Today, Alzheimer’s disease (AD) and other dementias affect over 55 million people worldwide. That number is projected to grow to 139 million by 2050, mostly because of the growth and aging of the global population¹. The good news is that ongoing research on lifestyle interventions and innovative therapies is showing a way forward for people living with AD and their loved ones. For example, lifestyle interventions focusing on nutrition, physical activity, cognitive stimulation, and vascular and metabolic health can reduce the risk of AD. These interventions can also improve the cognitive function of people at high risk of developing dementia^2,3. Another positive is that we are closer than ever to having successful treatments that modify the course of the disease–also known as disease-modifying treatments–available in the market.

With the expected growth of AD cases worldwide, the strong evidence on lifestyle interventions and the imminent development of new therapies, we are faced with another challenge–preparing our healthcare systems for what is to come. Bridgeable has partnered with the Healthcare System Preparedness team from the Davos Alzheimer’s Collaborative (DAC) to develop a model and prepare healthcare systems to deliver timely screening in six countries through a pilot program on early detection of cognitive symptoms of AD. DAC is a global initiative to accelerate the discovery, testing, and delivery of precision interventions for Alzheimer’s disease. The organization was initiated at Davos in 2020 and was co-convened by the World Economic Forum and the Global CEO Initiative on Alzheimer’s Disease.⁴

A look into the existing Alzheimer’s landscape

Alzheimer’s Disease (AD) is the most common type of dementia. It is a progressive disease that affects memory, thinking, and behaviour. It was discovered over a hundred years ago, but it wasn’t until the 1990s that we had sufficient knowledge of the disease to allow for the emergence of treatment options⁵. One of the possible causes of AD is the abnormal accumulation of certain proteins in the brain⁶. Although we don’t know what causes the process to begin, we do know that the pathology begins 10-20 years before symptoms appear and care-seeking often doesn’t come until symptoms have progressed significantly to the latest stages.

There is currently a global effort underway to develop early detection protocols and operationalize treatment options as new studies shed light on lifestyle interventions and disease-modifying treatments. AD affects people all over the world. Therefore coordinating efforts and disseminating learnings is the key to expediting the early detection of symptoms, diagnosis, and treatment of Alzheimer’s disease.

Early detection of symptoms of AD becomes essential to lower the burden of AD as it facilitates timely access to lifestyle interventions. Early detection allows patients to benefit from non-medical interventions and lifestyle changes that can slow down the progression of the disease. Individuals can also benefit from making choices, planning for the future, or accessing clinical trials of new treatments⁷. Similarly, early detection of changes in the brain facilitates timely access to DMTs as these treatments are aimed at people in the early stages of the disease^8,9. Despite the evidence of the benefits of early detection, the care pathways to scale it up in health systems worldwide still need to be developed¹⁰. But DAC’s pilot program on early detection is starting to change that. Bridgeable has joined the efforts of DAC and other major healthcare organizations to prepare healthcare systems to build new care pathways for implementing early detection strategies. Learnings of this program are expected to guide the global scaling of early detection.

DAC & Bridgeable Collaboration

Scaling up the learnings from a global project like the pilot program on early detection requires a collaborative, evidence-based, and multi-phased approach. There are two main building blocks that have allowed the translation of the knowledge generated from this project into a usable resource for other organizations worldwide. One is the development of a Community of Practice (CoP) that has made the learning-sharing process more organic and effective among its members. The second is building on implementation science–an approach that aims to understand what hinders and facilitates the implementation of evidence-based interventions–to translate the rich learnings from the group into a durable toolkit.

Phase 1: Co-Designing the Community of Practice Engagement Model

The first step was to understand the group. We conducted background research to identify the most relevant components of a CoP model that would best support the group. Then, we carried out in-depth interviews with each key stakeholder in the group to understand their needs and incentives to participate in the CoP.

The main findings from this phase were the importance of designing mechanisms that accounted for people’s different cultural backgrounds, communication styles, and specific context-related challenges to allow all voices to be heard. Another insight was being intentional in acknowledging the commonalities across all the pilot sites and not focusing only on the differences. Also, being clear in terms of expectations of each member’s participation in the regular meetings and leveraging asynchronous communication to make efficient use of time–most of the group members are leaders in the AD space with multiple responsibilities and working from different time zones.

The second step was defining the CoP model. We synthesized the data collected into the first version of the engagement model and went through several iterations to incorporate the feedback from participating stakeholders. The final engagement model included the vision and purpose of the CoP and the group meetings’ scope, governance, and cadence. Bridgeable also developed a bespoke adaptation of an implementation science framework¹¹ to capture the CoP learnings and ensure that the right data was collected at the right time to make a durable and evidence-based toolkit in a subsequent phase.

Phase 2: Designing and Running CoP Laboratories (CoP Labs)

After co-designing an effective engagement model for the Community of Practice with the participants’ needs in mind, Bridgeable developed and facilitated two learning laboratories in an effort to collaborate on strengthening the group cohesiveness and capturing the group’s learnings and reflections from implementing an early detection strategy. Three groups of stakeholders attended and participated in the CoP laboratories: the DAC leadership team, the seven pilot sites: Brazil, Mexico, Scotland, US-Adventhealth, US-IU/IUHealth, Jamaica, and Japan, and several DAC funding partners.

The DAC CoP laboratories are collaborative hybrid workshops that engage multiple CoP stakeholders to strengthen the relationship between its members and consolidate their learnings when implementing the early detection pilot program. The CoP laboratories involved a set of interactive activities that enabled candid peer reflection and sharing of learnings and challenges. In addition, these activities enabled the collaborative development of an implementation roadmap that served as the building blocks of the toolkit.

Phase 3: Creating a Durable Toolkit

There have been three primary data sources that supported the development of the toolkit. First, the information gathered using the implementation science framework we adapted in order to capture key learnings, challenges, and strategies shared at the recurring meetings from the group. Second, in-depth interviews with each site team, and third, the insights obtained from the CoP Labs. We have been conducting a continuous implementation-focused synthesis to portray the main insights into a durable toolkit that is expected to guide the early detection efforts of other healthcare systems around the world.

The toolkit consists of two modules, one focused on the planning stage –everything that happens before providing early detection services to patients–and another about the actual implementation stage. When building the first module, we learned that when developing new care pathways, the complexity of the planning stage might be underestimated, but it is the foundation of a sustainable health system transformation. The planning stage is when health systems discover strengths and gaps they were unaware of and additional resources they need to gather.

The planning module has four components: key considerations per health system, planning steps, anticipated barriers, and resources. One of the challenges when developing a toolkit that aims to reach multiple types of health systems worldwide is making it relevant for everyone but maintaining a usable simplicity. During our synthesis, we identified that regardless of the health system, they all went through three main steps in their planning stage. What changed was how each system navigated those steps. The toolkit will be finalized later this year once the implementation of the DAC pilot program on early detection concludes.

Transforming health systems

Our work with the Davos Alzheimer’s Collaborative is equipped to help other health systems around the world in implementing early detection strategies and scaling the development of early detection of cognitive symptoms of Alzheimer’s disease. While transforming health systems to create new care pathways is a massive endeavour, we have found that one of the keys to sustaining and scaling change is designing mechanisms for genuine collaboration that enable sharing of high-quality learnings; and feeding these learnings into a tool that can guide and ease the way for other health systems in their efforts to transform care for Alzheimer’s disease and our global aging populations.

References

1 —Ball DE, et al. A framework for addressing Alzheimer’s disease: Without a frame, the work has no aim. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association. Alzheimer’s Association. 2022 Dec 8. https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.12869
2 —Fingers Brain Health Institute. 2021. https://fbhi.se/our-journey/
3 —Kivipelto M, et al. World-Wide FINGERS Network: A global approach to risk reduction and prevention of dementia. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association. Alzheimer’s Association. Vol. 16, Issue 7. July 2020 5. https://alz-journals.onlinelibrary.wiley.com/doi/full/10.1002/alz.12123
4 —Davos Alzheimer’s Collaborative. 2023. https://www.davosalzheimerscollaborative.org/
5 —Milestones, Research and Progress. Alzheimer’s Association. 2023. https://www.alz.org/alzheimers-dementia/research_progress/milestones#1990-1999
6 —Causes, Alzheimer’s Disease. National Health Service (NHS). 2021 July 05. https://www.nhs.uk/conditions/alzheimers-disease/causes/#:~:text=Alzheimer’s%20disease%20is%20thought%20to,form%20tangles%20within%20brain%20cells
7 —Rasmussen J, Langerman H. Alzheimer’s Disease – Why We Need Early Diagnosis. Degener Neurol Neuromuscul Dis. 2019 Dec 24. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6935598/
8 —Your questions, answered: What should Canadians know about lecanemab’s U.S. FDA approval?. Alzheimer Society of Canada. 2023 January 11. https://alzheimer.ca/en/whats-happening/news/lecanemab-leqembi-canada-fda
9 —What should Canadians know about aducanumab? Or Aduhelm?. Alzheimer Society of Canada. 2022. https://alzheimer.ca/en/about-dementia/how-can-i-treat-dementia/what-aducanumab
10 —Gauthier S, Rosa-Neto P, Morais JA, Webster C. World Alzheimer’s Report 2021: Journey through the diagnosis of dementia. Alzheimer’s Disease International. 2021 September. https://www.alzint.org/u/World-Alzheimer-Report-2021.pdf
11 —Damschroder LJ, Reardon CM, Widerquist MAO, et al. The updated Consolidated Framework for Implementation Research based on user feedback. Implementation Sci 17, 75. 2022 October 29. https://implementationscience.biomedcentral.com/articles/10.1186/s13012-022-01245-0