Heron

Anyone navigating life with a chronic condition knows their triggers, interventions, and symptoms fairly well. But they often don’t know exactly how their condition responds to specific variables — and that’s a problem.

The interfaces for personal health data — for both collection and interpretation — leave a lot to be desired. Yet this data is critical for those with chronic conditions to see how their personal health is responding to the variables in and outside of their control.

Without good visibility, it’s hard to improve health outcomes.

That’s what this research project is about: improving visibility into personal health data for those with chronic conditions in support of their efforts in self-management and self-advocacy. We want to see a world where individuals with chronic conditions can understand the important correlations within their personal health, make improvements in faster iterations, and advocate for improved support from healthcare and insurance providers.

So — who are we, and why are we doing this? Sarah is a researcher in bioethics, and Alexander is a researcher in human-computer interaction. This research project is a collaboration that sits at the intersection of our fields of study, but it’s also more personal than that. Sarah was diagnosed at the age of sixteen with Rheumatoid Arthritis (RA). Living with RA gives Sarah intimate insights into the problems this project aims to address, and into the outcomes of our experiments with possible solutions.

Our project will primarily consist of many iterations designing, building, and reviewing potential concepts for a personal health system.

We will publish research updates here as we go. Our first few posts will share some background on how we’re thinking about the problem and some hunches and experiments we’ll try out first. Then we’ll move into regular cycles iterating on the various experiments, and we’ll share what we find along the way.

We’ve found working in the open to help route key resources and intersecting work to our inboxes, and help spark guiding conversations. We will continue that tradition with this project to benefit from the knowledge of the commons as we go, and contribute to it, rather than working in silence and only publishing at the end. So — please don’t hesitate to reach out as you read along.

If you want to receive these updates via email when we post them, you can sign up at the top of this page.

Published March 19, 2024

Before we jump into our first experiment, we want to set some context on the problems our work aims to address.

Self-management and self-advocacy are essential for achieving positive health outcomes, particularly for individuals with chronic conditions.

Today’s healthcare landscape presents unique challenges for those with chronic conditions. It can take months for an initial appointment with a specialist, requiring immediate self-management Self-management is the process by which someone manages their disease(s), symptoms, treatment, and lifestyle for their self-determined quality of life. and self-advocacy Self-advocacy is the process by which someone expresses their experiences, concerns, needs, desires, and decisions to healthcare professionals, to improve their healthcare outcomes. while going untreated during the critical initial months of a disease’s progression.

During medical appointments, patients must quickly communicate a wide range of information with their doctors, often relying on memory to recall experiences and express health goals and preferences gathered over a long span of time.

Health insurance providers make the final decision on which medications and procedures will be approved and how they will be administered, requiring continued self-advocacy for the prescribed treatments to avoid a lapse in care.

Reviewing outcomes and reacting to problems only at doctor visits would greatly limit the number of adaptive strategies Adaptive strategies are changes made to therapeutic interventions and lifestyle. that can be implemented and evaluated each year. Chronic conditions require regular at-home experimentation with adaptive strategies to find potentially compounding improvements. This self-management is critical for anyone navigating life with a chronic condition.

Because of these constraints, self-management and self-advocacy are essential for achieving positive health outcomes.

Individuals with chronic conditions have limited access to meaningful data needed to enable transformative self-management and self-advocacy.

To make well-informed decisions, individuals with chronic conditions need to know how their condition responds to variables in and outside of their control. But the data that tells this story is not meaningfully accessible, if it’s recorded at all.

Medical information, including bloodwork and laboratory results, x-rays, and doctor's notes, is tucked inside electronic health records which are often illegible and difficult to access. Records of movement, diet, and sleep routine can be found in health tracking apps, if used. Various notes of side effects, aches and pains, or confusing symptoms are written in journals or recorded in note taking apps.

Data collection can be cumbersome and tedious for the individual, adding to the burden of disease management. Existing data is disparate and disconnected, making it nearly impossible to recognize and understand connections to inform adaptive strategies.

Unable to access meaningful data, individuals are not well-supported in their efforts to self-manage and self-advocate.

Personal technology harbors the potential to support individuals in search of positive health outcomes with new methods of data collection and interpretation.

Today’s technology landscape presents the potential for a very different story for how individuals with chronic conditions leverage data related to their personal health.

We envision a future in which such an individual can easily collect all relevant data in one place, and flexibly arrange visualizations that help discern possible answers to the questions they care most about. These visualizations give individuals an opportunity to actually “see” the data instead of relying on hunches or holding information solely in their memories. They’re able to experiment with and refine their adaptive strategies quickly, forming many small iterative cycles, the benefits of which compound. They can follow along with the outcomes of changes to their prescriptions, and find correlations between possible triggers and their symptoms. They are able to make more informed decisions, and advocate to their healthcare providers with clear data. And, as people with chronic conditions often rely on one another, better outcomes for one mean better outcomes for their network.

Such a future is feasible with today’s technology. But what’s needed now are new constructs for data collection purpose-built to work well within the context of someone’s life while navigating a chronic condition, and interfaces that are able to flexibly represent diverse data and the associations within it to answer individuals’ questions.

A focus on individuals with chronic conditions maximizes the potential impact.

As elaborated above, individuals with chronic conditions experience the challenges with today’s personal health landscape with more difficulty.

These individuals know their conditions intimately, as they’re often lifelong and affect every day activities. They understand aspects of their conditions that their doctors don’t see, requiring clear communication to help guide their doctor’s support.

These individuals are already engaging in daily adaptive strategies, big and small. This existing behavior can be supported with data that helps people more concretely, and more quickly, confirm positive health outcomes from changes to their adaptive strategies, and iterate on ineffective adaptations.

Individuals with chronic conditions dedicate a considerable portion of their time to their health with some individuals allocating up to two hours each day on activities associated with personal healthcare including treatments, medical appointments, health insurance claims, lifestyle interventions, and beyond. Jowsey, T., Yen, L. & W, P.M. Time spent on health related activities associated with chronic illness: a scoping literature review. BMC Public Health 12, 1044 (2012). https://doi.org/10.1186/1471-2458-12-1044. Given the time and cost of the many interactions with doctors, insurance providers, and pharmacists, and the mental and physical toll of the therapeutic interventions employed, there is a lot of room for little improvements to have a significant impact over the course of one’s life.

Six in ten US adults are living with chronic conditions, and 90 percent of the $4.1 trillion in annual health care expenditures About chronic diseases (2022) Centers for Disease Control and Prevention. https://www.cdc.gov/chronicdisease/about/index.htm. are for those with chronic and mental health conditions. This problem is vast, and so is the opportunity.

We believe that with better methods of data collection and interpretation, individuals with chronic conditions will be able to make more informed decisions, engage tighter feedback loops for compounding improvements, and advocate for themselves to receive improved support from healthcare providers.

Published March 21, 2024

In this project, we are experimenting with new software and hardware systems for personal health data collection and interpretation. We will work in quick, iterative cycles, building on what we learn as we go. We will engage one-on-one with individuals with chronic conditions to uncover the kinds of intimate insights that can only be found at this proximity.

Our iterations will seek answers to some core questions: How can data collection be made more empathetic and less obtrusive? How can more data be collected with less effort required by the individual? What methods increase the quantity and quality of data collected? How can data interpretation be made more flexible, so anyone can arrange data visualizations that surface meaningful answers to the questions that are most important to them?

The most important insights are the ones we will uncover through the course of our work with individuals in this project, although we do have some inclinations to inform our initial experiments. As individuals with chronic conditions already have to think about their conditions more than they’d like, we aim to reduce any added burdens to their day. We have some ways that we can begin experimenting with collecting meaningful data unobtrusively:

“No news is good news” — Some explorations in data collection expect individuals to log health outcomes frequently, otherwise leaving gaps in the data. Individuals with chronic conditions inherently think about their disease and symptoms more when their health is worse; because of this, we can experiment with an approach that presumes a certain baseline (e.g. neutral or positive) when logging doesn’t occur, reducing the burden placed on the individual.

In-context devices — Some explorations in data collection ping individuals requesting input at specific times each day, via text message, email, or push notification. These might arrive while an individual is not well-suited to be bothered with this kind of reflection. Instead, we can experiment with low-cost purpose-built devices that can be placed in appropriate contexts for regular input. For example, a small touchscreen device placed by the sink or in the closet where one prepares for the day could be used to provide the baseline measure of each day’s wellness without obtrusion into life experiences that should otherwise go undisturbed.

Time-aligned data visualizations — Bringing together independent data that’s related by time is a simple but effective way to allow people to find connections they need to answer their key questions. We’ve previously explored this concept, in LN 038: Semantic zoom. This inclination is not well-supported by today’s landscape of apps, which silo their particular domain of data, and further experimentation needs to be done with the interactions used.

Data providers — What data is already generated everyday that can be used to glean important insights without the need for any additional data entry? Some examples: weather forecasts, meetings and travel in calendar events, activities from photos, time spent typing or on the computer, and additional metrics from mobile phones and wearables such as distance walked or hours slept. Further, what unstructured data about an individual’s day can be transformed into structured data?

A focus on self-empowerment — An interface that focuses solely on how bad someone feels won’t be used for long. In order to be a durable tool in someone’s life, it needs to be empowering; it needs to support the outcomes an individual most wants to see, and reinforce their hopes and progress.

No prescribed changes or judgments — What we build will not push individuals to engage in any prescribed behavior changes. In reviewing prior art, we found many examples of health apps and research prototypes that strive to promote specific behavior changes, such as increased exercise or changes to diet. But the landscape for individuals with chronic conditions has many particulars. Every condition is different, and how each body responds to variables is different too. Our project will not make judgments or motivate any prescribed changes. Rather, our project specifically aims to empower individuals with an improved, data-supported understanding of their condition(s); to put the power in the hands of the individual to self-manage and self-advocate for their desired quality of life.

Published March 25, 2024

Development for the first cycle is underway. Check back soon for our next project updates.