Enhancing chronic care pathways with Health Lean Management: a case study in a Spanish hospital

Anna Tiso (Department of Management Engineering, Universita degli Studi di Padova, Padova, Italy)
Caterina Pozzan (Department of Management Engineering, Universita degli Studi di Padova, Padova, Italy)
Manuel Francisco Morales Contreras (Department of Management, ICADE, Universidad Pontificia Comillas, Madrid, Spain, and)
Chiara Verbano (Department of Management Engineering, Universita degli Studi di Padova, Padova, Italy)

International Journal of Lean Six Sigma

ISSN: 2040-4166

Article publication date: 14 January 2025

214

Abstract

Purpose

Facing the burden of chronic diseases has become a priority for health-care systems’ economic and social sustainability. To this end, this paper aims to focus on adopting Health Lean Management (HLM), a widely used managerial approach, to improve the performance and quality of care provided in chronic care pathways. HLM addresses not only efficiency and timeliness issues but also care effectiveness and integration. Indeed, the lack of continuity and co-ordination of care constitutes a major challenge for chronic pathways. This research provides an innovative contribution, by extending the implementation of HLM to chronic pathways developed across hospital and territorial care. Indeed, HLM scope typically regards hospital units and departments; hence, analysing the interaction between different levels of care represents a novelty from an academic and practical perspective.

Design/methodology/approach

With the aim of understanding how to extend the adoption of HLM towards the territory, an action research project has been developed. In particular, an improvement project focused on breast cancer care pathways has been launched in a Spanish hospital. The research investigates which HLM activities, tools and practices need to be accomplished in this kind of project, grasping insights into emerging wastes. To this end, the HLM project followed the Define, Measure, Analyse, Improve and Control (DMAIC) cycle, supporting the project team in effectively conducting a preliminary context analysis, qualitative and quantitative data collection, the current state analysis and the countermeasure proposals.

Findings

The analysis conducted on the breast cancer care pathway highlighted major criticalities in managing the diagnosis of new patients. In particular, waiting times to obtain diagnostic imaging and breast specialist consultations highly impacted the care pathway effectiveness and efficiency. Specific wastes that caused these delays have been investigated, leading to the definition of specific countermeasures that could minimise the inefficiencies: an 85% reduction of the staging process lead time was estimated.

Originality/value

The achieved results contribute to enhancing the quality of care delivered to breast cancer patients. This paper enriches the theoretical knowledge about HLM, extending its typical field of application; provides practical support to health-care providers, managers and leaders with a case demonstrating how to develop HLM projects adopting the DMAIC cycle; and finally, it has valuable social implications, addressing the global threat of chronic disease.

Keywords

Citation

Tiso, A., Pozzan, C., Morales Contreras, M.F. and Verbano, C. (2025), "Enhancing chronic care pathways with Health Lean Management: a case study in a Spanish hospital", International Journal of Lean Six Sigma, Vol. 16 No. 8, pp. 1-36. https://doi.org/10.1108/IJLSS-04-2024-0070

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Anna Tiso, Caterina Pozzan, Manuel Francisco Morales Contreras and Chiara Verbano.

License

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode


Introduction

Advancing innovation in health care has the potential to significantly enhance equity and sustainability within health-care systems. In this context, promoting responsible innovation plays a crucial role in ensuring equitable services and personalised care. Key objectives include reducing access barriers, optimising the alignment between clinical staff skills and patient needs and customising technological tools for specific settings (Lehoux et al., 2018). Within the international context, innovation can significantly support health-care systems in facing financial constraints and demographical changes, such as the increasing number of people suffering from chronic diseases. Enhancing managerial innovation can support process-orientated strategies, helping health-care organisations achieve both quality- and cost-related objectives (Kim et al., 2016).

Noncommunicable diseases (NCDs), also known as chronic diseases, are responsible for approximately 70% of all deaths worldwide, with cardiovascular diseases, cancers, chronic respiratory diseases and diabetes as the main pathologies (OECD, 2021; WHO, 2016). The increasing prevalence of NCDs represents a critical challenge within the global landscape. In high-income countries, this exacerbates existing issues linked to austerity measures, an ageing population and the high costs associated with technology-intensive care (Hunter and Reddy, 2013). People affected by NCDs often encounter fragmented services, resulting in suboptimal health outcomes and interruptions in care transitions between hospitals and community settings (Frandsen et al., 2015; Hofer and McDonald, 2019; Ljungholm et al., 2022). Ensuring care co-ordination is of the utmost importance to align care providers in addressing the requirements of service users and ensure the delivery of integrated, person-centred care across different health-care settings. From the patient’s perspective, this leads to a continuum of services that are cohesive and integrated, tailored to their health needs and personal preferences (WHO, 2018).

In a context characterised by a lack of care co-ordination and continuity, Health Lean Management (HLM), as a managerial innovation approach, can enhance the quality of care within clinical care pathways by implementing improvement measures to promote care integration (Tiso et al., 2022). HLM is globally recognised as the most widely adopted improvement methodology in health care (Henrique and Godinho Filho, 2020). Its primary objective is to promote continuous process improvement through a comprehensive toolkit and methodologies, all aimed at minimising waste and enhancing value for patients (Radnor et al., 2012).

With the main focus on improving the quality delivered in chronic care pathways and adopting a qualitative methodology based on Action Research (AR) and a case study, the current research aims to explore the implementation of HLM in an innovative context that extends its scope from the hospital setting to the community level.

In particular, two research questions (RQ) have been formulated:

RQ1.

How can HLM be implemented in chronic pathways, referring to project activities, HLM tools and organisational practices?

RQ2.

Which are the main wastes emerging in chronic pathways developed across hospitals and territories?

Thus, the theoretical contribution of this study consists in exploring and identifying how HLM, and in particular the Define, Measure, Analyse, Improve, and Control (DMAIC) cycle, can be adopted and implemented in poorly explored settings: the health-care processes that encompass both the hospital setting and the territorial settings (i.e. home care, primary care, secondary care) (de Bittencourt et al., 2023), with the focus on a chronic care pathway. Addressing the burden of chronic disease, with particular attention to breast cancer care pathways, represents a significant contribution not only to the economic sustainability of the health-care system but also to social sustainability. Indeed, enhancing the quality of care delivered means to increase the quality of life, life expectancy and access to care, thus reducing social inequalities.

Theoretical background

HLM is globally recognised as one of the most prevalent managerial approaches to advance continuous improvement within health-care organisations. This methodology has been adapted over time to address specific challenges of this sector, often characterised by inadequate investments, resistance to change among clinical staff and pressing demand for quick results (Henrique and Godinho Filho, 2020). Its origins can be traced back to the early 1900s in the Japanese automotive sector, and it has since gained worldwide recognition, extending its application to various other manufacturing fields (Womack and Jones, 1990). The application of HLM in health care was initially proposed by Womack and Jones (1996) and has been established as an effective approach to reduce inefficiencies and wastes in health-care processes, with a primary focus on improving service quality (Antony et al., 2019; Crema and Verbano, 2013a, 2013b; Radnor et al., 2012). HLM supports a process-oriented culture within health-care organisations intending to minimise fragmentation and enhance sustainability (Pless et al., 2017). Continuous and sustainable improvement implementation often involves the use of problem-solving approaches to support project management. These high-level algorithms encompass many tools and techniques that are adaptable to specific situations. Among the most used in health care, there is the DMAIC cycle (Costa et al., 2023). This supports process improvement through five standardised phases: “Define” and “Measure” the problem, “Analyse” causes, “Improve” countermeasures and “Control” results (Henrique and Godinho Filho, 2020; Pyzdek, 2003). Adoption of the DMAIC cycle in health care contributes to improved quality performance and increased value for patients (Ahmed, 2019; Costa et al., 2023; Vaishnavi and Suresh, 2020). Within each DMAIC phase, some typical lean tools are used. For instance, in the Define phase, Demand maps are useful to delineate the involved services and the entity of patient flows in terms of volumes; the value stream instead is analysed and represented in the value stream maps (VSM), which help to visualise the care process with the patient perspective; swim lane maps share some similarities with cross-functional flow charts, highlighting the deployment of a care process into single activities across various actors or settings of care. The Measure phase quantifies the problem defined in the first project phase. Lean methodology promotes the use of Gemba waste walks, visiting and observing the places in which the process takes place, and the value is generated. Another important tool is the Ishikawa diagram, applied in the Analyse phase to define the sources of each encountered waste, through the definition of its root causes considering four aspects: machines, methods, people and patients.

However, the use of appropriate lean tools and techniques proves to be insufficient to guarantee sustainable and successful results, unless supported by a system of values and cultural change. These aspects must be carefully integrated to support continuous improvement (Henrique and Godinho Filho, 2020; Hines et al., 2004). Successful HLM implementations are closely tied to significant organisational and cultural changes, which involve effectively engaging personnel in improvement projects and fostering a supportive environment (Hoxha et al., 2024). One of the most important factors that influence implementation success is leadership involvement. In HLM projects, this is achieved through the proactive participation of senior management in scheduled activities and their consistent effort to motivate and engage employees. Top management is responsible for allocating the necessary resources and technological tools, providing support in case of difficulties and ensuring the achievement of improvement objectives (Al-Balushi et al., 2014; Albliwi et al., 2014; Alnajem et al., 2019; Antony et al., 2012; Ben‐Tovim et al., 2008; Costa et al., 2023; Narayanamurthy et al., 2018). Moreover, to support effective HLM implementations, project team members should be selected based on their ability to collaborate and work in teams. They must be encouraged to trust each other, share ideas and suggestions and act as decision-makers. However, achieving this goal is challenging, especially considering that promoting a system-wide approach to improvement requires project team members from different departments and with multiple roles, who are not always accustomed to working together (Al-Balushi et al., 2014; Alnajem et al., 2019; Costa et al., 2023; Delgado et al., 2010; Henrique et al., 2021; Narayanamurthy et al., 2018).

In terms of its application, HLM has been predominantly implemented within hospital settings, particularly in care units like the emergency department, oncology ward and surgery (Akmal et al., 2020). The primary benefits, as highlighted in the literature, are related to efficiency and are closely linked to the reduction of waste, errors and delays (Antony et al., 2019). However, there is limited evidence of studies that extend beyond a single department or encompass the broader health-care network. The implementation of HLM outside the hospital walls, along the entire patient care pathway, is still in its early stages. This compartmentalised approach appears to be prevalent, although weak co-ordination among different care providers during HLM implementations hinders the realisation of full benefits and higher levels of care quality (Akmal et al., 2020; Antony et al., 2019; Henrique and Godinho Filho, 2020; Tiso et al., 2022). In this regard, the theoretical and empirical knowledge of this methodology are not yet exhaustively detectable in chronic care pathways. According to Tiso et al. (2022), less than half of the existing HLM experiences regarding the integration between hospital and territorial care (which already constitute a minority in HLM literature), focuses on chronic diseases. Among them, the most studied pathologies are diabetes, cardiovascular diseases and cancers. This means that there is poor evidence about the development of HLM projects in chronic care pathways across hospital and territory. Indeed, care for chronic patients requires a multifaceted approach that includes hospital services during disease exacerbations and daily home and community care. Effective management of chronic diseases at the local level requires patient collaboration and continuous support from different health professionals to minimise acute events (Bodenheimer et al., 2002; Damery et al., 2016). Ensuring co-ordination of care among different providers, including hospital inpatient and outpatient services, as well as territorial care, requires a high level of integration. Overcoming this challenge is not always straightforward but is fundamentally necessary for the optimal management of NCDs and the improvement of patient quality of life (Nuño et al., 2012; Struckmann et al., 2018). Although methodologies aimed at improving health-care processes are rarely applied to the entire care pathway and thus to chronic conditions as a whole (Akmal et al., 2020), HLM could lead to improved performance, care quality objectives and integration (Tiso et al., 2022). This approach has the potential to address the need for improvement in variable, unpredictable, complex and long-term care pathways (Pless et al., 2017).

In this scenario, cancer patients’ care pathways are particularly critical among all NCDs due to their high mortality rates. According to the World Health Organization (WHO, 2016), there are 9.3 million cancer-related deaths worldwide each year. Among these, breast cancer ranks as the second leading cause of cancer-related female deaths in all OECD countries, with significant social consequences. The criticality of this care pathway arises not only from the number of deaths but also from its high prevalence among women and the significant impact of delays in screening and treatment on care outcomes (OECD, 2021). Moreover, there is a clear association between the development of breast cancer and the ageing population, with more than 80% of breast cancers occurring in women aged more than 50 years (Walker and Martin, 2007). Considering the demographic trends, the number of elderly women diagnosed with breast cancer is likely to increase substantially in the coming decades, with profound implications for the delivery of medical care (Alberg and Singh, 2001). As declared by the WHO, the goal is to reduce global breast cancer mortality by 2.5% per year, leaning on three pillars: early detection; timely diagnosis; and comprehensive breast cancer management. Consequently, early diagnosis and easily accessible diagnostic services are crucial for reducing breast cancer mortality (WHO, 2023). Due to the relevance and characteristics of this care pathway, the implementation of HLM can yield effective results in improving disease detection, diagnosis, treatment and follow-up; reducing time, costs and waste; and improving productivity and standardisation (Tiso et al., 2022).

In this context, the definition of “quality” extends many concepts historically associated with the industrial world, integrating key objectives such as safety, patient-centredness, equity and integration of care (WHO, 2020). This broader perspective aligns more closely with the motivations driving the implementation of HLM, combining efficiency and cost reduction goals with patient satisfaction and organisational culture transformation (Antony et al., 2019). Effective co-ordination among various care providers is essential to meet these demanding requirements and provide a seamless patient care experience (WHO, 2018). Achieving care continuity within a clinical pathway is associated with reduced hospitalisation, lower mortality rates and health-care cost savings (Hofer and McDonald, 2019). Inadequate continuity and co-ordination of care result in fragmented and poorly integrated services, significantly impacting the most vulnerable patients, including those with chronic conditions (Ljungholm et al., 2022; WHO, 2018).

Methodology

The objective of this article is to explore the potential implementation of HLM to improve breast cancer care pathways within the context of a Spanish hospital. To this end, a qualitative methodology has been designed based on a case study and AR, given the dual nature – theoretical and practical – of the research aim.

A qualitative case study methodology is suitable when the objective is to understand the “how” and “why” of a phenomenon, particularly within the context of contemporary events (Yin, 2017). Building theory from case studies offers significant advantages such as novelty, testability and empirical validity, which stem from the close association with empirical evidence (Eisenhardt, 1989). Furthermore, case studies are likely to be engaging, precise and testable due to their utilisation of diverse data sources, including interviews, documentation, quantitative data and direct observations (Eisenhardt and Graebner, 2007; Stake, 1995).

AR can be defined as “an emergent process in which applied behavioural science knowledge is integrated with existing organisational knowledge and applied to address real organisational issues” (Shani and Coghlan, 2021). In operations management, AR projects actively involve non-academic people and business organisations to build scientific knowledge, assessing the effects of changes and improvements (Ollila and Yström, 2020). An AR methodology aims at concurrently generating practical actions for an organisation or industry and developing theoretical knowledge derived from these activities (Coughlan and Coghlan, 2002), thanks to the involvement of academic researchers, managers and other employees (Coghlan and Shani, 2014). The primary challenge lies in integrating the execution of improvement actions with activities aimed at fostering shared learning and operational initiatives designed to test theoretical concepts (Ollila and Yström, 2020). Critical steps in the early stages of an AR project launch include defining the research purpose and rationale within the specific context, as well as deepening the methodology details. The project is then implemented in iterative cycles to address the specific issue and collect data and information. As the project nears completion, a reflective phase is initiated, involving a comprehensive analysis of the outcomes. This phase lays the groundwork for exploring how the specific action research project can be integrated into a theory-based framework that extends beyond the local context (Coghlan and Shani, 2014; Coughlan and Coghlan, 2002).

García-Navarro et al. (2019) propose a structure of AR cycles composed of seven activities or cases:

  1. diagnosing: understanding the context and purpose of the study;

  2. action research planning;

  3. data collection;

  4. data analysis and action planning;

  5. action implementation;

  6. action assessment; and

  7. learning.

This study adopts an AR methodology following a DMAIC cycle (Bhat et al., 2021), an increasingly adopted approach for quality improvement initiatives in the health-care sector (da Silva et al., 2018). The AR methodology proposed by García-Navarro et al. (2019) and the DMAIC cycle have been integrated and concurrently employed in a joint and combined approach. In Figure 1, the coexistence of the AR cycle and the DMAIC is highlighted: in particular, within each coloured slice representing a phase of the DMAIC cycle, the AR steps are reported, specifically:

  • Define: problem(s) definition that leads to specific project motivations, aims, focus and scheduling. These activities coincide with the first two AR activities of diagnosis (context understanding) and project planning.

  • Measure: this phase aims to quantify the defined problem, through quantitative and qualitative data gathering, highlighting the overlap with the third AR step of data collection.

  • Analyse: analysis of the problem and its causes, based on data measured, corresponding with the fourth activity of AR “data analysis and action planning”.

  • Improve: this phase concerns the generation of improvement countermeasures to solve the identified issues and their subsequent implementation. It coincides with the AR activity of “action implementation”.

  • Control: the achieved results are measured and monitored, assessing the action implemented. In AR the last activities are “action assessment and learning”, in which practical results are discussed to obtain relevant research findings.

Avison et al. (2018) identified the significant amount of time and resources of an AR project as a main barrier. They suggested “publishing single AR cases, but not the entire AR project, if there is sufficient contribution in each case to merit publication” (Avison et al., 2018, p. 180). This is aligned with Alfaro-Tanco et al. (2023) who considered that not all cases need to be part of the research project and the researcher needs to differentiate between the practical action and the research project. Alfaro-Tanco et al. (2021) stated that: “the goal should be to generate different outputs from different AR stages, that is, diagnosis, proposals, and implementation. This means that an AR study does not have always to imply “action” outputs (implementation)”.

This study analyses the breast cancer pathways in a Spanish hospital following an AR methodology and the DMAIC approach with a very detailed focus on the Define, Measure, Analyse and Improve stages. It also provides a set of proposals for the stage of Control, which is still in progress. The long project duration, as well as the valuable produced outcomes from the diagnosis, planning, data collection and data analysis (Alfaro-Tanco et al., 2021; Avison et al., 2018) allows the research team to present the results in the following section.

Case study

The empirical context where the AR project was conducted required three main characteristics: (a) the presence of a network of care encompassing both hospital and territorial care; (b) the necessity of improving the performance and quality of care delivered in chronic pathways; and (c) the inclination of collaborating in a research project.

Hence, a public Spanish hospital responding to these requirements has been selected for the project implementation. In particular:

  • Compliance with criteria (a): the hospital covers a population of 350,000 people, offering about 900 beds and counting 5,000 employees. It provides tertiary and secondary care services, and it is connected to a network of 15 primary care centres of pertinence, two specialistic outpatient clinics and three mental health centres;

  • Compliance with criteria (b): the hospital highlighted from the very beginning relevant criticalities in managing breast cancer patients, due to long waiting lists and consequent waiting time which characterised the care process;

  • Compliance with criteria (c): the selected hospital has an internal Innovation Unit responsible for quality improvement initiatives, research collaboration and data analysis, which acted as a facilitator and support in the current project. Moreover, the hospital already had experience with quality improvement projects, offering the possibility to collaborate with a proactive team of clinicians. Indeed, a multidisciplinary project team, in which academics and practitioners worked together both in the research and operational project, was created.

In this research, AR is ensured by the collaboration of two teams who worked closely on this project: a core research team and an operational team.

A core project research team was designated to organise and co-ordinate the project development and scheduling, making key decisions and conducting specific managerial analysis, given their expertise in the HLM approach. It was composed of two professors for support and supervision, a PhD student with the twofold task of supporting the project development but also accomplishing operational activities in the field, a master student, two data analysts who contributed with data mining and statistical analysis and a doctor who helped to contact and engage other health-care professionals.

The operational project team was formed by the health-care workforce directly involved in the breast cancer pathway, dedicated to providing useful information and insights about the process, validating the analysis and revising the work conducted. In particular, a breast specialist, an oncology care co-ordinator, two oncologists, two radiologists, two radiologic technologists, a doctor from palliative care, the head and a technician of the pathological anatomy unit.

Data sourcing and analysis

Different sources have been considered for data gathering: documentation, statistics and data provided by the hospital; direct observation; and semi-structured interviews with professionals. The fieldwork and data and statistics gathering took place from April to September 2022.

Interviews have been conducted by two researchers following a semi-structured approach (Kvale, 1996; Rubin and Rubin, 1996). Interview scripts were created based on the literature review and data from direct observation. Interviews were conducted on-site in the hospital, with professionals working in the breast cancer pathways; they were recorded and then information was extracted based on the research needs. The two interviewers coded data independently and then discussed the results to check the reliability of the analysis; moreover, the final results were presented and discussed for verification with the interviewees, when some missing aspects were recalled. Results were shared with both the research and the operational project teams for triangulation, eliminating bias and ensuring the validity of the results.

A formal research project was prepared to take into account ethical considerations in different stages: thematising, designing, interview situation, transcription, analysis, verification and reporting (Kvale, 1996). Confidentiality agreement documents were signed by the researchers and presented to the participants in the project to guarantee that all data would be anonymised, used only for academic and research purposes and not disseminated to third parties.

Results

Define

To analyse the breast cancer clinical pathways, the project team started with a preliminary understanding of the care process structures and fundamental activities. Regarding chronic diseases, care pathways are typically regulated by national or international guidelines. They provide an overview of how the process should be ideally performed: the actors involved, the activities and their sequences, the phases, the clinical parameters and the therapeutic responses. The purpose pursued with this analysis was twofold: on one side to gain an introductory knowledge about the breast cancer pathways, and on the other side to highlight the differences between the theoretical processes and the ones effectively implemented. These gaps could represent the starting points for the improvement intervention.

Hence, internationally acknowledged procedures and guidelines adopted by the selected hospital have been examined and discussed with doctors and nurses operating in breast cancer pathways. To obtain the most likely representation of the theoretical process, several documents have been merged and summarised into a single flowchart, which was designed with the support and supervision of the hospital doctors. The care pathway was composed of two main macro processes – diagnosis and treatment and follow-up – and of two secondary supporting macro processes – screening programs and awareness and prevention campaigns. The analysis focused on the first two: according to the health-care workforce involved in the project team, the processes dedicated to the diagnostic and therapeutic management of breast cancer patients turned out to be the most critical in terms of performance and number of patients needing complex care. Indeed, screening programmes and prevention campaigns do not involve breast cancer patients, but individuals with a possible risk of tumour.

In particular:

  • The diagnosis and treatment process was articulated in four phases:

    • Staging, coinciding with the diagnosis assignment, conducted in primary or secondary care.

    • The current phase begins with a patient physical examination, performed by the general practitioner (GP) based on the detected symptoms and personal clinical history. Through this examination, it is possible to determine the probability degree of breast cancer presence: patients with low probability but a high-risk personal history can be referred to the general gynaecologist who will arrange a follow-up, whereas patients with high probability can be referred to the breast specialist. The latter therefore proceed with a first-level diagnostic imaging, consisting of mammography or echography, performed whether in outpatient care or hospital. Based on the resulting Bi-RADS classification, patients could end the process with follow-up if the tumour was not detected, or patients could undergo a biopsy if the tumour malignancy emerged. Biopsies (core needle biopsy, vacuum-assisted biopsy, fine-needle aspiration and ancillary biopsy) are performed by hospital units. Tissue samples are then analysed; when the result is positive, patients need a second level diagnostic imaging, consisting of an MRI scan or mammography with contrast, followed by chest-abdomen computed tomography or bone scintigraphy when the risk of metastasis arises. Integrating all the results of the conducted diagnostic activities, a multidisciplinary committee defines the treatment and therapeutic plans for each patient.

    • Post-staging: secondary care activities to support patients and/or reduce the cancer dimension before the surgery. Indeed, in specific clinical conditions, patients can undergo neoadjuvant therapy to make the tumour mass smaller.

    • Treatment of operable cancers: elimination of the tumour mass, conducted in secondary or tertiary care. The pre-surgery activities encompass blood tests, X-ray tests, ECG, anaesthetic examinations and integrated oncoplastic evaluation. Surgeries can be conservative or not (mastectomy). In the first case, intraoperative radiotherapy is conducted. In some cases, after the tumour mass removal, the sentinel lymph node biopsy is conducted, the sample analysed by the pathological anatomy unit and based on the biological results, an axillary dissection is performed.

After surgery, further adjuvant therapies are often necessary: radiotherapy, chemotherapy, hormone therapy or a combination of them.

  • Treatment of non-operable cancers. For some kinds of cancers, surgery is not practicable, thus it is substituted with different kinds of therapies: palliative care, which can be basic or specialist, conducted at home or in hospices; chemotherapy; hormone therapy; and immunotherapy.

  • The follow-up process encompasses four different pathways:

    • The monitoring care activities performed after the adjuvant therapy administration;

    • The care activities performed to monitor the non-operable cancers after the therapy administration;

    • Medium-risk follow-up for patients with a medium risk of developing breast cancer; and

    • High-risk follow-up for patients with a high risk of developing breast cancer.

In all these cases, the follow-up activities are regularly accomplished throughout the patients’ lifetime and demonstrated to be similar independently from the categorisation provided. It consists of regular mammography and blood tests, with the addition of an MRI scan for high-risk follow-up, followed by endocrinological, cardiological and gynaecology tests combined with breast specialist and oncologist visits.

A swim lane map of the process has been designed to better visualise the process, also underlining the settings of care responsible for each activity and the relationships between them (Figure 2). The map shows how the initial and final stages of the care process are delivered by territorial services, while the remaining activities are conducted inside the hospital, in oncology, breast pathology, pathological anatomy and radiotherapy units.

The pathway reported in the swim lane map represents a theoretical process, which has been compared with the care process currently implemented in the hospital considered in the project. In this regard, some inconsistencies between the theoretical maps and the real care process implemented in the selected hospital have been highlighted by project team brainstorming and focus groups.

Firstly, the activity named “physical examination” comprehends all the visits, performed by general practitioners in primary care and by specialists in outpatient care, which provide the opportunity to obtain a preliminary diagnosis without conducting mammography or ultrasound tests. The purpose is to reduce avoidable diagnostic imaging, especially when the presence of the cancer can be certainly excluded. However, in reality, this step is often skipped and retained useless by GPs and gynaecologists who opt for directly referring patients to radiology consultations.

The second aspect concerns the second level of diagnostic imaging: although the studied guidelines question the systematic use of MRI scans to assess the cancer local extension, all the patients undergo this exam.

Third, within the treatment of operable cancers, performing intraoperative radiotherapy emerged to be impossible – thus only theoretical – due to the lack of adequate equipment.

In addition, mammography represents a crucial point for breast cancer care pathways, because it receives patients from diverse processes and likewise creates various process branches, based on the exam outcomes. In this regard, the operational project team emphasised also how critical mammography is for the hospital: indeed, high patient volumes have to be managed in this activity, and the health workforce is overloaded, also because of the lack of an adequate number of human resources, causing increasing overcrowding, waiting times and waiting lists. Moreover, mammography is conducted in diverse phases of the breast cancer pathway, such as the diagnosis and the follow-up, significantly impacting the care process effectiveness.

Hence, to deepen this last aspect, the project team focused on the investigation of patient volumes for mammography, defining also patients’ origin and destination through a demand map:

  • 100% of patients undergo a mammography;

  • mammography is performed in the hospital radiology unit;

  • 66% of patients who undergo mammography come from the hospital or outpatient care; among them, the Gynaecology, Radiology and Oncology units are responsible for 98% of mammography prescriptions; and

  • the primary care centre 072 is responsible for 44% of mammography prescriptions.

Furthermore, the same study has been repeated to also analyse the demand for the first breast pathology unit visit. This visit is performed among the first care process activities, provided by a specialist upon referral by the GP.

The 74% of patients needing a visit to the breast pathology unit come from primary care centres, which have been divided into three categories, according to the Pareto Analysis (Appendix 1Figure A1):

  • RED (eight centres): >199 visit prescriptions;

  • ORANGE (six centres): 10–199 visit prescriptions; and

  • PURPLE (64 centres): <10 visit prescriptions.

Thanks to this analysis, it has been possible to identify which primary care centres constituted the main hospital providers, responsible for 80% of visit prescriptions in the breast pathology unit. Specifically, the RED group encompasses 75% of prescriptions, reaching 98% when also the ORANGE group is considered. Therefore, the project team concluded that patient flows were mainly co-ordinated by 14 PC centres spread in the territory around the hospital. A bubble diagram representing the geographical distribution of these centres has been produced (Appendix 1 – Figure A2), highlighting two clusters of primary care centres, gravitating around the hospital and the A.P. clinic, respectively. While the hospital is near the barycentre of the first cluster, the A.P. clinic is located 5 km away from the second cluster, underlying potential logistical issues that limit access to care for certain patients.

Measure

Both qualitative and quantitative data have been collected. Qualitative data have been gathered through semi-structured interviews with the health-care workforce collaborating in the project team, extracting information concerning patient characterisation, process care activities, organisational and co-ordination activities, clinical aspects, such as specific therapies and parameters, logistic aspects (i.e. transportation routes of materials, patients or clinicians’ movements, unit layout) and criticalities. Also, Gemba waste walks contributed to grasp useful data about criticalities and inefficiencies: indeed, HLM promotes direct observations on the field to deepen how the process is performed and understand how the value is created, but also how and why wastes are generated.

To perform the quantitative analysis, the hospital database has been investigated. A patient sample, representing the population of breast cancer patients, was extracted according to the following inclusion criteria:

  • Patients cared by the oncology unit. Indeed, breast cancer patients could be cared by the breast pathology unit or oncology unit: anyway, considering the research aim of analysing the entire care pathway, only the oncology unit assists patients up to the final follow-up activities.

  • Female patients, given the higher volumes as compared to male patients.

  • Patients undergone hospital services in 2018–2019 to exclude COVID-19 effects on breast cancer pathways.

These criteria led to the selection of 1,835 patients, associated with 295,542 activities of care conducted in the selected period. Not all of these activities were related to the breast cancer care pathway: they have been filtered with the support of the project team, arriving to identify a database of 179,269 care activities. The obtained database has been analysed through a process mining software (Disco), which provided a graphical representation of the breast cancer care activities performed by the selected sample.

In this case, process mining did not help with the definition of the sequence of activities of the care process, but it contributed to assign timings, highlighting how critical the waiting times for a visit in breast pathology and for a mammography are, thus the need to deepen the staging process.

In this regard, doctors and nurses of the project team have been interviewed. Their opinion confirmed the criticality that emerged from process mining, estimating a mean waiting time of two weeks for the first mammography and the breast specialist visit. Reducing these timings would speed up the staging process, contributing to provide a precocious diagnosis to patients, with benefits for the outcomes of care. In addition, the resources used in the staging process coincided with those used in the follow-up process. Therefore, improving the performance of the staging process could lead to relevant advantages also for the follow-up.

Hence, with the team agreement, the project focused on the staging process.

The indications provided by the health workforce, the information gathered during the Gemba waste walks, and data extracted from the databases contributed to derive a list of key points and criticalities concerning the staging process:

  • As highlighted by the demand map, general practitioners refer directly to radiology all the patients who need mammography, without prior physical evaluation or a breast specialist evaluation: this means that all the patients, also who may not need the mammography, undergo the examination, overloading the radiology unit.

  • The first step of analysis of the biological sample taken during the biopsy is performed by radiology instead of pathological anatomy, overloading the radiology unit.

  • Conducting high- and medium-risk follow-ups is responsibility of the breast pathology unit.

  • Providing the results of diagnostic imaging and biopsy to patients is responsibility of the breast pathology unit.

  • Biopsy is the most time-consuming activity: 40 min as a mean.

  • Waiting time to obtain the biopsy result: 13 days as a mean.

  • Waiting time for mammography after a breast specialist visit: 10 days as a mean.

  • Communication issues between radiology and breast pathology units, with potential delays in the transmission of the diagnostic imaging results.

  • A study of the layout, conducted in the radiology unit, highlighted the existence of a bottleneck causing flow braking and complications. The Spaghetti chart represented in Figure 3, shows doctors and technicians’ routes (red and blue lines) followed to perform dye injections, mammography, ultrasounds and biopsies. Doctors and technicians (five for each shift) are obliged to pass through two closed doors to move across mammography, ultrasound and reading rooms. To avoid this obstruction, the pathway should be considerably lengthened. Moreover, the distance between the mammography or ultrasound room from the reading is very high, causing a waste of movement and time. Finally, looking at the red lines, it is clear how complex the technicians’ routes are, due to the lack of standardised work and tasks.

  • Staging, follow-up and screening are managed by the same resources, but patients present diverse needs based on the process. However, the system is not able to adequately respond to their needs, causing delays and overcrowding.

In addition to these main criticalities, a detailed list of wastes encountered in the process has been formulated (Appendix 2 – Table A1).

To complete the analysis of the current state of the staging process, a VSM has been produced, integrating data and information collected through interviews, data mining and direct observation (Figures 46). The VSM offers a picture of the staging process, specifying all the activities performed, their sequence, the time needed to accomplish each task and the time between them. In addition, it confirms that the most impacting non-value-added activities concern the waiting times for mammography, breast pathology visits and the time needed to complete the pathological anatomy service. Moreover, it emerged that breast specialists take two weeks from the first visit to reserve the subsequent consultation. Looking at the VSM, this interval time should be considered as a necessary non-value-added activity – thus not disposable – because it is needed to ensure that mammography results are available to patients.

All these aspects cause a very low flow index: indeed, value-added activities constitute only 3.3% of the lead time to deliver the diagnosis to patients.

The analysis of the current state contributed to define where the main criticalities reside and identify the most inefficient activities and the most impacting aspects of the care process on the quality of care provided. In this regard, a list of key process indicators (KPIs) has been defined by the project team:

  • waiting rate: number of biopsies “to be done”/number of accomplished biopsies (week);

  • average delay for the first breast specialist visit (week);

  • breast specialist new patients (week);

  • average process lead time (month); and

  • continuity of care for breast specialist visits: number of first visits conducted by the same specialist who conducted the last visit.

The project objective was to reduce the average process lead time of the staging phase by 50%.

Analyse

The measure phase contributed to define the dilated times of the staging process as the main criticality to solve. The motivations for these delays have been identified, conducting a root cause analysis (Figure 7), as follows:

  • Lack of patient categorisation and prioritisation: breast cancer patients in staging, screening, or follow-up do not have different degrees of priority or urgency to access care, being part of the same waiting list for diagnostic visits and specialistic consultations. Moreover, they share the same resources, in terms of human resources and medical/technological equipment.

  • Difficulties in estimating the staff workload, roles and responsibilities, with effects on the effectiveness of tasks performed in the staging process.

  • Lack of standardised activities, causing inefficient staff movements, lack of work organisation, delays and queues.

  • The presence of a push system which is responsible for overcrowding, waiting lists and bottlenecks.

  • Incorrect or missing data in the hospital database which hinders the performance assessment and measurement.

  • Lack of rationale for workstation positioning and unit layouts.

Improve

Several improvement proposals have been generated by the project team in brainstorming sessions to overcome and solve the encountered issues. The countermeasures are reported in Table 1:

The generation of the improvement proposals led to the definition of a future state VSM (Appendix 3Figures A6–A8), in which the following changes have been introduced:

  • Patients do not return home after the breast specialist visit but are directly sent to the radiology unit to perform the mammography, according to a FIFO logic. Hence, the waiting time between the two activities is reduced from 10 days (patients had to wait for a new mammography appointment) to 13 min, estimated as the sum of the time needed to move from the breast pathology unit to radiology and the waiting time for the test.

  • The time between mammography, echography and core needle biopsy has been zeroed thanks to the introduction of the pull system and the elimination of the agenda.

  • Reduced waiting time (from 6 days to 13 h) for the second breast specialist visit, in which the medical results of the diagnostic tests are delivered to patients.

  • Reduced waiting time (from 9 days to 5 days) to accomplish the MRI scan after the second breast specialist visit.

  • Reduced waiting time (from 5 days to 3 h) for the final breast specialist visit.

All these changes, concerning the elimination of waiting time and the reorganisation of roles, responsibilities, waiting lists and layout, significantly reduced the process lead time, estimated to measure 9 days, with an 85% reduction in comparison with the current state process (60 days).

Control

Further steps beyond the scope of the current research paper could concern the design of an implementation plan, which needs to be approved by the hospital top management and by the project team. Once the proposals are implemented, the control phase will be launched, to monitor the results in the short and long term.

Discussion

The current research reports how HLM can be implemented in breast cancer pathways not only in hospital settings but also in territorial care. Indeed, chronic care is typically developed along long clinical pathways that integrate the assistance delivered in hospitals with outpatient and primary care, in particular by GPs and specialistic clinics. The aim is to test the application of HLM to improve the quality of care provided and performance. A specific focus is pointed at highlighting which activities, tools and organisational practices should be performed and which wastes need to be addressed in this context.

Regarding RQ1 (How can HLM be implemented in chronic pathways, referring to project activities, HLM tools and organisational practices?), the HLM project has been conducted following the DMAIC cycle, as described in the methodology section. Although project outcomes have not yet been assessed through KPI measurements, the preliminary findings from the future state analysis indicate that the sequence of phases, activities, tools and practices had positive impact on performance, especially in terms of timeliness and efficiency. Specifically:

  • The creation of a multidisciplinary project team involving the health workforce operating in the selected clinical pathway with lean experts, data analysts and quality engineers. The health workforce engagement in the improvement intervention became fundamental to increase the success of HLM projects. Their point of view is crucial to define the project focus, validate the managerial and statistical analysis, assess the feasibility of the countermeasure proposals and create a collaborative environment in which changes are perceived positively. It is very important to be able to appropriately identify the most collaborative individuals, assigning them project leadership roles.

  • The enthusiasm and participation should be kept high by performing organisational activities, such as project meetings, sharing and discussion events, frequent communication and updates and celebration of achieved results that are arranged during the entire duration of the project. These practices are also important to remove departmental barriers and minimise conflicts that can be encountered in this kind of projects: indeed, given the chronic pathway complexity, health professionals working in very different units or facilities, are required to work together for a common goal, independently from their personal interests.

  • Context analysis of the project setting and of the clinical guidelines adopted, given the high degree of complexity of chronic pathways, characterised by long and articulated processes encompassing several health professionals. Maps (flow charts, swim lane maps and cross-functional flow charts) are produced to clearly visualise processes, fostering the understanding of the current state situation by clinicians – who learn how to consider their daily routinary activities as a part of a process that includes clinical, organisational and managerial aspects – and by engineers – who understand the structure and sequence of activities constituting the analysed pathway.

  • The analysis of demand to define the project focus. Indeed, chronic pathways, as said before, are developed along long sequences of activities, encompassing huge amounts of activities, patient flows, health professionals, care facilities, patient volumes and services provided. The demand analysis fosters the identification of the most significant patient volumes and the most populated patient flows, the origin and destination of each care activity, the most committed care facilities and the most prescribed services.

  • Data collection: after the qualitative process definition, a quantitative representation of the pathway should be provided. In hospital settings, it is not always easy to obtain accurate and useful data; they often need to be integrated with interviews to the health workforce with expertise on the analysed care pathway and direct observation on the field (Gemba waste walks). For instance, in the current project, the information derived from process mining has been combined with the indications provided by the health workforce during interviews and focus groups and with the information extracted by the notes taken by the engineers during Gemba waste walks in the involved hospital units and clinics.

  • Current state mapping, which constitutes one of the HLM pillars. Creating graphical maps of the analysed process (swim lane map, VSM and spaghetti chart) contributed to distinguish value-added and non-value-added activities, understanding and sharing where the inefficiencies reside. Swim lane maps are particularly useful for representing chronic pathways, as they visually depict interactions between different levels and sites of care, which often entail criticalities.

  • The analysis and identification of process wastes, which emerge from the integration of current state maps, the information gathered during Gemba waste walks and interviews and quantitative data extracted from the hospital databases.

  • Once a list of wastes is obtained, a root cause analysis should be accomplished to define the sources of these wastes, facilitating their reduction or elimination.

  • Countermeasures definition and evaluation: the main contribution comes from the health workforce, who, through brainstorming and focus groups, can easily determine how wastes generated in routine work activities can be minimised or removed. The effectiveness of improvement proposals can be assessed by developing future state maps and monitoring performance.

The subsequent activities of countermeasures implementation and monitoring have not been implemented in the current project. These final phases require a strong commitment and support of hospital leadership and top management, which should provide not only their approval and authorisation but also encourage and increase the health workforce engagement to actively introduce changes in the process. Indeed, clinical leaders and management play a crucial role in facilitating and supporting innovation and change by influencing and empowering individuals, thus creating an environment that fosters success (Aij and Rapsaniotis, 2017; Hilverda et al., 2023; McSherry and Pearce, 2016). Specifically, HLM projects require leadership at all levels of the organisation to systematically align Lean philosophy and tools with the organisation’s strategic goals, vision and value (Aij and Rapsaniotis, 2017). Therefore, engaging leadership and top management represents a gradual process that requires time; in the current research, time constraints represented a limitation to achieve this goal, but the operational project team committed to further involve the hospital leadership to proceed autonomously with the project.

However, despite the lack of significant achievements in performance, the project produced valuable results. Indeed, the health-care workforce has been involved in a research project, collaborating with researchers in every step of the process. Moreover, researchers frequently visited the hospital, working side by side with practitioners for several months. In this way, they could mutually transfer and share their knowledge and experience: researchers offered training sessions on HLM principles and values, project management, research methodology and data collection techniques; the health-care workforce instead provided all the useful information and details about the care process, activities and wastes, fostering the understanding and analysis of the breast cancer pathway. The synergic cooperation enabled the achievement of relevant goals both from academic and practical perspectives: on one side creating new knowledge about HLM projects in an unexplored contest and on the other side by providing a set of improvement proposals to the hospital’s top management. Moreover, the teamwork among the actors involved has been enhanced, through frequent communication and results sharing. According to the literature, engaging and empowering health-care employees in this kind of project constitutes a critical success factor: they must be encouraged to trust each other, share ideas and suggestions and act as decision-makers (Al-Balushi et al., 2014; Alnajem et al., 2019; Costa et al., 2023; Delgado et al., 2010; Henrique et al., 2021; Narayanamurthy et al., 2018).

The answer to RQ1 demonstrates how the DMAIC cycle constitutes a suitable tool to develop HLM projects also in this new setting – chronic care across hospitals and territories. Some fundamental elements of lean projects have also been found in this case, such as the creation of the multidisciplinary team, the analysis of the current state process through maps, the analysis of wastes and the analysis of the future state maps. Anyway, some adaptations implemented in the reported HLM project demonstrated to be necessary to better suit the specific setting, among them:

  • The project team counted a higher number of people because chronic pathways involve diverse professionals working in different settings and sites of care. Therefore, organisational practices revealed to be crucial to guarantee team co-ordination and engagement.

  • A context analysis, including also the study of clinical guidelines, is necessary to clarify the structure of care pathways, which are particularly complex and articulated in the case of chronic care pathways.

  • The demand analysis also demonstrated to be fundamental to understand which are the most critical sections of such long and articulated pathways.

Regarding RQ2 (Which are the main wastes emerging in chronic pathways developed across hospitals and territory?), the main inefficiencies refer to:

  • the lack of standardised procedures that should be followed by health professionals – also referring to different care settings – to provide chronic care, in particular concerning the care activities, the partition of roles and responsibilities;

  • the low adherence of the implemented care pathways to the existing process guidelines;

  • the onerous waiting times to accomplish specific activities or to obtain an appointment cause gaps in care. Indeed, chronic patients have to wait several months to proceed with visits and consultations, creating bottlenecks in the care process. This becomes particularly critical in the diagnostic process: delayed diagnosis causes delayed treatment, thus higher risks for patient safety and degraded care effectiveness; and

  • communication issues between hospital units and even more between different levels of care (i.e. GPs with specialists), highlighting low co-ordination and integration of care, which are fundamental characteristics of effective chronic care.

Hence, it emerged how inefficiencies and wastes had concrete impacts on some dimensions that are peculiar to chronic care pathways: the integration and continuity of care.

Conclusion

The current research represents rare evidence of HLM implementation in breast cancer care pathways. It demonstrates the applicability of the DMAIC cycle and lean tools to analyse and improve chronic care pathways developed across hospitals and territories.

The research offers an academic contribution by enriching the existing HLM knowledge and empirical literature, reporting how new and future projects could be implemented in an innovative context. It confirms some of the proposals from existing previous literature, but it also brings new insights and contributions. Indeed, the current study shows how the HLM approach needs to be adapted to each specific context to be effective. The DMAIC approach, widely used in hospital settings, can also be adapted for territorial settings, but with more complexities and challenges. It should consider existing barriers between hospitals and territories, such as longer communication channels, distance between facilities, conflicting interests of participants and different cultural and organisational backgrounds.

This research offers some practical implications that may be of interest to both practitioners and managers in the health-care sector. Managers could implement some of the recommended organisational practices for motivating and engaging the health workforce in continuous improvement projects. Managers and practitioners could also use direct observation in the field (Gemba waste walks), as well as the tools and maps (flow charts, swim lane maps, cross-functional flow charts, VSMs and spaghetti charts) to monitor the processes, identify the potential improvement areas and take actions to improve them. This study also provides managers and practitioners with a method to identify and analyse the main wastes emerging in chronic pathways, being:

  • the lack of standardised procedures;

  • the low adherence of the implemented care pathways to the existing process guidelines;

  • the long waiting times; and

  • some communication issues.

It is worthy to also underline the social impact of the research, which pursues to reduce and address the global burden of chronic diseases. Moreover, intervening in their clinical pathways could have significant effects on their quality of life and average life expectancy.

This research also presents some limitations and offers some future research directions for academia. One of the limitations has been the lack of time and resources for the Control stage within the DMAIC approach. Even though the rest of the stages provided interesting insights and contributions about the application of HLM to reduce the different types of waste and improve the quality and performance, further research could be conducted to explore the results of the Control stage with measurements and key performance indicators. However, the paper constitutes a valuable example showing how to implement four DMAIC phases in a new, complex and challenging context, as this case study.

This exploratory study has been conducted in a particular hospital in Madrid, Spain. In addition, more studies could be done in different hospitals, in different cities, countries or cultural environments to evaluate the implementation of HLM in breast cancer care pathways, as well as in other chronic pathways. Furthermore, considering the importance of promoting personnel participation through significant cultural changes, further studies could investigate how leadership and employee behaviour and involvement impact the implementation process. Critical factors such as the role of management during the project, their interaction with employees and the composition and behaviour of the project team should be thoroughly investigated to understand their impact on the completion and success of the project.

Figures

Correspondence between AR cycles and DMAIC cycles with tools applied in the project

Figure 1.

Correspondence between AR cycles and DMAIC cycles with tools applied in the project

Swim lane map – diagnostic, treatment and follow-up process

Figure 2.

Swim lane map – diagnostic, treatment and follow-up process

Spaghetti chart: radiology

Figure 3.

Spaghetti chart: radiology

VSM – part 1: staging process

Figure 4.

VSM – part 1: staging process

VSM – part 2: staging process

Figure 5.

VSM – part 2: staging process

VSM – part 3: staging process

Figure 6.

VSM – part 3: staging process

Root cause analysis: Ishikawa diagram

Figure 7.

Root cause analysis: Ishikawa diagram

Pareto chart

Figure A1.

Pareto chart

Bubble diagram

Figure A2.

Bubble diagram

Introduction of a FIFO logic for radiology exams

Figure A3.

Introduction of a FIFO logic for radiology exams

Layout improvement: first option

Figure A4.

Layout improvement: first option

Layout improvement: second option

Figure A5.

Layout improvement: second option

VSM to be – part 1

Figure A6.

VSM to be – part 1

VSM to be – part 2

Figure A7.

VSM to be – part 2

VSM to be – part 3

Figure A8.

VSM to be – part 3

List of countermeasures proposals

Root cause Countermeasure proposal Description
  • Lack of patient categorisation and prioritisation

  • Push system

  • Lack of rationale for layouts

Pull system for patients flows Assuring a breast specialist visit to all patients with suspected breast cancer before mammography, to avoid useless mammography to patients who do not need it. This visit will become the process pacemaker
Assigning a dedicated breast specialist to the staging process for new patients’ visits and medical report delivery
Reorganising the visit schedule, alternating a first breast specialist visit to a new patient and a visit to deliver medical reports to patients coming from radiology
Introducing a communication mechanism to support the pull system, blocking the flow when the subsequent activity is full: to this end, the breast specialist performs the first and last activity of the process
Pull system for tissue samples collected with biopsy Introducing a supermarket inside the room “reception of samples” in the pathological anatomy unit, to guarantee the availability of sample containers for biopsy: when the radiologic technologist delivers the tissue sample to the pathological anatomy unit, collects an empty sample container that will be used in radiology. If sample containers finish, no more patients are accepted
Removing the agenda and waiting list for radiology and biopsy Eliminating the waiting time between the breast specialist first visit and the subsequent radiology examination, directly referring patients to radiology with a FIFO logic. The same happens for biopsy after mammography. (Appendix 3Figure A3)
Radiology layout optimisation Improving the health-care workers movements and creating dedicated spaces for specific activities (Appendix 3Figures A4 and A5)
  • Difficulties in defining staff workload, roles and responsibilities

  • Lack of standardised activities

Roles and responsibility reorganisation To unload breast specialists, allowing them to perform a visit to all patients with suspected breast cancer:
– entrust the management of medium and high-risk follow-up to the radiology unit
– only oncologist and breast specialist can prescribe mammography and biopsy
– new patients’ first breast specialist visit can be performed only in facilities provided with radiology equipment: the optimisation analysis suggests performing them only in the hospital, moving the radiology general visit to the secondary care ambulatories
Standardisation Create a new standardised procedure for the radiologic technologist
Introducing standardised activities denomination in the hospital software
Visual management Coloured lights advise if mammography changing rooms are occupied
Coloured pathways guide patients in their movement across units
Explicative posters in mammography changing rooms with instructions about the procedure that patients will follow

Source: Authors’ own work

List of encountered wastes

Waste Description/Effects
Missing pathways indications Patients get lost inside the hospital
Wrong data entered in the hospital database The timing of visits and exams are not accurate
Missing data in the hospital database Data on patients, services provided and timings are often missing: physicians often skip the data entry activity
The same visit/exam has different denominations in the hospital database There is no standardisation among different hospital departments: every department registers the required information using the preferred denomination
Waste of time looking for information in paper sheets Given the lack of digitalisation, doctors and nurses register most of the information on paper sheets
Waste of time searching for patient information in the hospital software Software interfaces are not user-friendly: physicians and nurses have to take several steps to grasp the needed information
Waste of time searching for patient information in the medical record The medical record has the format of a free text, so grasping specific information is very difficult
Waste of movements between hospital and outpatient clinics Mammography and biopsy are performed in the hospital: patients who undergo a breast specialist visit in outpatient clinics then have to move to the hospital to proceed with the care pathway
Lack of ultrasound scanner Breast specialists do not have ultrasound scanners
Radiologic technologist’s waste of time While doctors perform X-ray exams, radiologists wait next to them without doing anything
Lack of standardisation of medical report Radiology medical reports are not regulated in a standardised format, complicating the assessment of breast specialists and oncologists
Lack of prioritisation and logic in MRI scans reporting The MRI scan arrives in the reading room randomly, so the reporting timings is very variable
Equipment and materials located in the wrong room The equipment needed in the mammography room is located in the warehouse; the material needed for the MRI scan is located in the mammography room
Mammography room overcrowding Too many radiologists stay simultaneously in the mammography room
Waste of time If a visit finishes before the time slot dedicated to those patients, doctors have to wait before calling the next patient

Source: Authors’ own work

Appendix 1. Define phase

Figure A1

Figure A2

Appendix 2. Measure phase

Table A1

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Acknowledgements

Anna Tiso and Chiara Verbano gratefully acknowledge funding from Next Generation EU, in the context of the National Recovery and Resilience Plan, Investment PE8 – Project Age-It: “Ageing Well in an Ageing Society” [DM 1557 11.10.2022]. The views and opinions expressed are only those of the authors and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission can be held responsible for them.

Disclosure: The authors report no conflicts of interest in this work.

Corresponding author

Anna Tiso can be contacted at: anna.tiso@unipd.it

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