There has been growing interest in partnering with patients, caregivers and community members in research and quality improvement (QI) to bridge the gap between research, practice and lived experience. Groups seeking to collaborate with patients and caregivers must develop effective strategies to communicate complex and nuanced research methods and findings as patients and caregivers may not have had the years of training needed to successfully interpret the results. However, effectively communicating the complexity and nuance of research concepts to diverse audiences is one of the greatest challenges for modern-day scientists. Oftentimes, this requires simplifying complex concepts to allow a heterogeneous group of stakeholders – from policy makers to patients and caregivers – to gain a clear understanding. Counterintuitively, this translation often erodes the complexity and rigor of the research methods employed and artificially simplifies the messages in the data. While intended to help broad audiences understand research concepts, this may unintentionally make the information less accessible and result in distrust in both the process of the research and its outcomes . 

Patients and caregivers as partners in research and QI efforts to reduce health system inequities is one of the key drivers of East Toronto Health Partners’ (ETHP’s) vision for its 300 ,000 residents living in 21 neighborhoods, served by more than 100 health and social care delivery organizations in East Toronto, Ontario. Unfortunately, the COVID-19 pandemic has both revealed and widened the health equity divide. In East Toronto, not only has access to treatment and services been affected but it has resulted in significant declines in preventive care, such as cancer screening rates, and has differentially impacted neighborhoods with long-term lack of social resources, such as employment, income, education, health and housing. To address this issue, ETHP partnered with patients, informal caregivers, community advocates, researchers, clinicians and the Centre for Quality Improvement and Patient Safety (hereafter referred to as “the team”) to utilize cancer screening rate-based data as the foundation for co-designing a community-embedded QI program to improve cancer screening rates in East Toronto.  

To this end, the team co-created a QI workshop inviting diverse ETHP stakeholders to understand the barriers to cancer screening, co-design locally tailored solutions and define priority populations and neighborhoods for implementation of interventions. To set the stage and to provide a rationale for a focus on cancer screening, the team planned to present the cancer screening data for the East Toronto region in the workshop. The challenge facing the team was how to translate complex data and statistical methods in ways that would not only be understood by their diverse community partners but also create trust in the process of generating and analyzing the data. The team worked together to translate the data and statistical approaches used into plain language, developing a patient-oriented data knowledge translation (DKT) approach. The three guiding principles of the DKT approach were:

1. Tell a compelling story using data: The team employed an iterative process centred on patient engagement and telling a compelling story using data. The team clearly defined the challenge, purpose and approach to cancer screening. During planning, the team shared the methodology and findings on cancer screening (mammogram, Papanicolaou, colorectal) for East Toronto in an hour-long presentation that suggested that cancer screening improvement strategies should focus on the following:
   1. multiple populations: those with low chronic conditions and those who are generally healthy or unattached to primary care and
   2. neighborhoods with the highest levels of material depravation.
   Given the similarities across the three cancer screening categories, the team decided to focus on presenting one category of cancer screening using a limited number of graphs to convey their messages to the participants.
    
2. Explain complex concepts using simple visualizations: The team employed the LEGO analogy comparing raw data to unassembled LEGO bricks to tell the story of cancer screening and improvement opportunities in East Toronto. The team adapted the analogy (Figure below) to explain the use of population segmentation methods (i.e., segmenting the total population on a series of common characteristics such as health conditions). The team then linked the methodology to their challenge (decrease in cancer screening), purpose (prioritizing certain populations and neighborhoods) and approach (co-design).
   
    
3. Facilitate participants to draw connections to their lived experience: As a group, the team understood that the cancer screening data represented the lives of individuals living in East Toronto. Their hypothesis was that their audience – patients, caregivers or clinicians – already had a good understanding of the state of cancer screening in their neighborhoods based on lived experiences. So the team asked the audience to draw on their lived experience and share who (i.e., what population sub-groups) they think might have missed their cancer screening and in what neighborhoods. As expected, they knew the answer. The team then proceeded to present the data as a means to validate their lived experiences. The team constantly circled back to the identified challenge, purpose and approach, using the LEGO analogy.  

The ETHP's workshop on cancer screening improvement efforts is an example of a community-embedded approach to improving care. The team used data in new ways, created partnerships between patients and researchers and followed QI approaches with a DKT approach to improve cancer screening in East Toronto’s equity deserving neighborhoods. An example of the power of this approach was working with community members to raise awareness, educate and provide direct assistance with cancer screening that took on a life of its own. In sharing a practical DKT approach, the team hopes to contribute to the uptake of patient-oriented research and evidence-based decision making within the healthcare system.

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Peter Varga wrote:

Posted 2023/10/17 at 03:21 PM EDT