Healthcare systems are products of design. Therefore, improving healthcare systems and their outcomes requires smart, thoughtful decisions about how to improve their design. To do this, we must start with the people whom the systems serve.
Atlas of Caregiving’s founder and CEO, Rajiv Mehta, plays an active role in improving healthcare system design through deep research and collaboration with others who share the same mission. Mehta and collaborator John Chaffins recently studied the cystic fibrosis (CF) community, patients and professionals, for Cincinnati Childrens Hospital and the Cystic Fibrosis Foundation. Their report Cystic Fibrosis (CF) Ecology Model offers an important illustration offers an important illustration of what Atlas’s Core Research looks like in practice.
CF is an especially demanding chronic condition that requires extensive care and treatment throughout the patient’s lifetime. Advancements in treatment options and better access to healthcare overall have substantially increased the life expectancy of patients with CF over the course of a single generation. Increased life expectancies for CF and other chronic illnesses are, no doubt, a major achievement of modern medical science; however, the ability of systems to adapt to changes like these have not always been as impressive. The vast networks of caregivers, doctors, researchers, nurses, etc. who contribute to CF patient care are complex and not always in perfect sync with one another, which limits the knowledge available for treating the disease, particularly in patients further along in life.
The CF Ecology Model report was conceived after the Collaborative Chronic Care Network (C3N) developed a similar research initiative for IBD. Based on that report’s success, C3N launched two additional research initiatives for Cysitic Fibrosis and Type 1 Diabetes. By incorporating empirical research and data collection with theoretical models about collaboration and the transmission of knowledge in healthcare networks, it plays an important role in changing the way that healthcare systems are innovated to meet the needs of patients and caregivers.
The Cystic Fibrosis Ecology Model
The Cystic Fibrosis Ecology Model is the product of a 2015 research initiative carried out by the Collaborative Chronic Care Network (C3N) at Cincinnati Children’s Hospital Medical Center (CCHMC) and the Cystic Fibrosis Foundation (CFF). The model’s purpose is to contribute to understanding about the current state of CF care as it relates to the types of people affected by it, including, patients, family members, health practitioners, researchers, etc. Through insight into the personas and burdens of those dealing with CF, the model ultimately hopes to promote better decision making and create better experiences and outcomes for people living with CF.
Summary of the model
Research for the model follows the philosophy of Goal Directed Design (GDD). GDD is a user-centered approach to product development that is premised upon the belief that the best way to improve a product or process is to help members of the relevant ecosystem achieve their goals. In order to do this, research must first identify who the relevant members of a given ecosystem are and their corresponding goals.
Following this approach, researchers for the Ecology Model used tools from ethnography to investigate the CF ecosystem and understand the goals and corresponding behaviors and actions of its members. One of the main components of the study was ethnographic interviews. The research team conducted interviews with people with CF and their family members and caregivers; CF professionals including, physicians, medical researchers, nurse practitioners, and social workers; and other stakeholders from the CFF team.
Ultimately, these ethnographic studies resulted in the development of a set of personas based on clustered traits of actual interview participants. Detailed narratives were created for each persona. The narratives are meant to outline the common goals, attitudes, and behaviors exhibited by each persona while making them relatable to other members of the CF ecosystem based on their own experiences in the ecosystem.
Personas can be thought of as archetypes. Each one represents a type of person living with or affected by CF. The theory is that by understanding the archetypes better, more comprehensive – and more effective systems – can be designed to meet the needs of the people that they each represent. Using personas helps set clear design targets since the specific needs and goals of affected individuals are well-defined based on shared traits.
The CF Ecology Model report identifies ten different personas based on interviews with 31 individuals and some additional observations of clinical visits. By no means are the personas outlined in the report meant to be exhaustive. The CF Ecology Model report lays the foundation for implementing personas into healthcare systems design and provides a start for using personas and GDD in the cystic fibrosis ecosystem specifically, while acknowledging that more work needs to be done to address types of members not thoroughly represented so far.
Specific examples of personas included in the CF Ecology Model report include: Olivia Davis, an 11-year-old girl with CF whose goal is to keep up with her same-age cousins and avoid hospitalization; Tina Davis, the mother of Olivia whose goal is to keep her daughter as healthy as possible and away from the complications of CF while staying informed of treatment advancements and the CF research pipeline; Amanda Matthews, a 25-year-old woman with CF who wants to make the most of whatever time she has and be independent; and Dr. Reymond Hernandez who wants to help patients understand their disease and the risks of alternative treatments and find more balance in his busy schedule.
Following the development of personas, the CF Ecology Model report also proposes a Care Burden Characteristics Model. This model functions to characterize common burdens imposed by CF. Researchers identified seven different categories of burdens:
Once categories of burdens are identified, it is possible to assign specific details from the narratives of a persona to a category of burden.
For example, Tina Davis spends hours a month on the phone with insurance companies discussing pre-authorizations and trying to understand bills which is a burden of administrative requirements. Understanding different types of burdens clarifies the process of evaluating innovations in healthcare. Because most innovations are, by nature, limited in scope, they may only improve one burden. Typifying burdens makes it easier to predict how the ecosystem will be impacted by a change and to weigh relevant tradeoffs.
An innovation to improve one burden may negatively impact another. For example, a new treatment plan that effectively reduces the impact of disease symptoms may require so much paperwork to obtain approval from the patient’s insurance company that the increased administrative burden outweighs the improvements elsewhere.
Motivated by the philosophy that a problem must be well-understood before an effective solution can be developed, the CF Ecology Model report is meant to provide a starting point for continued brainstorming and experimentation with new interventions. Overall, the CF Ecology Model report combines the use of personas and the Care Burden Characteristics Model to create a set of optimally useful tools to be used by the CF learning health network.
The CF Ecology Model report in the current landscape of chronic care
By contributing knowledge and information to the CF Learning Network, the CF Ecology Model report is part of a movement to change healthcare system design through collaboration among patients, parents/caregivers, doctors, and researchers. C3N works as a Collaborative Innovation Network, or COIN. These networks approach innovation as a process that requires a mix of skillsets and expertise. By bringing together visionaries, experts, patients, and caregivers, C3N hopes to provide better outcomes for those suffering from chronic illness.
Similarly, C3N also fits the description of a learning healthcare system. The Institute of Medicine defines a learning healthcare system as a system in which “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.” C3N has so far worked on developing models for chronic illnesses such as Crohn’s disease and ulcerative colitis. The CF Ecology Model report brings C3N and its already established tools into the cystic fibrosis ecosystem.
The collection and effective transmission of knowledge between the parties involved is a crucial component of learning health systems and networks. The CF Ecology Model report focuses on exactly this component. By embracing the importance of information and a thorough understanding of the problems and shortcomings of current healthcare systems, ecology models, like the one for cystic fibrosis, provide valuable starting points for projects like C3N to take action on. Ultimately, this benefits the process of innovation and improves outcomes for patients with chronic illness.
Atlas of Caregiving’s role in building knowledge
Atlas of Caregiving believes that without deep, contextual knowledge of the day-to-day experience of patients and family caregivers, it will be difficult to address the critical challenges that lie ahead in developing innovations for chronic care. The development of the CF Ecology Model report fits well within Atlas’s mission to employ innovative research, practical solutions, and rich collaboration to transform current systems intended to support family caregivers.
In studying the everyday practice of family caregiving, Atlas recognizes that every family’s situation is unique. Applying models like personas and care burden characteristics to synthesize and distill information and knowledge about the situations of caregivers and the people they care for promotes the development of contextual solutions to current problems in family caregiving.
Collaboration with caregiver communities is also key to making family caregiving more effective. These communities may include doctors, researchers, nurses, and social workers, among others. The CF Ecology Model report encourages and depends on this collaboration while also requiring a systems approach to remaining flexible to ever changing needs.