities and mandates as well as complex governmental structures and that this was exacerbated by the unfamiliarity and uncertainty of the policy issue. We conclude that understanding the interaction between the comprehensiveness and complexity of the policy issue and the institutional context is crucial to achieving effective vertical policy coordination.

Many studies have focused on countries’ overall pandemic responses, but in order to improve the outcome of future pandemics, it is also important to learn from more specific response measures.