Topic Archives: Data and Your Doc

QS Primer: Case-Crossover Design

We’ve already published this QS Show&Tell talk by Mark Drangsholt about using self-tracking to identify the triggers of his heart problems, lessen their frequency, and make good decisions about treatment. I’m re-posting it here to focus on attention on the interesting and powerful method Mark used, the case-crossover design, and invite you to think about whether this has promise for your own self-tracking projects.


Mark is a professor and chair of oral medicine at the University of Washington School of Dentistry. He’s a triathlete and long time self-tracker. He is in good physical condition, but suffers from heart ailments that are frightening and dangerous. For instance, he has tachycardia (sudden acceleration of heart rate). At times his heart goes from 60 to 220 beats per minute. It feels like his heart is going to jump out of his chest. He also has atrial fibrillation, with palpitations, a feeling of immanent doom, and a sense that he is choking.

“The first time it happened in 2003 I really thought I was dying,” Mark says in his talk. He had always assumed that if he ever had a heart attack he, of all people, would know to pick up the phone and call 911, but the opposite happened. He just thought to himself “this is it,” and slumped down in his chair. Fortunately, he survived, and when he recovered he asked himself whether he could identify the triggers of these unpleasant events and avoid them. He created a simple Excel table of all episodes for one year, on which he recorded information about his attacks.

Mark is an expert on evidence based medicine, so he was naturally curious about what kind of evidence his self-tracking data contained. In standard reference material on medical evidence, students learn about a hierarchy that goes something like this:

  1. 1 or more randomized controlled trials
  2. 1 or more cohort studies
  3. 1 or more case-control studies
  4. 1 or more case-series
  5. expert opinion without above evidence

Mark’s self-tracking data didn’t naturally fit with any of these approaches. To understand whether these triggers actually had an effect on his arrhythmias, he used a special technique originally proposed by the epidemiologists Murray Mittleman and K. Malcolm Maclure. A case-crossover design is a scientific way to answer the question: “Was the patient doing anything unusual just before the onset of the disease?” It is a design that compares the exposure to a certain agent during the interval when the event does not occur to the exposure during the interval when the event occurs.

Using this method, Mark discovered that events linked to his attacks included high intensity exercise, afternoon caffeine, public speaking to large groups, and inadequate sleep on the previous night. While these were not surprising discoveries, it was interesting to him to be able to rigorously analyze them, and see his intuition supported by evidence.
“A citizen scientist isn’t even on the conventional evidence pyramid,” Mark notes. “But you can structure a single subject design to raise the level of evidence and it will be more convincing.”

Please let us know if you use this method in your own projects. We’ll post more reports when we have them.

REFERENCES AND GUIDES

There are some tricks to doing a good case-crossover study on yourself. Mark’s video provides a basic introduction.  For technical details, this detailed introduction to case-crossover design by Yue-Fang Chang especially useful.

The seminal paper on case-crossover design is “The Case-Crossover Design: A Method for Studying Transient Effects on the Risk of Acute Events” by Malcom Maclure. (1991) [PDF] A search on Google Scholar for case-crossover design will get you deep into this literature. Unfortunately very little of it involves the kind of n-of-1 studies we’re usually interested in, but there are many technical details that may contain clues for dedicated experimenters.

One paper that will be of special interest is this one: “Should We Use a Case-Crossover Design?” by K. Malcolm Maclure and his collaborator Murray Mittleman. (2000) [PDF] In the midst of discussing technical details important for scientists proposing to use this method in studies funding by research grants whose reviewers may not be familiar with it, Maclure and Mittlemen describe using case-crossover analysis to retrospectively understand more about the death of Maclure’s father. I quote the relevant section below:

We did an n-of-1 case-crossover study of hypothesized triggers of repeated syncope experienced by Kenneth Maclure (MM’s father), who was diagnosed with sick sinus syndrome and died of fatal MI at age 73 during a morning swim, after several other potential triggers. The target person times wereKenneth’s 62nd–74th years (and subsequent years if he had lived longer). The study base comprised the years 1980–1981 and 1986, during which there were 33 instances of syncope. We restricted the study base to those years because his wife, Margaret, was willing to review only 3 years of her diaries because the memories rekindled her grief. We had no intention to generalize the findings to other individuals, only to other years. Our goal was to identify triggers to which Kenneth may have been susceptible and to test Margaret’s general hypothesis, “Perhaps I should have done more to help him avoid stress.” Hypothesized triggers included visitors to the home, trips out of town, eating out, unusual exertion, and so on. The 24-h period before an episode of syncope was classified as a case day. Each case day was matched with a control day, the same 24-h period 2 weeks before. Margaret was surprised by our null findings and relieved some lingering feelings of guilt.

 

 

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Talking Data With Your Doc: The Doctors

One day you decide to lead a data-driven life and naturally data collection seeps into the realm of health. Maybe you buy a Zeo to better understand your sleep patterns. Or maybe you decide to start tracking your blood pressure with one of the various new connected tools. Heck, maybe you’re just tracking your daily pain symptoms using plain old paper and pencil. Whatever it is you’re tracking, most likely you have the urge, the need, to take it to your physician or medical provider. That data represents you, the whole you, not just the you that sits on that sterile paper that’s rolled onto the examination bed in the cramped room with the poor lighting and six-month old issue of Time magazine.

Last week we discussed how you could present that information, your health data, to your doctor. The wonderful Katie McCurdy helped us understand the power of simple visualizations for her ongoing care and her own personal health knowledge. The patient perspective is incredibly important, as they say, “everyone is a patient at some point.” But, not everyone sits on the other end of the table, not everyone is a doctor. So what do physicians think about patient data? What do they see happening in their practices? Today, we’re lucky to have two wonderful physicians join us to offer their insights into those questions and more.

Dr. Eric Topol is an innovator and pioneer in the fields of wireless medicine and genomics. He is the Director of the Scripps Translational Science Institute, a National Institute of Health funded program of the Clinical and Translational Science Award Consortium. He is also Professor of Genomics at The Scripps Research Institute; Chief Academic Officer and holder of the Gary and Mary West Chair of Innovative Medicine at Scripps Health; and, a Senior Consultant cardiologist practitioner at Scripps Clinic. He is also the author of the recently released book, Creative Destruction of Medicine.

Dr. Larry Chu is a practicing anesthesiologist and an Assistant Professor of Anesthesia at Stanford Medical School. He also directs two separate research labs at Stanford – the Opioid Physiology Lab and the Anesthesia Informatics Lab. In his spare time (the man doesn’t sleep!) he directs the efforts for the upcoming MedicineX conference: a showcase of academic research, new technology, and patient stories designed to help guide the future of healthcare. I highly recommend watching their newly released e-patient videos that highlight two QS community members – Sean Ahrens and Hugo Campos.

Both Dr. Topol and Dr. Chu were kind enough to lend some of their time to answer a few of our questions. I hope you enjoy their thoughtful answers as much as I did.

QS: We keep hearing horror stories about doctors reacting negatively to patients who bring in their own health data. Why do you think that is?

Dr. Eric Topol: It reflects “old medicine” which is the current standard of care, characterized by paternalism, the “medical priesthood” and “Doctor Knows Best.” This will change and desperately needs to change to a participatory partnership of the patient and physician.

Dr. Larry Chu: I’m not sure that I can speak for other doctors, but I can tell you that I not only encourage my patients to self-track, but that I actually use those information streams every day to make decisions about each patient’s care. I treat patients with chronic pain. I have my assistants call my patients each day to get their pain scores, and ratings of medication side effects. I also ask my patients to keep daily diaries of their pain scores, side effects, and ratings of their ability to do activities of daily living. Working together, we use this information to tailor daily adjustments to their medications that I think not only improves their overall care but makes us better partners in a process that aims reduce pain while minimizing medication side-effects. Self-tracking brings me new data about each of my patients on a daily basis, which gives me new information and ideas on how to continually improve their care.

QS: How can a patient more appropriately create a dialog about their self-tracking and health data with their health provider(s)?

ET: By simply collecting the data and finding a receptive physician. Most doctors are data-driven and many would be enthusiastically supportive. 

LC: I think it starts with sharing data that helps doctors understand what they want to know. Your doctor might ask you, “How’s your back pain been since I saw you last?” That might be the perfect opportunity to share pain diaries (or even a visualization of pain scores over time) to help your physician understand trends in symptoms and how they are affected by medications and other factors such as activity and exercise. 

Data overload is a concern, so a focus on presenting concise data relevant to your physician’s interest might be a good way to start introducing self-tracking data into your physician visits.

QS: You illustrate a lot of examples of how the digital revolution is foundation of the Creative Destruction of Medicine in your book. What are a few fundamental shifts you see happening in the near future (1y? 5yrs?)

ET: 1 yr-the introduction of a large number of biosensors and “adds” that are smartphone centered and measure most physiologic metrics, or perform medical diagnostic tests like skin scan, refracting the eyes for glasses, and so many more; rapid sequencing for rare conditions, cancer at the time of initial diagnosis for genomically guided thearpy. 

5 yr—marked change in the basic structure of the office visit with more Skype, Facetime, video chatting and less need of hospital beds except intensive care units—with the marked reliance on remote monitoring; routine genotyping before many drugs are given to avoid serious side effects and assure the drug will indeed be effective

QS: Do you think doctors are more receptive to the visual translation of data rather than the raw numbers that are commonly associated with health data?

ET: Yes, without question, anything that makes it more reductionist, simple, and less time consumptive.

LC: Absolutely. Physiologic processes have natural variability between patients and when tracked prospectively over time. Very rarely in my practice do I treat a “number”. I find that trends in data over time are the most useful in helping me understand physiologic processes in order to provide a diagnosis and therapeutic care plan for my patients.

QS: I’ve been thinking about the doc-patient relationship a lot lately. It seems the walls of authority are crumbling as we speak and we’re moving from a “You do this” or “You listen to me” type of authoritative approach to medicine to more conversational. How do you see data and visualizations helping to start and possibly support those conversations.

ET: There will be a Darwinian selection process for the “digital doctors” who have the plasticity to engage with patients in this way.

LC: Paternalism in medicine will hopefully diminish as physicians see that patients not only prefer but demand to participate and engage in their own care and that this engagement leads to better partnerships that produce better health outcomes. Self-tracking data and visualizations can help support that process. One example is medication compliance in my area of pain management. The very term “compliance” is a bit paternalistic because it implies that patients are expected to “comply” with a physician’s “orders”. If Mrs. Jones has been “non-compliant” with her medications, the reason might be more complicated than a simple failure to follow directions. Self-tracking allows me to see what happened: nausea and itching were out-of-control and limited her ability to increase her dose, or she had several high-activity days that exacerbated her pain. Self-tracking data, especially real-time streams that are passively collected with high resolution and granularity, have the potential to disrupt the paternalistic view of the patient-physician relationship. To me, that’s very exciting.

QS: Katie McCurdy mentions in her post that the reception from patients and caregivers has been really positive, how would do we help make it a positive and rewarding experience for the providers as well?

ET: Her remarkably careful and detailed self-assessment of her myasthenia gravis condition is prototypic of how data can be displayed. Our big mission is to reduce the work involved in capturing and graphing the data, but instead to have this done seamlessly. No question that data are good for one’s health. It’s the kind of data we did not have access to before in treating patients. Sensors, apps, and add-ons to smartphones will help to streamline this process.

LC: Make providers part of the process. Give us an opportunity to let you know what data we would love to see you track. Help us understand your concerns and how we can help you achieve your health goals. 

QS: What tips or advice would you give to someone who is taking their data to their doc for the first time? 

ET: Go for it! Don’t be shy. It’s your data, your body, your health. You are the most vested and important individual for the future of your health!

LC: Start with a picture, something simple, that helps your doctor better understand your body in relation to the reason for your visit. Data overload is a concern. Start by turning the spigot on slowly.

QS: How do you think self-tracking and data communication with physicians can support patient-initiated health experimentation?

ET: It will be the N of 1 story to find the right drug for conditions like high blood pressure or diabetes (Type 2, non-immune) and many other conditions. Moreover it will be invaluable for prevention, for which we will have a marked enabling capacity once we integrate genomics, sensors, health IT, the digital infrastructure and N of 1 —what I call Homo digitus–data! 

LC: I think self-tracking can provide real-time physiologic and symptom data to physicians to aid them in interpreting the success of patient-initiated health experiments. I use self-tracking to study physician-initiated health experiments in my NIH-funded clinical research lab at Stanford. I don’t see a reason why the tables can’t be turned.

We also have some questions from Susannah Fox, who was kind enough contribute her thoughts and insights to this piece:

SF: True or false: There have always been patients like Katie, who try to figure out what’s going on with their health. It’s just now that they have tools to polish up and express their observations in engaging ways. It’s just now that clinicians are ready to listen to and even welcome such patients.

ET: True for many conditions.

LC: True. We have been self-tracking even before there was the term. I got to mark my height on my door frame every birthday growing up: I was a self-tracker at age five! There is a temptation to focus on technologies and tools in self-tracking, but they are not a necessity for the process. A pen and paper will suffice. What I see today is an explosion of consumer-facing devices, some of which passively collect high-resolution and finely granular datasets. This may add to the data streams we can collect, but analysis and synthesis of the data into meaningful conclusions is a growing challenge.

SF: If you are observing a shift, in yourself or in your colleagues, why do you think that is?

ET: I have shifted my practice, but unfortunately I have not seen a significant shift in many others yet. That’s why I wrote the book—to educate, activate consumers to catalyze “new medicine”  They need to drive this—it is their medical information, their DNA, their tissue, their smartphone, and their social networks. Never before were we so well positioned for a consumer health care revolution as now. A veritable Kairos.

LC: I think mobile computing and wireless mobile devices have exposed physicians to many of the same consumer-facing self-tracking applications that their patients use. As patients ourselves, many physicians see the potential for self-tracking to impact our own health and lives.

Having read through these answers again and again I can safely say there are some major themes that are starting to creep up. Partnerships, excitement, mHealth – each of these concepts were mentioned on more than one occasion by these two amazing members of the medical establishment. Hopefully their insights will help give you the small push to begin speaking to your medical provider about your health data. The data you collect. The data that represents you.

Again, this is part two in a three-part series on the data centric conversation we engage in with the medical community. Look for our next part with insights from Susannah Fox next Thursday. If you have questions of comments feel free to discuss on FacebookTwitter, and here in our comments.

 

 

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Talking Data With Your Doc : The Patient

Data.

Health.

Communication.

In our daily lives, we are keenly aware of the power of each of these individual concepts. However taken together, their influence on our wellbeing, to borrow a phrase from my friend Karen Herzog, “our wholeness”, is exponentially influential. So why do they seem to rarely coalesce during our conversations, discussions, and interactions with the individuals and institutions tasked with tracking, diagnosing, and treating the cracks and fissures in our wholeness?

This is the first in a three-part series about the data we produce about our health and how we communicate that information to the medical system, specifically the providers of care. We’re starting from the perspective of the patient because we’ve all been there. Whether it was a routine check up or a 3AM visit to the emergency room, we’ve all had to relay information to a medical provider about out health. So what happens when we’ve collected, stored, and tried to understand our own health information in preparation for those visits?

Our guide today for the patient perspective of health data communication is Katie McCurdy. Katie is a user experience designer and researcher living and working in New York. She is also living with Myasthenia gravis, an autoimmune disease that causes muscle weakness  in voluntary muscles. Like many individuals with  autoimmune diseases, Katie spend a lot of time communicating and working with the medical system. These visits, although regular, were a point of contention between Katieand the individuals entrusted with her care. So when she was going to see a new physician for the first time she decided to apply her interaction design knowledge and skill. She’s talked about this on her blog and on the e-patients.net blog so I’ll let here words speak for themselves:

As I was getting ready to see a new doctor, I realized that the best way to tell my story would be to create a medical “life story” timeline that reflected:

  • The course of my autoimmune disease
  • Severity of my gastrointestinal problems
  • Key moments in time when I started and stopped certain medications or took antibiotics
  • Any significant dietary changes

I sketched out the two timelines (autoimmune and gastrointestinal) separately, and then created them electronically using Adobe Illustrator. (I’m an interaction designer by day, so fortunately I had the skills/know-how to create a somewhat legible artifact.) I used a peach color to represent gastrointestinal wellness/symptoms, and a blue color for Myasthenia Gravis.

Katie's Medical Timeline

Katie was kind enough to answer a few questions and we’re grateful to be able to share her responses here with you today.

QS: Why visualize? Do you think doctors are more receptive to the visual translation of data rather than the raw numbers that are commonly associated with health data?

KM: For me it’s about creating a representation of my history and my health that can be communicated most efficiently. I believe in the power of visualization to help tell stories that wouldn’t be possible with raw data alone. Knowing I would be ‘on the spot’ during my doctor visit put the pressure on to make something that would help me tell my story as succinctly as possible. Also…because I was not tracking my data (it’s all from memory) I didn’t have the raw data to share anyway!

QS: I’ve been thinking about the doc-patient relationship a lot lately. It seems the walls of authority are crumbling as we speak and we’re moving from a “You do this” or “You listen to me” type of authoritative approach to medicine to more conversational. How do you see data and visualizations helping to start and possibly support those conversations.

KM: I see it as, like you said, changing the dynamics of the relationship so that the patient is more of a partner in care. By tracking data, the patient can provide a more refined and nuanced picture of what is really going on with them. By visualizing that data, the patient is helping the doctor absorb the information more painlessly. The patient is providing contextual information about his or her OWN situation that compliments the doctor’s past experience, expertise, and test results.

QS: You mention in your post that the reception from patients and caregivers has been really positive, how would do we help make it a positive and rewarding experience for the providers as well?

KM: I think that giving patients tools to create simple, clean, and attractive visualizations could help make the experience better for doctors. If doctors are presented with high-quality visualizations that tell a coherent story, it may make office visits more efficient. Imagine if the doctor could work with the patient and suggest a type of graph or visualization that would be most helpful.

QS: What tips or advice would you give to someone who is taking their data to their doc for the first time?

KM: I suggest using the data as a storytelling tool. Bring a printed artifact or something on a tablet to refer to, and point out the highlights as you talk about what’s been going on with you. Don’t be disappointed if they don’t comment on your beautiful data and all of the work you put into it. Ask if there is anything you can do to to make the data more legible/easy to understand for the doc.

QS: You mention that self-tracking has given you better insights into your own health and that you’re even trying some self-experimentation like a no-carb diet. How do you think self-tracking and data communication with physicians can support patient-initiated health experimentation?

KM: Ah, I think self-tracking and visualization can help increase patient compliance! My low-carb diet was actually prescribed by my doctor. When I saw on the timeline that my diet changes were strongly correlated with my gastro symptoms improving, it was very reinforcing of my diet behavior. I mentioned antibiotics in my post. Now, if I even think of asking for antibiotics, all I can see in my mind is the number of antibiotics I took as my stomach issues got worse and worse. That is a big change in my outlook that resulted from internalizing the data I was seeing on the timeline.

QS: Who are your design/data viz heros? Anyone who really inspires you in your health visualizations?

KM: I have a few data viz heros! Jer Thorpe, of the new york times, makes beautiful interactive data visualizations and is one of the best speakers I have ever seen. Nicholas Felton, of Feltron and now a designer at Facebook, is a compulsive self-tracker who releases a gorgeous printed yearly report. I love Mortiz Stefaner’s work as well. I am really inspired by the natural world and the work of 19th century plant and wildlife documentor Ernst Haekel. I am also inspired by the awesome patients I’ve met and the folks on e-patients.net who remind me that patients need to be their own advocates.

We also have some questions from Susannah Fox, who was kind enough contribute her thoughts and insights to this piece:

SF: Would Katie care to comment on that from her own experience? That is, is it only recently that she has both found the right tools and that her own clinicians are interested? Had she attempted something earlier, with pencil & paper? What has made the difference?

KM: I never did anything before this apart from bringing notes to my doctor visits – things to remember to say. I literally had a realization one day at work and wrote an email to my personal account with the subject: ‘very important idea.’  :)  I think the idea had to incubate for a few years before it bubbled up.last fall. 

My goal is to keep pursuing this idea and work toward creating a tool for patients so they can at least assemble their own health timeline, and perhaps even track their data more regularly. I am holding interviews with patients, patient caregivers (or parents), and people who are active self-trackers; if you are interested in donating about 30 minutes of your time, email me at kathryn.mccurdy at gmail.com.

Again, this is part one in a three-part series on the data centric conversation we engage in with the medical community. Look for our next part with insights from Dr. Eric Topol and Dr. Larry Chu next Thursday. If you have questions of comments feel free to discuss on Facebook, Twitter, and here in our comments.

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