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Self-Care and Caregiving Apps Development

Have I gotten to the end of the beginning in developing tools that help people take care of themselves?

With the recent release of Unfrazzle, an app for caregivers, I believe I have. Unfrazzle builds upon the learnings of Zume Life and Tonic, earlier apps I developed. There were key lessons from hundreds of users and family caregivers that influenced Unfrazzle’s product design, driving it in directions very different from and hopefully much more useful than what you might expect.

These key lessons, explored in more detail below, I group into three themes:

  • Care regimens constantly vary, and so tools must accommodate such variation
  • We live in a network of mutual caregiving, and simple notions of “the patient” or “caregiver–care recipient” match few people’s reality
  • Living, yes living, is much more important than adherence
  • For those unfamiliar with Unfrazzle, here’s a brief description:It is an iPhone app (Android coming soon) that helps users remember and keep track of anything they do to take care of themselves and their family (parents, friends, children, pets), and to stay in-sync with other caregivers in their family. Unfrazzle is a Design-It-Yourself app — it essentially provides a platform, a framework that the user then shapes to meet his own ever-changing needs.

    If that sounds clear as mud, try this: take your favorite pill reminder app, and imagine that you can change all the screens and forms to accommodate any health & wellness activity (not just pills but also other things such as exercises, moods, symptoms, observations, and chores). Then imagine that you can share any of your data with others also using the app, so that you can see each other’s entries. Imagine you can even allow others to make entries for you, then you’ve got the gist of Unfrazzle.

    Care Regimens Constantly Vary

    From the start,  beginning with Zume Life, our focus has been on making it easier for people to remember and track their health regimens. We began by targeting a simple, logistical problem — in our busy lives it is easy to forget little details.

    Our idea was that adherence would be improved if we had a memory aid.

    Our tool had to be somewhat flexible, because we took the approach that we could not possibly know everything a person might be doing for his health. For example, allowing a person to include their supplements in their list of medications, and not just their prescriptions.

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    Building Cost and Quality Into the Electronic Medical Record

    Trends in US healthcare expenditures are financially unsustainable (1). I would like to propose two tweaks of the healthcare delivery process that may, in a small way, help rectify this problem.

    Although there is a widespread impression that health information technology (HIT) will eventually “bend” the cost curve and put healthcare spending on a sustainable course, there is, as of yet, little data that convincingly supports this hypothesis (2).

    Kaiser Permanente is a large, integrated healthcare delivery system which has invested heavily in HIT. George C. Halvorson, the chairman and CEO of Kaiser Permanente appears to have concluded that this investment will not solve the healthcare cost issue, when he was quoted in the New York Times (3/20/13) as stating “We think the future of health care is going to be rationing or re-engineering.”

    Because HIT, as currently implemented, will probably not solve the healthcare cost problem, I would like to suggest a minor “re-engineering” of the electronic health record user interface which may help bend the cost curve.

    At every office visit, the physician must make a myriad of decisions which incrementally effect the nation’s total healthcare expenditures. For example, the physician will have to decide which medicine to prescribe, and which radiology study or laboratory test to order.

    In many situations, there is more than one acceptable choice. The physician’s ultimate decision will integrate their understanding of the disease process, the treatment’s side effect profile, their familiarity with the treatment options, patient preferences and many other variables.

    I would suggest that every time a physician is about to order a test or a prescription, the cost of the test or prescription should be displayed to the physician. In the same vein, whenever a computer displays a test result, the cost of the test is immediately available to the reader. This information could then become an additional factor that the physician may choose to integrate (or ignore) at the moment when he/she is about to commit the patient and society (which is now paying >50% of all healthcare bills) to another healthcare expenditure. In terms of a risk/benefit analysis, I can see little downside to providing this cost information to physicians.

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    A Case for Open Data

    A couple of weeks ago, President Obama launched a new open data policy (pdf) for the federal government. Declaring that, “…information is a valuable asset that is multiplied when it is shared,” the Administration’s new policy empowers federal agencies to promote an environment in which shareable data are maximally and responsibly accessible. The policy supports broad access to government data in order to promote entrepreneurship, innovation, and scientific discovery.

    If the White House needed an example of the power of data sharing, it could point to the Psychiatric Genomics Consortium (PGC). The PGC began in 2007 and now boasts 123,000 samples from people with a diagnosis of schizophrenia, bipolar disorder, ADHD, or autism and 80,000 controls collected by over 300 scientists from 80 institutions in 20 countries. This consortium is the largest collaboration in the history of psychiatry.

    More important than the size of this mega-consortium is its success. There are perhaps three million common variants in the human genome. Amidst so much variation, it takes a large sample to find a statistically significant genetic signal associated with disease. Showing a kind of “selfish altruism,” scientists began to realize that by pooling data, combining computing efforts, and sharing ideas, they could detect the signals that had been obscured because of lack of statistical power. In 2011, with 9,000 cases, the PGC was able to identify 5 genetic variants associated with schizophrenia. In 2012, with 14,000 cases, they discovered 22 significant genetic variants. Today, with over 30,000 cases, over 100 genetic variants are significant. None of these alone are likely to be genetic causes for schizophrenia, but they define the architecture of risk and collectively could be useful for identifying the biological pathways that contribute to the illness.

    We are seeing a similar culture change in neuroimaging. The Human Connectome Project is scanning 1,200 healthy volunteers with state of the art technology to define variation in the brain’s wiring. The imaging data, cognitive data, and de-identified demographic data on each volunteer are available, along with a workbench of web-based analytical tools, so that qualified researchers can obtain access and interrogate one of the largest imaging data sets anywhere. How exciting to think that a curious scientist with a good question can now explore a treasure trove of human brain imaging data—and possibly uncover an important aspect of brain organization—without ever doing a scan.

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    Are Employers to Blame For Our High Medical Prices?

    In a recent New York Times blog, Uwe Reinhardt places much of the blame for high and rising medical prices on passive employers. He argues that employers should work just as hard to reduce healthcare benefit costs as they work to reduce other input costs. But he then observes:

    “One reason for the employers’ passivity in paying health care bills may be that they know, or should know, that the fringe benefits they purchase for their employees ultimately come out of the employees’ total pay package. In a sense, employers behave like pickpockets who take from their employees’ wallets and with the money lifted purchase goodies for their employees.”

    I think that Reinhardt gets the economics wrong here and, in the process, he puts too much of the blame on employers. Reinhardt is right in one respect – employees care about their entire wage/benefit packages. If benefits deteriorate, employers will have to increase wages to retain workers. Thus, it seems that if an employer reduces benefit costs, it must increase wages by an equal amount. If that is true, we can understand why employers are passive.

    The correct economic argument is a bit more nuanced. Employees do not care about the cost of their benefits; they care about the benefits. If an employer can procure the same benefits at a lower cost, the employer need not increase wages one iota. In this regard, there is nothing special about health benefits. Suppose an employer offers employees the use of company cars. Workers don’t care what the employer paid for the cars, and if the employer can purchase cars at a deep discount, it will pocket the savings.

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    Targeting Obesity With Health Care Reform

    The Medicare Board of Trustees just released its latest report on the program’s finances and the results are terrifying. Despite a decline in health care costs, the Medicare Trust Fund will be bankrupt in 2026.

    For the program to survive for future generations, innovation will be essential. The old medical paradigm of diagnosing and treating diseases must give way to a more holistic approach aimed at eliminating risk factors that lead to disease. The best place to start is by addressing the growing problem of adult obesity.

    In the past 30 years, the percentage of American adults who are obese has doubled, driving a sharp rise in such chronic conditions as diabetes, heart disease and hypertension.

    The ramifications for health spending are significant. Annual health costs for obese individuals are more than $2,700 higher than for non-obese people. That adds up to about $190 billion every year. And many of these costs are borne by Medicare, which will spend a half-trillion dollars over the next decade on preventable hospital readmissions alone.

    We cannot afford to wait until patients are on Medicare to fight obesity. Rather, we need to encourage weight control over the course of patients’ lives.

    Fortunately, we now have an ideal opportunity to implement reforms. The new health insurance exchanges created under the Affordable Care Act can establish effective care coordination strategies to identify and treat chronic conditions earlier, addressing not just the immediate conditions but the underlying ones as well. Obesity is one of the most common. Medicare, in turn, can adopt these strategies, and the benefits for both patients and taxpayers will be substantial. Continue reading…

    Online Won’t Ever Replace Face-to-Face. Or Will It?

    The simple explanation is a proverb that has been stated in similar ways in various cultures for more than 2,000 years: “The eyes are the window to the soul.”

    Not, mind you, “Windows® is the eye to the soul.”

    Trust me, I appreciate computer technology and am ever-grateful for the benefits it has yielded me personally and to the patient group I represent, Spontaneous Coronary Artery Dissection (SCAD). Without a computer, search engine, and online community, I never would have met another SCAD survivor, and Mayo Clinic definitely would not be in the weeds of a virtual registry of SCAD survivors, plus a DNA biobank of patients and families from around the globe, at this very moment.

    I grew up in locales where catching crabs with a chicken neck on a string and casting a net for shrimp were common practices, and in each, patience is the operative word. If you look at the case of patient-initiated research into SCAD (or any other rarely diagnosed condition), you see a progression that requires patience. The process begins vast – much like seining – and ends personal. For me, what began on AOL.com as my Internet search for any and all references to “heart dissection,” was turbocharged by Google and its evolution. (I remember worrying about what would happen to my computer if I tried this “thing” everyone was talking about. It seemed daring enough to be on AOL instead of mindspring!) But Google led me to an organization, WomenHeart: The National Coalition for Women with Heart Disease, and the online community it runs in partnership with Inspire, the Inspire/WomenHeart Support Community.

    And there, on www.inspire.com/groups/womenheart is where our little incubator of SCAD patients formed. Very slowly at first, but thanks to Google’s search and display features, the pace picked up over time and we grew into the hundreds. Then, Facebook was launched, providing a seemingly more personalized venue to interact. Next Twitter, which (although ultra concise at 140 characters per tweet) is an easy way to connect with likeminded souls, similar to that instant bond when walking down the street and sharing “Great game, huh?”

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    How My Parents’ Death Changed My Thinking About End-Of-Life Care

    My sister and I took our positions in the funeral home’s family room and greeted hundreds of mourners who had come to pay their respects. Everything seemed as it had four months earlier at our mother’s funeral. The ubiquitous tissue boxes. My navy pinstriped suit. The ripped black ribbon, a Jewish tradition, affixed to my lapel.

    But this time, we were accepting condolences after the death of our dad, who stood next to us such a short time before.

    It’s hard enough to lose one parent. Losing two within months is incomprehensible. When I left my parents’ Michigan apartment last month, I couldn’t believe it would be for the last time. I’ve replayed phone messages so that I could hear their voices again. And each morning, I look at Dad’s watch on my wrist, thinking it should be on his.

    Two days before my dad died, I celebrated the first Mother’s Day without my mom. Now, I’m marking the first Father’s Day without my dad.

    As I’ve mourned my parents, I’ve been struck by how many stories I’ve heard about husbands and wives dying soon after their spouses. One of my high school teachers lost both parents within a year; so did a journalist friend in Los Angeles. My rabbi told me his parents died only months apart.

    My mom buried both of her parents within the same week in April 1979, when I was 5. My zaydee died first, unable to fathom life without his wife, who lay dying in the hospital. My bubbe died during his funeral two days later.

    I wondered whether there was more to this than coincidence, and sure enough, there’s a well-documented “widowhood effect.” Those who lose a spouse are about 40 percent more likely to die within six months than those with living spouses. The effect has been found in a host of countries, across a range of ages, in widows and in widowers – though men are more likely to die soon after losing spouses than women are.

    S.V. Subramanian, a professor of population health and geography at Harvard University, co-wrote a review published in 2011 that looked at more than a dozen studies on the effect. “We never say that grief is a disease,” he told me. “But what some of this research is showing is that at older ages, grief can make you more vulnerable to mortality.”

    Subramanian said his uncle’s parents died within days of one another.

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    Chapter Nine: In Which Dr. Watson Discovers Med School Is Slightly Tougher Than He Had Been Led to Believe

    One of the computer applications that has received the most attention in healthcare is Watson, the IBM system that achieved fame by beating humans at the television game show, Jeopardy!. Sometimes it seems there is such hype around Watson that people do not realize what the system actually does. Watson is a type of computer application known as a “question-answering system.” It works similarly to a search engine, but instead of retrieving “documents” (e.g., articles, Web pages, images, etc.), it outputs “answers” (or at least short snippets of text that are likely to contain answers to questions posed to it).

    As one who has done research in information retrieval (IR, also sometimes called “search”) for over two decades, I am interested in how Watson works and how well it performs on the tasks for which it is used. As someone also interested in IR applied to health and biomedicine, I am even more curious about its healthcare applications. Since winning at Jeopardy!, Watson has “graduated medical school” and “started its medical career”. The latter reference touts Watson as an alternative to the “meaningful use” program providing incentives for electronic health record (EHR) adoption, but I see Watson as a very different application, and one potentially benefitting from the growing quantity of clinical data, especially the standards-based data we will hopefully see in Stage 2 of the program. (I also have skepticism for some of these proposed uses of Watson, such as its “crunching” through EHR data to “learn” medicine. Those advocating Watson performing this task need to understand the limits to observational studies in medicine.)

    One concern I have had about Watson is that the publicity around it has been mostly news articles and press releases. As an evidence-based informatician, I would like to see more scientific analysis, i.e., what does Watson do to improve healthcare and how successful is it at doing so? I was therefore pleased to come across a journal article evaluating Watson [1]. In this first evaluation in the medical domain, Watson was trained using several resources from internal medicine, such as ACP MedicinePIERMerck Manual, and MKSAP. Watson was applied, and further trained with 5000 questions, in Doctor’s Dilemma, a competition somewhat like Jeopardy! that is run by American College of Physicians and in which medical trainees participate each year. A sample question from the paper is, Familial adenomatous polyposis is caused by mutations of this gene, with the answer being, APC Gene. (Googling the text of the question gives the correct answer at the top of its ranking to this and the two other sample questions provided in the paper).

    Watson was evaluated on an additional 188 unseen questions [1]. The primary outcome measure was recall (number of correct answers) at 10 results shown, and performance varied from 0.49 for the baseline system to 0.77 for the fully adapted and trained system. In other words, looking at the top ten answers for these 188 questions, 77% of those Watson provided were correct.

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    What the Khan Academy Teaches Us About What Medical Education Will Look Like Ten Years From Now

    From SFO, I carefully followed my Droid Navigator’s directions off Highway 101 into a warren of non-descript low-slung office buildings—non-descript except for the telltale proliferation of Google signs and young adults riding colorful Google bikes.  I drove around to the back of several of those complexes and finally found the correct numbered grouping.  It really could have been any office or doctors’ office complex in the U.S.  The Khan suite is on the second floor.  There’s a simple brass plate saying “Khan Academy” on what looked like oak double doors. I let myself in and immediately encountered a large, central open space—with long dining tables, food, an ample sitting area with couches conducive for group discussions—and a friendly greeting by programmers and staff.  Oh, and computers—there were lots of computers.  As far as I could tell, nobody had their own office—though maybe Sal does.  Everyone was also open, friendly and passionate about the great work happening there.

    After some trial and error, Rishi and I found an unused office and huddled around his Mac for a Google Hangout interview with a Bay Area reporter about the Khan/RWJF health care education project.  Later, I met with Shantanu, the Khan COO and former “math jock” high school friend of Sal, as well as Charlotte, external relations, and Matt, software engineer. They’re all long termers at Khan—that means they’ve been there for about two years.  Overall, the energy was pretty electric.  One other small thing—do not be fooled—these incredible people are, how should I put it—ferociously—intense and focused.

    Pioneers in flipping the med school classroom

    The next morning, Rishi and I met at Stanford Medical School—in the Li Ka Shing Center for Learning and Knowledge—an enormous and beautiful building off Campus Drive near the hospital that did not exist back in my days as an earnest Stanford law student.   We were there to observe some pioneers in medical education attempt to use Khan-like videos to flip the medical school classroom.  This work at Stanford is part of the current Khan Academy and RWJF collaboration. We’re trying to understand what happens when a medical school attempts to use the Khan-style videos to change the classroom interaction.

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    #Dataviz + #Design + #Diabetes: The Beginning

    I love interactive data visualization (#dataviz).  It is one of the things that I definitely wanted to explore when I came out to the Bay Area on sabbatical, because I believe that it has great potential for helping both patients and clinicians with diabetes management.  The sheer volume of numbers available for this disease is overwhelming; we need #dataviz tools that can help us achieve greater understanding and make actionable clinical decisions to improve health.

    This is what we usually see in clinic: numbers written down on a piece of paper.

    Yes there are computer systems that link to blood glucose meters, but there are a number of complexities with the downloading of blood sugar numbers in clinic (which deserves an entire blog post sometime in the future).

    You can see there is some visual analysis and annotation that we do perform, albeit primitive.  The circles represent high blood sugars (>150 mg/dl)and the triangles represent low blood sugars (<70 mg/dl). This is almost better than the cave painters don’t you think?

    But even the minority of patients who download their BS to the computer, are viewing dashboards like this.

    Pie charts, need I say more? I can extract some useful insights from these charts, which improve over the previous one I showed, but a few things strike me: (1) some of the scatter plots overlay weeks of data, which I don’t find helpful because you can’t tell how BS on a given day are responding and relate them to life events; (2) some visualizations show a lot of numbers in many of the sections, and it just becomes onerous to go through them and find trends; (3) many provide statistics (area under the curve, MAD%) which I think only a minority of families and children really understand; (4) although some of the software programs do provide interactivity and let you see the data at different time scales (day, week, month), if you change to a different view, you are stuck trying to remember in your head what you saw on a previous screen because you can’t see the multiple levels at once; (4) finally, I find that the user interface and design could use major improvement.

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