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Archive for 2019

Gift Guide: Books for data, privacy, and healthcare nerds and disrupters

Got someone who is hard to shop for but loves data, healthcare, and disruption? Here’s a round-up of our top picks from our blog archives.

Get Well Soon: A History of the Worst Plagues and the Heroes Who Fought Them

This funny and frustrating look at plagues is an excellent gift. It’s fast-paced and you’ll learn the real story behind the ‘headlines’. Those who do not learn from history are doomed to repeat it. (ahem, measles). Get this for the medical history buff on your list.

In Shock: My Journey from Death to Recovery and the Redemptive Power of Hope

This true story reads like a medical suspense thriller, and guides readers to the power of empathy, and the indisputable value of seeing things from someone else’s viewpoint.in shock book cover

The Known Citizen: A History of Privacy in Modern America

For the privacy and data nerds, this history of privacy also shows that the roots of decisions today are often shaped by forces from previous generations. Why can’t we have a universal medical identifier? It’s probably related to why your social security card is a piece of paper. Get this for your security and privacy officer.

Invisible Women: Data Bias in a World Designed for Men

If you make data-driven decisions, how do you know if you actually have all the data? This book dives into how a lack of data leads to poor decisions that impact the health, safety, and income of women worldwide. If you need to convince anyone about the need for data-driven decisions, this will give you the back-up you need.

An American Sickness: How Healthcare Became Big Business and How You Can Take It Back 

What’s most interesting in this guide from a former physician and current editor of Kaiser Health News is that if you want to point fingers in healthcare, you need to point them at everyone. This review of how we got in this mess in the US, is key for anyone wanting to affect change. As a bonus, there’s a handy guide for dealing with your own escalating healthcare costs at the end.

And a few oldies but goodies from the very early days of digital health and healthcare disruption.

Posted in: Behavior Change, big data, Healthcare costs, Healthcare Disruption, Healthcare Legislation, Healthcare Policy, Healthcare Research, Healthcare transformation, machine learning

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Know Your User: User-Centered Design in Healthcare

Designing software is both an art and a science. Software developers by nature think about every possibility and edge case, while designers focus on the most common user paths. Handling unexpected failures gracefully is a hard problem to solve.

I’ve been re-reading the classic book The Inmates Are Running the Asylum, about the natural tension between design and functionality in software. While it’s a bit hard on developers (they don’t all think in ones and zeros and many have fantastic design instincts), many of the problems the book outlines are still prevalent today, and you can also see the architectural problems that are inherited by lack of user-centered design in software that’s been around a while.

User-centered design puts the end-user front and center, and it’s not just about thinking of what ‘jobs’ that user needs to accomplish, but also the users purpose for those jobs and mental state while solving them.

It’s often easier to illustrate a point by what not to do, so let’s start with two recent examples, one from my experience and one from an opinion piece in the New York Times.

Our accountant at Wellpepper uses QuickBooks. QuickBooks is designed for accountants and business owners. It’s the grand-daddy (or mommy) of accounting programs, and has been around in one form or another since 1984, so they should know their users and what they are trying to accomplish pretty well by now. Guess what? They don’t.

Here’s the error message I see when QuickBooks isn’t able to pull up my data.

quickbooks error message

What have you done with my data, Quickbooks?

Isn’t that cute? No, no it’s not. The job I’m trying to do is look at bank balances, profit and loss, expenses, accounts payable, and accounts receivable. QuickBooks has the data that runs the financial side of the business. I’d like to think they know where that data is, and take both the delivery and protection of that data seriously. This isn’t a situation like the now retired Twitter Fail Whale when a tweet isn’t sent. Even Twitter realized that when someone is trying to accomplish a task a cute error message is more frustrating than appeasing. Add QuickBooks’ inappropriate error message to the fact that they can’t display my business data, and that I get this message at least once per day, I start to worry about whether I can trust them.

Now let’s look at healthcare, where trust and empathy are really important. We’re all familiar with the whimsical Verona campus of Epic Systems. People clamor to visit during Epic’s annual conference. It’s a source of pride for employees. Some of that whimsy comes across in cow-splotch login screens. Is that appropriate in a healthcare setting? Well, we have a dog as a logo, so I’m not going to judge. What is never appropriate is making your users feel bad, as this physician outlines in her New York times opinion piece.

But on a recent Monday morning when I logged into so-called Epic Hyperspace for the first time, I was greeted with a pop-up box and an urgent message: “You currently have deficiencies that are either delinquent or will become delinquent within one week. Please complete at your earliest convenience.” https://www.nytimes.com/2019/11/01/health/epic-electronic-health-records.html

First run user-experience is so important. It sets the tone for how people will feel about using your product. Doctors have trained for years to be able to care for patients. Why make them feel lacking, and especially not on the first time they meet you?

We know it’s possible for software to be context aware, and deliver appropriate levels of empathy, and also we know when to sound the alarm. At Wellpepper we take user-centered design very seriously, and work with patients and providers to make sure the messages we send, and the overall experience is appropriate for the people using the software. Our patented adaptive notification system is just one example of this. It changes the type of messages people receive based on how they interact with the application.

Since our application is used by people in both acute and chronic conditions, standard messages also provide encouragement but don’t imply that someone will “recover” or “get better.” In the event that a patient records a symptom that indicates a life threatening emergency, we clear the screen of any other tasks, and display a short and clear alert. (We also alert the care team, but we make sure the patient clearly understands what they need to do next.) These are all examples of being aware of not just what the person needs to do, but their potential frame of mind when doing it.

We think a lot about what to leave out of the software. Someone who is recovering from surgery, or newly diagnosed with a chronic disease has enough to worry about. Figuring out a demanding interface shouldn’t be part of that. We like to think about the minimum information we need to help a patient-self manage, and to help the provider track the patient. As a result, we have what we call a deceptively simple user interface, both for patients and providers.

If you’re interested in how Wellpepper patient engagement platform can help support your patients, get in touch!

Posted in: Healthcare motivation, Healthcare Technology, M-health

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Healthcare Legislation & Innovation

In highly innovative industries like healthcare, innovation sometimes needs a bit of a push from unlikely bedfellows. We’ve previously worked with our colleagues and even competitors, to advocate for patient-generated health data, as we know it contains insights that won’t be found in the clinic, or in randomized clinical trials. Now CMS and HHS are asking for public comment on a number of questions and initiatives aimed at improving patient care and lowering costs, and in particular in areas of rural health, digital health, and the role of real-world evidence in care improvements.

This handy Twitter thread from Omada Health’s Chief Privacy and Regulatory Officer (and former HHS Privacy Officer), Lucia Savage summarizes the opportunities for comment.

In particular, we’re interested in how digital health, patient-generated data, and real-world evidence can lower costs of care. As well, in the world of value-based care, where preventative programs like the research we completed with Boston University and Harvard University can really shine.

From the RFI for digital health:

We believe that digital health technologies hold the promise of modernizing U.S. health care in ways that transform how Americans access medical services. Digital technologies have helped to transform other sectors of the U.S. economy in ways that improve access to products and services and decrease their costs without harming quality. It is time for that same transformation to occur in health care. Recognition of digital platforms as sources of medical services combined with reforms to how digital products may be covered and reimbursed for by payers such as Medicare will be critical to realizing this potential.

So do we!

Posted in: Healthcare costs, Healthcare Disruption, Healthcare Legislation, Healthcare Policy, Healthcare Research

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The Known Citizen: A History of Privacy in Modern America

Although the “P” in HIPAA stands for portability, the question of privacy and data protection is a big topic in healthcare. While at the same time we need to protect all personal health information for patients, individual patients have the right to share that data how they wish. New legislation on data interoperability seeks to break down silos and data blocking to enable patients and providers to have access to data to improve care. With this as the current situation in 2019, those interested in privacy should not miss Sarah Igo’s excellent history of privacy and policy “The Known Citizen.” We recommend this book to all data and privacy nerds. While not focused on healthcare, it provides a great primer on the evolution of privacy and technology’s ability to outpace our understanding and desires both to be known and to be forgotten.

The book kicks off with the advent of photography and the debate at the time about whether people own their likeness. (At the time they didn’t, and people found their pictures on boxes in the grocery store.) It details the evolution of thought, law, and popular sentiment in privacy, including the first ideas that patients have a right to privacy, championed by nurse Dorothy Smith in 1969, and institutionalized in the Patient Bill of Rights in 1973. The premise is that while the loss of privacy is required in the doctor/patient relationship and to deliver care, this doesn’t mean that all aspects of privacy should be ignored. “Arranging for privacy”: curtains, confidentiality, (robes that close at the back?), can created a zone of privacy around the patient and help preserve the individual’s dignity. Smith felt that this was the duty of the nurse, although now we see it as the responsibility of everyone in healthcare from the receptionist to IT.

Healthcare privacy is also touched on in the social determinants of health, and whether people receiving public aid should have their entire lives under the microscope, and again, in the introduction of internal review boards and ethics committees for medical research to protect patient/subjects from harm, but also from disclosure of private information without their full cooperation or understanding of its use.

While you may know Betty Ford for her disclosure of addiction and subsequent support of treatment, she is also responsible for destigmatizing breast cancer and showing that open discussion, and especially by prominent figures can drive public health agendas. After Ford disclosed her breast cancer and mastectomy in the media, there was a noticeable uptick in mammograms, and over 5,000 calls of support to the White House.

While healthcare is a small part of this book, the learnings from society at large, and the race between technology, sentiment, and legislation have great lessons to apply in healthcare. And interestingly much of the discussion we are having today about being known, has been going on for over hundred years, and the
“big data” discussions for at least 50 years. Finally, this book has the added bonus of a really interesting bon mot for your next cocktail or mocktail party: the first reality TV show was broadcast in 1973, on PBS of all broadcasters!

Posted in: Behavior Change, big data, Clinical Research, Data Protection, Health Regulations, Healthcare Legislation, Healthcare Policy, Healthcare Research, Healthcare Technology

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HIMSS WA Innovation Summit

I had the opportunity to attend the Washington HIMSS Innovation Summit, where leaders from Virginia Mason, Providence, Overlake, Seattle Children’s, UW Medicine, Vera Whole Health and Confluence spoke about innovation in their organizations. A lot of great themes and takeaways. These are the ones that stood out most to me.

Technology Adoption

Several panelists mentioned they have problems with their health systems adopting new technologies. Executives tend to bring in new technologies, get pilots kicked off, but struggle in the system-wide adoption. A lot of times new technologies are implemented and expected to work immediately. The reality is that no matter what Health Systems are implementing, they need to invest resources. Physicians and end users need to be engaged early on to really take ownership of the new technology. A well-defined change management process is also key to ensuring a successful adoption. Lastly, even though organizations are piloting the new technology, call it Phase 1 vs Pilot. Pilots imply a short-term project with and end date. Phase 1 makes the technology more real and gets people thinking about what Phase 2 and 3 look like.

Return on Investment

One of the panelists challenged any technology vendor to show him a technology that has ROI. He said his organization does over $200M in uncompensated care per year so he must evaluate new technologies against cost of patient care, which is a valid point. This brought up an interesting discussion about what health systems consider to be a ROI. Not all technologies will give Health Systems dollar-for-dollar return. Some technologies will. ROI can be a blend of hard and soft cost, so it’s important to spend time thoroughly defining a business case and make sure that success metrics align with the overall mission of the Health System.

Patients

I was surprised at how much of the discussion was focused around clinician-facing vs patient-facing technologies. I agree better tools and algorithms for clinicians will directly influence the quality of care that patients receive. Virginia Mason panelists did a great job bringing everything back to the patients. Patients should be the center and they should have access to all their data, regardless of where it comes from, in one place. They should have one seamless app and experience for all their healthcare needs. We at Wellpepper could not agree more!

Key Takeaways

When evaluating and implementing new technologies:

  • Define a realistic business case and what financial and non-financial ROI looks like
  • Ensure alignment to Health System’s mission and goals
  • Don’t assume that new technologies can just be plugged in and solve all problems
  • Allocate resources and engage providers and end users from the beginning
  • Treat it as a multi-year, phased journey; call it Phase 1 instead of a Pilot
  • Have a solid change management process
  • Keep patients’ experience and needs at the top of mind

Posted in: Adherence, Behavior Change, Healthcare costs, Healthcare Disruption, Healthcare Technology, Healthcare transformation, HIMSS, patient engagement, Patient Satisfaction, patient-generated data, Return on Investment, Uncategorized, Using Wellpepper

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Myth Busting and Data Gathering At Parks Connected Health

While Verona was abuzz with news of EPIC making patient-records available for research (and possibly without patient consent), a smaller group in San Diego was busy busting myths about seniors, remote monitoring, AI, and patient-generated data at Parks Connected Health Conference.

I had the pleasure of speaking about the positive clinical outcomes we’ve seen using Wellpepper for remote monitoring, in our case providing care plans that enable patients to self-manage, and letting care givers know when people need more help, on a panel with representatives from ResMed, Reflexion Health, AT&T, and Rapid Response Monitoring Systems. While a truly entertaining panel has some disagreement, we were largely in agreement that remote care is here to stay, value-based models support and enable it, and patient-generated data provides valuable insights. While the approach may have been different across companies from connected devices, to avatar coaches for home-based physical therapy, to our patient-focused interactive care plans, we all saw similar successes with a patient or consumer-centric approach.

It was refreshing to hear examples from AARP and United Healthcare recognizing the importance of walking, falls prevention, and gait speed in senior’s health. Our study with Dr. Jonathan Bean showed clinical improvements with gait speed and balance through a digital intervention based on the Live Long Walk Strong program. More programs based on prevention and activity for seniors rather than sensors that detect falls after the fact are needed, and it’s great to see such powerful and prominent organizations advocating for that as well.

Parks and Associates is a research-led analyst firm, so each panel started with results of market research they’d completed, and also real-time audience polls of key issues or drivers in connected health. The audience and most speakers were bullish on technology as an enabler and amplifier for humans, whether that’s enabling clinicians to see more patients, enabling caregivers to stay in touch with their charges, or enabling consumers or patients themselves to self-manage. Technology, and in particular machine-learning and AI were not seen as the be-all and end-all, but as ingredients to a successful human-led strategy. (With the exception of a keynote by CirrusMD who advocated for people-backed triage and staying away from chatbots and AI.)

With CMS announcing goals for 50% of reimbursement to be value-based, reimbursement was less of a topic at this conference than in previous years. However, the complexity and fragmentation of healthcare is still a challenge, whether that’s in care settings, the payer/provider divide, or consumer versus medical grade monitoring devices. Usability is key, with many speakers talking about the difficulty of setting up and managing devices, even the best designed consumer devices. And while the focus was on seniors, it seems that everyone has struggled with packaging, networking, and connectivity.

In addition to the “AI will replace humans” myth, my other favorite myth to be busted at this conference was the idea that sensors and sensor data alone will solve all the problems. During one panel an audience member referred to sensor data as superior to patient observations. (Actually referring to it as “the worst” type of data.) Thankfully both MDs on the panel he was addressing said “the best thing you can do is listen to what your patient is telling you.”

We couldn’t agree more.

Connected Health, Wellpepper results

Posted in: Adherence, Aging, Healthcare Policy, Healthcare Technology, machine learning, patient engagement, patient-generated data, Physical Therapy

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Study Results: The Rehabilitation Enhancing Aging Through Connected Health Prehabilitation Trial

In 2015, we announced a study with principal investigator Jonathan Bean, MD from Harvard Medical school to test his custom protocol for at-risk seniors using Wellpepper’s interactive care plan solution to deliver the intervention to patients, and for clinicians to monitor those patients. The intervention was based on a successful intervention that Dr. Bean delivered at Spaulding Rehab in Boston called “Live Long Walk Strong.” This intervention was aimed at improving strength and mobility in seniors to help prevent adverse events.  The project with Wellpepper, eventually called the REACH study, was to determine whether this type of intervention could be delivered remotely through a mobile interface, which would enable scaling the program to patients who weren’t able to attend in-person sessions (40% of the participants in the original Live Long Walk Strong Program deferred care due to travel requirements), and also decrease costs both for patients and providers. The REACH study used the following process. REACH study process

We’re pleased to report that the results of the study have now been published, with positive outcomes reported. This was designed as a quasi-experimental trial, where 75 participants were compared to a control group made up of a comparable sample of 100 people from the general population. Outcomes between groups were then compared, with clinically meaningful and statistically significant differences (as defined by P-values) observed in the study group.

Care Plan Intervention

Patients received a strength and conditioning program delivered first through in-person classes, and a mobile application, and then through the mobile application with remote messaging with a healthcare provider. During the last 4 months of the study, patients were left on their own and not monitored by a clinician. The study was designed to address not just physical health but incorporate aspects of motivational behavior change.

Motivational behavior change through an m-health intervention

Outcomes

  • Compared to the control group, participants in the program had a 73% decrease in emergency department visits during a 1-year period
  • Clinically meaningful improvements in mobility as recorded in the 6-minute walk test (+.8 meters/second) and Short Physical Performance Battery test (+.69 units)
  • 85% of patients were active at least twice per week
  • 89% rated application satisfaction at “good to excellent” and would recommend to a friend
  • 16-20 percentage point drop off in adherence during the last 4 unmonitored months

The REACH intervention shows positive outcomes in targeting functional decline and the avoidance of adverse event for older primary care adults. The potential benefits should be evaluated and confirmed on a larger scale. If your health system is managing a population that would benefit from an intervention like this, please be in touch.

More Information

If you are interested in deploying a solution in your organization based on the protocol used in this study, contact us.

Study Announcement Press Release

Study Methodology and Description

Published Study

Posted in: Healthcare Research, Outcomes, patient engagement, Patient Satisfaction, Physical Therapy, Prehabilitation, Research, Return on Investment

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Healthcare Summer Reading: Invisible Women

As artificial intelligence and machine-learning are increasingly touted as the solution for everything from shopping to healthcare, the need to better understand the data that goes into these solutions increases. We’ve written before about how trying to solve patient problems using only the EMR data delivers only half the equation because it leaves out everything that happened to the patient outside the clinic, and the patient’s own experience.

Machine Learning in Healthcare: How To Avoid GIGO

Self-Driving Healthcare

However, it turns out that this data may only deliver ¼ or less of the solution when it comes to women’s health, as the fact-packed “Invisible Women: Data Bias In a World Designed For Men” points out.

While Invisible Women tackles politics, healthcare, manufacturing, career, and finances, so many of the problem areas where key decisions are made without enough data result in population health and healthcare problems, even decisions about automobile manufacturing, snow shoveling, and portable cookstoves.

In example after example from every industry, the “normal” male is used as the standard, and women are seen as aberrations, resulting in health, safety, and finance inequality. One size fits all is actually one size fits average male.

If you need to make a case, either business or healthcare related, for the need for diversity of thinking, and for having the data for evidence-based decision making, this book will help you. You’ll also realize that in evidence-based decision making in healthcare, the data is missing for 51% of the population.

Examples include:

  • Crash test dummies that don’t approximate women’s bodies so that women are 17% more likely to die in a car crash.
  • Drug testing that does not require evaluation of outcomes by gender. (The UK does not require any gender evaluation for randomized control trials so researchers are advised to look at studies from other countries to ensure gender inclusion.)
  • Drug dosages that are not adjusted for size or hormones
  • Health trackers that underestimate women’s activities and don’t include menstruation tracking
  • Increased risk of hip fracture by making female solders match an arbitrary male gate length
  • Public transportation safety issues
  • Greater risk of women being misdiagnosed for heart failure because symptoms present differently
  • Portable cookstoves intended to decrease indoor pollution but aren’t used because they need constant tending, and mean that women can’t get other chores done.

The list goes on. Practically every paragraph in this book has a practical example where getting the right data, either qualitative or quantitative would have resulted in better quality of life for women (and everyone really.)

The good news is that this implicit bias that normal can be overcome with a contentious approach to collecting data and feedback, and a rigor of examining the data and outcomes by gender. Interestingly, when reading this book, I realized that this should be another way that we evaluate our Wellpepper care plans. We currently mostly segment our data analysis by age because there has been previous skepticism about older patients ability to use technology. Now I’m thinking that gender differences in care plan outcomes might be a really interesting source of insight. What might we learn about recovery? We know women experience pain and medication differently. Are their gender based clinical insights in our outcome data as well?

While Invisible Women is probably not beach reading, it’s still highly recommended book to add to your healthcare and data reading list.

Posted in: big data, Clinical Research, Healthcare Research, Healthcare transformation, machine learning, patient-generated data

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You Are Here: Voice Assistants In Healthcare

“We’re at the beginning of the end of the first phase of voice” said James Poulter, CEO of Vixen Labs.

The beginning of the end of the first phase might be optimistic for voice, but that did not dampen the enthusiasm at the second annual Voice.Summit in New Jersey this week. Another speaker likened voice to being at the same stage of technology as the release of the first iPhone. If you remember, at that time everyone else had feature phones, and Android didn’t exist. Voice Summit Keynote

Not surprisingly, this year’s summit reminded me a bit of the early days of mobile development: more talk about how than why, more developer content than business content, and just an inkling that we really don’t know what we don’t know about where voice will go. One of the great things about this conference is that it’s a cross-industry event, so was a specific healthcare track, with topics ranging from best-practices for designing voice care plans to ethical considerations of voice, AI, and bots in healthcare, there was also the opportunity to learn from other industries, and also directly from the key technology leaders in the space.

The following are some highlights, learnings, and implications for healthcare as well.

Amazon Alexa

Dave Isbitski, Alexa Developer Evangelist, kicked off the summit with a couple of announcements for Alexa, skill connections which enable one skill to invoke another skill, for example if you want to print content from a skill you can call another skill designed for printing, like the HP skill. While this is currently limited to named skills, it has huge value in healthcare where every skill shouldn’t have to recreate medication lists or a full lexicon of disease education, and it would be better to call on a proven authority like Mayo Clinic or WebMD to get more information.

Dave also announced Dialog Flow, which uses neural networks to develop skills with less coding, and less manual tagging, although admittedly we’re realistically still in the turn>multi-turn phase rather than full machine-learning and AI. This is probably okay for healthcare: let’s focus on getting patient feedback on structured conversations, like triage surveys, before trying to design a system that is completely responsive to any healthcare need.

Another announcement, the ability to have one skill that uses two languages, rather than installing a separate skill for each language would also be beneficial in healthcare to provide patient instructions, especially to family members who may have different “first” languages.

Samsung

Samsung has jumped into the voice fray with a voice assistant called Bixby, which is designed to be a developer platform for people to insert voice into any type of device. Microsoft has this strategy with Cortana, the difference is that Samsung themselves ship televisions and refrigerators that can be voice-enabled. Samsung is also in the “voice and” category with screens being key part of their delivery. This has some really interesting implications for healthcare if you think about the television as the focal point of the living room. Health reminders and actions delivered there could have great impact. We’re working on a mobile version of the MIND diet, which would have huge impact if delivered through voice and visual reminders on the refridgerator door. The challenges with these modalities though are that it may take generations for the technology to become ubiquitous, versus the $39 Echo Dot. Samsung sees a world where your voice assistant knows you across all your devices, which would definitely be helpful in maintaining health context.

Microsoft

Voice as an ingredient, and part of an iOT and AI strategy was echoed by Microsoft. No surprise since Cortana doesn’t have a body or even a hockey puck. This strategy could be very interesting in healthcare if you think about the talking EPI pen. Why wouldn’t all devices and complex equipment have voice prompts for both patients and providers? There was also a meetup group at the conference demonstrating voice running on an ARM chip, which could be very interesting for the cheaper medical devices.

Designers and Developers

The tradeshow floor was full of mostly developer tools for building, testing, and securing voice applications, and the rallying cry in sessions was for the platform providers (Amazon, Google, Apple, Samsung, Microsoft) to standardize on their approach to voice, if not for the developers, then for the end-users. One of the key areas for some standardization is in the lack of standard interface, just as the APIs from platform vendors use different terminology, there’s no standard interface or reusable components aside from the idea of a wake word, to help users navigate. Mobile had the same problem in the early days, and still does to some extent, something that was solved with on-boarding experiences and tours built into apps, something voice has yet to do, but if done consistently could really improve usability.

“Complexity and ecosystem lock-in are threats to ubiquity and frictionless experience. Let’s not build an ecosystem that locks that in.” James Poulter, CEO of Vixen Labs

There was also an admonition to not build apps for the sake of building apps, but to focus on user need, and understand that what users want most of all is convenience, and that they will use the most convenient interface for the task (web, mobile, TV, phone, voice).

What does this mean in healthcare? Context is very important. Make sure your users know exactly what your skill can and can’t do so they don’t expect the full canon of medical knowledge from your one skill. At Wellpepper, we are firmly in the “Voice and” category, (and yet I still get invited to speak at these events): our voice interactions are a subset of the patient’s care plan, and just as they don’t expect the mobile app to do more than deliver the care plan prescribed by their physicians, the same holds true for the voice experiences for Wellpepper interactive care plans.

Ethics

Ethics in designWhile I didn’t hear anyone talking specifically about the ethical issues of both the eavesdropping scandals, and the need for humans to manually tag voice snippets in order to improve machine learning, I did attend a great session by Brooke Hawkins on ethics and design implications in healthcare. Issues tackled included considerations for disclosure of the exact conditions for the efficacy of an app, whether A/B testing on patients can even be done, and understanding the implications of focusing on specific measures in a care plan. On this last one, she suggested that care plans that include weight, like our Sugarpod diabetes care plan

Brand

Along the same lines of not building voice apps for the sake of it, there was also a lot of talk of how your brand is reflected in your app. Not all healthcare systems think of their brand impact, although they should, and the voice skill is an extension of that. Interestingly David Ciccarelli from Voices.com which has voice talent, mentioned that most developers use the standard Alexa voice. It’s not surprising, as it’s expensive to have someone record every possible response for your application, although it’s interesting to think about a world where your healthcare app is speaking in the voice of your own doctor. Given what we’ve seen with the correlation between adherence and healthcare provider engagement, this could give a huge boost to patient outcomes. The technology is not that far off to synthesis voice from other recordings, so it wouldn’t require that your doctor record everything. Or perhaps it would make more sense to have a specific doctor be the voice of all of your apps, which might be more credible than Alexa dispensing healthcare information. Ciccarelli provided a nice matrix of when to use synthetic voice and when to use real humans that applies well in healthcare.

Users

There’s no question that voice spans all ages. Dave Isbitski opened the conference by saying that his kids and his parents were equally excited by voice applications. Speakers at on the Best Practices for Developing Voice Care Plans panel (myself included) were developing specialized care plans for children, seniors, and everyone else. While there are definite generational differences in usage patterns for voice assistant, and there is also a “voice-first” generation coming. One speaker mentioned how his child who had Alexa from birth knew the limitations of the device, and didn’t ask more than Alexa was capable to deliver, however a 6-year-old family friend who didn’t have that experience wanted to ask things like “do you know my teacher.”  In our testing we found similar differences between generations as well, with seniors more likely to try to have a conversation, and younger people sticking to the script of the care plan a bit more. I heard one developer say that they track slang used by end user to determine age and adjust the interactions accordingly.

Wrapping It Up For Healthcare

We’ve written before about the use cases for voice in healthcare, and there are many, from documenting clinic visits, transcribing physician notes, to medication adherence, education, and patient care plans, as well, voice biomarkers, which my fellow panelists called a huge pool of untapped diagnostic data. If we’re at the early days of voice apps, we’re also at the early days of voice data. There’s a ton to be discovered, and the research, especially in healthcare, is just starting.

Our expectations for voice are high. Let’s hope it delivers.

If you’re interested in learning more about voice in healthcare here are some great resources:

Posted in: Adherence, alexa, Behavior Change, big data, Healthcare Technology

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Summer Reading: “Get Well Soon: History’s Worst Plagues and the Heroes Who Fought Them”

Summer Reading: Get Well Soon: History’s Worst Plagues and the Heroes Who Fought Them, by Jennifer Wright

At Wellpepper, we’re huge proponents of evidence, and have worked for years with researchers from Boston University and Harvard University to prove that the things that seem like common sense, like providing help outside the clinic in a digital format, will truly improve patient outcomes. Given today’s focus on evidence-based medicine, and even the sometimes dismissal of common sense if there’s no randomized control trial (even chicken soup is subject to peer review), it’s amazing to remember that we once knew so little about what makes us sick, or the difference between correlation and causation.

If you don’t think you’re interested in plagues, think again. This book is a rollicking journey through a history of plagues that is both funny, sarcastic, and tragic. It reminds us that things that seem obvious today might not have been in the past, and that we’re never that far from mass hysteria when we don’t understand the root cause of a new healthcare epidemic.

While there is a chapter dedicated to each historical epidemic, Wright does not talk about the AIDs epidemic of the 1980s. She believes that history needs to be shared by the ones who were there, while her job is to amplify the voices of history so that we stop making the same mistakes. By uncovering how society, medical professionals, or government either did or didn’t cope with a particular epidemic, Wright offers valuable lessons for today.

For example, when exploring leprosy (which by the way, was a required medical test to get a Russian visa when I moved there in 2008 with Microsoft: spoiler alert, I don’t have it), Wright says:

“Diseases don’t ruin lives just because they rot off noses. They destroy people if the rest of society isolates them and treats them as undeserving of help and respect.”

When people blame others for their diseases, or treat them differently, we are not acting better than our ancestors.

Wright also puts into perspective why all types of people fall for information that now may seem ridiculous, with this analogy:

“If you were a peasant and someone said, “If you live in a sewer, the bubonic plague won’t kill you,” your reaction likely wouldn’t be, “I am curious to hear the science behind that.” Your response would be, “Point me to the nearest sewer.”

It’s up to medical professionals to understand why someone believes what they believe, and then try to provide alternate evidence, rather than dismiss it out of hand. It doesn’t mean that you can’t debunk the value of living in a sewer, but do it by understanding where the information came from in the first place. (And also don’t forget that the fake healthcare information is much easier to access than medical journals locked behind firewalls.

Stories of the Spanish flu, and government-sanctioned and media campaign to downplay (aka ignore or bury) the seriousness of the illness so as to not divert energy and enthusiasm for the war effort, versus the example of Marcus Aurelius during the Antonine Plague taking care of business by offering government burials and time off to go to funerals, which both kept bodies from piling up and acknowledged there was a serious problem.

Wright admonishes us to choose leaders well.

“When we are electing government officials, it is not stupid to ask yourself, “If a plague broke out, do I think this person could navigate the country through those times, on a spiritual level, but also on a pragmatic one? Would they be able to calmly solve one problem, and then another one, and then the next one? Or would bodies pile up in the streets?”

As we start to repeat the mistakes of the past (measles anyone?), Wright makes sure to remind us that with our natural human instinct to lean away from bad news, we often forget how bad things were. Measles, anyone?

“Polio was effectively eliminated throughout the world. And then people just … kind of forgot all about polio. This seems to be the human response to any disease. People forget diseases ever existed the minute they are no longer being affected by them. Maybe that’s understandable. Maybe if we all thought about all the potential diseases the world is teeming with, and the extent to which we are, every day, dancing on the edge of a volcano, the world would seem too terrifying to walk around in at all. Or we’d just vaccinate our kids.”

If you’re interested in medical history, policy, or historical epidemiology this makes a light summer read. I’m not kidding. Also, the chapter on Spanish flu should be made into a dystopian/future past film. It’s got everything: media and government cover up, bodies in the street, a mystery, and a hero fighting against the status quo.

Posted in: Behavior Change, Clinical Research, Healthcare motivation, Healthcare transformation, population health, Rare disease

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Partnership Announcement: eVideon and Wellpepper

eVideon and Wellpepper Announce Partnership to Deliver Comprehensive Patient Experience Across Care Settings

 

eVideon, a leader in hospital patient experience, and Wellpepper, a leader in interactive patient care plans, today announced a partnership to deliver comprehensive patient experiences across inpatient and outpatient settings. Both companies work with health systems to deliver a better patient experience. The partnership enables health systems to deploy integrated solutions from best-of-breed vendors. eVideon and Wellpepper are integrating their solutions so providers can deliver a consistent experience across care settings from hospital to home.

 

“Increasingly, health systems are looking for patient experiences that span inpatient and outpatient settings,” said Wellpepper CEO Anne Weiler. “The patient journey begins before a patient enters the hospital and continues long after discharge. This partnership enables an engaging and usable experience for patients across their entire journey of care.”

Wellpepper’s clinically validated digital treatment plans guide users through all the activities they need to do outside the clinic to manage an episode of care: from preparing for a clinic or hospital visit, to managing a chronic condition or recovering after hospital discharge, via patients’ preferred mobile, web, or voice devices. eVideon enhances the inpatient experience, providing personalized interactive bedside capabilities that empower patients to control their environment, learn about their conditions, access hospital services, order meals or watch movies on demand. Both companies are passionate about improving the patient experience while providing data and analytics to streamline clinician workflows and improve outcomes.

“eVideon and Wellpepper share a passion for bringing long overdue self-service to healthcare through personalized, engaging systems,” said Jeff Fallon, CEO of eVideon. “Interoperability is vital, and the value of better outcomes and streamlined workflows is undeniable – not just for patients, but for clinicians and staff too. We’re excited about the new possibilities this comprehensive solution will bring across care environments for our customers.”

The partnership enables health systems to own the end-to-end patient care pathway. Health systems can deploy eVideon’s and Wellpepper’s solutions simultaneously or sequentially. Solution architects from eVideon and Wellpepper are available to consult with healthcare technology and patient experience groups to determine the best approach for rolling out a comprehensive solution.

About eVideon

eVideon digitizes hospitals with a suite of bedside engagement systems, hospital TV, digital signage, and other interactive displays. Patients enjoy the convenience of self-service at the bedside with access to meal ordering, entertainment, education, hospital services and more, while staff enjoy streamlined, paperless workflows. Interactive surveys and patient feedback help patients communicate immediate needs, and help hospitals respond to those needs quickly. The platform leverages integrations with EHRs, building management systems, food service systems, real-time location systems and more. Data analytics provide valuable insights into patient behaviors and pain points, letting hospitals improve service and outcomes. Learn more at www.evideon.com.

About Wellpepper

Wellpepper is a healthcare technology company with an award-winning and clinically validated patient engagement platform used by major health systems to improve outcomes and lower costs of care. Wellpepper treatment plans can be customized for each health system’s own protocols and best practices and personalized for each patient. Wellpepper’s patented adaptive notification system helps drive over 70 percent patient engagement with treatment plans. Wellpepper was founded in 2012 to help healthcare organizations lower costs, improve outcomes and improve patient satisfaction. The company is headquartered in Seattle, Washington. Visit www.wellpepper.comfor more information.

Full press-release available at PRWeb.

Contact:

eVideon
info@evideon.com
616-588-8109

Wellpepper
Jennifer Allen Newton
Bluehouse Consulting Group, Inc.
jennifer@bluehousecg.com
503-805-7540

Posted in: Healthcare Technology, Patient Satisfaction, Press Release

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Transforming Health at Montana HIMSS Annual Spring Conference

Possibly the most interesting thing in healthcare technology is the breadth of scope that health tech needs to cover, and the talks at the HIMSS Montana annual spring conference represented that with talks about security, how to find money for projects, consumer engagement, and how to create a state-wide initiative for healthcare IT. Just like the state of Montana, talks covered a lot of territory.

 

 

 

Here’s a small review of what attendees experienced:

Voice Technology

I had the honor of kicking off the HIMSS Montana Chapter “Transforming Healthcare” conference with an introduction to how voice technologies show promise in patient care. There’s still a lot of concern in the industry about what these voice assistants are tracking, and the speaker immediately after me talked about a surgeon using Alexa to play music in the operating room (a non-compliant use as Alexa might be ‘listening’ to the conversation). However, today’s news that Comcast is also getting into the voice healthcare game shows that there is real promise and high stakes. If you’re interested in this topic you might want to check out our white paper on considerations for designing voice interfaces for patient care, or join me at Voice Summit in Newark this fall for a workshop.

Security

Not surprisingly security remains a hot topic in healthcare, probably because of the surface area of devices and IOT devices. While bad actors and hackers remain a constant threat, people and process are as important, and speakers stressed that often breaches are not malicious but when people don’t follow proper process like the backup company driver who left a van full of backup tapes in his driveway overnight where it was broken into.

Interestingly according to Fred Langston, CISSP, CCSK Executive VP of Professional Services CI Security, imaging systems account for almost 50% of security alerts, possibly because the systems involve both hardware and software, and have often been installed for years. EMRs are seen as relatively safe, and other risks come from devices, attached to the hospital network, where manufacturers have stopped upgrading or patching devices, or simply stopped support for them. The reason is that any sort of software or firmware upgrade requires new FDA certification, which may be cost prohibitive on a discontinued product. There are startups trying to solve this problem, however the FDA may also want to reconsider the unintended consequences of their certification program.

Generally, it takes 205 days within a hospital system until a compromised asset is detected. Decreasing this time and the time from the realization of the compromise and fix (known as dwell time), should be the goal of all IT departments. Hiring a security consultant organization may be the best bet for the broad scope of monitoring that needs to happen.

Finding Money for Innovation

Dianna Linder, MPA, FACHE Director of Grants and Program Development, Billings Clinic is a grant-writer who has been successful at finding funding sources for innovative projects. Much like targeting sales, donor targeting involves figuring out the value proposition you can offer to a particular donor. The Billings Clinic has a shark-tank day where everyone comes with their projects to request funding. Projects are stack-ranked and budget is applied. For those that don’t get budget, Linder looks for other sources like grants. She warns that grants are best used for projects that are new experiments and where the headcount is not part of the spend since they cannot ensure someone of a job when the grant money runs out. A great example of a use of grant money was for building an intake facility for mental health, so that people did not languish in the ED. This program used staff that were already at the system and proved successful enough that it became operationalized the following year.

At Wellpepper, we’ve seen a few projects start with grants, like the one that the Schultz Foundation provided to EvergreenHealth to kick off a patient engagement project that has since been operationalized. Grants for research projects like the one with Harvard are also interesting.

Consumer Experience

Ben WanamakerHead, Consumer Technology & Services from Aetna made us promise not to blog or tweet about his session where he shared some results from Aetna’s partnership with Apple’s smart watch. So, go see for yourself how the application uses behavioral economics and design principles to reward people for healthy behavior.

Building a State-Wide Healthcare IT Strategy

Did you know that 10 states have a state-wide healthcare IT strategy? No? Neither did I. These strategies, when aligned with Medicare and Medicaid initiatives can help drive adoption and support for healthcare technology, innovation, and modernization initiatives. The benefits of the roadmaps are to focus on healthier residents, and freeing information. Another important benefit is funding that is matched by the federal government. While this type of program may be out of reach for the average healthcare technology enthusiast, knowing that they exist can offer opportunities to align with larger initiatives.

Posted in: Adherence, Behavior Change, Health Regulations, Healthcare costs, Healthcare Disruption, Healthcare Policy, Healthcare Research, Healthcare Technology, Healthcare transformation, HIMSS, M-health, patient engagement

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Way Way Beyond HCAHPs: Cleveland Clinic’s Patient Experience Summit

It was the 10th year for the Cleveland Clinic’s innovation & empathy conference, a journey at Cleveland Clinic which started from a question from an MBA student to then CEO Toby Cosgrove asking if the Clinic’s physicians learned empathy.

You can hear him tell the story himself, and it’s personal for him.

And, if you haven’t seen Cleveland Clinic’s quintessential video on empathy, be sure to check it out.

Dr Toby Cosgrove at Cleveland Clinic

This year, Dr Cosgrove was back to talk about what Google could learn from healthcare and visa versa, as he is a newly appointed advisor to Google Health. As a surprise, he was interviewed by the same student who asked the question so many years ago. Not surprisingly, Dr. Cosgrove believes that healthcare needs to embrace big data, and care outside the clinic. He didn’t have much to offer about what Google could learn, but we’d say protecting personal data would be the biggest thing.

Possibly because he’s no longer running a physician organization and yet he is a physician himself, Dr Cosgrove was pretty blunt about the biggest barrier to transform an organization to deliver empathetic care: the doctors themselves.

Dr Victor Montori at Cleveland ClinicAnother notable keynote came from Mayo Clinic’s Dr. Victor Montori, an endocrinologist, and author of Why We Revolt: A Patient Revolution for Kind and Careful Care. Dr Montori asks us to question our biases, assumptions, and language. He decries “industrial healthcare” where we “provide care.” Care is already a verb. He advocates a person-centered approach where the goals and needs of the individual, not billing or the organization are center. Dr. Montori talked about the phenomenon of doctors doing volunteer travel vacations in other countries because it gets them back to why they became physicians: to care for people.

 

The example of a woman struggling to understand her medication, and make good food choices while being aware of her culture reminded me of visiting my mom when she was in a rehabilitation hospital. When we started bringing homecooked meals and even restaurant takeout, she ate. Physicians couldn’t understand her weight loss and hair loss, blaming it on medication. The problem was the terrible nutritional value and taste of the food.

Patient Stories

Patient stories were a key feature in the conference, while backing research up with data is important, it’s the stories that people remember.

How Walmart Started a Movement of Engagement

The power of human stories was prevalent in the presentation from Walmart’s David Hoke, who has created a movement of better health activities within the Walmart employee base, a challenging job when some stores have 100 per cent employee turnover. To create a movement that inserted a healthy virus into stores, David turned to military strategy:

  • Compelling reason to join
  • Place to join
  • Have to have something to do
  • Have something to share with people they love
  • People follow people

Instead of going directly to digital health, the program was designed to be analog to have the broadest reach, and to overcome people’s fears of being tracked. The program featured story booklets in breakrooms that highlighted other employees journey’s to health. Participants described thinking “well if that person can do it, so can I” after reading the stories, and seeing videos of successful program participants.  By the way, if you’re a Walmart customer, you can also join the program, which is now available digitally as well as analog.

Nebraska Medicine’s Situational Interviewing

Observational patient interviewingIn order to find the patient stories, you have to ask the right questions, and HCHAPs isn’t doing that. We see this all the time at Wellpepper: You need to talk to patients to get the story behind the data points. In this example, a patient had rated Nebraska Medicine highly for caring about her. Rather than just accepting this as praise, researchers dug deeper and asked how the patient perceived this, and the patient’s example was of a nurse who noticed she had dry skin and applied lotion. Another patient rated the facility high on cleanliness because he saw a physician pick up some garbage in the patient’s room. The key takeaway from this session was that patients infer intent.

Geisinger Longitudinal Patient JourneyGeisinger’s Longitudinal Patient Record

Chanin Wendling from Geisinger talked about their implementation of a CRM to be able to track a longitudinal patient experience. Knowing when and where patients are interacted with by the health system will go a long way towards understanding their overall experience.

Wellpepper Digital Intervention for Seniors

Dr. Jonathan Bean from Harvard, talked about why interventions for seniors are so important, and how design impacts whether someone is considered “able” by sharing an example of a cross walk timer being decreased so that slower people could no longer get across the street. Dr. Bean the Director of the New England GREC at the VA, professor at Harvard, and our research partner at Wellpepper, and we were extremely proud when he presented results of the REACH digital intervention using Wellpepper that reduced ED visits in seniors by 73%. We’ll share more when the study outcomes are published in the journal of PM&R.

Financial Impact of Care

Another theme that bubbled up in so many sessions at the conference is the financial impact of care, and the intertwined aspects of financial and physical health. A few key points:

  • Walmart has introduced a banking/payday loan application for employees so that they don’t have to pay the exorbitant rates of quick loan companies.
  • People cut back in other areas of their lives to pay for healthcare
  • 95% of patients want to talk to their provider about healthcare costs but providers aren’t equipped to do so. They don’t want to talk to the health plan or billing/collections department.

This was my first time at the summit, but it won’t be the last, especially as it evolves to encompass more aspects of patient experience outside the clinic, and through non-traditional methods like chatbots, virtual assistants, and virtual reality.

It’s hard to encapsulate all the learning at the conference, and no one person can attend all the sessions, but MobiHealth News has a great recap of the keynotes and individual sessions as well.

https://www.mobihealthnews.com/content/patients-more-vulnerable-other-consumers-technology-must-keep-human-empathy-center

https://www.mobihealthnews.com/content/north-america/without-co-design-technologys-healthcare-potential-wasted

https://www.mobihealthnews.com/content/north-america/providence-st-joseph-patient-engagement-begins-call-center

https://www.mobihealthnews.com/content/patient-stories-inspire-new-digital-tools-singapore-health-systems-sutter-health

Posted in: Adherence, Healthcare costs, Healthcare Disruption, Healthcare Research, Healthcare Technology, Healthcare transformation, HIMSS, M-health, Outcomes, patient engagement, Patient Satisfaction, patient-generated data, physician burnout

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Self-Driving Healthcare

It’s 2019 and your car can drive itself most of the way to your doctor’s office, but once there, you will be handed a clipboard with a paper form asking you for your name, date of birth, and insurance information. Then you will wait to be seen by a doctor, who will spend your visit facing a screen transcribing your spoken complaint into the EMR, and then ask you where you’d like your lab results faxed.

How can it be that technology is making such huge strides in some areas of our lives, while others are seemingly stuck in the last century? When will healthcare have its self-driving moment?

The Promise of Self-Driving Cars

Self-driving cars are a great example of how computer science has been applied to solve difficult real-world problems. It was less than 15 years ago that the computer science community celebrated the first autonomous vehicles successfully completing a 130 mi course in under 10 hours as part of the DARPA grand challenge. Most of the heavily-funded university research teams that entered used traditional programming techniques. The winner of this competition, Stanford University, was characterized by its use of machine learning to train a vehicle by example, rather than writing the if-then-else code by hand.

Since this time, machine learning generally, and deep neural networks in particular, have proven to be unreasonably effective in solving problems with huge and highly complex inputs like image recognition, sensor integration and traffic prediction, among others. Companies like Waymo, Volvo, Uber, and Tesla have been pouring money into the autonomous vehicle space and making rapid progress. Many cars sold today come with some level of assisted driving like lane holding and collision prevention, and Tesla vehicles even come with a “Full Self Driving” option.

Machine Learning in Healthcare

So, what about healthcare? People’s health is a highly complex function of genetics, medicine, diet, exercise, and a number of other lifestyle factors. In the same way you make thousands of little steering corrections to stay in a lane, you make thousands of choices each day that impact your susceptibility to disease, quality of life, and longevity to name a few. Can the same toolset that can help cars drive themselves help us build good predictive models for health and healthcare?

There have certainly been efforts. Including some high profile failures. One big limitation is the data. On the one hand, healthcare is awash in data. Some claim it won’t even fit in the cloud (spoiler: it will). Much of the data in healthcare today is locked up in EMR systems. Once you’ve liberated it from the EMR, the next problem is that it’s not a great input for machine learning algorithms. A recent study in JAMA focused on applications of ML in healthcare found that EMR data had big data quality issues, and that models learned on one EMR’s dataset were not transferrable to another EMR’s dataset, severely limiting the portability of models. Imagine trying to build a self-driving car with partial and incompatible maps from each city and you’ll start to understand the problem with using EMR data to train ML models.

All The Wrong Data

But more important than this: even if the EMR data was clean and consistent, a big piece of the puzzle is missing: the data about the person when they’re not in the doctor’s office. We know that a person’s health is influenced largely by their lifestyle, diet, and genetics. But we largely don’t have good datasets for this yet.

You can’t build a self-driving car no matter how much many fluid level measurements and shop records you have: “I don’t know why that one crashed, its oil was changed just 4 weeks ago. And with a fresh air filter too!”  You also can’t build meaningful healthcare ML models with today’s EMR-bound datasets. Sure, there will be some progress in constrained problems like billing optimization, workflow, and diagnostics (particularly around imaging), but big “change the world” progress will fundamentally require a better dataset.

There are efforts to begin collecting parts of this dataset, with projects like Verily’s Project Baseline, and the recently-failed Arivale. Baseline, and others like it will take years or decades to come to fruition as they track how decisions made today impact a person many years down the line.

On a more modest scale, at Wellpepper we believe that driving high-quality and patient-centered interactions outside the clinic is a major key to unlocking improved health outcomes. This required us to start by building a communication channel between patients and their care providers to help patients follow their care plans. Using Wellpepper, providers can assign care plans, and patients can follow along at home and keep track of health measures, track symptoms, and send messages. Collecting this data in a structured way opens the door to understanding and improving these interactions over time.

For example, using regression analysis we were able to determine certain patterns in post-surgical side-effects that indicate a 3x risk of readmissions. And more recently we trained a machine learned classifier for unstructured patient messages that can help urgent messages get triaged faster. And this is just scratching the surface. Since this kind of patient-centric data from outside the clinic is new, we expect that there is a large greenfield of discovery as we collect more data in more patient care scenarios.

Better patient-centric data combined with state of the art machine learning algorithms hold huge promise in healthcare. But we need to invest in collecting the right patient-centric datasets, rather than relying on the data that happens to be lying around in the EMR.

 

Posted in: Healthcare Disruption, Healthcare Technology, Healthcare transformation, machine learning, patient-generated data

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Reading for Healthcare Disrupters: In Shock, by Rana Awdish, MD

May 13-15, I’m heading to the Patient Experience Conference at Cleveland Clinic where Dr. Jonathan Bean, our research partner from Harvard Medical School will be presenting the results of a study using Wellpepper to deliver an interactive care plan for people between 65 and 85 who are at risk of adverse events. We’re excited about the positive clinical outcomes he saw, but more importantly, about the ability for technology to deliver empathy in patient care.

in shock book coverThe ultimate in empathy is to “walk a mile in someone’s shoes.” While this is often not physically possible, if you can emotionally understand someone else’s view this is the beginning of empathy. Research shows that reading fiction increases empathy, but I can imagine that non-fiction like Dr Rana Awdish’s compelling and gripping “In Shock” would do the same. Dr Awdish chronicles her near-death experience and subsequent recovery at the hospital where she practices. By becoming a patient with the mind of a doctor, she is able to deeply experience and understand both sides of a situation: the doctor who sees a case, and the patient who is so much more than a collection of symptoms. As a patient she experiences incorrect diagnoses, not being believed or listened to, arrogance, and condescension. As a physician, she struggles with her training to not get involved emotionally involved with patients and to shrug off traumatic events with her newfound understanding that experiencing pain is the only way to really empathize and connect with each other, and the only thing that will enable physicians to truly deliver care.

The book can be read as case study of experiences from both sides of the equation as Dr. Awdish struggles to make sense of her experiences, and learn how well-meaning instructions can result in the wrong outcome. For example, Dr Awdish reflects on her medical school and residency training and how it was designed to search for diagnosis not for meaning.

“We weren’t trained to listen. We were trained to ask questions that steered people to a destination”

When she’s taken to emergency and immediately steered to OB despite her protestations that the problem is not the pregnancy it’s something else, she directly experiences the impact of this training.

When Awdish is admitted to the hospital for bed rest during later pregnancy, her room becomes a defacto support group for medical professionals who need somewhere to properly process and sometimes grieve patient outcomes. This community defies their training which was to shrug off the emotions, and it’s during this period that Awdish comes to her hypothesis that switching communication may have the most powerful impact of all.

“This way of questioning, this recommendation built on empathy and a patient-centered narrative has the potential to heal everyone involved.”

Awdish is full of hope that the medical community can change. She’s a frequent lecturer and has won awards for building empathy and communication programs. The book also includes a study guide, and is being included in medical school curriculum.

You can hear Dr Awdish read from her book in this clip, or follow her on twitter @RanaAwdish

If you’re looking for more great reads check out these recommendations from our blog. Or, if podcasts are more your style, we’ve got those too.

Posted in: Behavior Change, Healthcare Disruption, Healthcare Research, physician burnout, Uncategorized

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HIPAA Compliant Voice Interfaces: Amazon Alexa Team Announcement

As an early adopter of voice interfaces, and winner of the Alexa Diabetes Challenge, we couldn’t be more excited by today’s announcement from the Amazon Alexa team about HIPAA compliance. You can read about it on the Alexa Developer Blog.

We’ve been working with voice prototypes, and have over developed voice interfaces for most of our interactive care plan building blocks, including things like tracking medication, food diaries, and hearing quick tips about your care plan. If you’re consider how to integrate voice into your patient experience, you may be interested in our new white paper on Designing Effective Voice Interfaces.

Get your copy today!

Register to get the full report

 

Verification

Posted in: alexa, Voice, voice interfaces

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The Healthcare of the Future: Equity and Access

If the sold-out “Healthcare of the Future” event presented by Puget Sound Business Journal, is any indication, Seattle is ready for healthcare transformation. Last week’s event at the Fairmont Olympic featured prominent local healthcare leaders discussing equity and access to care, and why Seattle is the right community to deliver.

Healthcare of the Future

Interesting, the panel discussion started with a definition of access, framed as not just being able to receive care, but also to navigate and understand care. Speakers mentioned that in the transition from uninsured to insured, people might now have access to care but not enough health literacy to receive care. This was exemplified when one of the panelists, a physician herself talked about a recent experience with getting care for her son where she navigated multiple providers and care settings, and all the while had a firm handle on who she was talking to, why her concerns were important, and the eventual diagnosis.

You can see examples of this everyday on #medtwitter when physicians or other healthcare professionals talk about how hard it was for them to navigate the system as caregivers for their families. Now, just imagine that you’ve never had healthcare coverage before. How do you know what your options are, how much you may have to pay, or when and where to see a doctor?

Panelists also felt that in addition to access, health equity needed to include helping patients make decisions based on their own values, not the values of the system. Again, a difficult situation to navigate for someone new to the system, or potentially being intimidated by the ‘white coat.’ Equity also looks at whether anyone is being left behind in the system, which could be from a myriad of reasons: language, cultural, or even geographical barriers. Given the problems of staffing rural clinics and hospitals, are people in remote areas able to receive the same level of care as those in the cities?

Unsurprisingly, panelists were bullish on Seattle’s ability to deliver, both from the collaborative nature of the healthcare organizations in the region, and from our stronghold of technology. Tech and healthcare partnerships were cited as the best opportunity to shorten the 17 year cycle from research to clinical practice, with technology disruption in the areas of big data, AI, and cloud infrastructure from local tech giants Microsoft and Amazon pushing the healthcare industry forward. (Let’s hope they can also solve the interoperability of data problems, as one speaker equated having the largest Epic installation at Providence as being a substitute for data portability and interoperability.)

All in all, this was a great event, and discussions at my table ranged from best practices for oncology care, especially with patient-facing tools outside the clinic, to how smart hospital room design includes sensors in the furniture to predict patient falls. That the room was buzzing before 7:30 on a Friday morning shows that we have a lot of great momentum for solving hard problems in healthcare in Seattle.

Posted in: Healthcare costs, Healthcare Disruption, Healthcare Technology, Healthcare transformation

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