Beware “too much” and “too little” advice in Exocrine Pancreatic Insufficiency (EPI / PEI)

If I had a nickel every time I saw conflicting advice for people with EPI, I could buy (more) pancreatic enzyme replacement therapy. (PERT is expensive, so it’s significant that there’s so much conflicting advice).

One rule of thumb I find handy is to pause any time I see the words “too much” or “too little”.

This comes up in a lot of categories. For example, someone saying not to eat “too much” fat or fiber, and that a low-fat diet is better. The first part of the sentence should warrant a pause (red flag words – “too much”), and that should put a lot of skepticism on any advice that follows.

Specifically on the “low fat diet” – this is not true. A lot of outdated advice about EPI comes from historical research that no longer reflects modern treatment. In the past, low-fat diets were recommended because early enzyme formulations were not encapsulated or as effective, so people in the 1990s struggled to digest fat because the enzymes weren’t correctly working at the right time in their body. The “bandaid” fix was to eat less fat. Now that enzyme formulations are significantly improved (starting in the early 2000s, enzymes are now encapsulated so they get to the right place in our digestive system at the right time to work on the food we eat or drink), medical experts no longer recommend low-fat diets. Instead, people should eat a regular diet and adjust their enzyme intake accordingly to match that food intake, rather than the other way around (source: see section 4.6).

Think replacement of enzymes, rather than restriction of dietary intake: the “R” in PERT literally stands for replacement!

If you’re reading advice as a person with EPI (PEI), you need to have math in the back of your mind. (Sorry if you don’t like math, I’ll talk about some tools to help).

Any time people use words to indicate amounts of things, whether that’s amounts of enzymes or amounts of food (fat, protein, carbs, fiber), you need to think of specific numbers to go with these words.

And, you need to remember that everyone’s body is different, which means your body is different.

Turning words into math for pill count and enzymes for EPI

Enzyme intake should not be compared without considering multiple factors.

The first reason is because enzyme pills are not all the same size. Some prescription pancreatic enzyme replacement therapy (PERT) pills can be as small as 3,000 units of lipase or as large as 60,000 units of lipase. (They also contain thousands or hundreds of thousands of units of protease and amylase, to support protein and carbohydrate digestion. For this example I’ll stick to lipase, for fat digestion.)

If a person takes two enzyme pills per meal, that number alone tells us nothing. Or rather, it tells us only half of the equation!

The size of the pills matters. Someone taking two 10,000-lipase pills consumes 20,000 units per meal, while another person taking two 40,000-lipase pills is consuming 80,000 units per meal.

That is a big difference! Comparing the two total amounts of enzymes (80,000 units of lipase or 20,000 units of lipase) is a 4x difference.

And I hate to tell you this, but that’s still not the entire equation to consider. Hold on to your hat for a little more math, because…

The amount of fat consumed also matters.

Remember, enzymes are used to digest food. It’s not a magic pill where one (or two) pills will perfectly cover all food. It’s similar to insulin, where different people can need different amounts of insulin for the same amount of carbohydrates. Enzymes work the same way, where different people need different amounts of enzymes for the same amount of fat, protein, or carbohydrates.

And, people consume different amounts and types of food! Breakfast is a good example. Some people will eat cereal with milk – often that’s more carbs, a little bit of protein, and some fat. Some people will eat eggs and bacon – that’s very little carbs, a good amount of protein, and a larger amount of fat.

Let’s say you eat cereal with milk one day, and eggs and bacon the next day. Taking “two pills” might work for your cereal and milk, but not your eggs and bacon, if you’re the person with 10,000 units of lipase in your pill. However, taking “two pills” of 40,000 units of lipase might work for both meals. Or not: you may need more for the meal with higher amounts of fat and protein.

If someone eats the same quantity of fat and protein and carbs across all 3 meals, every day, they may be able to always consume the same number of pills. But for most of us, our food choices vary, and the protein and fat varies meal to meal, so it’s common to need different amounts at different meals. (If you want more details on how to figure out how much you need, given what you eat, check out this blog post with example meals and a lot more detail.)

You need to understand your baseline before making any comparisons

Everyone’s body is different, and enzyme needs vary widely depending on the amount of fat and protein consumed. What is “too much” for one person might be exactly the right amount for another, even when comparing the same exact food quantity. This variability makes it essential to understand your own baseline rather than following generic guidance. The key is finding what works for your specific needs rather than focusing on an arbitrary notion of “too much”, because “too much” needs to be compared to specific numbers that can be compared as apples to apples.

A useful analogy is heart rate. Some people have naturally higher or lower resting heart rates. If someone tells you (that’s not a doctor giving you direct medical advice) that your heart rate is too high, it’s like – what can you do about it? It’s not like you can grow your heart two sizes (like the Grinch). While fitness and activity can influence heart rate slightly, individual baseline differences remain significant. If you find yourself saying “duh, of course I’m not going to try to compare my heart rate to my spouse’s, our bodies are different”, that’s a GREAT frame of mind that you should apply to EPI, too.

(Another example is respiratory rate, where it varies person to person. If someone is having trouble breathing, the solution is not as simple as “breathe more” or “breathe less”—it depends on their normal range and underlying causes, and it takes understanding their normal range to figure out if they are breathing more or less than their normal, because their normal is what matters.)

If you have EPI, fiber (and anything else) also needs numbers

Fiber also follows this pattern. Some people caution against consuming “too much” fiber, but a baseline level is essential. “Too little” fiber can mimic EPI symptoms, leading to soft, messy stools. Finding the right amount of fiber is just as crucial as balancing fat and protein intake.

If you find yourself observing or hearing comments that you likely consume “too much” fiber – red flag check for “too much!” Similar to if you hear/see about ‘low fiber’. Low meaning what number?

You should get an estimate for how much you are consuming and contextualize it against the typical recommendations overall, evaluate whether fiber is contributing to your issues, and only then consider experimenting with it.

(For what it’s worth, you may need to adjust enzyme intake for fat/protein first before you play around with fiber, if you have EPI. Many people are given PERT prescriptions below standard guidelines, so it is common to need to increase dosing.)

For example, if you’re consuming 5 grams of fiber in a day, and the typical guidance is often for 25-30 grams (source, varies by age, gender and country so this is a ballpark)…. you are consuming less than the average person and the average recommendation.

In contrast, if you’re consuming 50+ grams of fiber? You’re consuming more than the average person/recommendation.

Understanding where you are (around the recommendation, quite a bit below, or above?) will then help you determine whether advice for ‘more’ or ‘less’ is actually appropriate in your case. Most people have no idea what you’re eating – and honestly, you may not either – so any advice for “too much”, “too little”, or “more” or “less” is completely unhelpful without these numbers in mind.

You don’t have to tell people these numbers, but you can and should know them if you want to consider evaluating whether YOU think you need more/less compared to your previous baseline.

How do you get numbers for fiber, fat, protein, and carbohydrates?

Instead of following vague “more” or “less” advice, first track your intake and outcomes.

If you don’t have a good way to estimate the amount of fat, protein, carbohydrates, and/or fiber, here’s a tool you can use – this is a Custom GPT that is designed to give you back estimates of fat, protein, carbohydrates, and fiber.

You can give it a meal, or a day’s worth of meals, or several days, and have it generate estimates for you. (It’s not perfect but it’s probably better than guessing, if you’re not familiar with estimating these macronutrients).

If you don’t like or can’t access ChatGPT (it works with free accounts, if you log in), you can also take this prompt, adjust it how you like, and give it to any free LLM tool you like (Gemini, Claude, etc.):

You are a dietitian with expertise in estimating the grams of fat, protein, carbohydrate, and fiber based on a plain language meal description. For every meal description given by the user, reply with structured text for grams of fat, protein, carbohydrates, and fiber. Your response should be four numbers and their labels. Reply only with this structure: “Fat: X; Protein: Y; Carbohydrates: Z; Fiber; A”. (Replace the X, Y, Z, and A with your estimates for these macronutrients.). If there is a decimal, round to the nearest whole number. If there are no grams of any of the macronutrients, mark them as 0 rather than nil. If the result is 0 for all four variables, please reply to the user: “I am unable to parse this meal description. Please try again.”

If you are asked by the user to then summarize a day’s worth of meals that you have estimated, you are able to do so. (Or a week’s worth). Perform the basic sum calculation needed to do this addition of each macronutrient for the time period requested, based on the estimates you provided for individual meals.

Another option is using an app like PERT Pilot. PERT Pilot is a free app for iOS for people with EPI that requires no login or user account information, and you can put in plain language descriptions of meals (“macaroni and cheese” or “spaghetti with meatballs”) and get back the estimates of fat, protein, and carbohydrates, and record how much enzymes you took so you can track your outcomes over time. (Android users – email me at Dana+PERTPilot@OpenAPS.org if you’d like to test the forthcoming Android version!) Note that PERT Pilot doesn’t estimate fiber, but if you want to start with fat/protein estimates, PERT Pilot is another way to get started with seeing what you typically consume. (For people without EPI, you can use Carb Pilot, another free iOS app that similarly gives estimates of macronutrients.)

Beware advice of "more" or "less" that is vague and non-numeric (not a number) unless you know your baseline numbers in exocrine pancreatic insufficiency. A blog by Dana M. Lewis from DIYPS.orgTL;DR: Instead of arbitrarily lowering or increasing fat or fiber in the diet, measure and estimate what you are consuming first. If you have EPI, assess fat digestion first by adjusting enzyme intake to minimize symptoms. (And then protein, especially for low fat / high protein meals, such as chicken or fish.) Only then consider fiber intake—some people may actually need more fiber rather than less than what they were consuming before if they experience mushy stools. Remember the importance of putting “more” or “less” into context with your own baseline numbers. Estimating current consumption is crucial because an already low-fiber diet may be contributing to the problem, and reducing fiber further could make things worse. Understanding your own baseline is the key.

You Can Create Your Own Icons (and animated gifs)

Over the years, I’ve experimented with different tools for making visuals. Some of them are just images but in the last several years I’ve made more animations, too.

But not with any fancy design program or purpose built tool. Instead, I use PowerPoint.

Making animated gifs

I first started using PowerPoint to create gifs around 2018 or 2019. At the time, PowerPoint didn’t have a built-in option to export directly to GIF format, so I had to export animations as a movie file first and then use an online converter to turn them into a GIF. Fortunately, in recent years, PowerPoint has added a direct “Export as GIF” feature.

The process of making an animated GIF in PowerPoint is similar to adding animations or transitions in a slide deck for a presentation. I’ve used this for various projects, including:

Am I especially trained? No. Do I feel like I have design skills? No.

Elbow grease and determination to try is what I have, with the goal of trying to use visuals to convey information as a summary or to illustrate a key point to accompany written text. (I also have a tendency to want to be a perfectionist, and I have to consciously let that go and let “anything is better than nothing” guide my attempts.)

Making icons is possible, too

Beyond animations, I’ve also used PowerPoint to create icons and simple logo designs.

I ended up making the logos for Carb Pilot (a free iOS app that enables you to track the macronutrients of your choice) and PERT Pilot (a free iOS app that enables people with exocrine pancreatic insufficiency, known as EPI or PEI, to track their enzyme intake) using PowerPoint.

This, and ongoing use of LLMs to help me with coding projects like these apps, is what led me to the realization that I can now make icons, too.

I was working to add a widget to Carb Pilot, so that users can have a widget on the home screen to more quickly enter meals without having to open the app and then tap; this saves a click every time. I went from having it be a single button to having 4 buttons to simulate the Carb Pilot home screen. For the “saved meals” button, I wanted a list icon, to indicate the list of previous meals. I went to SF Symbols, Apple’s icon library, and picked out the list icon I wanted to use, and referenced it in XCode. It worked, but it lacked something.

A light purple iOS widget with four buttons - top left is blue and says AI: top right is purple with a white microphone icon; bottom left is periwinkle blue with a white plus sign icon; bottom right is bright green with a custom list icon, where instead of bullets the three items are an apple, cupcake, and banana mini-icons. It occurred to me that maybe I could tweak it somehow and make the bullets of the list represent food items. I wasn’t sure how, so I asked the LLM if it was possible. Because I’ve done my other ‘design’ work in PowerPoint, I went there and quickly dropped some shapes and lines to simulate the icon, then tested exporting – yes, you can export as SVG! I spent a few more minutes tweaking versions of it and exporting it. It turns out, yes, you can export as SVG, but then the way I designed it wasn’t really suited for SVG use. When I had dropped the SVG into XCode, it didn’t show up. I asked the LLM again and it suggested trying PNG format. I exported the icon from powerpoint as PNG, dropped it into XCode, and it worked!

(That was a good reminder that even when you use the “right” format, you may need to experiment to see what actually works in practice with whatever tools you’re using, and not let the first failure be a sign that it can’t work.)

Use What Works

There’s a theme you’ll be hearing from me: try and see what works. Just try. You don’t know if you don’t try. With LLMs and other types of AI, we have more opportunities to try new and different things that we may not have known how to do before. From coding your own apps to doing data science to designing custom icons, these are all things I didn’t know how to do before but now I can. A good approach is to experiment, try different things (and different prompts), and not be afraid to use “nontraditional” tools for projects, creative or otherwise. If it works, it works!

Facing Uncertainty with AI and Rethinking What If You Could?

If you’re feeling overwhelmed by the rapid development of AI, you’re not alone. It’s moving fast, and for many people the uncertainty of the future (for any number of reasons) can feel scary. One reaction is to ignore it, dismiss it, or assume you don’t need it. Some people try it once, usually on something they’re already good at, and when AI doesn’t perform better than they do, they conclude it’s useless or overhyped, and possibly feel justified in going back to ignoring or rejecting it.

But that approach misses the point.

AI isn’t about replacing what you already do well. It’s about augmenting what you struggle with, unlocking new possibilities, and challenging yourself to think differently, all in the pursuit of enabling YOU to do more than you could yesterday.

One of the ways to navigate the uncertainty around AI is to shift your mindset. Instead of thinking, “That’s hard, and I can’t do that,” ask yourself, “What if I could do that? How could I do that?”

Sometimes I get a head start by asking an LLM just that: “How would I do X? Layout a plan or outline an approach to doing X.” I don’t always immediately jump to doing that thing, but I think about it, and probably 2 out of 3 times, laying out a possible approach means I do come back to that project or task and attempt it at a later time.

Even if you ultimately decide not to pursue something because of time constraints or competing priorities, at least you’ve explored it and possibly learned something even in the initial exploration about it. But, I want to point out that there’s a big difference between legitimately not being able to do something and choosing not to. Increasingly, the latter is what happens, where you may choose not to tackle a task or take on a project: this is very different from not being able to do so.

Finding the Right Use Cases for AI

Instead of testing AI on things you’re already an expert in, try applying it to areas where you’re blocked, stuck, overwhelmed, or burdened by the task. Think about a skill you’ve always wanted to learn but assumed was out of reach. Maybe you’ve never coded before, but you’re curious about writing a small script to automate a task. Maybe you’ve wanted to design a 3D-printed tool to solve a real-world problem but didn’t know where to start. AI can be a guide, an assistant, and sometimes even a collaborator in making these things possible.

For example, I once thought data science was beyond my skill set. For the longest time, I couldn’t even get Jupyter Notebooks to run! Even with expert help, I was clearly doing something silly and wrong, but it took a long time and finally LLM assistance to get step by step and deeper into sub-steps to figure out the step that was never in the documentation or instructions that I was missing – and I finally figured it out! From there, I learned enough to do a lot of the data science work on my own projects. You can see that represented in several recent projects. The same thing happened with iOS development, which I initially felt imposter syndrome about. And this year, after FOUR failed attempts (even 3 using LLMs), I finally got a working app for Android!

Each time, the challenge felt enormous. But by shifting from “I can’t” to “What if I could?” I found ways to break through. And each time AI became a more capable assistant, I revisited previous roadblocks and made even more progress, even when it was a project (like an Android version of PERT Pilot) I had previously failed at, and in that case, multiple times.

Revisiting Past Challenges

AI is evolving rapidly, and what wasn’t possible yesterday might be feasible today. Literally. (A great example is that I wrote a blog post about how medical literature seems like a game of telephone and was opining on AI-assisted tools to aid with tracking changes to the literature over time. The day I put that blog post in the queue, OpenAI announced their Deep Research tool, which I think can in part address some of the challenges I talked about currently being unsolved!)

One thing I have started to do that I recommend is keeping track of problems or projects that feel out of reach. Write them down. Revisit them every few months, and explore them with the latest LLM and AI tools. You might be surprised at how much has changed, and what is now possible.

Moving Forward with AI

You don’t even have to use AI for everything. (I don’t.) But if you’re not yet in the habit of using AI for certain types of tasks, I challenge you to find a way to use an LLM for *something* that you are working on.

A good place to insert this into your work/projects is to start noting when you find yourself saying or thinking “this is the way we/I do/did things”.

When you catch yourself thinking this, stop and ask:

  • Does it have to be done that way? Why do we think so?
  • What are we trying to achieve with this task/project?
  • Are there other ways we can achieve this?
  • If not, can we automate some or more steps of this process? Can some steps be eliminated?

You can ask yourself these questions, but you can also ask these questions to an LLM. And play around with what and how you ask (the prompt, or what you ask it, makes a difference).

One example for me has been working on a systematic review and meta analysis of a medical topic. I need to extract details about criteria I am analyzing across hundreds of papers. Oooph, big task, very slow. The LLM tools aren’t yet good about extracting non-obvious data from research papers, especially PDFs where the data I am interested may be tucked into tables, figure captions, or images themselves rather than explicitly stated as part of the results section. So for now, that still has to be manually done, but it’s on my list to revisit periodically with new LLMs.

However, I recognized that the way I was writing down (well, typing into a spreadsheet) the extracted data was burdensome and slow, and I wondered if I could make a quick simple HTML page to guide me through the extraction, with an output of the data in CSV that I could open in spreadsheet form when I’m ready to analyze. The goal is easier input of the data with the same output format (CSV for a spreadsheet). And so I used an LLM to help me quickly build that HTML page, set up a local server, and run it so I can use it for data extraction. This is one of those projects where I felt intimidated – I never quite understood spinning up servers and in fact didn’t quite understand fundamentally that for free I can “run” “a server” locally on my computer in order to do what I wanted to do. So in the process of working on a task I really understood (make an HTML page to capture data input), I was able to learn about spinning up and using local servers! Success, in terms of completing the task and learning something I can take forward into future projects.

Another smaller recent example is when I wanted to put together a simple case report for my doctor, summarizing symptoms etc, and then also adding in PDF pages of studies I was referencing so she had access to them. I knew from the past that I could copy and paste the thumbnails from Preview into the PDF, but it got challenging to be pasting 15+ pages in as thumbnails and they were inserting and breaking up previous sections, so the order of the pages was wrong and hard to fix. I decided to ask my LLM of choice if it was possible to automate compiling 4 PDF documents via a command line script, and it said yes. It told me what library to install (and I checked this is an existing tool and not a made up or malicious one first), and what command to run. I ran it, it appended the PDFs together into one file the way I wanted, and it didn’t require the tedious hand commands to copy and paste everything together and rearrange when the order was messed up.

The more I practice, the easier I find myself switching into the habit of saying “would it be possible to do X” or “Is there a way to do Y more simply/more efficiently/automate it?”. That then leads to portions which I can decide to implement, or not. But it feels a lot better to have those on hand, even if I choose not to take a project on, rather than to feel overwhelmed and out of control and uncertain about what AI can do (or not).

Facing uncertainty with AI and rethinking "What if you could?", a blog post by Dana M. Lewis on DIYPS.orgIf you can shift your mindset from fear and avoidance to curiosity and experimentation, you might discover new skills, solve problems you once thought were impossible, and open up entirely new opportunities.

So, the next time you think, “That’s too hard, I can’t do that,” stop and ask:

“What if I could?”

If you appreciated this post, you might like some of my other posts about AI if you haven’t read them.

How Medical Research Literature Evolves Over Time Like A Game of Telephone

Have you ever searched for or through medical research on a specific topic, only to find different studies saying seemingly contradictory things? Or you find something that doesn’t seem to make sense?

You may experience this, whether you’re a doctor, a researcher, or a patient.

I have found it helpful to consider that medical literature is like a game of telephone, where a fact or statement is passed from one research paper to another, which means that sometimes it is slowly (or quickly!) changing along the way. Sometimes this means an error has been introduced, or replicated.

A Game of Telephone in Research Citations

Imagine a research study from 2016 that makes a statement based on the best available data at the time. Over the next few years, other papers cite that original study, repeating the statement. Some authors might slightly rephrase it, adding their own interpretations. By 2019, newer research has emerged that contradicts the original statement. Some researchers start citing this new, corrected information, while others continue citing the outdated statement because they either haven’t updated their knowledge or are relying on older sources, especially because they see other papers pointing to these older sources and find it easiest to point to them, too. It’s not necessarily made clear that this outdated statement is now known to be incorrect. Sometimes that becomes obvious in the literature and field of study, and sometimes it’s not made explicit that the prior statement is ‘incorrect’. (And if it is incorrect, it doesn’t become known as incorrect until later – at the time it’s made, it’s considered to be correct.) 

By 2022, both the correct and incorrect statements appear in the literature. Eventually, a majority of researchers transition to citing the updated, accurate information—but the outdated statement never fully disappears. A handful of papers continue to reference the original incorrect fact, whether due to oversight, habit (of using older sources and repeating citations for simple statements), or a reluctance to accept new findings.

The gif below illustrates this concept, showing how incorrect and correct statements coexist over time. It also highlights how researchers may rely on citations from previous papers without always checking whether the original information was correct in the first place.

Animated gif illustrating how citations branch off and even if new statements are introduced to the literature, the previous statement can continue to appear over time.

This is not necessarily a criticism of researchers/authors of research publications (of which I am one!), but an acknowledgement of the situation that results from these processes. Once you’ve written a paper and cited a basic fact (let’s imagine you wrote this paper in 2017 and cite the 2016 paper and fact), it’s easy to keep using this citation over time. Imagine it’s 2023 and you’re writing a paper on the same topic area, it’s very easy to drop the same citation from 2016  in for the same basic fact, and you may not think to consider updating the citation or check if the fact is still the fact.

Why This Matters

Over time, a once-accepted “fact” may be corrected or revised, but older statements can still linger in the literature, continuing to influence new research. Understanding how this process works can help you critically evaluate medical research and recognize when a widely accepted statement might actually be outdated—or even incorrect.

If you’re looking into a medical topic, it’s important to pay attention not just to what different studies say, but also when they were published and how their key claims have evolved over time. If you notice a shift in the literature—where newer papers cite a different fact than older ones—it may indicate that scientific understanding has changed.

One useful strategy is to notice how frequently a particular statement appears in the literature over time.

Whenever I have a new diagnosis or a new topic to research on one of my chronic diseases, I find myself doing this.

I go and read a lot of abstracts and research papers about the topic; I generally observe patterns in terms of key things that everyone says, which establishes what the generally understood “facts” are, and also notice what is missing. (Usually, the question I’m asking is not addressed in the literature! But that’s another topic…)

I pay attention to the dates, observing when something is said in papers in the 1990s and whether it’s still being repeated in the 2020s era papers, or if/how it’s changed. In my head, I’m updating “this is what is generally known” and “this doesn’t seem to be answered in the literature (yet)” and “this is something that has changed over time” lists.

Re-Evaluating the Original ‘Fact’

In some cases, it turns out the original statement was never correct to begin with. This can happen when early research is based on small sample sizes, incomplete data, or incorrect assumptions. Sometimes that statement was correct, in context, but taken out of context immediately and this out of context use was never corrected. 

For example, a widely cited statement in medical literature once claimed that chronic pancreatitis is the most common cause of exocrine pancreatic insufficiency (EPI). This claim was repeated across numerous papers, reinforcing it as accepted knowledge. However, a closer examination of population data shows that while chronic pancreatitis is a known co-condition of EPI, it is far less common than diabetes—a condition that affects a much larger population and is also strongly associated with EPI. Despite this, many papers still repeat the outdated claim without checking the original data behind it.

(For a deeper dive into this example, you can read my previous post here. But TL;DR: even 80% of .03% is a smaller number than 10% of 10% of the overall population…so it is not plausible that CP is the biggest cause of EPI/PEI.)

Stay Curious

This realization can be really frustrating, because if you’re trying to do primary research to help you understand a topic or question, how do you know what the truth is? This is peer-reviewed research, but what this shows us is that the process of peer-review and publishing in a journal is not infallible. There can be errors. The process for updating errors can be messy, and it can be hard to clean up the literature over time. This makes it hard for us humans – whether in the role of patient or researcher or clinician – to sort things out.

But beyond a ‘woe is me, this is hard’ moment of frustration, I do find that this perspective of literature as a process of telephone makes me a better reader of the literature and forces me to think more critically about what I’m reading, and take papers in context of the broader landscape of literature and evolving knowledge base. It helps remove the strength I would otherwise be prone to assigning any one paper (and any one ‘fact’ or finding from a single paper), and encourages me to calibrate this against the broader knowledge base and the timeline of this knowledge base.

That can also be hard to deal with personally as a researcher/author, especially someone who tends to work in the gaps, establishing new findings and facts and introducing them to the literature. Some of my work also involves correcting errors in the literature, which I find from my outsider/patient perspective to be obvious because I’ve been able to use fresh eyes and evaluate at a systematic review level/high level view, without being as much in the weeds. That means my work, to disseminate new or corrected knowledge, is even more challenging. It’s also challenging personally as a patient, when I “just” want answers and for everything to already be studied, vetted, published, and widely known by everyone (including me and my clinician team).

But it’s usually not, and that’s just something I – and we – have to deal with. I’m curious as to whether we will eventually develop tools with AI to address this. Perhaps a mini systematic review tool that scrapes the literature and includes an analysis of how things have changed over time. This is done in systematic review or narrative reviews of the literature, when you read those types of papers, but those papers are based on researcher interests (and time and funding), and I often have so many questions that don’t have systematic reviews/narrative reviews covering them. Some I turn into papers myself (such as my paper on systematically reviewing the dosing guidelines and research on pancreatic enzyme replacement therapy for people with exocrine pancreatic insufficiency, known as EPI or PEI, or a systematic review on the prevalence of EPI in the general population or a systematic review on the prevalence of EPI in people with diabetes (Type 1 and Type 2)), but sometimes it’s just a personal question and it would be great to have a tool to help facilitate the process of seeing how information has changed over time. Maybe someone will eventually build that tool, or it’ll go on my list of things I might want to build, and I’ll build it myself like I have done with other types of research tools in the past, both without and with AI assistance. We’ll see!

TL;DR: be cognizant of the fact that medical literature changes over time, and keep this in mind when reading a single paper. Sometimes there are competing “facts” or beliefs or statements in the literature, and sometimes you can identify how it evolves over time, so that you can better assess the accuracy of research findings and avoid relying on outdated or incorrect information.

Whether you’re a researcher, a clinician, or a patient doing research for yourself, this awareness can help you better navigate the scientific literature.

A screenshot from the animated gif showing how citation strings happen in the literature, branching off over time but often still resulting in a repetition of a fact that is later considered to be incorrect, thus both the correct and incorrect fact occur in the literature at the same time.

The prompt matters when using Large Language Models (LLMs) and AI in healthcare

I see more and more research papers coming out these days about different uses of large language models (LLMs, a type of AI) in healthcare. There are papers evaluating it for supporting clinicians in decision-making, aiding in note-taking and improving clinical documentation, and enhancing patient education. But I see a wide-sweeping trend in the titles and conclusions of these papers, exacerbated by media headlines, making sweeping claims about the performance of one model versus another. I challenge everyone to pause and consider a critical fact that is less obvious: the prompt matters just as much as the model.

As an example of this, I will link to a recent pre-print of a research article I worked on with Liz Salmi (pre-print here).

Liz nerd-sniped me about an idea of a study to have a patient and a neuro-oncologist evaluate LLM responses related to patient-generated queries about a chart note (or visit note or open note or clinical note, however you want to call it). I say nerd-sniped because I got very interested in designing the methods of the study, including making sure we used the APIs to model these ‘chat’ sessions so that the prompts were not influenced by custom instructions, ‘memory’ features within the account or chat sessions, etc. I also wanted to test something I’ve observed anecdotally from personal LLM use across other topics, which is that with 2024-era models the prompt matters a lot for what type of output you get. So that’s the study we designed, and wrote with Jennifer Clarke, Zhiyong Dong, Rudy Fischmann, Emily McIntosh, Chethan Sarabu, and Catherine (Cait) DesRoches, and I encourage you to check out the pre-print and enjoy the methods section, which is critical for understanding the point I’m trying to make here. 

In this study, the data showed that when LLM outputs were evaluated for a healthcare task, the results varied significantly depending not just on the model but also on how the task was presented (the prompt). Specifically, persona-based prompts—designed to reflect the perspectives of different end users like clinicians and patients—yielded better results, as independently graded by both an oncologist and a patient.

The Myth of the “Best Model for the Job”

Many research papers conclude with simplified takeaways: Model A is better than Model B for healthcare tasks. While performance benchmarking is important, this approach often oversimplifies reality. Healthcare tasks are rarely monolithic. There’s a difference between summarizing patient education materials, drafting clinical notes, or assisting with complex differential diagnosis tasks.

But even within a single task, the way you frame the prompt makes a profound difference.

Consider these three prompts for the same task:

  • “Explain the treatment options for early-stage breast cancer.”
  • “You’re an oncologist. Explain the treatment options for early-stage breast cancer.”
  • “You’re an oncologist. Explain the treatment options for early-stage breast cancer as you would to a newly diagnosed patient with no medical background.”

The second and third prompt likely result in a more accessible and tailored response. If a study only tests general prompts (e.g. prompt one), it may fail to capture how much more effective an LLM can be with task-specific guidance.

Why Prompting Matters in Healthcare Tasks

Prompting shapes how the model interprets the task and generates its output. Here’s why it matters:

  • Precision and Clarity: A vague prompt may yield vague results. A precise prompt clarifies the goal and the speaker (e.g. in prompt 2), and also often the audience (e.g. in prompt 3).
  • Task Alignment: Complex medical topics often require different approaches depending on the user—whether it’s a clinician, a patient, or a researcher.
  • Bias and Quality Control: Poorly constructed prompts can inadvertently introduce biases

Selecting a Model for a Task? Test Multiple Prompts

When evaluating LLMs for healthcare tasks—or applying insights from a research paper—consider these principles:

  1. Prompt Variation Matters: If an LLM fails on a task, it may not be the model’s fault. Try adjusting your prompts before concluding the model is ineffective, and avoid broad sweeping claims about a field or topic that aren’t supported by the test you are running.
  2. Multiple Dimensions of Performance: Look beyond binary “good” vs. “bad” evaluations. Consider dimensions like readability, clinical accuracy, and alignment with user needs, as an example when thinking about performance in healthcare. In our paper, we saw some cases where a patient and provider overlapped in ratings, and other places where the ratings were different.
  3. Reproducibility and Transparency: If a study doesn’t disclose how prompts were designed or varied, its conclusions may lack context. Reproducibility in AI studies depends not just on the model, but on the interaction between the task, model, and prompt design. You should be looking for these kinds of details when reading or peer reviewing papers. Take results and conclusions with a grain of salt if these methods are not detailed in the paper.
  4. Involve Stakeholders in Evaluation: As shown in the preprint mentioned earlier, involving both clinical experts and patients in evaluating LLM outputs adds critical perspectives often missing in standard evaluations, especially as we evolve to focus research on supporting patient needs and not simply focusing on clinician and healthcare system usage of AI.

What This Means for Healthcare Providers, Researchers, and Patients

  • For healthcare providers, understand that the way you frame a question can improve the usefulness of AI tools in practice. A carefully constructed prompt, adding a persona or requesting information for a specific audience, can change the output.
  • For researchers, especially those developing or evaluating AI models, it’s essential to test prompts across different task types and end-user needs. Transparent reporting on prompt strategies strengthens the reliability of your findings.
  • For patients, recognizing that AI-generated health information is shaped by both the model and the prompt. This can support critical thinking when interpreting AI-driven health advice. Remember that LLMs can be biased, but so too can be humans in healthcare. The same approach for assessing bias and evaluating experiences in healthcare should be used for LLM output as well as human output. Everyone (humans) and everything (LLMs) are capable of bias or errors in healthcare.

Prompts matter, so consider model type as well as the prompt as a factor in assessing LLMs in healthcare. Blog by Dana M. LewisTLDR: Instead of asking “Which model is best?”, a better question might be:

“How do we design and evaluate prompts that lead to the most reliable, useful results for this specific task and audience?”

I’ve observed, and this study adds evidence, that prompt interaction with the model matters.

A Tale of Three Artificial Intelligence (AI) Experiences in Healthcare Interactions

AI tools are being increasingly used in healthcare, particularly for tasks like clinical notetaking during virtual visits. As a patient, I’ve had three recent experiences with AI-powered notetaking tools during appointments with the same clinician. Each time, I consented to its use, but the results were very different across the three encounters. The first two involved similar tools with mostly good results but surprising issues around pronouns and transparency of the consent process. The third was a different tool with a noticeable drop in quality. But what really stands out, when I compare these to a visit without AI, is that human errors happen too — and the healthcare system lacks effective processes for identifying and correcting errors, no matter the source.

Encounter One: Good Notes, Incorrect Pronouns

At the start of my first virtual appointment, my clinician asked for my permission to use an AI-powered tool for notetaking. I consented. After the visit, I reviewed the clinical note, and the summary at the top described me using “he/him” pronouns. I’m female, so they should have been “she/her”.

The rest of the note was detailed and clinically accurate and useful. But the pronoun error stood out. It seemed like the AI defaulted to male pronouns when gender information wasn’t explicitly mentioned, which made me wonder whether the model was trained with gender bias or if this was a design flaw in this tool.

Encounter Two: Clarifying Pronouns, Learning About Chart Access

At the next appointment, my clinician again asked for consent to use an AI-powered notetaker. I agreed and pointed out the pronoun error from the previous visit, clarifying that I am female and use she/her pronouns. My clinician looked at the prior note and was equally puzzled, commenting that this issue had come up with other patients — both directions, sometimes assigning female pronouns to male patients and vice versa. The clinician mentioned that the AI system supposedly had access to patient charts and should be able to pull gender information from existing records. That really surprised me: the consent statement had described the tool as a notetaking aid, but nothing had been said about access to my full chart. I would have given permission either way, but the fact that this hadn’t been disclosed upfront was disappointing. I had understood this to be a passive notetaking tool summarizing the visit in real time, not something actively pulling and using other parts of my health record.

This time, the pronouns in the note were correct (which could be because we talked about it and I declared the pronouns), and the overall summary was again accurate and detailed. But the fact that this was a recurring issue, with my provider seeing it in both directions across multiple patients, made it clear that pronoun errors weren’t a one-off glitch.

Encounter Three: A Different AI with Worse Results

By the third appointment, I knew what to expect. The clinician again asked for consent to use an AI notetaker, and I agreed. But after reviewing the note from this visit, two things stood out.

First, the quality of the notetaking was noticeably worse. Several errors were obvious, including situations where the note reflected the exact opposite of what had been discussed. For example, I had said that something did not happen, yet the note recorded that it did.

Second, this time the note disclosed the specific software used for notetaking at the bottom of the document. It was a different tool than the one used in the first two visits. I hadn’t been told that a different AI tool was being used, but based on the change in quality and the naming disclosure, it was clear this was a switch.

This experience reinforced that even when performing the same task — in this case, AI notetaking — the software can vary widely in accuracy and quality. I much preferred the output from the first two visits, even with the initial pronoun error, over the third experience where clinically significant details were recorded incorrectly.

Notably, there doesn’t seem to be a process or method (or if there is one, it is not communicated to patients or easily findable when searching) to give the health system feedback on the quality and accuracy of these tools. Which seems like a major flaw in most health systems’ implementations of AI-related tools, assessing and evaluating only from the healthcare provider perspective and overlooking or outright ignoring the direct impact on patients (which influences patient care, the clinician-patient relationship, trust with the health system….).

A Human-Only Encounter: Still Not Error-Free

To give further context, I want to compare these AI experiences with a separate virtual visit where no AI was involved. This was with a different clinician who took notes manually. The pronouns were correct in this note, but there were still factual inaccuracies.

A small but clear example: I mentioned using Device A, but the note stated I was using Device B. This was not a critical error at the time, but it was still incorrect.

The point here is that human documentation errors are not rare. They happen frequently, even without AI involved. Yet the narrative around AI in healthcare often frames mistakes as uniquely concerning when, in reality, this problem already exists across healthcare.

A Bigger Issue is Lack of Processes for Fixing Errors

Across all four encounters — both AI-assisted and human-driven — the most concerning pattern was not the errors themselves but the failure to correct them, even after they were pointed out.

In the first AI note where the pronouns were wrong, the note was never corrected, even after I brought it up at the next appointment. The error remains in my chart.

In the human-driven note, where the wrong device was recorded, I pointed out the error multiple times over the years. Despite that, the error persisted in my chart across multiple visits.

Eventually, it did affect my care. During a prescription renewal, the provider questioned whether I was using the device at all because they referenced the erroneous notes rather than the prescription history. I had to go back, cite old messages where I had originally pointed out the error, and clarify that the device listed in the notes was wrong.

I had stopped trying to correct this error after multiple failed attempts because it hadn’t impacted my care at the time. But years later, it suddenly mattered — and the persistence of that error caused confusion and required extra time, adding friction into what should have been a seamless prescription renewal process.

My point: the lack of effective remediation processes is not unique to either AI or human documentation. Errors get introduced and then they stay. There are no good systems for correcting clinical notes, whether written by a human or AI.

So, What Do We Do About AI in Healthcare?

Critics of AI in healthcare often argue that its potential for errors is a reason to avoid the technology altogether. But as these experiences show, human-driven documentation isn’t error-free either.

The problem isn’t AI.

It’s that healthcare systems as a whole have poor processes for identifying and correcting errors once they occur.

When we evaluate AI tools, we need to ask:

  • What types of errors are we willing to tolerate?
  • How do we ensure transparency about how the tools work and what data they access?
  • Most importantly, what mechanisms exist to correct errors after they’re identified?

This conversation needs to go beyond whether errors happen and instead focus on how we respond when they do.  It’s worth thinking about this in the same way I’ve written about errors of commission and omission in diabetes care with automated insulin delivery (AID) systems (DOI: 10.1111/dme.14687; author copy here). Errors of commission happen when something incorrect is recorded. Errors of omission occur when important details are left out. Both types of errors can affect care, and both need to be considered when evaluating the use of AI or human documentation.

In my case, despite the pronoun error in the first AI note, the notetaking quality was generally higher than the third encounter with a different AI tool. And even in the human-only note, factual errors persisted over years with no correction.

Three encounters with AI in healthcare - reflecting on errors of omission and commission that happen both with humans and AI , a blog post by Dana M. Lewis from DIYPS.orgAI can be useful for reducing clinician workload and improving documentation efficiency. But like any tool, its impact depends on how it’s implemented, how transparent the process is, and whether there are safeguards to address errors when they occur.

The reality is both AI and human clinicians make mistakes.

What matters, and what we should work on addressing, is how to fix errors in healthcare documentation and records when they occur.

Right now, this is a weakness of the healthcare system, and not unique to AI.

Infection is not inevitable: how to stop the spread of infections like COVID-19, flu, RSV, colds, and more in your house

I observe a number of people who seem to think it’s inevitable that once someone gets sick, the rest of the house is going to get sick with 100% certainty.

Nope.

First of all, household transmission rates are less than 100% for all of these conditions, even if you didn’t take any precautions or make any behavior changes.

Secondly, with knowledge about how these things spread and some mitigation measures, you can reduce this a lot – and in some cases to nearly zero.

I will caveat: that of course depending on the situation some of these precautions may not make sense or be possible. For example, if you have kids, your exposures may be different. We don’t have kids in our house, so we are dealing with adult to adult possible transmission. That being said, some of these things may still be worth doing to some degree, to cut down the risk of exposure and/or to limit the viral dose you are exposed to, even in a situation that is less straightforward like a parent taking care of sick kids.

PS – if you’re reading this in January 2025 and don’t read the rest, make sure you’ve gotten your flu shot (yes, it helps) for the 2024-2025 flu season. No, it’s not too late. If you’re >65, you should also check about the RSV vaccine (which like the flu shot is a seasonal vaccine). It’s not too late and given the current high rates of RSV and flu (and soon to be uptick in COVID), they can help prevent getting or limit the severity if you do get exposed.

Our experience preventing the spread of RSV and the common cold

I can speak with recent, practical experience on this.

Twice.

First, let’s talk about RSV.

Before Thanksgiving, Scott and I were exposed to a nibling (aka a niece or nephew – of which we have 10 plus several honorary ones!) who had what we thought was a lingering cough from a cold from a few weeks ago. Because I am avoiding infection, I wore a mask inside and did not get up close to the nibling, so as a result of all of this likely had minimal exposure. Scott did not mask and had spent a lot more time with this nibling hanging all over him and coughing near or on him. Within 48 hours, he started to get symptoms of something.

We activated our plan for household transmission avoidance. Well, with a rolling start: Scott recognized by Thanksgiving evening that he was starting to feel unwell and had a tiny bit of coughing. I thought I could hear something in his chest differently, in addition to the occasional cough, so I went into full precaution mode while Scott did a partial precaution mode. This meant we set up air purifiers by each of our beds, and a fan pointed in my direction so all air was blowing away from me. I also wore a mask to go to sleep in. (This was super annoying and I don’t like doing this, especially because I usually take a shower and go to bed with wet hair. Wearing an n95 with head straps on wet hair plus having a fan and purifier blowing on me is chilly and unfun.) I would’ve preferred Scott to mask, too, or go to the guest bedroom to sleep, but it was late in the evening; he wasn’t convinced he was really sick; and I was too exhausted to argue about it on top of the fact that we were leaving on a trip the next morning. So he did not mask that night.

The next morning, though, he was definitely sick. He tested negative for COVID, and the nibling and everyone else from that house had been testing for COVID and negative, so we were fairly confident based on serial testing that this was not COVID. At the time, the thought was this was a common cold.

Since we were planning to mask in indoor spaces, anyway, including in the airport and on the plane, we felt comfortable going on our trip as planned, because we would be unlikely to infect anyone else. (This includes no indoor dining: we don’t take off our masks and eat inside.)

Because Scott realized he was sick, he masked from that point forward (with a non-valved N95). We both masked in the car, in the airport, on the plane, and again when we arrived while driving in the rental car. Then a challenge: we needed to eat dinner (we got takeout), and we were sharing a hotel room overnight. We switched from a hotel room with a king bed to a room with two queen beds, which would give us some more space overnight. But we took turns eating dinner unmasked in the hotel room (it was too cold to be outside) with the far-UVC lights on and the purifiers around each of us when we ate. While we ate, the other person was masked. (And I went first, so there was no unmasked air from Scott while I was eating and he went second). We also took turns showering, again with me going first and him not having been in the bathroom unmasked until after I had gone in. Other than that, we stayed masked in the hotel room including overnight, again with purifiers between us and the far-UVC lights running.

(This hotel did not have windows that opened to outside, but if there had been windows I would’ve eaten in front of the open window and we would’ve likely kept it cracked open and the heat turned up, to improve the room’s ventilation).

The next day, we had more of a drive, and again we masked. We also slightly rolled down the windows in the backseat to improve ventilation. Scott sometimes took his mask off for comfort stretches, because he was driving, but put it back on fully and sealed it before coughing. I kept my mask on without ceasing. We did a 4.5 hour drive this way.

Luckily, once we arrived at our destination, there was a spare bedroom, so that became Scott’s headquarters. He stayed masked in the living room/shared areas. He sat downwind outside and masked up when coughing if anyone was outside. We left the sliding door to the outside cracked open, in order to keep the air in the common areas well-ventilated. This worked, because we were able to keep CO2 levels (a proxy for ventilation) down below 700 ppm most of the time.

Because we had separate bedrooms, we did not mask while sleeping the rest of the week, because we each had our own rooms (and own airflow). I did keep a purifier running in my room all week, but that’s my habit regardless because I’m so allergic to dust.

And guess what? It all worked. We masked again on the drive back to the airport and in the airport and on the plane and again once we got home.

I never got RSV. The four other adults we spent time with and shared a house with….also did not get RSV. So we are pretty confident that the transmission chain stopped completely at Scott.

In summary, what worked:

  • Masking in shared spaces, and two-way masking when it wasn’t possible to ventilate
  • When we had to sleep in the same room, two-way masking even for sleeping overnight
  • Scott masking in shared spaces that were well ventilated, and often left the room to go cough even when masked (or coughing outside). This often meant he masked, but the rest of us did not mask inside the whole time.
  • Generally keeping distance. Droplets were managed by the N95 mask, and we were ventilating to reduce aerosol transmission risk, but still keeping physical distance to further reduce the risk.

RSV is *very* transmissible especially with aerosols, and Scott was coughing a lot all day and night. (At one point, his Sleep Cycle app was estimating 18 coughs per hour). It took a long time for that to get down to normal, so he continued to sleep in our guest room when we got back and we continued to ventilate well even when we gradually reduced masking once he stopped coughing. It took about 10 or so days for all of his biometrics to normalize, and about 14 days for his cough to completely go away. It probably was closer to three weeks before he finally felt all recovered.

So with that timing in mind, you know what happens 4 weeks after Thanksgiving? Christmas/other end of year holiday gatherings.

We had plans to see 8 kids and 8 adults (plus us) for Christmas. And at Christmas, it seemed like everyone had a cold already. So again, I went in and mostly masked except for when I was in front of an open window and the room was well ventilated, without anyone coughing actively in the room. (If anyone was in the room with me and coughing, especially the kids, I would mask even with the window open).

I did not get the cold that 8-10 (out of 16) people eventually got.

But…Scott did. And this time, he was mostly masked, but he still spent more time up close with kids who were coughing quite a bit. And this is where some of the dynamics of knowing WHAT people have is helpful. You can’t always know, but you can sometimes use the symptoms to figure out what people have.

For example, based on symptoms of the nibling who passed on germs to Scott around Thanksgiving, and Scott’s symptoms (instant, incredible chest cough but no runny nose, sore throat, fever, or aches) we had ultimately guessed that Scott had RSV. We then knew that the biggest risk was either droplets from coughing (especially because the volume of coughing), which could be reduced drastically by masking, or aerosols, which again would be helped by his masking and also ventilation, and in closed spaces, two-way masking (me masking).

For the Christmas germs, everyone seemed to have mild symptoms with congestion, runny noses, some coughs. But no fevers or aches and it seemed less severe. Given our recent experience with RSV, we narrowed it down to likely being a cold (rhinovirus), given again everyone testing repeatedly negative for COVID.

Given that, we knew the risk was going to be highest for us from droplets and fomites. So we again masked in shared spaces; Scott went to sleep in the guest bedroom as soon as he started getting symptoms; and we both did a lot of hand washing. Scott washed his hands before touching any of my things and regularly wiped down the kitchen. I tried not to go in the kitchen much (our main overlapping shared space), but also wash my hands after any time that I did. He didn’t have much of a cough and it was more controlled, so he would hold his cough until he could cover it with a mask or be in the room by himself. We also did our usual running of purifiers and opened windows and ran fans to increase ventilation to keep CO2 low.

And again? It worked. I did not get the cold, either from any of the ~8+ folks who did across the holiday period, or from Scott. Scott’s vitals all returned to normal at the five day mark, although we continued to mask in the car through day 7, to be more cautious (due to my personal situation).

So, infection is not inevitable, even in small houses and apartments.

Here’s what we’ve taken away from these experiences with more aerosol-based (RSV) transmission diseases and more droplet and fomite-based (cold) experiences:

  1. Two-way N95 masking works. Mask in the car, run the fan, keep the windows cracked, run purifiers at home, and ventilate spaces, but you still want two-way masking when something is aerosolized and you’re in the same spaces. This can prevent transmission.
  2. Keep distance when someone is coughing and sneezing (and if they have a cough or sneeze type illness, you want 6 foot distance even when they’re not actively coughing or sneezing, because they make droplets just from breathing and talking). The person who’s coughing and sneezing should mask, even inside, unless they are in their own room in private (and it’s not a shared room).Keep your air ventilated (if you haven’t, read my post about ventilation and using a Co2 monitor)Depending on the illness, to fully protect yourself you’ll need to commit to wearing a mask at all times indoors to protect yourself if the person who is sick is not masking. (Eg, Scott got a cold while mostly masked around heavily coughing niblings, but not throughout the whole house the whole day). With adults, the adults who are sick should definitely mask if they’re in shared spaces with other adults. (It’s harder with kids, and it should be a conversation depending on the age of the kids about them masking in shared spaces, such as if they want to play with Uncle Scott, or help them understand that someone may not want to play up close if they’re sick and coughing and not willing to mask. That’s fine, but that’s a choice they can make when kids are old enough to understand.)
  3. Have the infected person sleep in a different space (on the couch or in another room if you have a spare bedroom). If you have to share a room, both should mask.
  4. Use cleaning wipes to wipe down shared surfaces (e.g. fridge handles, microwave, counters, bathroom surfaces like the flush on the toilet or sink faucet, etc) and wash your hands after using these shared spaces every time. Fomites can last longer than you’d expect.
  5. Use metrics from your wearable devices (eg Apple Watch or Oura ring or similar) to track when your temperature, respiratory rate, heart rate, cough rate, etc. return to normal. That tied with symptom elimination can help you determine how long you’re likely most infectious for. The general estimates of contagiousness for each condition generally seem to be right (e.g., two weeks for an adult with RSV and 5-7 days for a cold) in our recent experiences. I would continue precautions for at least those minimum time frames, if you can.
  6. Yes, there’s a cost to these precautions, in terms of human contact. There was no hugging or hand holding or kissing or any touch contact during these time periods. I felt pretty lonely, especially because it was me we were trying to protect (because I am at high risk for bad outcomes due to immunosuppression right now), and I’m sure Scott also felt lonely and isolated. That part sucked, but we at least knew it was a fixed period of time, which helped.

What we’d do differently next time

Infection is not inevitable -how to reduce transmission of illness in your household (including COVID-19, RSV, flu, and the common cold), written by Dana M. Lewis from DIYPS.orgThis basically has been our plan for if either of us were to get COVID-19 (or the flu), and it’s good to know this plan works for a variety of conditions including RSV and the common cold. The main thing we would do differently in the future is that Scott should have masked the very first night he had symptoms of RSV, and he has decided that he’ll be masking any time he’s in the same room as someone who’s been coughing, as that’s considerably less annoying than being sick. (He really did not like the experience of having RSV.) I obviously did not get it from that first night when he first had the most minor symptoms of RSV, but that was probably the period of highest risk of transmission of either week, given the subsequent precautions we took after that.

Combined, everything we did worked, and we’ll do it again when we need to in the future, which should not be very often. We went five full years without either of us getting any type of infection (yay), and hopefully that continues from here on out. We’ll also continue to get regular COVID-19 boosters; annual flu shots; and other annual shots if/when they become available (e.g. when we reach the age, getting the RSV vaccine).

Remember, if you’re reading this in January 2025, RSV and flu levels are very high in the US right now, with COVID-19 expected to pick up again soon. It’s not too late to get your boosters and given the rates of respiratory illness, consider situational masking even if you don’t typically mask.

You are a sail and not an anchor

When you’re dealing with a challenging health situation, it can be hard. Hard because of what you are dealing with, and hard because you need to navigate getting and seeking care. That typically looks like going to a doctor, getting the doctor to understand the problem, and then finding solutions to deal with the problem.

Each of those has their own challenges. You may not have a doctor that specializes in the area you need. For example, you may not have a primary care doctor when you have strep throat, and have to go to urgent care instead. Or maybe you develop a problem with your lungs and need a pulmonologist, but that requires a referral from someone and several months’ wait to be seen.

Once you face that challenge and are in fact seen by the specializing provider (and hopefully the problem you have is in fact the one this specialist can address, rather than referring you on to a different kind of specialist), you have to figure out how to communicate and show what issues you have to the doctor. In some cases, it’s really obvious. You have a red, angry throat which leads to the doctor ordering a strep test. Or you go to the dermatologist for a skin check because you have a mole that is changing, and you get a skin check and a biopsy of the mole. Problem identified and confirmed.

It takes identifying and confirming the problem, and usually diagnosing it, to then reach the stage of addressing it, either with symptom management or with curing or fixing or eliminating the source.

But…what happens when you and your doctor can’t define the problem: there is no diagnosis?

That’s a challenging place to be. Not only because you have a problem and are suffering with it, but also, the path forward is uncertain. No diagnosis often means no treatment plan, or the treatment plan itself is uncertain or delayed.

No diagnosis means that even if your provider prescribes a treatment option, it may get denied by the insurance company because you don’t have the clinical diagnosis for which the treatment is approved for. Maybe your doctor is able to successfully appeal and get approval for off-label use, or maybe not.

And then, there’s no certainty that the treatment will work.

So. Much. Uncertainty. It’s hard.

It’s also made hard by the fact that it’s hard to tell people what’s going on. A broken leg, or strep throat, or a suspicious mole: these are things that are relatively easy to explain to other people what is going on, what it means, how it might be treated, and what a rough expectation of timeline for resolution is.

Most stories are like this. There’s a story arc, a narrative that has a beginning, middle, and an end.

With the uncertain health situations I’m describing, it’s often never clear if you’ve even reached “the middle”, or what the end will be…or if there even is an end. Certainly no guarantee of a happy ending, or an ending at all if you have been diagnosed with a chronic, lifelong disease.

I’ve been there (here) many times, now living with more than a handful of autoimmune diseases that I’ll have for life. But the first few were relatively “simple” to diagnose, treat, and understand what they looked like. For example, with type 1 diabetes, the symptoms of weight loss, excessive urination, incredible thirst, etc. led to a blood test confirming high glucose, an A1c test confirming it had been high for months, and a diagnosis of type 1 diabetes. The treatment is managing glucose levels with insulin therapy, presumably for the rest of my life. (22 years and counting, here). It makes things challenging, but it’s something I can explain to other people for the most part what it means and how it does or does not impact my life.

Lately, though, I’ve found more uncertainty. And that makes it hard, because if there is no diagnosis then there is no clear explanation. No certainty, for myself or to give my loved ones. Which makes it feel isolating and hard psychologically, in addition to the physical ramifications of the symptoms themselves.

There’s a saying in medicine: When you hear hoofbeats, think horses, not zebras.” It’s a reminder for clinicians to consider common explanations first, rather than go straight to explanations of rare conditions. Most of the time, the advice is helpful—common issues should be ruled out before rarer ones.

In my case, that’s what we did. We ruled out every possible common condition…and then pretty much all the rare ones. So what do you do, when your symptoms don’t match the pattern of a horse…or a zebra?

You might have an uncommon presentation of a common disease or a common presentation of a rare disease.

Either way, whether horse or zebra, the symptoms cast a shadow. They’re real.

Whether the animal in question has stripes or not, you’re still living with the impact. What makes this even harder is that many diagnostic processes rely on pattern recognition, yet undiagnosed conditions often defy easy patterns. If your symptoms overlap with multiple conditions—or present in a way that isn’t fully typical—then the search for answers can feel like trying to describe a shadow, not the thing itself.

And shadows are difficult to explain.

This makes a meta-challenge on top of the challenge of the situation, which is trying to explain the unexplainable. This is crucial not just for helping your doctors understand what is going on, so we can improve the diagnostic pursuit of answers or gauge the efficacy of hand-wavy treatment plans meant to do something, anything, to help… and it’s also crucial for explaining to your friends and family what is going on, and what they can do to help.

We often want to see or hear health stories in the format of:

  • Here’s the problem.
  • Here’s what I’m doing about it.
  • Here’s how I’m coping or improving.
  • Bonus: here’s how you can help

I’ve seen so many examples of friends and family responding to the call for help, for me and for others in health situations. I know the power of this, which is why when you can’t explain what’s going on, it makes it challenging to ask for help. Because it’s hard to explain the “what” and the “why”: you are only left with the “so what” of ‘here’s what the end result is and how I need help’.

(And if you’re like me, a further challenge is the situation being dynamic and constantly changing and progressing, so what help you might need is a constant evolution.)

You might also feel like you shouldn’t ask for help, because you can’t explain the what and the why. Or because it is ongoing and not clear, you may want to ‘reserve’ asking for help for later ‘when you really need it’, even if you truly do need help then and there at that point in time. As weeks, months, or even years drag on, it can be challenging to feel like you are burdening your loved ones and friends.

But you’re not.

The best meta explanation and response to my attempts to communicate the challenges of the meta-challenge of the unexplainable, the uncertainty, the unending saga of figuring out what was going on and how to solve it, came from Scott (my husband). We’ve been married for 10 years (in August), and he met me when I had two of my now many autoimmune diseases. He knew a bit of what he was getting in to, because our relationship evolved and progressed alongside our joint interests in problem solving and making the world better, first for me and then for anyone who wanted open source automated insulin delivery systems (aka, we built OpenAPS together and have spent over a decade together working on similar projects).

That being said, to me it has felt drastically different to be living with ‘understandable’ chronic autoimmune diseases like type 1 diabetes and celiac, and this latest saga where it’s unclear if it’s an extension of a known autoimmune disease (presenting and progressing atypically) or if it’s a new, rare autoimmune or other type of disease. So much is unknown. So many challenges. When we would adapt and address one problem or challenge, it evolved and needed another solution, or another problem cropped up. I’m honestly at this point exhausted of adaptations and problem solving. I’m tired of asking, seemingly endlessly, for help and support. Amazingly, Scott does not seem exhausted by it or tired of me, whereas many people would be. And he said something a few weeks ago, completely off the cuff and unplanned that really resonated with me. I was talking, again (he’d heard this many times), about how hard this all has been and is, and that I was also aware of the effect it has on him and on our relationship. I can’t do all the things I did before, or in the way I did before, so it’s changed some of what we do, where we go, and how we are living our lives. I’m having a hard time with that, and it would be natural for him to have similar feelings. (And frustrations, because if I feel frustrated with being out of control and unable to change the situation and fix it, so too would he be except worse secondhand because it’s so hard to love someone and not be able to help them!)

But what he said literally stopped me in my tracks after he said it, because we were out walking and I had to physically stop after he said it to process it in my heart (and leak some tears from my eyes).

It was something along the lines of:

“You’re not an anchor, you’re a sail.”

Meaning, to him, I’m not holding him back from living his life (as I was and am concerned about).

He continued by saying:

“Yes, the sail is a little cattywampus sometimes, but you’re still a sail that catches wind and takes us places. It’s much more interesting to let you sail us, even in a different direction, than to be without a sail.”

(Yes, you can pause and tear up, I do again just thinking about how meaningful that was.)

What a hit, in the most wonderful way, to my heart, to hear that he doesn’t see me and all these challenges as an anchor. He recognizes them, and that we are dealing with them, but he’s willing and wanting us to sail in the direction they take us, even when that makes us go in some unplanned directions.

Probably some of this is personality differences: I love to plan. I love spreadsheets. I love setting big goals and making spreadsheets of processes and how I’ll achieve them. In the current situation, I can’t make (many) plans, there are no spreadsheets or processes or certainty or clear paths forward. We’re in an ocean of uncertainty, with infinite paths ahead, and even if I set sail in a certain direction…I’m a cattywampus sail that may result in a slightly different direction.

But.

Knowing I’m a cattywampus sail, and not an anchor, has made all the difference.

If you’re reading this and dealing with an uncertain health situation (undiagnosed, or diagnosed but untreated, or diagnosed but with no certainty of what the future looks like), you may feel like you’re a boat adrift in the middle of an ocean. No land in sight. No idea which way the wind will blow you.

But.

You’re a boat with a sail. Maybe a cattywampus one, and maybe you’re going to sail differently than everyone else, but you probably are going to still sail. Somewhere. And your family and friends love you and will be happy to go whichever direction the wind and the cattywampus sail take you.

If you’re reading this and you’re the friend or family of a loved one dealing with an uncertain situation, first, thank you. Because you clearly love and support them, even through the uncertainty. That means the world.

You may not know how to help or be able to help if they need help, but communicating your love and support for them alone can be incredibly meaningful and impactful. If you want, tell them they’re a sail and not an anchor. It may not resonate with them the way it resonated with me, but if you can, find a way to tell them they and their needs are not a burden, that life is more interesting with them, and that you love them.

You are a sail, not an anchor, a post about dealing with hard health situations by Dana M. Lewis from DIYPS.orgThis has become a long post, with no clear messages or resolutions, which in of itself is an example of these types of situations. Hard, uncertain, messy, no clear ending or answer or what next. But these types of situations happen a lot, more than you know.

If you’re going through this, just know you’re not alone, you’re loved and appreciated, and you’re a sail rather than an anchor, whether you’re a zebra or a horse or a zebra-colored horse or a horse-shaped zebra shadow.

PS – I’ll also share one specific thing, for loved ones and friends, as something that you can do if you find out about a situation like this.

If someone trusts you and communicates part or all of their situation, and they specifically tell you in confidence that they are not sharing it publicly or with anyone else or with X person or Y group of people…honor that trust and request not to communicate that information. They have a reason, if not multiple reasons, for asking. When dealing with uncertain health situations, we can control so little. What we can control, we often want to, such as choosing when and how and to whom to communicate about our challenges and situations.

If someone honors you by telling you what’s going on and asks you not to tell other people – honor that by not disabusing the trust in your relationship. Yes, it can be hard to keep it to yourself, but it’s likely about 1% hard of what they are dealing with. Passing on the word becomes a game of telephone that garbles what is going on, often turns out to be passed on incorrectly, and causes challenges down the line…not in the least because it can harm your relationship with them if they perceive you have violated their trust by explicitly passing on information you asked them not to. And that, on top of everything else, can make a challenging situation more so, and it may then later influence how they want to communicate with others, potentially shutting down other avenues of support for them. So please, respect the wishes of the person, even if it’s hard for you. You can always ask “can I share this with so and so”, but respect if the answer is no, even if you would do something different in your situation. Because, after all, it is not your situation. You’ve been invited on the boat, but you are not the sail.

What it’s like to get intravenous immunoglobulin (IVIG) infusions for the first time

When I first found out I was going to get IVIG (intravenous immunoglobulin), I was nervous because I didn’t know what to expect. New medical treatments or therapies and the uncertainty of what to expect can make it harder. This is a little bit about my experience, what to expect with IVIG, and some differences in the experience depending on location (outpatient or not).

Preparing for the first infusion – prior authorization and scheduling

First, know that IVIG usually needs prior authorization from your insurance. This is approval not only for the treatment itself; but the volume (how much you’ll get); the schedule (do you do it a single day or multiple days in a row) and the cadence (how often do you get it, if you get it over and over again). And, the location.

The first time my provider prescribed IVIG, my insurance denied it. And again. And again. My provider had to do a round of peer to peer with the insurance company before they approved it.

(Note: IVIG is used for dozens of conditions including numerous autoimmune disease conditions. Sometimes this is the only approved treatment for these conditions; sometimes there are other treatments your insurance company will want you to try before IVIG. IVIG is rather expensive, more on that below, which plays into this.)

I was approved for a handful of infusions at an outpatient location in downtown Seattle. Once that was approved, I was able to actually schedule my appointments. If you get IVIG in multiple sessions (e.g. 2 days in a row, like I do, or 3 days in a row), it may make scheduling a tiny bit harder, but usually the clinics can get you in. Luckily, you don’t have to do the exact same time every session, e.g. you can start at 9am on Tuesday and then do 11am on Wednesday, if that’s what works for your schedule or theirs. Or if you prefer and they have availability, you can do it at the same time each day.

For your first appointments though, they’ll probably schedule you earlier in the morning and tell you to expect it to take all or most of the day. My first appointments were scheduled as 6 hour (!) blocks on back to back days. Gulp.

The first infusion experience

When I arrived for my first infusion, they did the usual check in at a front desk (like a typical doctor’s appointment) and then assigned me to a room/bay. This outpatient infusion center has open room bays with curtains to the hallway (and walls in between the bays), with numbers. Across the hall are several bathrooms. Once I got into my room, a nurse came in and introduced herself and walked me through what we would be doing. She started by asking if I had taken any pre-meds (pre medication) such as Tylenol or Benadryl. I said no (I didn’t know that I was supposed to), so she brought me two Tylenol and a Benadryl. This apparently is fairly common, because headaches are a common side effect and in rare cases (something like <1%) of the time allergic reactions can happen, so the Tylenol and Benadryl can slow down or minimize any allergic reaction that might occur.

I’ll admit, I was nervous about IVIG because of what I had read about allergic reactions, but I’ll say up front: I did not have any allergic reactions to IVIG at the first or any subsequent sessions.

While we were waiting for those to kick in, they put in the order for the IG itself, which had to be sent over from the pharmacy. They inserted the IV into my arm, which involves using a needle then immediately pulling it back out so only a small thing of tubing is left behind. (This is similar to an insulin pump site!) They tape it and wrap it so it won’t get jostled from normal movements, and we waited until the IG arrived.

Note: if you need to have labs run to check anything before or around the time of your infusion, they can pull blood from the same IV first, then they flush it with saline and can then use it to infuse your IG.

When they start the IVIG, they start it at really low (slow) rates. Your provider will have prescribed the rates and the schedule. For example, you start at a slow rate and then it increases every 30 minutes. This way, if you do have any symptoms (sudden headaches or start feeling itchy, for example), you can go back to a slower rate to finish the infusion. That will take longer, overall, than if you went at the planned schedule because as your rate gets higher (larger), more goes in faster.

An example schedule might be 0-30 minutes at 30 mL/hr; 30-60 minutes at 60 mL/hr; 60-90 minutes at 120 mL/hr; 90-120 minutes at 240 mL/hr; 120-150 minutes at 375 mL/hr. If you still have IG left to infuse after 2.5 hours (aka 150 minutes), they continue at the highest rate, eg 150-180 minutes will continue at 375 mL/hr. Note that with this typical progression, your rate starts slow and doubles every half hour, until you get to the max dose. I believe this is calculated based on body weight. I am not sure if this is the number they were referring to (for max rate determination), but I heard the nurses discussing that one of the numbers is calculated based on ideal body weight, not actual body weight. That is one of the factors that will influence how much you get (volume wise, as in how much liquid) as well as the rate schedule.

If you start to feel yucky for any reason, you have a button you can call the nursing team with. But they also have scheduled checks. My experience was that they took blood pressure, pulse, and temperature at the start (0 minutes) and every 15 minutes up to the first hour, then every half hour after that. So with the rates described above, the schedule might look like this table:

Time Rate  Checks
Start (0 min) 30 mL/hr BP, pulse, temp
15 min (no change, continues) BP, pulse, temp
30 min 60 mL/hr BP, pulse, temp
45 min (no change, continues) BP, pulse, temp
60 min 120 mL/hr BP, pulse, temp
90 min 240 mL/hr BP, pulse, temp
120 min 375 mL/hr BP, pulse, temp
150 min (no change, continues) BP, pulse, temp
180 min (no change, continues) BP, pulse, temp
(runs until you infuse all liquid)

In the scenario where you had no side effects, and let’s say you had 400mL of IG to infuse, that means you would finish the initial infusion in around 2 hours and 15 minutes. After the main infusion finishes, they will hang a small bag (often 50mL) of saline, and then infuse that at the same highest rate of your IG, which means that all the remaining IG in the tube will get infused in. This may take something like 10-30 minutes, depending on your rate.

Remember, though, for your first infusion you may be on slower rates than this progression, to watch for side effects. A typical first infusion might be roughly double the time as this (4+ hours) even if you don’t have side effects, as you progress through the rates. If you do have side effects (feeling yucky, headache, itching, etc), it may take a lot longer because they will go back to the slower rate where you didn’t have side effects. For example, if you had issues at 240 mL/hr but not 120, they will finish infusing at 120 mL/hr, which would take an estimated 4 hours and 45 minutes, rather than 2.5 hours.

Another thing that can slow down the total time is bubbles. If your infusion line develops bubbles, the infusion machine will detect them and sound an alarm and stop the infusion. A nurse will come in, clear the alarm, shake the bubbles back up the tube, and proceed. That might take 2-3 minutes total, but if that happens several times (which is common with IVIG), that may add another 15 or so minutes.

Once that’s complete, you will get the IV removed (which is like pulling a bandaid off, in terms of the experience) and you’re ready to go for the day!

With the slow first infusion rates, bubbles, and saline flush at the end, this is why they schedule you for 6 hours or so, even if the infusion itself may take 4.5 or so hours.

See below though, because the next round of infusions are usually quicker than the original rounds, if you don’t experience side effects during the infusions.

Creature comforts – what to take to an IVIG session for your infusion

Most infusion centers have semi-comfortable recliner chairs. You can put the foot of the chair up; you can lay the chair back. Some of them have a seat heater, although admittedly it doesn’t get super warm. You may want to dress in layers so that if you get cold, you can add items. For example, if it’s summer and you typically wear shorts and a t-shirt, you may want to take loose pants you could pull over your shorts or a jacket to throw over your torso, or socks if you aren’t wearing them. The nursing staff will offer you heated blankets, too.

That being said, my experience with IVIG was freezing. Not from the ambient room temperature, but because the liquid arrives very cold from the fridge, and infusing cold liquid into your arm at the higher rates caused my arm to be ice cold and uncomfortable. I tried warm blankets, throwing a jacket over my torso, wrapping a towel around my arm… and I still had a cold arm and cold hand that took over an hour to warm up after my infusion ended. What finally ended up working best for me was to bring my own heating pad, and place it on a low temp and sit against it. This warmed up my core temperature which then helped keep my extremities (arms) warmer. Now, I regularly use my heating pad every time and don’t need a jacket, long sleeves, a blanket, or anything else! It’s surprising how effective it was to warm my core in order to combat the cold in my arm. Another option is an infusion hoodie, like this one that my sister in law got me. It has zippers in both arms, so you can wear it with your IV tubing.

You’ll absolutely be able to get up and go to the bathroom! At this infusion center, the infusion machine is on a pole with wheels. It’s plugged into the wall with a power cord, but they’ll unplug it for you or show you how to do it, so you can get up anytime and roll yourself to the bathroom, then come back. The battery on the machine lasts 6-8 hours, so you don’t have to bother plugging it back in, and this makes it easy to get up and go to the bathroom whenever you need to, especially if you’re doing a good job staying hydrated (e.g., drinking lots!).

Especially at those longer first infusions, you’re there a long time (4 or 6 hours or more). At my first infusion, they offered me a breakfast menu (because we were there at 8am) and a lunch menu to order food from. At shorter infusions you won’t get a menu if you’re not there at meal time (and at other locations, see below, there are no meals but just snacks), but they still offer to bring you juice, water, snacks periodically.

I have celiac disease which means I’m gluten free and that cuts down on my ability to take whatever from the menu or snacks. (I’m also choosing to mask to avoid infection exposure, and know that masking works, so I’d rather not eat if I don’t have to, and so I don’t). They probably do have some GF options, but I don’t bother with them and bring my own snacks if I want them, and my own drink bags. I have a soft insulated bag I throw water bottles and diet sodas into with an ice pack, so they stay cold and I can have a drink any time I want to, of my preferred choice.

You don’t have to bring your own stuff, but if it would make you happier or more comfortable, you can!

The first few sessions, I brought my laptop, (and phone), headphones, and a tripod for my phone. I tried to get some work done on my laptop, but because the infusion was in the crook of my arm, I risked kinking and stopping the infusion. I eventually gave up on that (but it might be more feasible if it was infusing into my forearm, for example), and stuck to using my phone. Sometimes I watch a show; sometimes I listen to a podcast or audiobook or music; sometimes I’m on zoom calls on my phone with video off, depending on my schedule. But plan to bring entertainment/something to occupy yourself with. If you want, you can nap – they’ll dim the lights, but they’ll likely be doing blood pressure etc checks every 30 minutes so don’t plan to get uninterrupted sleep for the most part.

Side effects from IVIG at first infusion and subsequent infusions

At my first round of infusions, I honestly felt like I was in “time out”. I felt awkward sitting in the chair, tied to the infusion machine. I wanted to be working or out walking and going about my day. I wanted to be normal! (Well, I wasn’t normal, which was why I was getting an infusion). I felt fine during and after my infusions, so I got home and went for my usual walk. It was really hot that day (90 F in July in Seattle), so I felt pretty gross and overdone, and probably overdid it. Then I came home and tried to get some work done, but felt like garbage – I thought because of walking in the heat.

The second day, I did the same thing, but decided not to walk in the heat. I still wanted to try to get work done, and did some, but still felt generally kind of gross and tired and just not great. I had a little bit of a headache, so I kept taking Tylenol (in addition to the dose they gave me before my infusion).

The third day (so the day after my second infusion), I still had pretty strong headaches and felt a little gross. Not sick – I wasn’t infected, all my biomarker data from my wearables was fine (e.g. heart rate, HRV, temperature, respiratory rate etc), but I felt worn down.

Fourth day? Same.

Fifth day? Same.

It probably took those ~3 days after the two days of infusions of feeling gross, then I started to feel better.

Then I started to feel GREAT. I had more energy than I had had in months! It felt like I went from Eeyore to Tigger. Wahoo! So much energy (and no more headaches). I was thrilled.

(Spoiler alert: this is probably unique to my situation, but this also did not last).

For me, the first week I felt sluggish and had headaches. The second week I felt better. The third and fourth week I continued to have symptom progression like before I was on IVIG. That’s probably unique to my situation – from what my doctor says, this is not a common response to IVIG to have an improvement and then a decrease like I do, in a cyclical fashion. But this pattern has continued in all subsequent months, where week two I see an improvement and then drop back down to the previous progression in weeks three and four.

What I did change in subsequent infusions – my personal approach

The headaches I got from IVIG weren’t quite debilitating, but they were obnoxious and cut down on my ability to work or rest like I wanted to.

Over time, I gradually figured out that for me, working on IVIG days (during, or even only after infusions) tends to cause more headaches for several days after. Sometimes I need to work (well, I choose to work) on those days, but I’ve gradually shifted my schedule so that I’ll do audio-only calls that are listen only while I’m infusing, or after I’m home, but I don’t plan any intensive cognitive work on IVIG days. I also don’t try to go out and do anything anymore because that typically results in several days of minor but annoying headaches, even with Tylenol. I can certainly do those things, but it comes with a cost.

In other words, I went from trying to live my normal life on IVIG days (and feeling like I was in time out) to changing my approach and treating them like rest days (minimal to no work planned; no requirement for physical activity but to do a short, gentle walk only if I feel really great) and also often the day after. That is frustrating when I think about how much time I am losing (3 days every month!), but when I calculated the lost productivity in the next few days after IVIG, I realized I was losing out on even more time by trying to work through it, and so resting up on IVIG days and maybe the day after ultimately retains more productive and energetic time for me in that first week.

I continue to take Tylenol and a Benadryl prior to each infusion, although I have never experienced any allergic reaction symptoms (eg itching, rash, etc), but the cost of a Benadryl is low and it provides peace of mind. The Tylenol before I start does seem to help, and I find that putting reminders on my calendar for Tylenol in the afternoon and evening before bed on IVIG days both helps me more proactively remember to take them, and taking them proactively makes the headaches minimal or non existent, compared to if I wait for a headache to start and then am chasing the headache with the Tylenol. Not sure how common that is for everyone else, but in my experience after several months of testing, this is true for me that Tylenol proactively for 2-3 days can eliminate the headaches, in addition to reducing the cognitive load.

Note that you can also adjust your infusion rates, especially if you get headaches DURING infusion. My headaches are never during the infusion, nor bad enough that I want to adjust my rates to be slower – they instead seem to correlate with cognitive burden after infusions and activity burden on my body, so I choose to address them with less work, more rest, and Tylenol for a few days.

The financial cost of IVIG

My eyes about popped out of their sockets when I looked at my EOB (insurance document that says how much was charged and how much insurance paid) for my IVIG experiences. It was in the ballpark of $30,000 billed PER DAY, so $60,000 or so total for two days of IVIG.

Oh my gosh.

(Luckily, I have health insurance; and in fact I typically hit my out of pocket max and deductible within a few days of the new years, so I was not paying for this directly).

As those of you who have looked at EOB know, that’s not what actually gets paid, but still. Yeeesh.

The insurance company rate was more like $17,000 per day, or $34,000 for the two days. Still yikes, that’s a LOT of money. And to do this every month?!

That’s probably part of the reason why insurance pushes back on requests to cover treatments like IVIG. It. Is. Expensive.

But in some cases like mine, they are literally the only option and often the only FDA-approved treatment option for certain conditions.

But, there are things you can do to lower costs, and your insurance will likely tell you this. For example, my prior authorization was originally for something like 41 days, enough for two rounds of treatment. After that, we would have to resubmit for prior auth. I read that approval letter though and noted that they would be more willing to approve outpatient, ambulatory infusion centers.

…which is what I went to the first time. It’s not at the hospital; it’s in a standalone building across from the hospital. But for some reason, they source from the inpatient hospital pharmacy (I think) and so while they bill outpatient costs for nursing staff and facility, the IG liquid itself gets charged at hospital prices. Sheesh. Thus, the $30,000 per day, the bulk of which is hospital priced IG (which is already expensive).

So I looked around and found another ambulatory infusion center that is equal distance from my house, but actually a shorter drive most of the time due to traffic patterns, plus I wouldn’t have to pay for parking. The downside is that they’re not tied into MyChart so I can’t see their records or the status of my prior authorizations like I could with the other ‘outpatient’ center. The upside is: they are significantly cheaper.

How much cheaper?

They bill $17,000 per day of IVIG for the same volume, and my insurance therefore pays about $5,500 per day, or $11,000 total for two days every month.

$34,000 per month, or $11,000 per month. Same amount of time. Same drug volume. Same concept…but much cheaper.

There was no way to find out in advance how much IVIG would cost at each of these locations. I only know now, after having experienced at both locations, what the relative costs are. It’s the same treatment, the same drug/liquid (IG) with the same cost for the same volume…. Except it’s not. Outpatient doesn’t always mean ‘outpatient’, depending on what services they use such as where they are sourcing via the pharmacy.

Note: this won’t be what anyone else’s IVIG costs, of course. It’s based on the volume of IG I am getting (based on my weight and medical conditions), plus the insurance plan, plus where they source it from, etc. But I’m sharing my costs to give you a ballpark (expect thousands, if not tens of thousands as the “price” that you or insurance won’t pay, but is the upper cap on what to expect).

Other infusion experiences including a different outpatient infusion center clinic experience

My second series of IVIG, due to the cost, was at this other outpatient center. This is in an ambulatory infusion clinic that’s basically plopped inside an older medical office or business building. It’s less shiny and new, but works the same. There are rows of bays with infusion chairs (so you’re in your own ‘room’), the infusion still works the same, etc.

I ended up in this location because I was actually trying to get home infusions. If I was going to be doing this two days a month, I thought, I’d rather have a home health nurse come in and do it and save me the travel time. But it turns out they won’t do mine as home  infusions because I do two days in a row. Stupid policy, and they lied to me up front about it, which made me really mad, because I was stuck going to this outpatient location. (I’m less mad now that I see the comparable cost, so it’s worth saving $25,000 a month to go to the less great location, because it’s not $25,000 worth of value to go to another location or fight prior authorization again to find another outpatient ambulatory site that may or may not be any better.)

They’re pretty efficient. You are basically scheduled directly with a specific nurse each time and you know who it is. They text you a reminder and some questions the day before, and you walk in and say hi and immediately get seated. They set up your IV and ask some questions and off you go. It’s the same infusion time (eg 2.5 hours, in my case), plus the infusion set up time which is usually pretty quick (15-20 minutes) and the flush at the end (~15 minutes), plus any bubble time, which means about 3 hours at the clinic, plus my ~30-40 minute drive each way depending on traffic. Times two days in a row. So, not as bad as those first infusion appointments (6 hours estimated), but it’s still 4-5 hours round trip of time for two days in a row. The nursing staff is great, and like the other clinic you’ll get offered warmed blankets, snacks, and drinks. So in terms of experience, it’s not too different. The main functional difference is that your infusion machine is on a pole on the wall, so you can’t get up and go to the bathroom with your infusion set up. Instead, you have to ask (or time it so when they come in to do a rate change) for them to pause the infusion, unhook you, then you go to the bathroom and come back and get your infusion hooked up again and you’re back at it. (This adds another 5 min or so to the total time, so I usually try to time it so I am doing it when they’re coming to change for the saline flush, or make it until the end. Sometimes I make it, sometimes I don’t because I’m also trying to hydrate really well and drink a lot, because that helps reduce headaches, too.)

At the end of each appointment round, they also take on the hassle of calling the scheduler for me and getting my appointments scheduled. I generally stick to roughly the same times of day and prefer earlier in the week appointments so that I can feel better by the weekend (again, perhaps my unique response timeline to IVIG).

I like this location a little bit less than the downtown location, but not $25,000 less, so I continue to use them every month for my IVIG.

Final tips – infusion rate spreadsheet to estimate time of IVIG

You’ll maybe have picked up that I don’t like uncertainty and not knowing what to expect. The vagaries of time uncertainty related to infusions bother me, because I like to know roughly how long things will take so I can schedule the rest of my day. After the first round of IVIG once we figured out what my rates are (and that I don’t have to slow them down for side effects), it should be predictable for how long things take every time, with margins for getting set up and flushed, etc. I ended up making a spreadsheet with my rates and time increments (every 30 minutes) and since I know my total volume of IG, I can see roughly what time my infusion will take. I also estimated the flush time of the 50 mL of saline (which is given at my max rate), and added that in. My spreadsheet therefore is set up so each time I change the start time and it auto-populates every 30 minutes how much will be given, how much has been given cumulatively, and including the estimated flush time at the end, what time the infusion will finish. This way I can estimate what time I’ll be leaving and when I’ll get home. For example, if I have a 10:30 appointment time, my infusion might start flowing at 10:48 (usually plus or minus 5 minutes from this, depending on if they unboxed all my stuff before I arrived). I might finish at an estimated 1:22pm, plus flush time, which means I can expect to be walking out the door at 1:35pm.

This way, if it takes a lot longer (say, start infusion at 10:57 and I’m having tons of bubbles), I know that I’m likely to be a half hour behind my typical schedule.

(If you make your own spreadsheet, it won’t be exact: it takes them a minute or two after the rate change alarm goes off to come and change it, so I actually add a minute to every 30 minute estimate to adjust for this time. I also add ~3 minutes buffer to the overall time to account for bubble pauses, too, as usually I average 2-3 rounds of bubbles that pause the infusion each time.)

Schedule may change (and IVIG may not be forever)

I had some existential angst when I realized that I needed IVIG. In part, due to the situation that caused the need for IVIG. But in part, for the idea that I would be on this monthly schedule for IVIG for the foreseeable future. Two days a month seemed like a LOT, especially with not knowing how long I needed it for. (At the point in time I’m writing this, it has been six months, and I’m still getting it for my situation.)

But if you need it, it’s usually worth it. (If not, you’ll stop it). So that my final piece of advice for folks:

  • If you need it, it’s worth the (time and usually financial) cost
  • It may not be forever. Your situation may improve to the point where you can space out your infusions more than your initial schedule. For example, you might first get it every 4 weeks, then do well enough to push it out to every 6 or 8 weeks, or more.
  • You might get to eventually discontinue it.

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That’s been my experience with IVIG so far, after 6 months of sessions where I get IVIG two days in a row every four weeks. There’s not a lot out there about IVIG, and I’ll caution that my experiences may not be universal, but this may help others know what to expect when they’re going for IVIG for the first time, regardless of condition. You’ll note I did not specify what condition I have or the reason I’m getting IVIG, and hopefully that helps people understand this has been my n=1 personal experience.

Feel free to drop any questions below, or share your own experiences or any tricks you’ve come up with to improve your own IVIG experiences (like I do with my heating pad to fight the cold arm effect).

Best practices in communication related to writing a journal article and sharing it with co-authors

I’ve been a single author, a lead author, a co-author, a corresponding author, AND a last author. Basically, I have written a lot of journal articles myself, solo / single, and with other people. One area in this process that I observe frequently gets overlooked is what happens during and after the submission process, as it relates to communicating about the article itself.

I’m not talking about disseminating the article to your target audience or the public, either (although that is important as well). I’m talking about making sure all authors know the article has been accepted; when it is live; have access to a copy of the article (!); etc.

Most people don’t know that by default, not all journals give all authors access to their own articles for free.

Here are some tips about the process of submitting and saving published articles that will help all authors – even solo authors – in the future.

Basically, help you help your future self! (As well as help your co-authors).

Journals typically only notify the lead/corresponding/submitting author about where the manuscript is in terms of revision, acceptance, and publication. That puts the responsibility on the lead/corresponding/submitting author to notify the full team of authors of where the article is in the process. Similarly, some journals will send a PDF/final copy of the proofed, final, version of record article to the lead author (not always, but usually), but that often does not go out to the full author team by default.

This means that it is the lead author’s responsibility to forward the copy of the final, PDF, proofed article to the entire authorship team so everyone has a copy.

(No, most of the time authors do not have free access to the journal they are submitting to. No, most authors do not have budget to make articles open access and free to all, which means unless they manage to snag and save this PDF article when it is sent to them at the time of publication, in the future, they may not have access to their very own article! Just because you, as the lead/corresponding author do have access, this does not mean everyone on your article team will.

I’m a good example of someone who authors frequently but is not at an institution and has zero access to any paywalled journals. If I’m not given a copy of my articles at the time of publication, I have to phone-a-friend (thanks, Liz Salmi, for being the go-to for me here) to help pull articles. There are things like S c i H u b, but they more often than not do not have super recent, fresh off the press articles. So yes, people like me exist on your authorship teams.)

Best practices for authors include:

  • Once you submit a manuscript, mark your file name (somehow) with “Submitted”. This way you know this is the version that was submitted. This is a useful step related to the below, we’ll come back to why we may want to use only the ‘submitted’ version.

    Example: “JournalAcronym-Article-Blah-Blah-SUBMITTED.docx”.

    Even as the non-lead author, when co-writing articles, as any type of author I prefer to have access to this submitted version. This way, I can see all incorporated edits and the ‘final’ version we submitted. There’s also cases where, see below, I need this for sharing it with other people.

  • Usually, the article goes through peer review and you get comments, so you make revisions and re-submit your article. Again, once submitted, make sure you’ve marked this as ‘revision’ somehow (usually people do) and that is was submitted.

    Example: “JournalAcronym-Article-Blah-Blah-SUBMITTED-R1.docx”.

    Again, best practice would be to send out this re-submitted revision version to all authors so everyone has it.

  • You may end up with multiple rounds of revisions and peer review (moving to R2, etc), or you may get an acceptance notice. Your article will then move to copyediting stage and you get proofs. It’s useful to save these for your own purpose, such as making sure that the edits you make are actually executed in the final article. This is less important for dissemination, though, although I do recommend giving all co-authors the ability to edit/review/proof and request changes.
  • Accepted, proofed, published! THIS is the step that I see most people miss, so pay attention.If you are the lead or solo author, you will probably get an email saying your article is now online, either online first or published. You may get an attachment PDF of your article. If not, you should be able to click on your access link and go to access the article online.

    IMPORTANT STEP HERE: go ahead and download the PDF of the article then. Right then, go ahead and save it.

    Example: “JournalAcronym-Article-Blah-Blah-Year.PDF”.

    (Why do you care about this if you are a solo author? Because the link may expire and you may lose access to this article. More on sharing your article below.)

  • Email your entire author team (if you’re not a solo author). Tell them the article was published; provide a link and/or the DOI link; and attach the PDF to the email so everyone on the team has a copy of the final article. Not all of your co-authors will work at an institution that has unlimited library access; if they do, that might change in the future. Give everyone a copy of the article to save for themselves.You can also remind everyone what the sharing permissions (or limitations) are for the article.

    For example, some articles are paywalled but authors have permission to store the final copy (PDF of the final version) on their own repository or not-for-profit website. For an example, see my research page of DIYPS.org/research – you’ll notice how sometimes I link to an “author copy” PDF, which is what this is – the final article PDF like you would get by accessing the paywalled journal.

    Other times, though, you are specifically not permitted to share the final/proofed/formatted copy. Instead, you’ll be allowed to share the “submitted” manuscript (usually prior to the revision stage). Remember how step 1 that I told you was to save a SUBMITTED copy? This is why! You can PDF this up; add a note to the top that references the final version of record (usually, journals give you recommended language for this) and a link/DOI link to it, and share away on your own site. Again, look at DIYPS.org/research and you’ll notice some of my “author copy” versions are these submitted versions rather than the final versions.

    You’ll also notice that sometimes I link to articles that are open access and then also have a link to a PDF author copy. This is in case something changes in the future with open access links breaking, the journal changing, etc. I have actually had free non-paywalled articles get turned into paywalled journal articles years later, which is why I do point to both places (the open access version and a back up author copy).

    Regardless of what the permissions are for sharing on your own website/repository/institutional repository: you as the author always have permission to give this PDF out when you are asked directly. For example, someone emails you and asks for a copy: you can email back and attach the PDF! This is true even if the permissioning for your own website is the submitted version (not the final version), you can still hand out the final, formatted, pretty PDF version when asked directly.

    As a related tip, this is a great way to disseminate your research and build relationships, so if someone does email you and ask for an author copy…please reply and send them a copy. (Saying this as someone without access to articles who sends requests to many authors to get access to their research, and I only get responses from 50% of authors. Sad panda.) Again, this is why it is helpful to get in the habit of saving your articles as you submit and have them published; it makes it easy to jump into the “Published copy” folder (or however you name it) and attach the PDF to the email and send it.

To recap, as a best practice, you should disseminate various versions of articles to your entire co-author team at the following points in time:

  • Original submission.

    Suggestion: Write an email, say you’ve successfully submitted, remind everyone which journal this was submitted to, and attached a copy of your “JournalAcronym-Article-Blah-Blah-SUBMITTED.docx”(If you end up getting a desk rejection, and you are re-submitting elsewhere, it is also nice to email co-authors and tell them so. You don’t necessarily need to send out a newly retitled version, unless there’s new changes to the submission, such as if you did go through a partial round of peer review before getting rejected and you are submitting the revised version to the new target journal.)

  • Revision submission.

    Suggestion: Write an email, say you’ve successfully submitted the revisions, remind everyone which journal this was submitted to, and attached a copy of your “JournalAcronym-Article-Blah-Blah-SUBMITTED-R1.docx” and the reviewer response document so everyone can see how edits/feedback were incorporated (or not).

  • Acceptance.

    Suggestion:

    A) Forward the email if it has the PDF attached to your full author team. Say congratulations; the article was accepted; and point out the article is attached as PDF.

    B) If you don’t have a PDF attachment in your email already, go to the online access link the journal gave you and save a copy of the PDF. Then, email the author team with the FYI that the article is live; provide the link to the online version; and attach the PDF directly to that email so everyone has a final version.

    Regardless of A or B, remind everyone what the permissions are for sharing to their own/institution repository (eg final PDF or use the submitted version, which you previously shared or could also re-share here).

Bonus tip:

Depending on the content of your article, you may also want to think about sending copies of the final PDF article to certain people who are not co-authors with you.

For example, if you are heavily citing someone’s work or talking about their work in a constructive way – you could email them and give them a heads up and provide a copy of the article. It’s a great way to contribute to your relationship (if you have an existing relationship) and/or foster a relationship. Remember that many people will have Google Scholar Alerts or similar with their name and/or citation alerts from various services, so people are likely to see when you talk about them or their work or are heavily citing their work. Again, some of those people may not have access to your article and may reach out to ask for an article; you can (and should) send them a copy! (And again, consider thinking about it as a relationship building opportunity rather than a transactional thing related to this single article.)

I would particularly flag this as something to pay attention to and do if you are someone working in the space of patient engagement in healthcare. For example, if you write an article and mention them or their body of work by name, it would be courteous to email them, let them know about the article, and send them a PDF.

Otherwise, I can speak from the experience of being talked about as a patient like I’m an ant under the microscope where someone cites an article where my work is mentioned; talks about me by name and references my perspective; and I get a notification about this article….but I can’t access it because it’s in a paywalled journal. Awkward, and a little weird in some cases when the very subject of the article(s) are about patient engagement and involving patients in research. Remember, research involvement should include all stages from design, planning, doing the research, and then disseminating the research. So this meta point is that if there is scholarly literature of any kind (whether original research articles or reviews, commentaries, letters in response to other articles, etc) talking about specific patients and their bodies of work – best practice should be to email them and send a copy of the article. Again, think less transactional and more about relationships – it will likely give you benefit in the long run! Plus, less awkward, a short-term benefit.

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best practices for communicating with co-authors about published articles, by Dana M. Lewis from DIYPS.orgAs an example for how I like to disseminate my articles personally, every time a journal article is published and I have access to it, I updated DIYPS.org/research with the title, journal, a DOI link (to help people find it online and/or cite it), and a link to the open access version if available and if not, an author copy PDF of the final or submitted version. So, if you’re ever looking for any of my articles, you can head there (DIYPS.org/research) first and grab copies any time!

If you are looking for a particular article and can’t find it or it’s not listed there yet (e.g. likely because it just came out and I haven’t been sent my own copy by my co-authors yet…), you can always email me directly (Dana@OpenAPS.org) and I’m more than happy to send you a copy of whatever version I have available and/or the final PDF once I have access to it.