Healthcare transformation

Archive for Healthcare transformation

Simple Patient-Centered Design

At Wellpepper, we work hard to make sure our software is intuitive, including working with external academic researchers on randomized control trials for people who may have cognitive or other disabilities. This is both to make sure our software is easy-to-use for all abilities, and to overcome a frequent bias we hear about older people not being able to use applications, and also to provide valuable feedback. We’ve found from these studies, the results of which will be published shortly in peer-reviewed journals, that software can be designed for long-term adherence, and this adherence to programs can lead to clinically-meaningful patient outcome improvements.

User-centered design relies on three principles, all of which can be practiced easily, but require continual discipline to practice. It’s easy to assume you know how your users or patients will react either based on your own experiences, or based on prior knowledge. There’s really no substitute for direct experience though. When we practice user-centered design, we think about things from three aspects:

Immersion

Place ourselves in the full experience through the eyes of the user. This is possibly the most powerful way to impact user-centered design, but sometimes the most difficult. Virtual reality is proving to be a great way to experience immersion. At the Kaiser Permanente Center For Total Health in Washington, DC, participants experience a virtual reality tour by a homeless man showing where he sleeps and spends his days. It’s very powerful to be right there with him. While this is definitely a deep-dive immersion experience, there are other ways like these physical therapy students who learned what it was like to age through simple simulations like braces, and crutches. Changing the font size on your screens can be a really easy way to see whether your solution is useable by those with less than 20/20 vision. With many technology solutions being built by young teams, immersion can be a very powerful tool for usable and accessible software.

Observation

Carefully watch and examine what people are actually doing. It can be really difficult to do this without jumping in and explaining how to use your solution. An interesting way to get started with observation is to start before you start building a solution: go and visit your end-user’s environment and take notes, video, and pictures.

Understanding what is around them when they are using your solution may give you much greater insight. When possible we try to visit the clinic before a deployment of Wellpepper. Simple things like whether wifi is available, how busy the waiting room is, and who is initiating conversations with patients can help us understand how to better build administrative tools that fit into the clinician’s workflow. Once you’ve started with observing your users where they will use your solution, the next step is to have them test what you’ve built. Again, it doesn’t have to be complicated. Starting with asking them how they think they would use paper wireframes or voice interface testing with Wizard of Oz scenarios can get you early feedback before you become too attached to your creations.

Conversation

Accurately capture conversations and personal stories. The personal stories will give you insight into what’s important to your users, and also uncover things that you can’t possibly know just by looking at usage data. Conversations can help you with this. The great thing about conversations is that they are an easy way to share feedback with team members who can’t be there, and personal stories help your team converge around personas. We’ve found personal stories to be really helpful in thinking about software design, in particular understanding how to capture those personal stories from patients right in the software by letting them set and track progress against their own personal goals.

Doctor’s often talk about how becoming a patient or becoming a care-giver for a loved one changes their experiences of healthcare and makes them better doctors. This is truly user-centered design, but deeply personal experience is not the only way to learn.

To learn more:

Check out the work Bon Ku, MD is doing at Jefferson University Hospital teaching design to physicians.

Visit the Kaiser Permanente Innovation Center.

Learn about our research with Boston University and Harvard to show patient adherence and outcome improvements.

Read these books from physicians who became patients.
In Shock: My Journey from Death to Recovery and the Redemptive Power of Hope, Rana Adwish, MD
When Breath Becomes Air Paul Kalanithi, MD

Posted in: Adherence, Aging, Behavior Change, Clinical Research, Healthcare Technology, Healthcare transformation, patient engagement, Patient Satisfaction, Research

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Promise, Adoption, and Reality: Dispatches from Connected Health 2018

It’s a rare feat to be engaged, educated, and entertained at the same time, but the Oxford-style debate at Connected Health on telehealth’s effectiveness did all three. Moderated by new Chief Digital Officer for Partners Healthcare, Alistair Erskine, MD, with Ateev Mehrotra, MD debating that telehealth is not effective, and head of the American Telemedicine Association, Andrew Watson, MD debating that it is, the format and discussion delivered a provocative closing session on Day 1 of Connected Health. As decided by the audience, the winner was Dr. Watson, citing effective programs like telestroke, consults and expert referrals, and rural medicine. However, applause for Dr. Mehrotra was also strong, and I suspect that his major points that telehealth has not reached broad adoption, and in fact there have been observations that telehealth is actually increasing utilization as people follow a telehealth visit with an in-person visit. The question is whether that visit wouldn’t have happened and we’d see worse health outcomes, or whether the person had a problem that couldn’t be helped with telehealth.

In another deep dive session on telehealth, “Making Connected Health Work for Physicians”,  Kevin Fickenscher, MD talked about a unique program to train clinicians on virtual visits. Given that the diagnostic capabilities are different, for example, you can’t touch the patient, this makes perfect sense. Questioning and listening skills are going to be more important than physical exam, and observation may be limited by (current) video technology. Also in this session, Ami Blatt MD from Partners, talked about how her young and mobile patients essentially lead her to telemedicine, by insisting that was how they wanted to communicate: the consumerization of healthcare in action. She also recommended to any physicians wanting to deploy a telemedicine solution to make sure that the goals of the program align with the financial incentives available for the hospital.

So, what do we take away from this? Twenty years later, telemedicine is still in the promise stage. Practice and reimbursement needs to change even more to find true breakthroughs, and perhaps we should look at pattern matching to find other successful workflows and outcomes that resemble the benefits for telestroke.

In no particular order, here are some other observations from the conference:

  • Patients are taking a bigger role, whether that was a patient co-presenting in a session on Patient Generated Health data, the Wego Health Awards honoring LupusLady as an activated and collaborative patient, or the society for Participatory Medicine pre-day with patients included, the voice of patients is increasingly being listened to with a real seat at the table.
  • Digital therapeutics and behavioral health are hot. There was a special pavilion on the tradeshow floor dedicated to digital therapeutics where our fellow Seattle health innovators, 2Morrow presented great results from their smoking cessation programs.
  • Patient-generated data is starting to show promise and much greater acceptance by clinicians, particularly in the ability for clinicians and patients to talk to each other. However, we’d still like to see a better connection of data and actionable care plans, and there was still some mention of the data being better because patients cheat when verbally relating data like blood sugar after the fact. Data alone isn’t enough to support patients or change behavior, and it shouldn’t be continued punitive.


From Session: PGHD End User Experience: Patients and Providers

  • There’s a continual blurring of the lines with engagement, particularly member and patient engagement, and there were a ton of new companies in this space (again), all offering to get members and patients engaged. From their overviews it was hard to tell how targeting providers and payers was even different aside from the terminology.
  • Although a full-day devoted to voice interfaces definitely showed it’s a hot topic, AI was definitely the buzzword of the show.

We’re already gearing up for HIMSS 2019 where we hope the buzzword of the show will be “outcomes”. We just heard that our talk on the (really positive) results of the REACH study has been accepted. See you there?

Posted in: Health Regulations, Healthcare motivation, Healthcare Technology, Healthcare transformation, HIMSS, M-health, patient engagement, Patient Satisfaction, patient-generated data, Telemedicine, Voice

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Voice.Health Shows The Promise of Conversational Interfaces

“By embracing voice, healthcare has the opportunity to leapfrog technology from other industries” John Brownstein, PhD, Chief Innovation Officer, Boston Children’s Hospital

Dr. Brownstein was speaking in shared keynote at the Voice.Health summit about why he and other healthcare innovators are so pumped about the opportunity for voice in healthcare. On a later panel Shivdev Rao, MD from UPMC Enterprises described what makes voice a natural fit.

75-80 percent of the signal in a hospital is voice-driven
Shivdev Rao, MD, Vice President, UPMC Enterprises

The one-day concentrated pre-day at Connected Health focused on all things voice tech in healthcare and was kicked off by Klick Health founder and CEO Leerom Segal, who talked about the factors that made this time ripe for voice in the tech industry overall. Putting technology in context is exactly what’s needed at more healthcare events versus a sometimes myopic view of healthcare technology.

So why is voice having a moment?

  • Compute power necessary for processing the large amounts of data that voice creates and requires is now available and relatively inexpensive through cloud offerings from Amazon, Google, and Microsoft
  • Devices are cheap and ubiquitous
  • We’re already trained to expect instant answers but starting to be sensitive to the impact of screen time
  • Voice is seen as more accessible to broader groups
  • And of course, voice is being used as a Trojan horse for commerce (at least by Amazon), for Google it’s for more data

In addition to panels on clinical and consumer impact of voice in healthcare, there was an immersive experience with examples of voice technology in different healthcare settings including clinic, hospital room, operating room, senior home, and an actual home living room. We participated on the consumer panel, and showcased Sugarpod (in the living room since there wasn’t a bathroom.) During the course of the day, and in the keynote at least a hundred potential uses for voice in healthcare were explored. At the same time, participants didn’t shy away from challenges either, like using voice for the wrong purposes like converting pages and pages of web content, or the challenges for people with hearing, cognition, or speech problems to use the devices, all of which can be mitigated with thoughtful voice interaction design, accessibility design, and user testing.

Clinicians have particular concerns about voice. From UPMC, Dr. talked about the challenges of any new and shiny technology in healthcare

As well, similar to what we’ve seen with other technology starting with the real problem of EMR screen time but also including mobile outside the clinic to machine-learning and artificial intelligence, clinicians are concerned about any technology getting between them and their patients. From Robert Stevens, Executive Director and Head of Digital for Novartis summed up what he had heard from physicians “I don’t to be usurped by a smart hockey puck at patient point of care.”

We’re bullish on voice, and agree with Brownstein, that embracing this technology puts healthcare on the cutting-edge technology-wise. It’s also an opportunity for new players, as the incumbents have not proved themselves capable of embracing consumer or end-user centric design that voice requires. We’re also still firmly in the “voice and” camp, looking at voice user interface as one of a number of tools for engaging patients as part of a comprehensive overall digital strategy. Planning and delivering on  a context-aware omni-channel adoption strategy for digital health is another way healthcare has an opportunity to evolve with the overall technology and consumer markets who also haven’t solved this thorny problem.

If you’d like to talk about how to deliver a consistent and engaging omni-channel experience that improves patient outcomes, get in touch sales@wellpepper.com

If you’re interested in voice, check out our other blog posts on the topic:

Posted in: Adherence, Healthcare Social Media, Healthcare Technology, Healthcare transformation, M-health, patient engagement, Patient Satisfaction, Voice

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Podcasts for Healthcare Transformation Enthusiasts

If you like to nerd out about healthcare, we’ve got a cornucopia of great podcasts for you to choose from in no particular order. Happy listening!

White Coat Black Art

This long-running podcast from CBC radio in Canada is hosted by Brian Goldman, MD, and does not shy away from tough topics like assisted suicide, medical errors, or the health impacts of legalizing marijuana.

 

A Healthy Dose

Steve Kraus of Bessemer Partners and Trevor Price of Oxeon partners interview a who’s who of health tech pioneers and entrepreneurs. Their conversation with AthenaHealth founder Jonathan Bush on cold medicine is not to be missed.

 

 

Inside Health

This BBC podcast hosted by Mark Porter, MD, explores fact and fiction for common health issues, and the state of the National Health System in the UK. It’s worth listening both for the medical advice and for insight into a different system of care.

 

 

Tech Tonics

Tech Tonics David Shaywitz, MD, PhD, and Venture Valkyrie, Lisa Suennen weigh in on unicorns and reality, and interview physicians and founders in this health tech focused podcast.

 

 

 

This Week In Healthcare IT

This Week In Health ITFormer hospital CIO current expert in cloud computing for healthcare, Bill Russell interviews health IT experts, with a heavy emphasis on hospital healthcare IT experts on topics like security, interoperability, and the shift to the cloud.

 

 

Well Connected

Innovation veteran, Joe Kvedar, MD from Partners Health interviews peers and colleagues on both current and new technologies.

 

Outcomes Rocket


This podcast from Saul Marquez delivers with a focus on outcomes, value, and cost-savings in healthcare.

 

 

 

Voice First Health

Alexa enthusiast, and Canadian physician, Teri Fisher, MD is bullish on the potential for voice interactions in healthcare.

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

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Reflecting on Wellpepper

I am a third year internal medicine resident from the University of Georgia. For the last four weeks I had the good fortune to travel from Athens, Georgia to Seattle, Washington and work with Wellpepper as a resident physician consultant. As a young physician, I have a lot of hope for electronic health systems and their ability to decrease our workload, increase our efficiency, and improve patient care. In residency, we spend anywhere from 25% to 75% of our time looking at the electronic medical record, but we do not get the opportunity to see it from the other side. When I found out about the opportunity to work with a health tech company for an elective rotation, it seemed like a great way to see things from different perspective. There was the added benefit of escaping a humid Georgia summer month and instead spending it in the beautiful Pacific Northwest where I hope to work after residency.

While at Wellpepper I worked on a variety of projects in several different roles. My primary responsibility was to work on care plan development. A particular care plan they were interested in based on feedback from their customers was pain and opioid management. Considering the opioid epidemic we are currently facing in medicine, this seemed like a great idea. Many of the patients in our resident clinic are chronic pain patients or come to us already on opioids from other providers. Unfortunately, I have received very little training in opioid management (our residency clinic is not allowed to prescribe opioids or benzodiazepines) . While I understand the sentiment behind this, it is not helpful to residents who need to learn how to manage these types of medications for their future practices . Developing a care plan around opioid management presented a wonderful learning opportunity. I designed the opioid care plan and taper program with the opioid-naïve physician in mind, providing a platform to help guide patients and physicians through the intricacies of opioid management and withdrawal. Many of the other care plans I helped work on throughout the month were more on the surgical side of things, but closely related to internal medicine because of how often we work with pre and post-surgical management of patients and these also provided great learning opportunities.

The month culminated in a trip to meet with Mayo Clinic in Rochester, Minnesota. Wellpepper has a unique partnership with Mayo Clinic to build their care plan best practices into the Wellpepper platform to help improve patient care and outcomes. Participating in meetings with administrators, secretaries, clinical research nurses, and physicians at the forefront of their specialties was an extremely unique opportunity . I thought my medical school, the University of Kansas, was a big hospital. It paled in comparison to the small city of Mayo Clinic. It was quite the experience just to be there.

In short, my month with Wellpepper provided a glimpse into the medical tech industry and provided a unique opportunity to work as a consultant outside of patient care. In the electronic medical record world, the focus is on functionality for the healthcare providers. Apps for patient use present an interesting challenge in creating something that is clinically useful for providers but also user friendly and not bogged down in medical jargon for the patients to be able to navigate. It was nice to experience seeing what creating those types of tools for patients looked like from a perspective other than the provider. There were plenty of learning opportunities throughout the month (as well as plenty of extremely valuable study time with board exams on the horizon). While I do not see working exclusively as a physician consultant in my immediate future, I plan to continue to champion electronic health records and mobile services to pursue continued improvement in patient care and outcomes .

From left to right: Myself, Anne Weiler, and Luke Feaster visiting Mayo Clinic.

Posted in: Healthcare Technology, Healthcare transformation

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Machine Learning in Medicine

As a new intern, I remember frequently making my way to the Emergency Department for a new admission; “Chest pain,” the attending would tell me before sending me to my next patient. Like any good intern I would head directly to the paper chart where I knew the EKG was supposed to be waiting for me, already signed off on by the ER physician. Printed in standard block print, “Normal Sinus Rhythm, No significant ST segment changes” I would read and place the EKG back on the chart. It would be later in the year before I learned to ignore that pre-emptive diagnosis or even give a thought to about how it got there. This is one of many examples how machine learning has started to be integrated into our everyday life in medicine. It can be helpful as a diagnostic tool, or it can be a red herring.

Example of machine-learning EKG interpretation.

Machine learning is the scientific discipline that focuses on how computers learn from data and if there is one thing we have an abundance of in medicine, data fits the bill. Data has been used to teach computers how to play poker, learn laws of physics, become video game experts, and provide substantial data analysis in a variety of fields. Currently in medicine, the analytical power of machine learning has been applied to EKG interpretation, radiograph interpretation, and pathology specimen identification, just to name a few. But this scope seems limited. What other instances could we be using this technology in successfully? What are some of the barriers that could prevent its utilization?

Diagnostic tools are utilized in the inpatient and outpatient setting on a regular basis. We routinely pull out our phones or Google to risk stratify patients with ASCVD scoring, or maybe MELD scoring in the cirrhotic that just got admitted. Through machine learning, these scoring systems could be applied when the EMR identifies the correct patient to apply it to, make those calculations for the physician, and present it in our results before we even have to think about making the calculation ourselves. Imagine a patient with cirrhosis who is a frequent visitor to the hospital. As a patient known to the system, a physician has at some point keyed in the diagnosis of “cirrhosis.” Now, on their next admission, this prompts this EMR to automatically calculated and provide a MELD Score, a Maddrey Discriminant Function (if a diagnosis of “alcoholic hepatitis” is included in the medical history). The physician can clinically determine relevance of the provided scores; maybe they are helpful in management, or maybe they are of little consequence depending on the reason for admission. You can imagine similar settings for many of our other risk calculators that could be provided through the EMR. While machine learning has potential far beyond this, it is a practical example where it could easily be helpful in every day workflow. However, there are some drawbacks to machine learning.

Some consequences of machine learning in medicine include reducing the skills of physician, the lack of machine learning to take data within context, and intrinsic uncertainties in medicine. One study includes that when internal medicine residents were presented with EKGs that had computer-annotated diagnoses, similar to the scenario I mentioned at the beginning of this post, diagnostic accuracy was actually reduced from 57% to 48% went compared to a control group without that assistance (Cabitza, JAMA 2017). An example that Cabitza brings up regarding taking data in context is regarding pneumonia patients with and without asthma and in-hospital mortality. The machine-learning algorithms used in this scenario identified that patients with pneumonia and asthma had a lower mortality, and drew the conclusion that asthma was protective against pneumonia. The contextual data that was missing from the machine learning algorithm was that the patient with asthma who were admitted with pneumonia were more frequently admitted to intensive care units as a precaution. Intrinsic uncertainties in medicine are present in modern medicine as physician who have different opinions regarding diagnosis and management of the same patient based on their evaluation. In a way, this seems like machine-learning could be both an advantage and disadvantage. An advantage this offers is removing physician bias. On the same line of thought, it removes the physician’s intuition.

At Wellpepper, with the Amazon Alexa challenge, machine learning was used to train a scale and camera device (named “Sugarpod“) in recognizing early changes in skin breakdown to help detect diabetic foot ulcers. Given the complications that come with diabetic foot ulcers, including infections and amputations, tools like this can be utilized by the provider to catch foot wounds earlier and provide appropriate treatment, ideally leading to less severe infections, less hospitalizations, less amputations, and lower burden on healthcare system as a whole. I believe these goals can be projected across medicine and machine learning can help assist us with them. With healthcare cost rising (3.3 Trillion dollars in 2016), most people can agree that any tools which can be used to decrease that cost should be utilized to the best of its ability. Machine learning, even in some of its simplest forms, can certainly be made to do this.

Posted in: Healthcare costs, Healthcare Technology, Healthcare transformation

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The Challenge of Challenges: Determining When To Participate

There’s an explosion of innovation in healthcare and with that comes a plethora of incubators, accelerators, pitches, challenges, prizes, awards, and competitions. Trying to sort through which ones are worth paying attention to can be a full-time job. At Wellpepper we’ve tried to be selective about which ones we enter. A recent post by Sara Holoubeck, CEO and founder of Luminary Labs about the outcomes of challenges got me thinking about the cost/benefit analysis of entering challenges. Both costs and benefits come in hard and soft varieties.

If you want to be scientific, you can assign a score to each of the costs and the benefits, and use it to decide whether to throw your hat in the ring. (For the purposes of this blog post, we’ll use the term “challenge” to refer broadly to all of these opportunities.)

Costs

  • Time: How many hours will your team need to put into this challenge? How much of your team needs to be involved?
  • Focus: Does the focus on this challenge distract your team from core customer or revenue priorities?
  • Financial: Is there an entry fee to participate? What other costs, like travel, may you need to incur to deliver on the challenge?
  • Strategy: Is this challenge aligned with your
  • IP: Do you have to give up intellectual property rights as part of this challenge? Do you have to give away any confidential information that you are not yet ready to share publically?

Benefits

  • Financial: Is there prize money? Does it cover your expected costs? Could you actually profit from entering? If winner receives funding who decides the terms? Is this an organization that would be beneficial to have on your cap table?
  • Focus: Does this challenge provide the team with a forcing function to deliver innovation in an area that is aligned with your overall strategy?
  • Innovation: Does this challenge take your team in stretch direction or enable you to demonstrate a direction on your roadmap that you may otherwise not immediately approach due to market issues?
  • Publicity: Where will the winner be announced? Is there a PR strategy for the entire process or just the winner? Does it help your organization to be aligned with the content or sponsors of this challenge?
  • Introductions: Who will this challenge help you meet that can further your business goals?

It’s up to you to consider the cost/benefit analysis. Both may not have to be high, but when they are the opportunity can be high if you have the ability to put in the effort. You may also consider your chances of winning if it’s defined as a competition, and whether there is any drawback to losing, or if just participating provides enough benefit.

Here are a few examples from our own history that may help illustrate the tradeoffs.

Low cost/medium benefit

We entered a local pitch event for a national organization. The effort to pitch was minimal: we had case studies and examples that fit the thesis directly. The event was nearby and there was no cost to enter. The pitch was short. We won this pitch and got some local awareness and leads. However, when we were offered to go to the national conference and pitch for an even shorter period in a showcase heHIMSS Venture+ Winnersld simultaneously with other conference activities and with no actual competition, we declined as the cost/benefit was not there.

Medium cost/medium benefit

Each year HIMSS has a venture competition at the annual conference. We won this event in 2015, and received PR as well as in-kind benefits at HIMSS conferences including booth space. The effort to prepare was medium: any startup should be prepared for an onstage venture pitch, and the audience was exactly right. As a follow on from this event we’ve been involved in panels showcasing our progress.

High cost/migh benefit

Both the Mayo Clinic ThinkBIG challenge, and the Alexa Diabetes Challenge had a relatively high effort and opportunity cost to participate and high rewards, but both were aligned with directions our company had already embarked on, and both resulted in deeper connections for us with the sponsoring organizations, positive press, validation of our company and solution, and financial support.

In the case of the Mayo Clinic ThinkBIG challenge, we received investment on our convertible note for winning, and the challenge afforded us introductions to important clinical and IT contacts at Mayo Clinic. We were also able to showcase our solution to other potential customers live at the annual Transform event.

Our team put in a tremendous effort on our winning entry for the Alexa Diabetes Challenge but the pay-off was worth it in a number of ways. Certainly the prize money and publicity was welcome, but more importantly, we have created new IP and also come to a whole new understanding of how people can move through their daily lives with technology to support them in managing chronic conditions.

Both of these challenges have afforded us ongoing opportunities for engagement and awareness as a result our participation, and our positive outcomes.

One thing to note, none of these challenges I mention had an entry fee. Sometimes nominal entry fees are used to deter casual entries, but for the most part if a challenge is seeking to fund itself by charging the startups to participate, it’s the wrong model.

While you don’t have to be this explicit when making your decisions about entering a challenge, consideration of the costs and opportunity cost of either participating or not, can help you sort through the ever increasing number of grand challenges.

Posted in: Healthcare Disruption, Healthcare Technology, Healthcare transformation, Uncategorized, Voice

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Dispatches from the Canadian E-Health Conference: The same but different

Bear statue in VancouverThe annual Canadian E-Health Conference was held in Vancouver, BC last week. I had the opportunity to speak about the work we’re doing at Wellpepper in applying machine learning to patient-generated data, and in particular the insights we’ve found from analyzing patient messages, and then applying a machine-learned classifier to alert clinicians when a patient message might indicate an adverse event. Our goal with the application of machine-learning to patient generated data is to help to scale care. Clinicians don’t need to be alerted every time a patient sends a message; however, we don’t want them to miss out if something is really important. If you’d like to learn more about our approach, get in touch.

My session was part of a broader session focused on ‘newer’ technologies like machine-learning and blockchain, and some of the other presenters and topics definitely highlighted key differences between the US and Canadian systems.

Aside from the obvious difference of Canada having universal healthcare, there were subtle differences at this conference as well. While the same words were used, for the most part: interoperability, usability, big data, and of course blockchain and AI, the applications were different and often the approach.

Interoperability: Universal doesn’t mean one

Each province has their own system, and they are not able to share data across provinces. Unlike the UK which has a universal patient identifier, your health records in Canada are specific to the province you live in. As well, apparently data location for health records is sometimes not just required to be in Canada, but in the actual province where you reside and receive care. As for interoperability, last we heard, British Columbia was doing a broad roll out of Cerner while large systems in Alberta were heading towards EPIC, so Canada may see the same interoperability challenges we see here if people move between provinces.

Privacy: The government is okay, the US is not

What’s interesting is as a US company, is that whenever we talk to health systems in Canada they bring up this requirement, but as soon as you mention that the PIPEDA requirements enable patients and consumers to give an okay for out of Canada data location they agree that it’s possible. Regardless, everyone would rather see the data in Canada.

What was possibly the most striking example of a difference in privacy was from one of my co-presenters in the future technologies session, who presented on a study of homeless people’s acceptance of iris scanning for identification. 190 out of 200 people asked were willing to have their irises scanned as a means of identification. This identification would help them access social services, and healthcare in particular. The presenter, Cheryl Forchuk from the Lawson Health Research Institute said that the people who participated didn’t like to carry wallets as it was a theft target, that they associated fingerprinting with the criminal justice system, and that facial identification was often inaccurate due to changes that diet and other street conditions can make. When I tweeted the 95% acceptance rate stat there were a few incredulous responses, but at the same time, when you understand some of the justifications, it makes sense. Plus, in general Canadians have a favorable view of the government. The presenter did note that a few people thought the iris scan would also be a free eye exam, so there may have been some confusion about the purpose. Regardless, I’m not sure this type of identification would play out the same way in the US.

Reimbursement: It happens, just don’t talk about it

The word you didn’t hear very much was reimbursement or when you did, from a US speaker the audience looked a bit uncomfortable. The funny thing is though, that physicians have billing codes in Canada as well. It’s just that they are less concerned about maximizing billing versus being paid for the treatment provided and sometimes even dissuading people from over-using the system. Budgets were discussed though, and the sad truth that money is not always smartly applied in the system, and in a budget-based system, saving money may decrease someone’s future budget.

Blockchain: It’s not about currency

Probably the biggest difference with respect to Blockchain was the application, and that it was being touted by an academic researcher not a vendor. Edward Brown, PhD from Memorial University suggested that Blockchain (but not ethereum based as it’s too expensive) would be a good way to determine consent to a patient’s record. In many US conferences this is also a topic, but the most common application is on sharing payer coverage information. Not surprisingly this example didn’t come up at all. If you consider that even though it is a distributed ledger, a wide scale rollout of Blockchain capabilities for either identification or access might be more likely to come from a system with a single payer. (That said, remember that Canada does not have a single payer, each province has its own system, even if there is federal funding for healthcare.)

“E” HR

Physician use of portalFor many of the session the “E” in e-health stood for EHR, which while also true in the US, the rollout of wide scale EHRs is still not as advanced. Cerner and EPIC in particular have only just started to make inroads in Canada, where the a telecommunications company is actually the largest EHR vendor. In one session I attended, the presenter had done analysis of physician usage of a portal that provided access to patient labs and records, but they had not rolled out, what he was calling a “transactional” EHR system. Physicians mostly accessed patient history and labs, and felt that if the portal had prescribing information it would be perfect. Interesting to see this level of access and usage, but the claim that they didn’t have an EHR. What was also interesting about this study is that it was conducted by a physician within a health system rather than an academic researcher. It seemed like there was more appetite and funding for this type of work within systems themselves.

Other Voices: Patients!

Patients on the mainstageDuring the interlude between the presentations and judging for the well-attended Hacking Health finals, and on the main stage, presenters interviewed two advocate patients. While they said this was the first time they’d done it, both patients had been at the conference for years. So while the mainstage was new, patient presence was not, and patient advocate and blogger Annette McKinnon pushed attendees to go further when seeking out engaged patients. Noting that retirees are more likely to have the time to participate in events she asked that they make sure to seek out opinions for more than 60 year old white women.

There was also an entire track dedicated to First Nations Healthcare. Think of the First Nations Health authority as a VA for the indigenous people of Canada, which incorporates cultural differences and traditional practices of the First Nations people. The track started and concluded with an Elder song and prayer.

Manels

Speaking of diversity, I didn’t witness any manels.

Best Quote

 

Posted in: big data, Clinical Research, Health Regulations, Healthcare Disruption, Healthcare Research, Healthcare Technology, Healthcare transformation, Interoperability, M-health, patient-generated data

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Healthcare Transformation: Emulating Disney Is Not A Bad Idea

Last week, I had the privilege of speaking to a group of CMIOs about disruption and consumerism in healthcare. We had a lively discussion, with the two main takeaways being that having a broad digital strategy is key, and also that healthcare really needs to find its own way to delivering the things consumers want. While looking to other industries for inspiration is a good way to think about change, blindly implementing strategies without thinking about how to adapt them for your own industry is not a good path.

We started off the discussion with this quiz from Elizabeth Rosenthal, former physician and health editor of the New York Times, and author of An American Sickness. Try it for yourself: it’s fun to try to figure out which is the hospital and which is the luxury hotel. (The CMIOs got 8/12 correct. Can you beat them?)

This prompted a debate about how much environment matters to healing, and why hospitals have no “back office.” Having a calming environment can definitely promote healing, however, it wasn’t clear from some of the images presented in the quiz whether healing or luxury was the goal.

Adopting ideas from other industries without fully understanding their priorities and understand how they might differ from your goals. For example, people may complain about the Disneyfication of healthcare, and point to managing to the HCHAPS survey as driving this and other evils. However, did you know that Disney’s #1 corporate value is safety? Adopting safety as a number one organizational value in healthcare would be completely relevant and appropriate. What has happened with these hotel-like experiences is adopting the surface of what Disney stands for without understanding the core goals and objectives of the experience or of the patient, or even of what Disney is trying to achieve.

Recently I received this in the mail from UnitedHealthcare.

Much has been written about the power of hand-written notes, however, usually within business situations and often from a senior manager to a junior manager. This, however, is not a good use of a handwritten note. It’s so many kinds of wrong, and bordering on creepy, especially since I had just gone for my annual physical.

The pressure to deliver better service, and better outcomes is not going to decrease in healthcare. However, it’s easy to avoid these types of pitfalls by considering what people are really looking for. This might not be the same for all patients, but we think this sets up a good framework to approach consumerization.

In addition to thinking about how your offerings, outreach, and engagement with patients fulfills these needs, going a step further, you could try to think about which one of these is most important to each individual patient, and that’s really the crux of delivering a great patient or consumer experience.

Posted in: Healthcare Technology, Healthcare transformation, Meaningful Use, Outcomes, patient engagement, Patient Satisfaction

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HIMSS 2018: We’re having a party in your house!

From the opening keynote of HIMSS 2018, you could tell things were going to be different. Unlike last year, where actors touted the marvels of flash drives and backup storage, this year kicked off with singers from The Voice. Not sure how to interpret their music choices, though, I’m sure Leonard Cohen never envisioned his anthem Hallelujah pumping up 45,000 healthcare IT experts.

Keynote speaker Eric Schmidt executive chairman of Alphabet, admonished the crowd to get to the cloud, any cloud, even Google Cloud’s competitors. He also described a scenario with an assistant named Liz, listening in on a doctor/patient visit and transcribing notes. Ironically, this exact scenario was announced by Microsoft the week before. I’ve witnessed shifts to digital and cloud before in other industries, and it does take a village, so Eric calling on the power of the technology and being rather vendor agnostic is a good sign. That said, there were a few things in his talk that might have ruffled his audience. First, where were the partners? In the utopia of voice and cloud for healthcare that Schmidt described the only partner referenced was Augmedix, poster child for Google Glass, and absolutely no healthcare system examples. Which makes sense, as when asked by HIMSS president emeritus, Steven Lieber for his parting words to the crowd, Schmidt said:

“You’re late to the party.”

Which is an interesting comment at as he was a guest keynote speaker at a healthcare IT event and representing big tech, so you could interpret this to mean:

“You’re late to the party (that we’re throwing in your house).”

As the keynote emptied in a mass stream to the tradeshow floor, I eavesdropped on a number of conversations, and many people weren’t too happy about the message: “they (aka tech) don’t understand how complicated our lives are.” It’s an interesting conundrum, because Google et al have solved some pretty complicated problems making sense of what we’re all looking for online, a problem of completely unstructured data, and yet, as recent Facebook incidents show, there can be a lack of respect for people’s data and privacy that is crucial for any type of healthcare deployment in big tech.

The tradeshow floor itself showed a lot of new entrants, including booths from Lyft and Uber, who previously had only partnered with companies like Circulation for medical transportation, and a much larger Google Cloud and Amazon Web Services presence than the previous year. Microsoft and IBM have been at the healthcare party for a long time, and have settled in.

Big tech is indeed at the party. Who else is at the party? Purveyors of security and in particular block-chain crypto were definitely there. We saw APIs hanging around the punch bowl, this time invited by the new Blue Button 2.0 initiative, unlike previous years as the date of big tech.

Who wasn’t at the party? Patients. On the one hand, we’ve found that the digital patient experience and patient engagement is now mainstream, and our research partner Tamara Deangelis from Boston University Center for Neurorehabilitation was awesome talking about patient/provider messaging at the patient engagement summit. At the broader HIMSS conference, it seemed only vendors were representing patients. Most of the patient invitations must have gotten lost in the mail.

One CIO I talked to suggested that there was a different feeling at HIMSS this year and that this is the year we’ll look back and see that things really changed for healthcare IT. We’ve seen an acceleration of the shift to the cloud for new patient-facing applications, and a rapid realization of a need for an overall patient digital strategy. All heartening, especially since it will take everyone at the party to accomplish this transformation, debutantes and charming hosts alike.

Until next year’s party, cheers!

(Footnote: The actual Google Cloud party had a long line immediately, so some people heeded Schmidt’s words about not being late for the fantastic view of the Bellagio fountains, poke bowls, and open bar. The party was predominantly male, which hopefully isn’t part of the vision. Of course, it was at the same time as the Women in Healthcare IT event, which I heard was awesome. Perhaps a poor party choice on my part.)

Posted in: Healthcare Technology, Healthcare transformation, HIMSS, Interoperability

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Supporting Patient Motivation

What motivates people to improve their health and stay on the right track over time?

This question is on the mind of every practitioner, whether it’s a physician sending someone home with a wound care plan, a nutritionist giving dietary advice to help manage diabetes or a physical therapist providing exercises to get a frozen shoulder moving again. They’re thinking: “Will the patient do it?” To a great extent, the answer to this question determines how successful their treatment plans will be.

Some of this blog’s most popular posts have explored the issue of motivation because it is a major underpinning of patient engagement technology – will the patient use, and stick with, the technology that in turn helps them adhere to their care plans?

The subject of motivation usually starts with a discussion about goal-setting. This process, at least in the medical context, typically begins when the practitioner sets goals for the patient and provides a care plan that tells the patient what they need to do in order to get there. Some practitioners feel this should be motivation enough for a patient. In reality, they know it’s not.

So what is motivation? A great deal of research has gone into the subject, particularly with regard to behavior change. It is most often described as being either extrinsic (outside the individual) or intrinsic (inside the individual). With extrinsic motivation, we engage in a behavior or activity either to gain some sort of external reward or avoid a negative consequence. With intrinsic motivation, we engage in something because we find it personally fun or rewarding.

While these are the two areas most often discussed, there are other, deeper dimensions to motivation, including fear-based and development-based motivators – and these can be either extrinsic or intrinsic. Understanding the interplay among these different forms of motivation is an important element in successful health coaching and in the creation of successful, supportive technologies that assist people in reaching their health goals.

Fear-based motivation comes in two basic flavors: deficiency-based and threat-based. Deficiency-based motivations come from the sense you are lacking in some way. These can have an external, socio-cultural source (just watch any personal care product advertisement: you smell bad, your hair is the wrong color and your teeth aren’t nearly white enough) or an intrinsic source (e.g. internal pressure “shoulds,” self-imposed discipline or overcoming the deficiency of lost health). Threat-based motivations tap into fear at a deeper level. In the world of medicine, this might be a medical incident that serves as a wake-up call, and the threat of disability or death propels a person to make serious lifestyle changes.

Development-based motivation tends to come from the desire for personal growth or self-actualization. It can also be externally sourced (e.g. from positive peer health norms or positive environmental conditions like smoke-free public spaces) or intrinsic – from the satisfaction, pleasure or joy we derive from doing something.

Research has shown that while fear can be a great motivator for getting people started on something, the positive, development-based motivators tend to be more powerful in keeping people engaged and active in behavior change over the longer term.

I believe one of the reasons the Wellpepper patient engagement platform is so successful at driving patient engagement with care plans (70% engagement compared to an average of 20% engagement with portals) is because the Wellpepper team understands this complex motivation dynamic very well and they have incorporated some of the most successful elements from it into their platform. They call it the “3rd approach” and here’s why I think it works.

Wellpepper takes a very obvious extrinsic motivator – the practitioner’s care plan – and turns it into an application that incorporates both intrinsic and extrinsic development-based motivators that keep people engaged over time. There are many layers we could explore here, but we’ll start with a few of the big ones.

Setting aspirational goals: In addition to the functional goals set by the practitioner, Wellpepper provides the ability for patients to set their own personally meaningful, aspirational goals that can support and reinforce their motivation to heal. For example, someone recovering from a total joint replacement operation might set a future vision of wanting to hike to their favorite fishing spot with a grandchild. They can use Wellpepper to set interim goals that lead them toward that vision and can rate their own progress on a Likert scale.

Research in positive psychology has shown that this kind of personal vision and goal setting is highly successful at sustaining motivation over time. In this case the patient is more likely to complete their prescribed exercises because it leads them toward goals that are personally meaningful about their own healing and about doing something special with someone they love.

Personalized experience: Wellpepper also provides a personalized experience for the patient. Using the same joint replacement example, instead of getting a piece of paper with a series of exercise diagrams or a generic video, the practitioner can record the patient doing their own exercises. Seeing yourself, and hearing the personal comments of the physician or physical therapist as you do it, is not only easier to follow, it feels personal. And, as you begin to improve, when you watch yourself then and now, seeing your own progress can be very satisfying (a powerful development-based motivator).

Adaptive notification: Wellpepper’s patented adaptive notification system means the patient doesn’t get the same generic reminder every day – it changes the notification based on the patient’s progress and level of engagement, keeping the extrinsic motivator relevant, fresh and focused on personal development.

Tracking progress: By enabling people to track progress on their goals and sharing that information with their practitioners, patients tap into positive, extrinsic motivation. Also tracking progress on personal, aspirational goals helps people feel a greater sense of accomplishment and direction over their own developmental outcomes.

While motivation for any one individual can be elusive, the way Wellpepper weaves together the positive extrinsic and intrinsic development-based motivators may be the key to its success in helping patients stay motivated and helping practitioners answer the age-old question: “Will the patient do it?”

If they’re using Wellpepper, chances are, they will.

Jennifer Allen Newton is Wellpepper’s PR lead, and also a Functional Medicine Certified Health Coach. 

Posted in: Adherence, Healthcare motivation, Healthcare Technology, Healthcare transformation, patient engagement, Physical Therapy

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Your Cupcakes Are Not My Goals

This year Google Maps tried out a short-lived motivational technique of showing how many cupcakes you would burn off or ostensibly could eat if you chose to walk to your destination. Not surprisingly this backfired, and they quickly retracted the feature. The reasons ranged from users expressing feelings of shame for not walking, to those with eating disorders saying it would encourage more obsessive behavior. Beyond that, many questioned how Google was even calculating both caloric expenditure and the actual calories in the cupcakes.

Regardless of the myriad of criticisms the experiment illustrated a key point: motivation and goal setting is best left to the individual, and understanding someone’s personal context is extremely important if you want to help them set goals.

One of our most read blog posts of 2017 was a 2015 post on whether setting SMART or MEANINGFUL goals was most effective for patients. I’m not sure why this bubbled to the top this year but the post provides an overview of two thoughtful frameworks for helping patients set goals.

At Wellpepper, we’d like to propose a third methodology: let people figure out what’s important to them. This year we expanded a capability we’ve had since V.1 that enables patients to set their own goals. This is a free-form, 140 character text box where patients write about what’s important to them. Over the years, we’ve had some clinicians express concern about whether patients could set their own goals. Functional goals are best left to the experts, but these are life goals, things that are important to people and why they are even bothering to use this app which helps them through healthcare activities to manage chronic diseases or recover from acute events.

Since we already knew that setting patient-generated goals is motivating, we also got to wondering whether you could track progress in a generic way based on patient-generated goals. After analyzing thousands of patient-generated goals, we figured out that asking a question about the patient’s perception progress on a Likert scale would work, and so this year we expanded the patient goal task type to include tracking.

It looks like this.

In case you’re skeptical that this works, here are a few examples of patient-generated goals.

Spend more time with family.

Get outside more frequently.

Walk more.

Be ready for vacation.

Now ask the question. See, it’s entirely possible for patients to set their own goals, unaided, and track progress against those goals. We’re pretty excited about the possibilities of this for improving motivation, and also for further analysis of patient adherence and outcomes. If you’d like to know more, or see a demo, we’d love to hear from you.

Posted in: Behavior Change, Healthcare motivation, Healthcare Technology, Healthcare transformation, patient engagement, patient-generated data

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May You Live In Interesting Times: Wellpepper’s Most Interesting Blog Posts of 2017

Who would have predicted 2017? As soon as the election results were in, we knew there would be trouble for the Affordable Care Act no one could have predicted the path through repeal with no replacement to claw backs in a tax bill that no one has read. It’s been a crazy ride in healthcare and otherwise. As we look ahead to 2018, we’ve found that a good place to start is by looking back at what was popular in 2017.

Looking back over the past year’s top blog posts, we also believe trends that started in 2017, but will even stronger in 2018. These four themes bubbled up to the top in our most-read blog posts of 2017:

Shift to the cloud

We’ve noticed a much wider spread acceptance of cloud technologies in healthcare, and the big cloud platform vendors have definitely taken an interest in the space. Wellpepper CTO Mike Van Snellenberg’s comprehensive primer on using AWS with HIPAA protected data was one of our most read posts. Since he wrote it, even more AWS services have become HIPAA-eligible.

Using AWS with HIPAA-Protected Data – A Practical Primer

Consumerization of healthcare

Consumer expectations for efficient online interactions have been driven by high-deductible plans and an expectation from consumer technology and industries like retail and banking that customer service should be personalized, interactive, and real-time. These two posts about the consumerization of healthcare were among the most popular.

The Disneyfication or Consumerization of Healthcare

Consumerization Is Not A Bad Word

Value of patient-generated data

In 2017 we saw a real acceptance of patient-generated data. Our customers started asking about putting certain data in the EMR, and our analysis of the data we collect showed interesting trends in patient adherence and predictors of readmission. This was reflected in the large readership of these two blog posts focused on the clinical and business value of collecting and analyzing patient-generated data.

In Defense of Patient-Generated Data

Realizing Value In Patient Engagement

Power of voice technology

Voice technology definitely had a moment this year. Okay Google, and Alexa were asked to play music, turn on lights, and more importantly questions about healthcare. As winners of the Alexa Diabetes Challenge, we saw the power of voice firsthand when testing voice with people newly diagnosed with Type 2 diabetes. The emotional connection to voice is stronger than mobile, and it’s such a natural interaction in people-powered healthcare. Our blog posts on the Alexa Diabetes Challenge, and developing a voice solution were definitely in the top 10 most read.

Introducing Sugarpod by Wellpepper, a comprehensive diabetes care plan

Building a Voice Experience for People with Type 2 Diabetes

Ready When You Are: Voice Interfaces for Patient Engagement

Since these themes are still evolving we think 2018 will present a shift from investigation to action, from consideration to deployment and possibly insights. Machine-learning and AI will probably remain high in the hype cycle, and certainly the trends of horizontal and vertical healthcare mergers will continue. We also expect a big move from one of the large technology companies who have all been increasing their focus in healthcare, which in turn will accelerate the shift to a consumer-focus in healthcare.

There’s a saying “may you live in interesting times.” We expect 2018 to be at least as interesting as 2017. Onwards!

Note: There was one additional post that hit the most popular list. Interestingly, it was a post from 2014 on whether SMART or MEANINGFUL goals are better for patients. We’re not sure why it resurfaced, but based on analysis we’ve done of patient-directed goals, we think there’s a third approach.

Posted in: Behavior Change, Healthcare Disruption, Healthcare motivation, Healthcare Research, Healthcare Technology, Healthcare transformation, HIPAA, patient engagement, patient-generated data, Voice

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Pointing Fingers at Healthcare Problems

I’m only halfway through Elizabeth Rosenthal’s “An American Sickness: How Healthcare Became Big Business and How You Can Take It Back” which means that I haven’t gotten to the “what you can do about the problem” part. It’s a slow read, not because it’s not compelling but because it’s too compelling, and if like the current President, you were surprised at how complicated healthcare is, this book will do nothing to dissuade you. It’s really really complicated.

So far, I have two main takeaways from the book, that are easily illustrated through my recent experience of breaking and dislocating my finger: a simple, non-life-threatening problem, that unearthed a couple of key dysfunctions and unintended consequences.

My first takeaway is that everyone is complicit, and yet seem to manage to finger point at everyone else. Rosenthal spares no punches in unearthing decisions that are not made with the best interest in of the patient at heart. Providers, healthcare organizations, payers, pharma, and employers all are complicit in the mess that is our current healthcare system.

This past fall, I broke and dislocated my finger. It wasn’t a big deal, but because it happened on a Saturday night, my only option for care was at the ER. Last week I received a letter in the mail from my insurance company, that according to the envelope required my urgent reply. In the letter, the insurance company suggested that perhaps someone other than them may be on the hook for my ER bill. While I understand they wanted to make sure this wasn’t a worker’s compensation claim, the form was basically for me to tell them whose fault my injury was so that they could go after another insurance company to pay. This was a sports injury in a game of Ultimate Frisbee, a game so granola-like that there are no referees: players call fouls on themselves. . No one was at fault, and even if they were, I would never have considered suing. However, the form didn’t give me that option: only gave me the option of saying whether I had settled my claim. I created a new box that said “NA” and checked it.

When I received the letter, I couldn’t help but think back to Rosenthal’s book, and also consider the amount of effort and cost that was going into finding someone else to blame and pay. Just imagine what this effort and cost would have been if there were legal action….

The second takeaway is that the original intention of a decision always has much farther reaching implications than anyone who agreed on what seemed like a reasonable decision though. Again with the finger, I was asked a number of times if I wanted a prescription for OxyContin. I did not. As has been well publicized we have an opioid addiction problem in North America. While my finger hurt, aside from morphine during inpatient for an appendectomy, I hadn’t had opioids, and really didn’t think that it was necessary, which I explained to the physician. It wasn’t. Tylenol worked fine—however, it seemed that it was very important that I be the one to make this call, not the physician.

One of the unintended consequences of patient satisfaction scores may be the over prescription of pain medication, as many of the questions on the HCAHPS are about whether the patient’s pain was well managed. In Rosenthal’s book, I was also surprised to learn that a finger fracture where an opioid is prescribed has a different billing code than if it is not prescribed, and that with the fracture plus opioid billing code, hospitals get paid more. Now, if you are wondering how this may be the case, if you think about it, a fracture that requires an opioid must be more severe than one that doesn’t and therefore the billing code reflects the severity. This is exactly where the unintended consequences of billing codes can result in exactly the wrong behavior for patient care and safety.

It’s quite possible that the physicians on duty were not aware of either of these two drivers for prescribing, especially the billing code one. They may have just been told “this is our standard of care” and were following guidelines.

If a simple finger fracture and dislocation can shine a light on two key problems in our healthcare system, just imagine what else is out there. Actually, you don’t have to, just get a copy of Elizabeth’s book yourself, and let’s compare notes when I get to the part about what the fix is. It’s going to take all of us.

Posted in: Health Regulations, Healthcare costs, Healthcare Disruption, Healthcare Legislation, Healthcare Policy, Healthcare transformation, Opioids

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Boston University Center for Neurorehabilitation: A Novel Mobile Intervention For People With Parkinson’s Disease

In 2013, when we were a brand new m-health company, we had the good fortune to meet Terry Ellis, PhD, Director of the Center for Neurorehabilitation at Boston University. Dr. Ellis was an early investigator in the value of digital interventions, and saw an opportunity to partner with Wellpepper so that her team could focus on the new care models, and Wellpepper could focus on the technology. The first building blocks in the Wellpepper platform aligned closely with outpatient rehabilitation, and Dr Ellis and team wanted to prove that people who had Parkinson disease could improve strength and mobility without costly in-person visits. At Wellpepper, we also had an interest in proving that mobile health can improve outcomes, and also that those 50 plus could use mobile technology.

Persons with Parkinson Disease (PD) have been described as 29% less active than older adults without PD, and see a 12% decline in mobility for each year after their first diagnosis with the disease. In-person interventions with physical therapists can help, but in the usual care condition, a person has one in-person assessment at The Center for Neurorehabilitation, and may not be seen again for 6 months to a year, during which time there was a decline in mobility. Dr Ellis and team were looking for a way to prove out a novel intervention that could improve outcomes for these patients.

Patient Experience

This video does a great job of showing the patient experience, both with the clinician and while using the application at home.

User Journey from Wellpepper on Vimeo.

Outcomes

While Dr. Ellis and team are still analyzing additional data, and will be submitting to a peer-reviewed journal, and are exploring expanded studies on the topic, we can share some very promising results.

  • This study revealed that using mobile health technology to remotely monitor and adapt exercise programs between bouts of care in persons with Parkinson disease was feasible and acceptable.
  • On average, subjects engaged with the app every week for 85% (+/- 20%) of the weeks with an 87% satisfaction rating.
  • Significant improvements in physical activity, walking and balance measures were observed over 12 months.
  • People who showed lower exercise self-efficacy at the beginning of the study saw the greatest gains.

Technology

  • This technology used the Wellpepper platform, clinic application for iPad, and patient application for iOS. Requirements were for ease of use for both clinicans and patients. Features include the ability to record custom video of patients doing their exercises, for patients to record results, and for patients and providers to message securely with each other.
  • Fitbit was used for patients to track non-exercise activity, and this was the first integration of a consumer exercise tracker with the Wellpepper platform.
  • The entire Wellpepper platform is built on Amazon Web Services, in a HIPAA secure manner, which was a requirement for the study. No data was stored on mobile devices and all personal health information was encrypted in transit and at rest.
  • The Boston University team required a monthly data extract of all patient-generated data for their analysis purposes.
  • Post study, we were able to analyze anonymized patient-provider messages using a machine learned message classifier, and have presented this data at digital health conferences.

The positive preliminary results of this study, lead to a larger study with seniors at risk of falls, lead by principal investigator Jonathan Bean, MD from Harvard Medical School. Details of this intervention are available here. While Dr Bean is also in the process of submitting to a peer-reviewed journal, his assessment is that outcomes exceeded clinically significant measures.

We are looking forward to sharing more about the results of both of these studies when they are publicly available in peer-reviewed journals. If you are a researcher who would like to know more, contact us and we may be able to put you in touch with the study leads.

Posted in: Clinical Research, Exercise Physiology, Healthcare Technology, Healthcare transformation, M-health

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Wellpepper Wins $125K Grand Prize in Alexa Diabetes Challenge

NEW YORK: Today, the Challenge judges awarded Wellpepper the $125,000 grand prize in the Alexa Diabetes Challenge. Wellpepper is the team behind Sugarpod, a concept for a multimodal diabetes care plan solution using voice interactions.

The multi-stage Challenge is sponsored by Merck & Co., Inc., Kenilworth, New Jersey, U.S.A., supported by Amazon Web Services (AWS), and powered by Luminary Labs. In April, the competition launched with an open call for concepts that demonstrate the future potential of voice technologies and supporting Amazon Web Services to improve the experience of those who have been newly diagnosed with type 2 diabetes.

“Technology advances are creating digital health opportunities to improve support for people managing life with a chronic disease,” said Tony Alvarez, president, Primary Care Business Line and Customer Strategy at Merck & Co., Inc. “One purpose of the Alexa Diabetes Challenge was to identify new ways to use the technology already present in a patient’s daily routine. The winner of the Challenge did just that.”

Sugarpod is a concept for an interactive diabetes care plan solution that provides tailored tasks based on patient preferences. It delivers patient experiences via SMS, email, web, and a native mobile application – and one day, through voice interfaces as well. Since much of diabetes management occurs in the home, the Wellpepper team recognized that integrating voice was the natural next step to make the platform more convenient where patients are using it most. During the Challenge, Wellpepper also prototyped an Alexa-enabled scale and foot scanner that alerts patients about potential foot problems, a common diabetes complication.

“Sugarpod helps newly diagnosed people with type 2 diabetes integrate new information and routines into the fabric of their daily lives to self-manage, connect to care, and avoid complications. The Challenge showed us the appeal of voice solutions for patients and clinical value of early detection with home-based solutions,” said Anne Weiler, co-founder and CEO of Wellpepper.

The Challenge received 96 submissions from a variety of innovators, including research institutions, software companies, startups, and healthcare providers. The panel of judges, independent from Merck, narrowed the field down to Wellpepper and four other finalists, who each received $25,000 and $10,000 in AWS promotional credits and advanced to the Virtual Accelerator. During this phase of the competition, the finalists received expert mentorship as they iterated their solutions in preparation for Demo Day. At Demo Day on September 25, 2017, the five finalists presented their solutions to the judges and a live audience of industry leaders at the AWS Pop-up Loft in New York to compete for the grand prize.

“The Alexa Diabetes Challenge has been a great experiment to re-think what a consumer, patient, and caregiver experience could be like and how voice can become a frictionless interface for these interactions. We can imagine a future where technological innovations, like those provided by Amazon and AWS, are supporting those who need them most,” said Oxana Pickeral, Global Segment Leader in Healthcare and Life Sciences at Amazon Web Services.

Learn more at alexadiabeteschallenge.com and follow the Challenge at @ADchallenge.                                                                   

###

Contact: Emily Hallquist

(425) 785-4531 or emily@luminary-labs.com

Posted in: Healthcare Technology, Healthcare transformation, patient engagement, Press Release

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Ready When You Are: Voice Interfaces for Patient Engagement

We started experimenting with voice as a patient interface early this year, and showed a solution with a voice-enabled total-joint care plan to a select group of customers and partners at HIMSS 2017. Recently we were finalists in the Merck-sponsored Alexa Diabetes Challenge, where we built a voice-enabled IOT scale and diabetic foot scanner, and also a voice-powered interactive care plan.

Over the course of the challenge we tested the voice experience with people with Type 2 diabetes. We also installed the scale and scanner in a clinic, and we found that clinicians also wanted to engage with voice. Voice is a natural in the clinical setting: there’s no screen to get in the way of interactions, and people are used to answering questions. Voice is also great in the home.

However, voice isn’t always the best interface which is why we think multimodal care plans including voice, text, mobile, and web can deliver a more comprehensive solution. Since it’s easier for someone to overhear a conversation than look at your smartphone or even computer screen, mobile or web are often better interfaces depending on the person’s location (for example taking public transit), or the task they need to do (for example, reporting status of a bowel movement). We do think that voice has many great healthcare applications, and benefits for certain interactions and populations.

In our testing, we found that both patients and providers really enjoyed the voice interactions and wanted to continue the conversation. They felt very natural, and people used language that they would use with a human. For example, when asked to let the voice-powered scale know when he was ready to have his foot scan, one person responded with:

“Ready when you are.”

This natural user interface presents challenges for developers. It’s hard to model all the possible responses and utterances that a person would use. Our application, would answer to ready, sure, yes, and okay, but the “when you are” caused her some confusion.

Possibly the most important facet of voice is the connection people have with voice is extremely strong, and unlike mobile voice is not yet associated with the need to follow up, check email, or other alerts. (Notifications on voice devices could change this.)

“Voice gives the feeling someone cares. Nudges you in the right direction”

Creating a persona for voice is important, and relying on the personas created by the experts like the Alexa team, is probably the best way for beginners to start.

“Instructions and voice were very calm, and clear, and easy to understand”

Calm is the operative word here. Visual user interfaces can be described as clean, but calm is definitely a personification of the experience.

Voice is often seen as a more ubiquitous experience, possibly because using fewer words, and constantly checking for the correct meaning are best practices, for example “You want me to buy two tickets for Aladdin at 7:00 pm. Is this correct?” We often hear pushback on mobile apps for seniors, but haven’t heard the same for voice. However, during our testing, a senior who was hard-of-hearing told us she couldn’t understand Alexa, and thought that she talked too quickly. While developers can put pauses to set the speed of prompts and responses in conversation, this would mean that the same speed would have used for all users of the skill, which might be too slow for some or two fast for others. Rather than needing to build different skills based on hearing and comprehension speed it would be great if end-users could define this setting so that we can build usable interfaces for everyone.

While this was our first foray into testing voice with care plans, we see a lot of potential to drive a more emotional connection with the care plan, and to better integrate into someone’s day.

People need to manage interactions throughout their day, and integrating into the best experience based on what they need to do and where they are provides a great opportunity to do that, whether that’s voice, SMS, email, web, or mobile. While these consumer voice applications are not yet HIPAA-compliant, like our tester patient said we’ll be “ready when you are.”

Posted in: Behavior Change, Healthcare Technology, Healthcare transformation, patient engagement

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