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The study aims to summarise the literature on cancer care pathways at the diagnostic and treatment phases. The objectives are to find factors influencing the delivery of cancer care pathways; to highlight any interrelating factors; to find gaps in the literature concerning areas of research; to summarise the strategies and recommendations implemented in the studies.

The study used a qualitative approach and developed a causal loop diagram to summarise the current literature on cancer care pathways, from screening and diagnosis to treatment. A total of 46 papers was finally included in the analysis, which highlights the recurring themes in the literature.

The study highlights the myriad areas of research applied to cancer care pathways. Factors influencing the delivery of cancer care pathways were classified into different albeit interrelated themes. These include access barriers to care, hospital emergency admissions, fast track diagnostics, delay in diagnosis, waiting time to treatment and strategies to increase system efficiency.

As far as the authors know, this is the first study to present a visual representation of the complex relationship between factors influencing the delivery of cancer care pathways.

The goal was to improve the quality of the hospitalization process and the management of patients, allowing the reduction of costs and the minimization of the preoperative Length of Hospital Stay (LOS).

The methodology used to improve the quality of the hospitalization process and patient management was Lean Thinking. Therefore, the Lean tools (Value stream map and Ishikawa diagram) were used to identify waste and inefficiencies, improving the process with the implementation of corrective actions. The data was collected through personal observations, patient interviews, brainstorming and from printed medical records of 151 patients undergoing oral cancer surgery in the period from 2006 to 2018.

The authors identified, through Value Stream Map, waste and inefficiencies during preoperative activities, consequently influencing preoperative LOS, considered the best performance indicator. The main causes were identified through the Ishikawa diagram, allowing reflection on possible solutions. The main corrective action was the introduction of the pre-hospitalization service. A comparative statistical analysis showed the significance of the solutions implemented. The average preoperative LOS decreased from 4.90 to 3.80 days (−22.40%) with a p-value of 0.001.

The methodology allowed to highlight the improvement of the patient hospitalization process with the introduction of the pre-hospitalization service. Therefore, by adopting the culture of continuous improvement, the flow of hospitalization was redrawn. The benefits of the solutions implemented are addressed to the patient in terms of lower LOS and greater service satisfaction and to the hospital for lower patient management costs and improved process quality. This article will be useful for those who need examples on how to apply Lean tools in healthcare.

Audit and feedback (A&F) often underlie implementation projects, described as a circular process; i.e. an A&F cycle. They are widely used, but effect varies with no apparent explanation. We need to understand how A&F work in real-life situations. The purpose of this paper, therefore, is to describe and explore mental healthcare full A&F cycle experiences.

This is a naturalistic qualitative study that uses four focus groups and qualitative content analysis.

Staff accepted the initial A&F stages, perceiving it to enhance awareness and reassure them about good practice. They were willing to participate in the full cycle and implement changes, but experienced poor follow-up and prioritization, not giving them a chance to own to the process. An important finding is the need for an A&F cycle facilitator.

Research teams cannot be expected to be involved in implementing clinical care. Guidelines will keep being produced to improve service quality and will be expected to be practiced. This study gives insights into planning and tailoring A&F cycles.

Tools to ease implementation are not enough, and the key seems to lie with facilitating a process using A&F. This study underscores leadership, designated responsibility and facilitation throughout a full audit cycle.

Open source software (OSS) communities devoted to the development of electronic medical records (EMRs) have grown in recent years. The purpose of this paper is to focus on the challenge the leaders of these communities face in terms of building perceptions of psychological ownership among community members.

Surveys (n = 50) and brief interviews (n = 56) with individual members of an open source EMR community (most of whom are based in African nations) were used.

Among community members, normative commitment (in comparison to extrinsic motivation and affective commitment) was the strongest predictor of psychological ownership. Interviews revealed that community members tended to feel a greater sense of ownership toward the end user (i.e. hospitals and clinics) than toward the community itself.

To foster engagement and retention – and enhance the worldwide impact of their community on healthcare practices – leaders of open source EMR communities can offer incentives related to certifications and status-based rewards, hold annual meetings to allow members to develop a better understanding of the community and encourage members to “pay it forward” by involving end users (i.e. hospital and clinic employees) within the community, thus furthering public health initiatives.

OSS communities experience unique challenges compared to traditional organizations. This necessitates a reconsideration of the applicability of commonly accepted principles, tenets and recommendations from the management literature.

The cardiomegaly can be determined by the cardiothoracic ratio (CTR) which can be measured in a chest x-ray image. It is calculated based on a relationship between a size of heart and a transverse dimension of chest. The cardiomegaly is identified when the ratio is larger than a cut-off threshold. This paper aims to propose a solution to calculate the ratio for classifying the cardiomegaly in chest x-ray images.

The proposed method begins with constructing lung and heart segmentation models based on U-Net architecture using the publicly available datasets with the groundtruth of heart and lung masks. The ratio is then calculated using the sizes of segmented lung and heart areas. In addition, Progressive Growing of GANs (PGAN) is adopted here for constructing the new dataset containing chest x-ray images of three classes including male normal, female normal and cardiomegaly classes. This dataset is then used for evaluating the proposed solution. Also, the proposed solution is used to evaluate the quality of chest x-ray images generated from PGAN.

In the experiments, the trained models are applied to segment regions of heart and lung in chest x-ray images on the self-collected dataset. The calculated CTR values are compared with the values that are manually measured by human experts. The average error is 3.08%. Then, the models are also applied to segment regions of heart and lung for the CTR calculation, on the dataset computed by PGAN. Then, the cardiomegaly is determined using various attempts of different cut-off threshold values. With the standard cut-off at 0.50, the proposed method achieves 94.61% accuracy, 88.31% sensitivity and 94.20% specificity.

The proposed solution is demonstrated to be robust across unseen datasets for the segmentation, CTR calculation and cardiomegaly classification, including the dataset generated from PGAN. The cut-off value can be adjusted to be lower than 0.50 for increasing the sensitivity. For example, the sensitivity of 97.04% can be achieved at the cut-off of 0.45. However, the specificity is decreased from 94.20% to 79.78%.

This study aims to investigate how dynamic tensions between performance measurement system (PMS) uses enable organizations to achieve both exploitation and exploration and enhance firm performance.

The authors collected survey data on 153 Italian companies. Scales for each construct were validated through an exploratory factor analysis. Data on firm performance were cross-validated by using lagged accounting data. The authors tested our hypotheses using hierarchical ordinary least squares regressions, together with bootstrapping procedures for the test on mediation.

A diagnostic use of PMS has a positive association with both exploitation – e.g. reductions in total costs and lead times – and exploration, e.g. introduction of new products and extension of product ranges. The dynamic tension created by a joint diagnostic and interactive use has the strongest association with organizational ambidexterity, measured as the multiplicative interaction between exploration and exploitation.

If an organization or business unit is mainly pursuing exploitative goals, a mainly diagnostic use of PMS would be most suitable. If goals are both exploitative and explorative, a mix of diagnostic and interactive uses would be most effective.

This research helps reconcile conflicting views in the literature. The diagnostic use of PMS, far from acting as a “negative force,” appears to be necessary to guide opportunity search and to establish an appropriate scope for exploration-related activities. The authors’ focus on the uses of PMSs shows that ambidexterity is achieved through managerial capability, rather than just through the introduction of systems and structures.

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.

Routine general practice (GP) care is rarely comprehensively described in clinical trials. This paper examines routine GP care within the lifestyle approach to managing panic (LAMP) study. The aim of this paper is to describe/discuss routine GP care for panic disorder (PD) patients within both study arms in the LAMP study. An unblinded pragmatic randomised controlled trial in 15 East of England GP practices (2 primary care trusts). Participants met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for PD with/without agoraphobia. Follow-up measures recorded at 20 weeks/10 months following randomisation. Control arm, unrestricted routine GP care (practice appointments, referrals and prescriptions). Trial arm, occupational therapy-led lifestyle treatment comprising lifestyle review of fluid intake, diet pattern, exercise, caffeine, alcohol and nicotine. Primary outcome measure: beck anxiety inventory. At baseline, participants attended 2-3 times more GP appointments than population average, reducing at 10 months to 1.6 times population average for routine GP care and 0.97 population average for lifestyle arm. At 10 months, 33% fewer referrals (6 referrals; 0 mental health) than at baseline (9 referrals; 2 mental health) were made for lifestyle arm patients compared with 42% increase (from 12 referrals; 8 mental health at baseline to 17 referrals; 7 mental health) in GP care arm. Selective serotonin reuptake inhibitors were prescribed most often. Benzodiazepines and beta-blockers were prescribed more often than tricyclic against current clinical guidelines. In conclusion, we found that PD patients at baseline were high healthcare resource users. Treatment in both study arms reduced resource use. Routine GP care requires further review for this patient group.

Considering the significant increase in researchers’ interest in human resource management (HRM) in the public sector domain, this study aims to focus on producing a scale of HRM practices customized for the context of public organizations.

Experts and semantic analysis were performed for the scale development (qualitative stage), and exploratory and confirmatory factor analysis through structural equation modeling was conducted for the scale validation (quantitative stage).

The public HRM practices scale (public HRMPS) is composed of 19 items, distributed along four factors/dimensions, named training, development and education; relationship; work conditions; and competency and performance appraisal. The scale showed evidence of internal and construct validity (convergent, divergent, criterion-related and discriminant), as well as reliability and content validity.

The public HRMPS can be applied in relational studies to test structural models of prediction, mediation and moderation to evaluate relationships with organizational behavior variables, such as leader-members exchange, engagement at work, life quality at work and well-being at work, among others.

The public HRMPS may also serve as a useful diagnostic tool for the decision-making process made by public managers so they can promote a strategic, evidence-based HRM. Furthermore, the transforming role of strategic HRM can be operationalized by adopting practices gathered in the public HRMPS, advancing toward new HRM strategies to promote healthier and more productive work environments.

Healthier and more productive environments translate into real impacts for society, the first beneficiary of public services with more quality, efficiency and accountability.

The public HRMPS is the first attempt to produce an operationally valid and reliable measure to evaluate strategic HRM practices, responding to calls in the literature concerning the need for an integrated, comprehensive and customized HRM practices scale for the public service context.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.