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Abstract
Background In 2017, the Canadian Partnership Against Cancer, a Canadian federally sponsored organisation, initiated a national multijurisdictional quality improvement (QI) initiative to maximise the use of synoptic data to drive cancer system improvements, known as the Evidence for Surgical Synoptic Quality Improvement Programme. The goal of our study was to evaluate the outcomes, determinants and learning of this nationally led initiative across six jurisdictions in Canada, integrating a mix of cancer surgery disease sites and clinicians.
Methods A mixed-methods evaluation (surveys, semistructured interviews and focus groups) of this initiative was focused on the ability of each jurisdiction to use synoptic reporting data to successfully implement and sustain QI projects to beyond the completion of the initiative and the lessons learnt in the process. Resources provided to the jurisdictions included operational funding, training in QI methodology, national forums, expert coaches, and ad hoc monitoring and support. The programme emphasised foundational concepts of the QI process including data literacy, audit and feedback reports, communities of practice (CoP) and positive deviance methodology.
Results 101 CoP meetings were held and 337 clinicians received feedback reports. There were 23 projects, and 22 of 23 (95%) showed improvements with 15 of 23 (65%) achieving the proposed targets. Enablers of effective data utilisation/feedback reports for QI included the need for clinicians to trust the data, have comparative data for feedback, and the engagement of both data scientists and clinicians in designing feedback reports. Enablers of sustainability of QI within each jurisdiction included QI training for clinicians, the ability to continue CoP meetings, executive and broad stakeholder engagement, and the ability to use pre-existing organisational infrastructures and processes. Barriers to continue QI work included lack of funding for core team members, lack of automated data collection processes and lack of clinician incentives (financial and other).
Conclusion Success and sustainability in data-driven QI in cancer surgery require skills in QI methodology, data literacy and feedback, dedicated supportive personnel and an environment that promotes the process of collective learning and shared accountability. Building these capabilities in jurisdictional teams, tailoring interventions to facility contexts and strong leadership engagement will create the capacity for continued success in QI for cancer surgery.
- Quality improvement
- Audit and feedback
- Surgery
Data availability statement
No data are available.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
Measuring treatment patterns and quality of surgery is essential to evaluating cancer system performance. It is unclear how utilisation of synoptic surgical and pathology reports can facilitate quality improvement (QI) efforts by cancer clinicians. The Evidence for Surgical Synoptic Quality Improvement (ESSQUI) Programme initiated by the Canadian Partnership Against Cancer aimed at understanding the determinants of a successful QI programme that maximised the use of synoptic reports in cancer surgery.
WHAT THIS STUDY ADDS
Here, we report the outcomes and learning of this large-scale nationally led initiative to build capacity for QI in cancer surgery, integrating a mix of cancer surgery disease sites (breast, colorectal, endometrial, ovary, prostate, thoracic and thyroid cancer) across five jurisdictions and one national subspecialty in Canada. The ESSQUI Programme led to cross-Canada improvements in cancer care quality, demonstrating that effective utilisation of synoptic reporting data, combined with appropriate resources and training, facilitated trust, comparative feedback and clinician engagement for successful QI initiatives on a large scale.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
The implications of this study are significant for research, practice and policy in cancer care. It underscores the necessity of systems investing in QI methodology, data literacy, physician score cards and audit and feedback mechanisms to drive improvements in cancer surgery outcomes. Providing ongoing support and fostering a culture of collective learning and shared accountability are essential for sustaining QI efforts.
Introduction
The quality of cancer surgery provided to Canadians is better than ever, but there are still large gaps between what is known as high-quality care and the care that many Canadians receive.1 2 The Canadian Partnership Against Cancer is a federally sponsored organisation (hereafter known as the ‘Partnership’) whose mandate is to accelerate action on cancer control for all Canadians.3 It works with partners to support uptake of the knowledge emerging from cancer research and best practices in order to optimise cancer control planning and drive improvements in quality of practice across the country. Partners include provincial and territorial cancer programmes, national health and patient organisations, and individual experts who provide strategic cancer control insight and advice from both patient and professional perspectives. Since 2007, the Partnership has supported the use of electronic synoptic reporting of pathology and surgical data across multiple Canadian cancer jurisdictions and organisations. It was thought that because synoptic data reports capture consistent information in a standardised way and facilitate easier retrieval of information, data would be used to not only improve communication between members of the healthcare team but also for quality improvement (QI) initiatives at multiple levels. To this end, the Partnership initiated a national multijurisdictional QI initiative to maximise the use of synoptic data to drive cancer system improvements, known as the Evidence for Surgical Synoptic Quality Improvement (ESSQUI) Programme, over the period of 2017–2021. A national call for proposals was conducted, and six jurisdictions across Canada were selected (table 1) and provided the funding as well as resources necessary to implement QI projects in cancer surgery (Box 1).
Characteristics of six jurisdictional teams participating in the ESSQUI Project
Summary of resources provided by the Canadian Partnership Against Cancer during the Evidence for Surgical Synoptic Quality Improvement Initiative
Resources provided by the Canadian Partnership Against Cancer synoptic initiative
Flexible funding: ranged from $C100 000 to $C723 000 per jurisdiction over the 5 years. Teams used the funding for clinical stipends, meetings, travel, supplies, digital technology and staff salaries to support the project (project managers, analysts, programmers).
National forum: six 1–2 days of national forums were held over 5 years, initially every 6 months at the beginning of the initiative. These forums invited project teams and were either in person (prior to the COVID-19 pandemic) or virtual and provided opportunities for education on quality improvement (QI) processes, exchange of ideas and updates on the progress of all the projects from each of the jurisdictional teams.
Training in QI process and tools: the Partnership recognised that the foundation for any initiative’s success is having the tools to carry out the work and having the knowledge through training to support continuous learning. As such, project team members were supported with an accredited QI course (https://www.ideasontario.ca/foundations-of-quality-improvement/) within the national forums, to train team members in data fluency, plan–do–study–act methodology, process optimisation, root-cause diagrams and change management skills. These investments ensure team members share common QI methodology and have access to tools for success.
Expert coaches: a group of five coaches with expertise in QI, feedback reports, physician engagement, communities of practice, positive deviance methodology, change management and implementation science were provided to all teams to help with their projects on a regular and as-needed basis. The expert coaches also provided one-on-one consultation to the practice champions or facilitated group discussions with the practice care team during the national forums. Many clinicians needed assistance with translating new or evolving evidence-based research into their everyday practice.
Regular monitoring and ad hoc support: the Partnership held monthly status calls with team leads to review and address emerging barriers to progress. Teams also submitted annual reports on their progress and budget used. Status calls with the Partnership helped teams move their projects forward, discuss and troubleshoot challenges, and collect and submit project documentation. Calls helped teams feel supported throughout project implementation. Teams especially appreciated the additional support and flexibility offered by the Partnership throughout the COVID-19 pandemic.
In this article, we describe the results of an independently performed, mixed-methods evaluation of the success of the ESSQUI Programme. We use the experience of each of the six jurisdictions to answer the following questions:
To what extent has the Partnership effectively supported jurisdictions in engaging clinicians to use data to drive QI and what are the lessons learnt in this process?
To what extent has the Partnership effectively supported jurisdictions to implement data-driven QI projects?
To what extent has the Partnership contributed to the sustainability of performing QI projects for each jurisdiction and what factors determine sustainability?
Methods
Implementation of ESSQUI
From December 2017 to December 2021, the Partnership conducted several national forums with the six jurisdictional teams (figure 1). The programme emphasised two foundational concepts within the QI training, which informed the research questions, foci of data collection and analytical framework. The concepts included:
Data literacy, metrics and audit and feedback reports. Project team analysts were guided by coaches with expertise in QI, audit and feedback,4–6 data presentation and literacy, physician engagement and implementation science.7 The expert coaches provided one-on-one consultation and met with the teams on a regular basis. Audit and feedback reports provided benchmark goals, comparison points (to other physicians, sites or jurisdictions) and some level of interpretation of the data and trends in performance. Several teams engaged additional external data scientists to help with integration of these reports into organisational information technology (IT)/electronic medical record (EMR) systems, automated data extraction methods, and design and generation of feedback reports. Depending on the organisational IT system, software used to produce the feedback reports included Synoptec, Microsoft SQL, REDCap and RStudio.
Communities of practice (CoP) meetings and positive deviance methodology. As part of the ESSQUI Initiative, all teams had to engage in regular CoP meetings every 2–4 months. CoP meetings brought clinicians, allied health professionals, hospital leadership and administrators together to discuss where to focus QI efforts, use data to identify potential QI opportunities, assess the progress of QI projects, revise synoptic templates and/or feedback reports to improve accuracy and clinical relevance, and openly discuss ways to improve and standardise clinical care across individual clinicians and clinical groups. Using positive deviance methodology and peer-to-peer modelling,8–10 high-performing clinicians discussed best practices and ways to help others perform similarly. Any concerns related to privacy and liability were acknowledged and addressed. In order to facilitate attendance of clinicians, many teams leveraged pre-existing meeting slots or national meetings and forums.
Timeline of activities and evaluation points within the ESSQUI Initiative. CoPs, communities of practice; ESSQUI, Evidence for Surgical Synoptic Quality Improvement; PDSA, plan–do–study–act; QI, quality improvement.
Design of evaluation
The Partnership worked collaboratively with project teams to design a coordinated evaluation approach for the initiative, using a mixed-methods approach. For quantitative data, performance metrics for specific QI projects towards the last 6 months of the 4-year initiative were used. Qualitative data included semistructured interviews with QI team leads over a period of 6 months to incorporate the experience of jurisdictional team leaders. Each of the six jurisdictional teams also formed focus groups consisting of a clinical lead (often a senior physician), a project manager, others from a clinical or managerial background and an executive sponsor (a senior individual who reported to the board but was not involved in day-to-day running of the project), who were also interviewed. The goal of the individual and focus group interviews was to identify themes and lessons learnt (eg, barriers and enablers) about advancing and sustaining QI projects within cancer care settings (see online supplemental appendix for interview guide). Interviews were conducted by non-project-affiliated qualitative health researchers either on the phone or via video-conference. These were recorded digitally and transcribed verbatim.
Supplemental material
Data analysis and synthesis
Analysis and coding of the qualitative data were done using NVivo qualitative analysis software and involved examining the interview transcripts and relevant documents (such as minutes from the CoP and team meetings). By comparing data from multiple sources, the evaluators were able to group similar data into thematic categories based on their content or meaning. With the constant comparative approach, as new data were collected or analysed, they are compared with existing data to identify similarities, differences and patterns.11 This iterative process helped in refining categories and understanding the relationships between them. All teams had an opportunity to validate the summary of results for their jurisdiction. Cross-jurisdictional analysis was also conducted to develop higher-level concepts and broader lessons learnt across the national QI initiative.
Results
Overall, there were 23 QI projects implemented across 6 jurisdictional teams across Canada, engaging 221 clinicians. 101 CoP meetings were held where clinicians from different disciplines came together to review synoptic data, discuss what the data meant and decide where to focus their QI efforts. Overall, 22 of 23 (95%) showed improvements with 15 of 23 (65%) achieving their proposed targets. Among projects resulting in improvements:
18 increased the use of high-value practices in pathology assessment (eg, faster turnaround time, better documentation), pre-surgical treatment (neoadjuvant chemotherapy, use of preoperative staging tests) or surgery (decreased positive margins, increased lymph node retrieval, increase in immediate breast reconstruction, increase in laparoscopic technique)
Three improved postoperative outcomes (eg, reducing adverse events or shortening length of stay).
Two reduced low-benefit practices (eg, reduce unnecessary use of deep vein thrombosis).
Qualitative data included semistructured interviews with 18 project team leads and 37 participants across six jurisdictional teams where they reflected on their experience, enablers and barriers of using synoptic data reports to drive QI efforts.
In the account below, quantitative data from performance metrics and qualitative data from the interviews, focus groups and CoP meeting minutes were used to address the questions outlined in the aims of the evaluation.
1. To what extent has the Partnership effectively supported jurisdictions in engaging clinicians to use data to drive QI and what are the enablers and barriers of this process?
Over the course of the initiative, 101 CoP meetings were held and 337 clinicians received feedback reports. Enablers for using data and feedback reports to drive QI projects included the following:
Clinicians need to trust the data. Understanding where the raw data were coming from and participating in the methodology of data collection helped validate the data and therefore their interpretation. Many teams took the time to invest in foundational work to ensure everyone agreed with what the synoptic data represented and how they related to their clinical work, although one team noticed that too many iterations of reviewing data validity led to disengagement of some clinicians.
Sample quotation #2: We did some iterations and changes of the [synoptic] template so that we were capturing what [clinicians] wanted us to capture until they could trust the data was accurate. (Clinical lead; source: project team focus group)
Sample quotation #3: There’s been various iterations of [synoptic reporting] systems. There’s been burnout and we’ve lost people through that. (Team lead; source: project team focus group)
Engagement of data scientists and clinicians to co-design feedback reports. Designing effective feedback reports was an iterative process that requires a nuanced understanding of the data, user and healthcare context. Several teams engaged data scientists to help them design and implement the feedback reports. It was important for the data scientists to understand the clinician’s needs and clinical context, as well as the data and IT systems.
Sample quotation #1: Clinicians know if they’re having issues, they get back to us and we can tweak our templates to meet their needs. [The initiative] opened clear communication between us, ‘Here’s what we can do, what do you want us to do to help you?’ (Data scientist; source: project team focus group)
Sample quotation #2: We’ve only had two reports – we’re still early in the process. Between the first and second report, there was a big increase in how useful the information was. (Clinical lead; source: project team focus group)
Provision of comparative data in the feedback reports. Clinicians valued seeing benchmark targets of quality and clinical performance indicators, allowing them to compare their own performance with those of their peers, or of other sites and jurisdictions.
Sample quotation #1: By using indicators, we can compare ourselves to other parts of Canada and compare within our province. And I love that. (Project team member; source: project team focus group)
Barriers for using data and feedback reports to drive QI projects included:
Lack of automated data collection processes: while two jurisdictions still had manual entry of data, most teams used software compatible with hospital EMRs to automate data extraction and report generation in real time. Not only was this much less time-consuming, it also allowed for timely sharing of real-time data on a regular basis for updating dashboards and feedback reports. This process required specialised IT support as it was critical to integrate the software for data extraction with the hospital EMR and firewalls of hospital IT systems.
2. To what extent has the Partnership effectively supported jurisdiction to implement QI projects in cancer care?
Table 2 provides a summary of each project’s aim, target measures, performance outcomes. 22 of 23 (95%) showed improvements with 15 of 23 (65%) achieving their proposed targets. Among projects resulting in improvements:
18 increased the use of high-value practices in pathology assessment (eg, faster turnaround time, better documentation), pre-surgical treatment (neoadjuvant chemotherapy, use of preoperative staging tests) or surgery (decreased positive margins, increased lymph node retrieval, increase in immediate breast reconstruction, increase in laparoscopic technique).
Summary of the QI projects, their aims and target values for measurement
Three improved postoperative outcomes (eg, reducing adverse events or shortening length of stay).
Two reduced low-benefit practices (eg, reduce unnecessary use of deep vein thrombosis prophylaxis, unnecessary axillary clearance).
3. To what extent has the Partnership contributed to the sustainability of performing QI projects for each jurisdiction and what factors determine sustainability?
All teams planned to distribute feedback reports or present data on a regular basis going forward, continue their work on refining the report templates and attract more clinicians. Some teams have attracted other cancer disease site teams interested in participating in synoptic data collection and their own CoPs. Two teams have secured funding to continue QI work (eg, from their provincial health system or through private-sector partnerships). One of these teams aimed to build an integrated data warehouse with linked data from synoptic templates, the provincial cancer registry and the National Surgical Quality Improvement Program, which will provide more robust data for QI. Another team had plans to build a permanent national database that they can use to collect data for clinical trials and publications. Results of the interviews identified determinants of sustainability of QI efforts within each jurisdiction, which included:
QI training for clinicians (enabler). Through formal QI educational sessions at the national forums and coaches offering their expertise, clinicians reported being more comfortable with using QI language, tools and frameworks (eg, root-cause analysis; plan–do–study–act cycles; positive deviance methodology) to assess their own data and collective data to improve patient care going forward. Many clinicians felt that these tools were useful and would continue to be used beyond the initiative.
Sample quotation #1: We have been doing synoptic reporting for a decade, but not the feedback loops. (Clinical lead; source: project team focus group)
Sample quotation #2: I don’t think we would have done these directed feedback reports looking at variation or specific outcomes without [the partner meetings). We would have continued doing what we were doing… this more focused approach was completely invigorated by the [project]. (Team lead; source: project team interview)
Sample quotation #3: The [project] gave us ideas that we didn’t even know were out there. Meetings with coaches and touch-base meetings with the Partnership were helpful for moving us along. We are updating one of our feedback reports based on interactions with a coach. (Team lead; source: project team interview)
Emergence of a QI culture through the delivery of CoPs (enabler). CoP meetings were frequent and allowed clinicians to exercise common vocabulary not only for data definitions and standardised fields in synoptic templates, but also for QI methodology tools, processes and frameworks. CoP meetings were used as educational sessions in QI methodology and best practices in collecting and interpreting clinical information. Clinicians reported being able to discuss performance data and variations in practice without fear of judgement or reprimand. Seeing their peers engaged and witnessing even small improvements in patient care encouraged other clinicians to participate. Many teams noted they had developed a stronger culture of QI because of this initiative, some clinicians felt that the culture had started to ingrain in their daily practices such that it would continue beyond the initiative.
Sample quotation #1: You can feel the drive and energy. [Clinicians] are more comfortable with QI. They don’t seem so nervous about getting their data back. (Team lead; source: project team interview)
Sample quotation #2: The variability that we see in DVT [deep vein thrombosis] prophylaxis has made for very interesting discussions to see it from two different subspecialty perspectives, and we learned from each other. In many ways it’s brought our group closer together. (Clinical lead; source: project team focus group)
Sample quotation #3: I think the power is showing what our colleagues are doing in a semi-anonymized non-threatening way. I think that’s actually the best way to change behaviour. (Participating clinician; source: project team focus group)
Sample quotation #4: Our projects aren’t large projects, but they worked and showed that you can use [synoptic] data. You can do little things that make changes. [Hopefully], that will stay with the organization and help move things forward. (Team member; source: project team interview)
Executive level and broad stakeholder engagement (enabler). Executive-level attendance at CoP meetings demonstrated system-wide support for QI initiatives. Teams varied in the amount of executive-level support from hospital administration/leadership and provincial cancer agencies. Teams where health system leaders were engaged saw increased capacity for QI work (eg, with support from hospital IT in the data collection and synoptic reports, connections with other stakeholders). Senior leadership was more likely to be engaged when the QI priorities were aligned with organisational strategic priorities and/or demonstrated value (economic, political, strategic) to the organisation.
Sample quotation #1: Everyone else [non-clinicians] saw the advantages of the system in [the first site] and then were prepared to buy into the project. (Team lead; source: project team focus group)
Sample quotation #2: We engaged a lot of people in using the data for QI who didn’t get feedback report [nonclinicians]. This generated a lot more interest and discussion. (Clinical lead; source: project team focus group)
Utilisation of pre-existing organisational infrastructures and processes. Pre-existing time slots for meetings (multidisciplinary tumour boards, morbidity and mortality rounds) were leveraged to help bring together busy clinicians in the same room at the same time. While virtual meetings improved accessibility for busy or remote clinicians, in-person interactions had the benefit of strengthening relationships and trust between clinicians and other stakeholders.
Sample quotation #1: Being a small jurisdiction, we only have one tumor board round which is well attended…. Increasingly, we were using that forum to discuss quality initiatives and present some data. That’s ongoing, so again that was a very big positive. It was sustainable. (Team member; source: project team interview)
Lack of continued funding for core team members—project managers, data scientists, technical and analytical support (barrier). Without ongoing access to dedicated support from data analysts, project managers and dedicated IT support, many teams felt sole reliance on busy clinicians for QI projects would significantly decrease the momentum and reverse the progress made so far.
I think [clinicians] were all somewhat interested, but nobody was the leader. Nobody was saying, “I’m the champion of this and we need to get it done.” In their defense, they don’t get administrative time or support to lead projects. (Team lead; source: project team focus group)
Discussion
Since 2007, the Partnership has supported QIs, change initiatives and innovation across all aspects of cancer care to the benefit of everyone in Canada. Here, we report the outcomes and learning of this large-scale, nationally led initiative to build capacity for QI in cancer surgery, involving a variety of cancer surgery disease sites. Evaluation of this initiative was focused on the ability of each jurisdiction to use synoptic data to successfully implement and sustain QI projects to beyond the completion of the initiative and the lessons learnt in the process.
Overall, the ESSQUI Initiative demonstrated that data-driven QI in healthcare requires specific skills, time, intentionality on the part of the clinicians; dedicated supportive personnel; broad stakeholder engagement and an environment/means that promotes continued learning and improving. We were able to demonstrate that harnessing data for QI required competency in data literacy, management, analytics, integration (with hospital EMRs) and delivery in such a way that is conducive to reflection, audit and feedback by clinicians. To achieve this competency, clinicians benefited not only from formal QI training to learn the language, tools and methodology of QI, but also from continued expert coaching and monitoring along the way. Additionally, we demonstrated the importance of formal (dedicated personnel such as data analysts and project managers) and informal supports (clinician peers motivating each other) within the process. CoP meetings have traditionally been identified as a means to share knowledge across silos and professional interdisciplinary boundaries12 13, but have been instrumental in creating the environment for mutual reflection, learning, and improving among clinicians and non-clinicians during this initiative. Clinicians reported being able to discuss performance data and variations in practice in a zone of psychological safety. They were able to work with their peers to design interventions and begin a culture of shared responsibility. Finally, we demonstrated the importance of a supportive organisational environment that would contribute to the sustainability of QI efforts.14 Specifically, a lack of executive-level engagement and physician remuneration for time and effort dedicated to QI were identified as barriers to continued implementation.
The learning from the ESSQUI Initiative reveals that success in QI efforts is multifactorial and multidimensional, with varied contextual, people and process-related factors impacting on design, delivery and outcome. The ultimate goal of QI is for it to be continuously embedded in workflow and an integral part of care delivery. Many models have been proposed to achieve this; one approach that has emerged in recent years is the concept of a learning health system (LHS) coined by the US Institute of Medicine (now the National Academy of Medicine).15 LHSs were defined as systems where ‘science, informatics, incentives and culture are aligned for continuous improvement and innovation, with best practices seamlessly embedded in the delivery process and new knowledge captured as an integral by-product of the delivery experience’. In an LHS, internal data and experience are systematically integrated with external evidence and that knowledge is put into practice.15 16 As a result, patients get higher-quality, safer, more efficient care, and healthcare delivery organisations become better places to work. The quest for many oncology institutions to achieve the concept of an LHS has proved to be challenging, although many are developing their capacity to do so.17 18
Over the 4 years of the initiative, the Partnership also learnt what worked and what did not work in building capacity for QI across several different jurisdictional teams across Canada. First, avoiding a ‘one-size-fits-all approach’ and tailoring the frequency and intensity of supportive resources (coaching, ad hoc status calls) were important. In retrospect, perhaps a more formal organisational readiness assessment for each team at the start of the initiative would have facilitated the effectiveness of the Partnership’s support for each team earlier on, as understanding each team’s context and starting point, its current infrastructure, how QI efforts tied to the organisational strategy, the revenue streams, how decisions were made and presence of supportive resources (such as IT) would have been important. Second, teams benefited from starting smaller projects, in order to establish the culture and methodology of QI, and gain confidence in their efforts. Third, in terms of the value of resources provided, all teams and coaches found the formal training in QI methodology during the national forums was highly beneficial in bringing all the participants to the same knowledge level. Finally, the sharing and presentation of the status, successes and challenges of the QI projects by each team during the national forum enabled participants across the country to learn best practices from each other and feel connected to a shared goal. In essence, the jurisdictional teams formulated a national CoP for cancer surgery QI efforts.
Despite the hands-on and energetic efforts by the Partnership in supporting and building capacity for QI, jurisdictions have not uniformly had implementation success. Reasons for this may be the following. To begin with, it became clear towards the end of the initiative that some teams were not clear on expectations and goals of the initiative. Perhaps the Partnership should have ensured that the teams knew from the outset what success looked like, as well as help formulate the road map (including defining core elements, milestones and activities) to get there. Second, most jurisdictional teams found that they could have benefited from more coaching support. Increasing coaching availability, such as inviting them to the regular ongoing status calls by the Partnership, would have been one option. Third, as formal engagement of the Partnership with the organisational senior leadership for each team may have accelerated QI efforts. Finally, while the literature does reveal various challenges and barriers for engaging patients in QI work,19 20 their inclusion may have enhanced organisational leadership support. Engaging them within CoP meetings was initially suggested by the Partnership, but there was pushback by physicians who felt strongly that including patients would have altered the dynamics and inhibited open discussions of physician performance, potentially limiting the effectiveness of the CoP meetings as a learning environment. The Partnership recognises that patient perspectives and experiences are crucial for QI work, and future efforts should include their formal integration perhaps through other methodologies.
Conclusion
Success and sustainability in data-driven QI in cancer surgery require skills in QI methodology, data management and feedback, dedicated supportive personnel and an environment that promotes the process of collective learning and shared accountability. Building these capabilities in jurisdictional teams, tailoring interventions to facility contexts and strong leadership engagement will create the capacity for continued QI in cancer surgery. Our findings provide important lessons for policymakers, funders, organisations and clinicians interested in scaling up QI projects in cancer surgery and healthcare in general.
Data availability statement
No data are available.
Ethics statements
Patient consent for publication
Ethics approval
Not applicable.
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Contributors AA—project conceptualisation, supervision, methodology, data analysis, writing (original draft preparation) and guarantor responsible for overall content. PH, AM, DS, AS, GS, MT and NW—project conceptualisation and investigations. SM and SD—project conceptualisation, investigation, administration and supervision. LAM, MFKF, JP, JB and CH—project conceptualisation and supervision, data analysis and writing (review and editing). CE—project conceptualisation and organisational sponsorship.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.