# Idea: medical hypotheses app for mysterious chronic illnesses

(This post is not up to my usual standards but I was encouraged to publish it anyway to get feedback on the idea.)

I have been [ill](https://www.greaterwrong.com/posts/DJk86FE29ad4vr5e9/riceissa-s-shortform/comment/NbjHFrBokqbbSvJZZ) for the past four years with a mysterious chronic illness. One of the things that I keep thinking would be nice to have (but as far as I know, doesn't exist) is some sort of symptom-tracking app that would allow me to test various hypotheses for my various symptoms.

I already do a simple version of this just in my head, for example, I can notice that if I stand for too long at a time it gets kind of aversive and sitting down makes me feel better. But it's hard to do this in my head for anything more complicated. What if eating cheese subtly helps with my breathing problem? It is not so easy to figure this out on my own.

The things that make it hard to detect connections between "things I do" and "how I feel":

*   delayed effects (maybe eating cheese helps with my breathing, but only on the following day, or maybe the effect builds up over time)
*   conjunctions/combinations of things (maybe I need to both eat cheese *and* exercise on the same day *and* avoid other dairy, in order to feel better in some way)
*   small effects, which are still good to notice because [sometimes you just need to do more of it](https://thezvi.wordpress.com/2017/12/02/more-dakka/)
*   it's also hard to come up with hypotheses yourself

Also, if the thing is something you've already tried in the past, it's good to make use of the data you already do have instead of running every single experiment after you generate the hypothesis.

As you live through chronic illness, you keep generating new data every day. You also, occasionally, come across new hypotheses. It would be nice if you can test each new hypothesis against all the data you already have.

The closest thing I know is the app [Bearable](https://bearable.app/), but the only "hypothesis" it seems to have is in the form of correlations of things that happen in a single day (e.g. "there is a such and such correlation between sleep duration and mood"), and the interface was so bad I couldn't keep using it.

Currently I just track my diet, medications, and symptoms in a bulleted list in Roam. This makes it possible to check for more hypotheses than by my intuition alone, but it's too difficult to search for all the relevant days and track effects. For instance if the hypothesis is "if I eat oatmeal then seven days later I will have breathing problems", I will have to find every single instance of when I ate oatmeal, and then by hand check how I was doing seven days later. So the symptoms and the interventions being machine-specifiable is important.

I suspect that this sort of thing may be useful for healthy people and in domains other than health, though I think the barrier is that most people who are not seriously ill do not have the motivation to collect so much data and track how they are feeling each day.

Won't this "fit" a lot of spurious hypotheses, especially if the hypotheses are auto-generated? (Or in other words, won't p-hacking/"correlation but not causation" type things will be a problem?) I think it might, especially if the number of times an intervention was tried is too few. But I don't think this will be a big problem for this app because as long as there are only a smallish number of viable hypotheses, I can just run the experiment later to test them. ("The app says I felt way better 3 days after eating watermelons, and this happened on two occasions? Well then, I guess I'll start eating watermelons for a while.") It may help to iteratively make the hypotheses more complicated, until one reaches the point of having just the right number of plausible hypotheses to play around with.

Some hypotheses are expensive to test so I won't have a way to check it with the existing data, e.g. right now I am testing the hypothesis "if I stop eating gluten then after 6 months various symptoms will be reduced". Prior to testing this I had eaten gluten on most days so there is no way to figure this out with my existing data. I don't think this app will be helpful for answering this kind of long-term question, though it will help with figuring out which interventions to run long-term experiments on.

Another problem is if I start to want to test things that I haven't been tracking so far. In my time being ill, I've started and stopped tracking various things based on some intuition about how likely that thing is to actually have some effect on how I feel.

A minimum viable product for me would have:

*   a way to track any sort of intervention, e.g. diet, medications, sleep, exercise
*   a way to track various environmental variables, e.g. temperature, air pressure, humidity, pollen level, exposure to other allergens
*   a way to track how I am doing in terms of each symptom
*   a way to write queries like "if I do intervention X and Y then after a delay of N days symptom Z gets better or worse" and test them against specific date ranges of the existing data