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The purpose of this paper is to introduce translational mobilization theory (TMT) and explore its application for healthcare quality improvement purposes.

TMT is a generic sociological theory that explains how projects of collective action are progressed in complex organizational contexts. This paper introduces TMT, outlines its ontological assumptions and core components, and explores its potential value for quality improvement using rescue trajectories as an illustrative case.

TMT has value for understanding coordination and collaboration in healthcare. Inviting a radical reconceptualization of healthcare organization, its potential applications include: mapping healthcare processes, understanding the role of artifacts in healthcare work, analyzing the relationship between content, context and implementation, program theory development and providing a comparative framework for supporting cross-sector learning.

Poor coordination and collaboration are well-recognized weaknesses in modern healthcare systems and represent important risks to quality and safety. While the organization and delivery of healthcare has been widely studied, and there is an extensive literature on team and inter-professional working, we lack readily accessible theoretical frameworks for analyzing collaborative work practices. TMT addresses this gap in understanding.

This study investigates the relationships between team dynamics and performance in healthcare operations. Specifically, it explores, through wearable sensors, how team coordination mechanisms can influence the likelihood of surgical glitches during routine surgery.

Breast surgeries of a large Italian university hospital were monitored using Sociometric Badges – wearable sensors developed at MIT Media Lab – for collecting objective and systematic measures of individual and group behaviors in real time. Data retrieved were used to analyze team coordination mechanisms, as it evolved in the real settings, and finally to test the research hypotheses.

Findings highlight that a relevant portion of glitches in routine surgery is caused by improper team coordination practices. In particular, results show that the likelihood of glitches decreases when practitioners adopt implicit coordination mechanisms rather than explicit ones. In addition, team cohesion appears to be positively related with the surgical performance.

For the first time, direct, objective and real time measurements of team behaviors have enabled an in-depth evaluation of the team coordination mechanisms in surgery and the impact on surgical glitches. From a methodological perspective, this research also represents an early attempt to investigate coordination behaviors in dynamic and complex operating environments using wearable sensor tools.

The purpose of this paper is to investigate the impact of three different dimensions of customer‐induced uncertainty and task uncertainty on the mix of physicians' coordination practices.

An improvement and research project are combined resulting in 16 case studies in different departments from one university hospital. The paper relies mainly on patient data from hospitals' registration systems and on 140 dialogues between two physicians reflecting on their coordination practices.

Hospital units rely on time‐structured oral communication supplemented with feedback in cases of high levels of input variety, whereas severity of illness and service intensity increase the use of unstructured oral coordination practices. High levels of customer‐induced uncertainty reduce coordination by standardization of work processes. Supplementing verbal communication with written medical records has become an inherent part of coordination practices. Non‐surgical units rely mostly on time‐structured meetings, whereas surgical units use both time‐structured and unstructured meetings to deal with customer‐induced uncertainty.

The empirical part of this paper is limited to hospital units that are functionally organized. A further refinement and extension of measures for the contingency factors could help to better understand coordination practices.

The paper offers hospitals in‐depth understanding of how customer‐induced uncertainty and task uncertainty affect physicians' coordination practices.

The paper contributes to the knowledge on medical coordination from a contingency perspective. Further, the paper contributes to alternative methodologies in terms of data gathering as dialogues between organizational members are the main data source.

The purpose of this chapter is to highlight some of the critical multiteam system (MTS) issues that are faced in healthcare by utilizing case studies that illustrate the transition of a patient through the healthcare system and suggest a possible approach to studying these issues.

The approach taken by the authors is a case study approach, which is used to illustrate the transition of a patient through several venues in a healthcare system. This approach elucidates the MTS nature of healthcare. Moreover, a methodological explanation, social network analysis (SNA), for exploring the description and analysis of MTSs in healthcare is provided.

The case study approach provides concrete examples of the complex relationship between providers caring for a single patient. The case study describes the range of shared practice in healthcare, from collaborative care within each setting to the less obvious interdependence between teams across settings. This interdependence is necessary to deliver complex care but is also a source of potential errors during care. SNA is one tool to quantify these relationships, link them to outcomes, and establish areas for future research and quality improvement efforts.

This chapter offers a unique holistic view of the transition of a patient through a healthcare system and the interdependency of care necessary to deliver care. The authors show a methodology for assessing MTSs with a discussion of utilizing SNA. This foundation may offer promise to better understand care delivery and shape programs that can lead to improvement in care.

Using a complexity-informed approach, we aim to understand why introduction of a mobile service delivery model for osteoporosis across diverse organisational and country contexts in the UK National Health Service (NHS) met with variable success.

Six comparative case studies; three prospectively in Scotland using an action research-informed approach; and three retrospectively in England with variable degrees of success. The Non-adoption, Abandonment, Scale-up, Spread and Sustainability framework explored interactions between multi-level contextual factors and their influence on efforts to introduce and sustain services.

Cross-boundary service development was a continuous process of adaptation and evolution in rapidly shifting healthcare context. Whilst the outer healthcare policy context differed significantly across cases, inner contextual features predominated in shaping the success or otherwise of service innovations. Technical and logistical issues, organisational resources, patient and staff actions combined in unpredictable ways to shape the lifecycle of service change. Patient and staff thoughts about place and access to services actively shaped service development. The use of tacit “soft intelligence” and a sense of “chronic unease” emerged as important in successfully navigating around awkward people and places.

“Chronic unease” and “soft intelligence” can be used to help individuals and organisations “tame” complexity, identify hidden threats and opportunities to achieving change in a particular context, and anticipate how these may change over time. Understanding how patients think and feel about where, when and how care is delivered provides unique insights into previously unseen aspects of context, and can usefully inform development and sustainability of patient-centred healthcare services.

This study has uniquely traced the fortunes of a single service innovation across diverse organisational and country contexts. Novel application of the NASSS framework enabled comparative analysis across real-time service change and historical failures. This study also adds to theories of context and complexity by surfacing the neglected role of patients in shaping healthcare context.

Transitional care (TC) models emerged to ensure healthcare coordination and continuity, as at-risk patients transfer between different settings or different levels of care within the same setting. TC models have been developed in many countries as well as within different healthcare service delivery models and organizations. This paper aims to focus on a TC model developed in Italy called Operating Centre for Transition (OCT), in order to (1) explore its distinctive features by establishing a framework of analysis, (2) apply the framework to study two OCTs and (3) provide recommendations on how to use the framework to evaluate and develop new OCTs in the future.

The authors adopted a grounded theory method to develop and validate the framework of analysis. The authors employed several qualitative methods following four iterative and recursive steps: (1) desk analysis of relevant documents, (2) in-depth interviews to key informants, (3) three meetings of an expert working group and (4) application of the framework to two case studies.

The framework of analysis identifies three core dimensions that are always present in any OCT: the service model, the functions and the organizational features. Moreover, for every dimension several variables that capture and understand OCTs’ nature, role and development level are identified.

The results of the study highlight the key elements of the OCT model in Italy and show that the proposed framework can be useful both to analyse existing OCTs and to support health managers and policy makers to create new OCTs or develop those already active.

Ineffective management inventory of medical products such as blood and vaccines can create severe repercussions for hospitals, clinics or medical enterprises, such as surgery delays and postponements. Inventory sharing is a form of horizontal collaboration that can provide solutions to key actors of the healthcare supply chain (HSC), yet no prior study reviewed this topic.

This study conducts a systematic literature review of thirty-nine inventory-sharing studies in the context of HSCs published from 2012 until early 2022. The descriptive and thematic analyses include chronological distribution, geographical location, comparison between developed/developing regions, stakeholder and incident analysis.

Thematic analysis classified inventory sharing among five product supply chains (blood, medical supplies, medicines, vaccines and generic medical products). Benefits include shortage reduction, cost minimisation, and wastage mitigation. Barriers include (1) IT infrastructure, (2) social systems, (3) cost and (4) supply chain operations. Perishable inventory policies include Fresher-First (FF), Last-Expire-First-Out (LEFO), First-In-First-Out (FIFO) and First-Expire-First-Out (FEFO). The analysis also showed differences between developed and developing countries. The study identifies several future research opportunities that include (1) product utilisation rate, (2) cost reductions, (3) shortage mitigation and (4) waste reduction.

No prior study has systematically reviewed inventory sharing in HSCs to reveal benefits, barriers, patterns and gaps in the current literature. It makes five propositions and develops a research model to guide future research. The study concludes with theoretical and managerial implications.

Advanced Electronic Medical Records (EMR) provide many potential benefits to hospitals. However, because of their broad scope, many stakeholders deal with the EMR and a continuous effort has to be made to keep up with internal and external change. Therefore, hospitals need to deliberately shape their organizational competencies considering the pursuit of alignment, i.e. making sure that the EMR remains optimally aligned with strategies, goals and needs of the hospital and its stakeholders. This paper aims to investigate the evolutionary paths of these alignment competencies and their drivers, from a theoretical perspective of co-evolutionary information systems alignment (COISA).

This paper reports on a longitudinal multiple case study of three Dutch hospitals which each recently implemented an advanced EMR system. The authors conducted 35 in-depth interviews in 2 phases (before and after go-live of the EMR), and studied documentation related to the EMR implementations.

The findings show that each hospital's COISA capability shows a different evolutionary path. However, two of the three case hospitals ended up coordinating part of their COISA capability to an ecosystem level, i.e. they incorporated other hospitals using the same EMR system to coordinate their alignment efforts, either from an operational perspective, or in terms of orchestration and strategy. The found evolutionary paths' key drivers include “stakeholder initiative”, “accumulating experience”, “driving events” and “emerging issues”.

The findings help healthcare practitioners to deliberately shape their organization's COISA capability in pursuit of EMR alignment. Furthermore, the authors add to the knowledge base on co-evolutionary approaches to alignment through the longitudinal approach.

The purpose of this paper is to investigate the effect of trust with suppliers on hospital-supplier integration (SI) and hospital supply chain (SC) performance. Additionally, the mediating effect of SI on trust-hospital SC performance is investigated.

A research model and hypotheses were developed based on literature review. The study is based on survey data collected from 152 respondents in 55 private hospitals in Jordan. The proposed hypotheses were tested using structural equation modeling.

The paper finds that trust with suppliers has a positive impact on hospital-SI and hospital SC performance. Hospital-SI partially mediates the relationship between trust and hospital SC performance.

The findings of this research provide useful insights into the role of trust in boosting SC performance in the healthcare sector. High levels of SI not only improve hospital SC performance but also enhance the transformation of trust benefits into SC performance.

This research is one of the limited studies that investigated the effect of trust on hospital-SI and hospital SC performance in the healthcare sector. To the best of the authors’ knowledge, this is the first study to investigate those relationships in the Middle East in general and in Jordan in particular.

Diabetes is a chronic disease and the major types of diabetes are type 1 and type 2. On aging, people with diabetes tend to have long-term problems in hypertension, coronary artery disease, obesity, and nerves. Given the increasing number of complications in recent years, by 2040, 624 million people will have diabetes worldwide and l in 8 adults will have diabetes in the future. Machine learning (ML) is evolving rapidly, many aspects of medical learning use ML. In this study, tension-type headaches (TTH) were associated with diabetes using SPSS, Pearson correlation, and ANOVA tests. Data were collected from Delhi NCR Hospital. It contains 30 diabetic subjects. The purpose of this study was to correlate diabetes analysis from TTH and other diseases using the latest technologies to analyze the Internet of Things and Big Data and Stress Correlation (TTH) on human health. The authors used Pearson correlation to correlate study variables and see if there was any effect between them. There was an important relationship between the percent variable, the total number of individuals, the number of individuals, and the minimum variable. The age (field) of the number of individuals to one of the total number of individuals showed a strong correlation (1.000) with a significant value of p (1.000). Overall, cases of TTH increased with age in men and do not follow the pattern of change in diabetes with age, but in cases of TTH, patterns of headaches such as diabetes increase to age 60 and then tend to decrease.