Developing a maturity model for cancer multidisciplinary teams

Liu, Yiren; Evans, Lynleigh; Kwan, Terence; Callister, James; Poon, Simon K.; Harnett, Paul

doi:10.1016/j.ijmedinf.2021.104610

Cited by 7 publications

(5 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Those models were used to assess each factor that affects knowledge sharing practices in terms of benchmarking efforts and to develop progressive strategies that might improve its activities. Additionally, Yiren et al, [42] shed light on a maturity model for cancer multidisciplinary teams. That model consists of 17 indicators that are used to measure healthcare professionals’ performance and monitor the quality of performance at cancers centre over time.…”

Section: Discussionmentioning

confidence: 99%

“…Despite the variety of these models, few of them focus on knowledge sharing in healthcare in general and in the medical imaging department in particular [38]. There are several factors that affect knowledge sharing among healthcare professionals, including the maturity model of multidisciplinary team meetings, community of practice information and communication technology, social media networks, PACS, tele-medicine, and digital library [39][40][41][42][43][44][45]. Creating a maturity model for knowledge sharing that consists of all factors that affect their behaviours is vital to implementing a knowledge sharing environment among healthcare professionals.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Paper 3: - Towards a Knowledge Sharing Maturity Model for medical imaging departments

Almashmoum,

Cunningham,

Ainsworth

2024

Preprint

View full text Add to dashboard Cite

Background: Knowledge sharing in medical imaging departments is being driven by the need to improve healthcare services, develop healthcare professionals skills, and reduce repetitive mistakes. It is considered an important step in the implementation of knowledge management solutions. By following a maturity model of knowledge sharing, knowledge sharing practices can be improved. The aim of this study was to develop a maturity model knowledge sharing in medical imaging department for helping managers to assess the level of maturity for knowledge sharing practices. Objectives: In the modern healthcare institutions, improvements in healthcare professionals skills and healthcare services are often driven through practicing knowledge sharing behaviours. To understand the level of maturity of knowledge sharing, mangers can follow the indicators of maturity model knowledge sharing and its measurements in order to identify the current level and move to the next level. Methods: This study was conducted in three stages: An overview stage which highlighted the factors that affect knowledge sharing practices in medical imaging departments; an Analysis factor stage which was designed to assess the factors that affect knowledge sharing by using a concurrent mixed method approachs (questionnaires, and semi-structured interviews) in two medical imaging departments; and Structuring maturity model knowledge sharing stage, where a maturity model of knowledge sharing was developed based on the findings of the other stages. Results: The model presented in this study includes 17 indicators divided into 11 components. Those components derived from the findings of the questionnaires and semi-structured interviews that were applied in the medical imaging departments. It consists of five maturity levels: initial, aware, define, managed, and optimised. In each level were included measurements in order to help managers to assess the current level by answering to the measurements questions. Conclusion: This maturity model of knowledge sharing in medical imaging departments allows managers and policy makers to measure the maturity level of knowledge sharing in those departments. Although the model has been applied to the medical imaging departments, it might easily be modified to apply it to other institutions.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Paper 3: - Towards a Knowledge Sharing Maturity Model for medical imaging departments

Almashmoum,

Cunningham,

Ainsworth

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…We support these previously identified concerns with real-world examples from our PO stakeholder perspectives, including from the industry point of view. Finally, others have developed maturity models as self-assessment tools for multidisciplinary teams for cancer care to inform performance improvement over time [ 20 ]. We extend maturity model utility by conceptualizing the indicators of maturity in a precision oncology context that could drive LHS maturity strategies in an emerging field and other translational settings (See Fig.…”

Section: Discussionmentioning

confidence: 99%

Advancing maturity modeling for precision oncology

Hoffman-Peterson,

Marathe,

Ackerman

et al. 2023

J. Clin. Trans. Sci.

View full text Add to dashboard Cite

Introduction: This study aimed to map the maturity of precision oncology as an example of a Learning Health System by understanding the current state of practice, tools and informatics, and barriers and facilitators of maturity. Methods: We conducted semi-structured interviews with 34 professionals (e.g., clinicians, pathologists, and program managers) involved in Molecular Tumor Boards (MTBs). Interviewees were recruited through outreach at 3 large academic medical centers (AMCs) (n = 16) and a Next Generation Sequencing (NGS) company (n = 18). Interviewees were asked about their roles and relationships with MTBs, processes and tools used, and institutional practices. The interviews were then coded and analyzed to understand the variation in maturity across the evolving field of precision oncology. Results:The findings provide insight into the present level of maturity in the precision oncology field, including the state of tooling and informatics within the same domain, the effects of the critical environment on overall maturity, and prospective approaches to enhance maturity of the field. We found that maturity is relatively low, but continuing to evolve, across these dimensions due to the resource-intensive and complex sociotechnical infrastructure required to advance maturity of the field and to fully close learning loops. Conclusion: Our findings advance the field by defining and contextualizing the current state of maturity and potential future strategies for advancing precision oncology, providing a framework to examine how learning health systems mature, and furthering the development of maturity models with new evidence.

show abstract

“…Maturity models predicated on the CMMI framework have shown success in identifying areas requiring process improvements in the implementation of multidisciplinary care in oncology practices [4][5][6]. MTBs specifically pose a unique set of challenges to the practice of precision medicine and involve highly specialized multidisciplinary teams (MDT).…”

Section: Introductionmentioning

confidence: 99%

“…MTBs specifically pose a unique set of challenges to the practice of precision medicine and involve highly specialized multidisciplinary teams (MDT). A maturity model recently published by Liu et al was developed and validated for MDTs to perform selfassessments via survey to measure performance and track improvement in processes over time [6]. However, to date there is not a tool to perform similar maturity assessments for MTBs, resulting in a missed opportunity to identify areas of non-conformity with agreed processes and established standards.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of ACTE-MTB: A tool to systematically assess the maturity of molecular tumor boards

et al. 2022

View full text Add to dashboard Cite

Molecular tumor boards (MTBs) require specialized activities to leverage genomic data for therapeutic decision-making. Currently, there are no defined standards for implementing, executing, and tracking the impact of MTBs. This study describes the development and validation of ACTE-MTB, a tool to evaluate the maturity of an organization’s MTB to identify specific areas that would benefit from process improvements and standardization. The ACTE-MTB maturity assessment tool is composed of 3 elements: 1) The ACTE-MTB maturity model; 2) a 59-question survey on MTB processes and challenges; and 3) a 5-level MTB maturity scoring algorithm. This tool was developed to measure MTB maturity in the categories of Access, Consultation, Technology, and Evidence (ACTE) and was tested on 20 MTBs spanning the United States, Europe, and Asia-Pacific regions. Validity testing revealed that the average maturity score was 3.3 out of 5 (+/- 0.1; range 2.0–4.3) with MTBs in academic institutions showing significantly higher overall maturity levels than in non-academic institutions (3.7 +/- 0.2 vs. 3.1 +/- 0.2; P = .018). While maturity scores for academic institutions were higher for Consultation, Technology, and Evidence domains, the maturity score for the Access domain did not significantly differ between the two groups, highlighting a disconnect between MTB operations and the downstream impact on ability to access testing and/or therapies. To our knowledge, ACTE-MTB is the first tool of its kind to enable structured, maturity assessment of MTBs in a universally-applicable manner. In the process of establishing construct validity of this tool, opportunities for further investigation and improvements were identified that address the key functional areas of MTBs that would likely benefit from standardization and best practice recommendations. We believe a unified approach to assessment of MTB maturity will help to identify areas for improvement at both the organizational and system level.

show abstract

Developing a maturity model for cancer multidisciplinary teams

Cited by 7 publications

References 25 publications

Paper 3: - Towards a Knowledge Sharing Maturity Model for medical imaging departments

Paper 3: - Towards a Knowledge Sharing Maturity Model for medical imaging departments

Advancing maturity modeling for precision oncology

Development and validation of ACTE-MTB: A tool to systematically assess the maturity of molecular tumor boards

Contact Info

Product

Resources

About