Healthcare Disruption

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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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Voice Tech In Healthcare

Voice tech is a hot topic in healthcare, and for good reason. Healthcare is built on personal interactions, and voice technology can replicate and even replace the human interviewing experience. Voice has other valuable benefits in healthcare like being hands-free—for someone who is recovering from surgery and mobility challenged this might mean being able to get information without getting up. In the hospital setting, the hands-free interface has obvious benefits for hygiene.

At Wellpepper we first started experimenting with voice-enabling our interactive care plans in early 2017, and dug deeper into the topic, prototyping voice powered devices and testing with real people as part of our winning entry in the Alexa Diabetes Challenge. I’ll be talking more about this at the Voice Summit July 24-26, 2018 in Newark.

However, voice experiences in healthcare are not new. This week the Seattle Design for Healthcare meetup Ilana Shalowitz, Voice Design UI Manager, from EMMI Systems (part of Wolters-Kluwer) talking about best practices for voice design based her work on their interactive voice response system. This system effectively does outreach through “robocalls” to help influence people’s behavior, like getting them to schedule general health primary care visits, or get a flu shot. The pathways are designed to guide the patient through specific material, ensuring a basic understanding of the topic, and moving to take action (although not actually taking action), since that was not possible in the interface.

While they have been effective at changing patient behavior, the talk got me thinking about the differences between the interaction model for more traditional, non-AI based interactive voice response and the voice assistants like Alexa and Okay Google popping up in the home, the challenges of each, and the opportunities in healthcare.

Interactive voice response (IVR) can provide a structured pathway, which could be akin to an intake form or an interview. However, it doesn’t allow for an end-user driven experience. In her session, Shalowitz talked about designing a path to give the end user the illusion of control, where a yes or no answer to a knowledge question actually ended up in the same place. Compare that to the home voice experiences where the end user can drive any experience. The upside of this experience is that the end-user is in control, which is often not the case in healthcare, and can drive the direction of the conversation.

Here’s a common experience interacting with a Wellpepper care plan.”

Person: “Alexa, tell Wellpepper I have pain.”
Alexa: “Okay, what is your pain on scale of 0-10 where 0 is no pain, and 10 is the worst pain imaginable.”
Person: “Four”
Alexa: “Okay, I’ve recorded your pain as 4 out of ten. Is that correct?”
Person: “Yes.”
Alexa: “Anything else?”

The difference between this and a typical IVR communication is that the end-user is the initiator. However, the drawback with this type of scenario is that the end-user needs to know what they want to do. This is a notorious problem with headless interfaces like voice. In fact, each week, I get an email from the Alexa team that tells me what new thing I can do with Alexa, essentially a print-guide for the voice interface. Discoverability, context, and capabilities remain problems with these interactions even while they put the end-user at the center.

However, the benefits of these new consumer tools is that, they are designed to not anticipate each pathway in advance, and rather than the pre-recorded prompts of traditional IVR, they are learning systems where continual improvement can be made by examining successful and failed intents. We saw this is in our testing when a patient told Alexa he was “ready when you are.”

I’m excited to be heading to the Voice Summit this coming week, where we’ll talk about what we learned in the Alexa Diabetes challenge, and how we’re applying voice to all our patient experiences at Wellpepper. It’s still early days, but we see a lot of promise, and patients love it.

“Voice gives the feeling someone cares. Nudges you in the right direction.”
Test patient with Type 2 diabetes

Posted in: Healthcare Disruption, patient engagement, Voice

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Digital Transformation in Pharma: Digital Pharma West

Like the rest of the healthcare industry, the pharma industry is also grappling with lots of data, disconnects from end-users, and shifting to a digital-first experience while grappling with ongoing regulatory and privacy challenges. Actually it’s pretty much what every industry is grappling with, so the good news is that no one is getting left behind in this digital revolution.

In pharma though, the division between commercial and R&D creates both delays and lags in implementing new technology and the regulatory challenges cause specific issues in communication with both providers and patients.

Last week, I was invited to speak at Digital Pharma West about our work in voice-enabling care plans for people with Type 2 diabetes, and also how our participation in the Alexa Diabetes Challenge enabled us to engage with pharma. It was my first ‘pharma-only’ conference, so it was interesting to contrast with the provider and healthcare IT world.

If you think that there are a lot of constituents who care about digital health in provider organizations, pharma rivals that. For example, there was a discussion about the value of patient-facing digital tools in clinical trials. While everyone agreed there could be real value in both efficiencies of collecting data, and engaging patients and keeping them enrolled in trials, a couple of real barriers came up.

First the question of the impact of the digital tools on the trial. Would they create an intended impact on the outcomes, for example a placebo effect? Depending on how the “usual care condition” is delivered in a control group, it might not even be possible to use digital tools in both cohorts, which could definitely impact outcomes.

Another challenge with digital technology in randomized control trials is that technology and interfaces can change much faster than drug clinical trials. Considering that elapsed time between Phase 1 and Phase 3 trials can be years, also consider that the technology that accompanies the drug could change dramatically during that period. Even technology companies that are not “moving fast and breaking things” may do hundreds of updates in that period.

Another challenge is that technology may advance or come on the market after the initial IRB is approved, and while the technology may be a perfect fit for the study, principle investigators are hesitant to mess with study design after IRB approval.

Interestingly, while in the patient-provider world the number of channels of communication are increasing significantly with mobile, texting, web, and voice options, the number of touch points in pharma is decreasing. Pharma’s touchpoints with providers are decreasing 10% per year. While some may say that this is good due to past overreach, it does make it difficult to reach one of their constituents.

At the same time, regulations on approved content for both providers and patients means that when content has had regulatory approval, like what you might find in brochures, on websites, and in commercials, the easiest thing to do is reuse this content. However, new delivery channels like chatbots and voice don’t lend themselves well to static marketing or information content. The costs of developing new experiences may be high but the costs of delivering content that is not context or end-user aware can be even higher.

At the same time, these real-time interactive experiences create new risks and responsibilities for adverse event reporting for organizations. Interestingly, as we talk with pharma companies about delivering interactive content through the new Wellpepper Marketplace, these concerns surface, and yet at the same time, when we ask the difference between a patient calling a 1-800 line with a problem and texting with a problem there doesn’t seem to be a difference. The only possible difference is a potential increase in adverse event reporting due to ease of reporting, which could cause problems in the short term, but in the long term seems both inevitable and like a win. Many of the discussions and sessions at the conference were about social media listening programs for both patient and provider feedback, so there is definitely a desire to get and make sense of more information.

Like everyone in healthcare, digital pharma also seems to be at an inflection point, and creativity thinking about audiences, channels, and how to meet people where they are and when you need them is key.

Posted in: Adherence, Clinical Research, Data Protection, Health Regulations, Healthcare Disruption, Healthcare Policy, Healthcare Research, Healthcare Social Media, Healthcare Technology, HIPAA, M-health, Outcomes, pharma, Voice

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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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HIMSS 2018…See you there!

HIMSS17 in Orlando was a great conference for Wellpepper. We’re looking forward to HIMSS18 in Las Vegas even more!

We have a long list of sessions to attend and booths to visit, but below are some places you’re guaranteed to find us:

Monday, March 5th

  • Hear from Tami Deangelis on how our research partners at Boston University engaged patients outside the clinic and improved outcomes using Wellpepper care plans. She is speaking at the “Remote Patient Messaging for Adherence and Engagement” session from 4:05pm-4:25pm at the Patient Engagement & Experience Summit

Tuesday, March 6th

  • Hall G, Innovation Zone: Booth 9900-78 from 9am-6pm
  • CTO, Mike Van Snellenberg will be demonstrating our voice-powered scale and foot scanner, and integrated diabetes care plan at the Industry Showcase at BHI & BSN 2018 https://bhi-bsn.embs.org/2018/industry-showcase/

Wednesday, March 7th

  • Hall G, Innovation Zone: Booth 9900-78 from 9am-6pm
  • CEO, Anne Weiler, will be sharing the Wellpepper Vision and Mission at HIMSS VentureConnect http://www.himssconference.org/education/specialty-programs/venture-connect
  • CEO, Anne Weiler, will be joining other industry leaders to continue the conversation with CMS toward inclusion of patient engagement and outcomes tracking in the MIPS Improvement Activity for provider reimbursement

Thursday, March 8th

  • Hall G, Innovation Zone: Booth 9900-78 from 9am-4:30pm

We can’t wait to connect with friends, partners, colleagues and industry leaders to continue the journey towards an amazing patient experience. Hope to see you there!

Posted in: Healthcare Disruption, Healthcare Technology, M-health, Outcomes, patient engagement, Uncategorized

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Alexa, Get Well Soon

The unofficial winner of the Super Bowl ad race this year was “Alexa Loses Her Voice”, an ad that shows celebrities subbing for Alexa when she (anthropomorphic being that she is, comes down with a cold). Both USA Today and YouTube are calling it the most watched ad.

Alexa, who won USA TODAY’s 30th Ad Meter?

“Well, um – me.”

Jeff Bezos looks skeptical that his team can replace Alexa as he should be, since their solution of Gordon Ramsay, CardiB, Rebel Wilson, and Anthony Hopkins is both extremely expensive, (Wellppper CTO Mike Van Snellenberg did the math), and breaks the key trust relationship that people have with Alexa.

Voice is a natural interface, and empathy can be quickly established by the types of utterances and engagement. By default, Alexa apologizes when she doesn’t understand something and it feels genuine. Compare that to Gordon Ramsay insulting his poor hapless user—all the guy wants is a bit of help making some comfort food. What he gets is abuse.

Or, the woman who wants Alexa’s help while she’s in her boudoir presumably getting ready for a date with her love. Instead, Anthony Hopkins insinuates that something horrific has happened to her beau possibly involving a pet peacock.

Cardi B insults a young man’s interest in Mars. Let’s hope she has not squashed his spirit of discovery and his desire to ask questions.

Since this is an all-ages blog, we won’t even mention the response Rebel Wilson gives from her bubble bath to the poor gentleman who asked Alexa to set the mood for a party. He and everyone at his party were fully traumatized.

We get it, Alexa is just better at delivering what people are asking for than real people. Especially real people with attitude like these celebrities.

As we found in our research with people with type 2 diabetes, Alexa has a natural ability that these celebrity Alexa impersonators do not. You can see it in this feedback we received from real people trying to manage Type 2 diabetes.

  • “Voice gives the feeling someone cares. Nudges you in the right direction”
  • “Instructions and voice were very calm, and clear, and easy to understand”

Voice is a natural fit to deliver empathy and care. However, since each one of these people is expecting Alexa, and has no visual indicator that anything has changed, the negative experiences will reflect on Alexa and she’ll have to win back their trust.

While the implied message of the ad spot is that Alexa does a better job of delivering on your needs than any of these celebrity experts we’re still feeling a bit traumatized by the abuse they hurled. For the sequel to this commercial, we’d expect to see Jeff firing the team that replaced Alexa with celebrities, and Alexa as a therapist working through the trust issues that her replacements created. She can do it. We believe in her.

Posted in: Behavior Change, Healthcare Disruption, Healthcare Technology, Voice

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CES 2018 Review: More Consumer Healthcare Disruption Please

CES 2018 Review: More Consumer Healthcare Disruption Please

We went to CES 2018 to understand more about how the consumer technology space was poised to disrupt healthcare. As a digital healthcare company, we sit in many conversations with established healthcare organizations. We know that they are concerned about the consumerization of healthcare and how this could disrupt the very core of their business. Fears about the big-5 technology companies moving into healthcare are themes in many an executive healthcare planning retreat.

So, what did this bold, disruptive vision of consumer-driven, technology-driven healthcare look like? Hundreds of companies selling rip-off activity tracking watches, and connected blood pressure cuffs and scales. The big booths felt depressingly resigned to a future where consumers would somehow want to buy big clunky medical monitoring devices-rebranded-as-consumer-devices, and then maybe sign into a dusty old web portal to view the data. “Requires Internet Explorer 5 or higher” warned one brochure – a browser that was literally released in the 90s. A disruptive consumer story this was not. Nothing to worry about here, big healthcare.

There was some innovation to be seen, of course, including some truly interesting devices in the small 10×10 booths. Products like TytoCare’s tricorder for at-home vitals capture, and healthcare-relevant wearables like those from Sensoria. Also the number of do-it-at-home biological tests like Ellume’s at-home flu and strep tests and food allergen detectors like Nima are of particular interest to my household and our matrix of peanut, tree-nut, gluten, strawberry and peach allergies.

What’s missing is someone to pull these innovative ideas and devices together and offer a comprehensive vision for what consumer-driven healthcare could look like in a way that consumers would actually want to spend money on. Where’s the LG-OLED-tunnel of consumer health? Even if they didn’t have anything yet – at least sell the vision the way all those car vendors are selling the vision of self-driving cars.

We suspect that, as with self-driving cars (Tesla, Google) and smart phones (Apple), the companies with most complete vision in healthcare maybe just aren’t telling this story at CES. Google, Apple, Amazon, Microsoft, Facebook: can’t wait to see your consumer healthcare booth when it’s ready, either at CES or some other show.

Posted in: Healthcare Disruption

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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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Healthcare + A.I. Northwest

The Xconomy Healthcare + A.I. Northwest Conference at Cambia Grove featured speakers and panels discussing the opportunities and prospects for applying machine learning and artificial intelligence to find solutions for health care. The consensus was that we are no longer held back by a lack of technological understanding and ability. A.I. and M.L. models can be learned at a large scale by harnessing the power of the cloud and advances in data science. According to the panelists, today’s challenges to incorporating A.I. into healthcare include abundant, but inadequate data and resistance from health systems and providers.

Many researchers have found insufficient data to be an unexpected challenge. As keynote speaker Peter Lee of Microsoft Research pointed out, the more data we have, the better our machine learned models can be. He used an analogy to a speech identifier trained on multiple languages such that the model predicted English better after learning French to illustrate that improvements can be made with large sets of unstructured data. Unfortunately, because we are not capturing enough of the right kind of data for researchers, much patient data is getting lost in the “health data funnel” due to PHI and quality concerns. Lee called for more data sharing and data transparency at every level.

Physician researchers on multiple panels were concerned about a lack of suitable data. Soheil Meshinchi, a pediatric oncologist from Fred Hutchinson Cancer Research Center, is engaged in collecting data specific to children. He discussed his research on Acute Myeloid Leukemia on the panel titled, ‘Will A.I. Help Discover and Personalize the Next Breakthrough Therapy?’. While there is a large body of research on AML in adults, he has found that the disease behaves much differently at a genomic level in children. He also expressed distrust in some published research because studies are rarely reproduced and often a researcher who presents results contrary to existing research faces headwinds at journals who are reticent to publish “negative data”. His focus at this point is gathering as much data as he can.

Matthew Thompson, a physician researcher at the University of Washington School of Medicine, argued on the “Innovations for the Over-Worked Physician” panel that technology has made patient interaction demonstrably worse, but that these problems can and should be solved innovatively with artificial intelligence. His specific complaints include both inputting and extracting data from health system EHRs, as well as an overall glut of raw patient data, often generated by the patient himself, and far too much published research for clinicians to digest.

Both keynote speakers, Microsoft’s Lee and Oren Etzioni of the Allen Institute for Artificial Intelligence, referenced the large numbers of research papers published every year. According to Etzioni, the number of scientific papers published has doubled every nine years since World War II. Lee referenced a statistic that 4000 studies on precision cancer treatments are published each year. They are both relying on innovative machine reading techniques to analyze and categorize research papers to make them more available to physicians (and other scientists). Dr. Etzioni’s team has developed SemanticScholar.org to combat the common challenges facing those who look for research papers. He aims to reduce the number of citations they must follow while also identifying the most relevant and up-to-date research available. One of the advantages of taking this approach to patient data

is that scientific texts have no PHI concerns. Lee’s team is marrying patient data and machine reading to match potential research subjects with appropriate NIH studies.

Dr. Thompson was concerned that too much data is presented to the medical staff and very few of the “predictive rules” used by ER personnel are both ‘accurate and safe’. When reviewing patient outcomes and observations to predict the severity of an infection, he found that patients or their caregivers would provide ample information, but often clinicians would disregard certain details as noise because they were atypical symptoms. The amount of data that providers have to observe for a patient is massive, but machine learned models may be utilized to distill that data into the most relevant and actionable signals.

Before data is gathered and interpreted, it must be collected. Like Dr. Thompson, Harjinder Sandhu of Saykara sees ponderous, physician-driven data entry via EHR as significant barrier to efficient data collection. Sandhu notes that healthcare is the only industry where the highest-paid teammember is performing this onerous task and his company is using artificial intelligence to ease that burden on the physician.

Once patient data has been aggregated and processed into models, the challenge is getting the information in front of providers. This requires buy-in from the health system, physician, and, occasionally, the patient and his caregivers. Mary Haggard of Providence Health and Services spoke on the “Tech Entrepreneurs Journey into Healthcare” panel and stated that the biggest problem for entrepreneurs is defining the correct problem to solve. During the “Investment Perspective” panel, Matt Holman of Echo Health Ventures recommended tech startups emphasize an understanding of the context of the problem within a health system.

One of the most important and difficult hurdles for health technology companies is working into clinical workflow. Mike McSherry from Xealth has found that physician champions who know how they want to use technology help with integrating into a health system or physicians group. Lynn McGrath of Eigen Healthcare believes physicians want their data to be defined, quick to assess, condensed, and actionable, while Shelly Fitz points out that providers are not used to all the data they are receiving and they don’t yet know how to use it all. These are all issues that can and will be solved as healthcare technology continues to become more intelligent.

As Wellpepper’s CTO, Mike Van Snellenberg pointed out, health systems and doctors are resistant to “shiny new things”, for good reason. When approaching a health system, in addition to engaging the administration, clinicians need to understand why the machine learned model is recommending a given course of treatment. After integration, patients will also want to understand why a given course of treatment is being recommended. Applying artificial intelligence solutions to medicine must take into account the human element, as well.

The exciting possibilities of artificial intelligence and machine learning are hindered more by human constraints in health systems and data collection than by available technology. “Patients are throwing off all kinds of data when they’re not in the clinic,” according to our CTO. Wellpepper’s tools for capturing patient-generated data provide a pathway for providers to access actionable analysis.

Posted in: Healthcare Disruption, Healthcare Technology, patient engagement

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Disruptive Innovation, Sparks of Light, or the Evolution of Care: Recap of Mayo Transform Conference

In what has been a roller-coaster year for healthcare legislation, it’s the annual touchstone of the Mayo Clinic Transform Conference provided a welcome opportunity to reflect on where we are. This conference, sponsored by the Mayo Clinic Center for Innovation attracts powerhouse speakers like Andy Slavitt and Clayton Christensen, and yet manages to fly under the radar. This year’s theme was about closing the gap between people and health, so the social determinants of health were a key topic, as was whether disruption alone would solve the problem.

Dr Robert Pearl

This was my third year attending, and second year speaking at the conference, and I’ve noticed a trend: the conference starts by articulating the problem, and building up solutions and creative ways to reshape the problems over the course of the two days. This year the conference was deftly moderated by Elizabeth Rosenthal, MD,Editor-In-Chief of Kaiser Health News and author of “An American Sickness.” Rosenthal, an MD herself, and former NYTimes journalist, peppered her moderation with real-world examples of both waste and inefficiencies and effective programs based on her investigative journalism.

I’ve been wanting to write a blog post for a while that riffs on the theme of “You Are Here” trying to outline where we are in the digital evolution in healthcare, but it’s clear that we don’t know where we are, digital or otherwise: too much is currently in flux. There are points of light with effective programs, and things that seem very broken. The panel I was on, was titled “Disruptive Innovation” and I’m afraid we let the audience down, as while we are doing some very interesting things with health systems, we are not turning every model on its head. We work with providers and patients to help patients outside the clinic. Truly disruptive innovation would work completely outside the system, which leads to the question, can health systems disrupt themselves or will it come from entirely new entrants like say Google, Apple, or Amazon?

Dr. David Feinberg of Geisinger reads from debate opponent Dr. Robert Pearl’s book

Clayton Christensen, the closing keynote speaker, likens hospitals to mainframe computers, and basically says they will be overtaken by smaller more nimble organizations, much like the PC and now smartphone revolution. Organizations like Iora Health who holistically and preventatively manage a Medicare Advantage population are the epitome of these new entrants, and we’ve seen some hospitals struggle this year, but will they go away entirely? The answer to this question may lie in the excellent debate session “Is The US Healthcare System Terminally Broken” hosted by Intelligence Squared and moderated by author and ABC News Correspondent John Donovan.

 

Shannon Brownlee, senior VP of the Lown Institute and visiting scientist at the Harvard T.H. Chan School of Public Health, and Robert Pearl, MD, and former CEO of the Permanente Medical group were arguing that the system is broken, vs Ezekiel Emmanuel, MD, Senior Fellow Center for American Progress, and David Feinberg, MD, CEO of Geisinger.

While prior to the debate the audience favored the idea that the system is irreparably broken, by the end, they had come around to the idea that it’s not, which would point to the ability for healthcare to disrupt itself. The debate

Is Healthcare Terminally Broken

The final audience vote

was ridiculously fun, partially from the enthusiasm of the debaters, and because the topic was so dear to all attendees. You can listen to the podcast yourself. However, the posing of the question set up an almost impossible challenge for Pearl and Brownlee: they had to argue the patient is terminal, but without any possible solution. No one in the room wanted to hear that, and so when Emmanuel and Feinberg were able to point to innovative programs like the Geisinger Money Back Warranty or Fresh Food Pharmacy that just needed to find scale, the audience latched onto the hope that we can fix things, and we all have to believe in these points of light, to face each new day of challenges.

Posted in: Health Regulations, Healthcare Disruption, Healthcare Legislation, Healthcare Policy, Healthcare Technology, Healthcare transformation

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Alexa Voice Challenge for Type 2 Diabetes: Evolving An Idea

For the past couple of months some of our Wellpepper team, with some additional help from a couple of post-docs from University of Washington, have been working hard on a novel integrated device, mobile, and voice care plan to help people newly diagnosed with type 2 diabetes as part of our entry in the Alexa Diabetes Challenge.

Team Sugarpod

This challenge offered a great opportunity to evolve our thinking in the power of integrating experiences directly into a person’s day using the right technology for the setting. It also provided the opportunity to go from idea to prototype in a rapid timeframe.

Our solution featured an integrated mobile and voice care plan, and a unique device: a voice powered scale that scans for diabetic foot ulcers, a leading cause of amputation, hospitalization, and increased mortality, and is estimated to cost the health system up to $9B per year.

During the challenge, we had access to amazing resources, including a 2-day bootcamp held at Amazon headquarters during which we heard from experts in voice, behavior change, caring for people with type 2 diabetes, and a focus group with people who have type 2 diabetes. We also had 1:1 sessions with various experts who had seen our entry and helped us think through the challenges of developing it. After the bootcamp, we were assigned a mentor, an experienced pharmacist and diabetes educator, who was available for any questions. Experts from the bootcamp also held office hours where we explored topics like

Early Prototype Voice Powered Scale & Scanner

how to help coach people in what they can do with an Alexa skill, and how to build trust with a device that takes pictures in your bathroom.

As we evolved our solution, we were fortunate to have support from Dr Wellesley Chapman, medical director of Kaiser Permanente Washington’s Innovation Group. We were able to install the device in a Diabetes and Wound Clinic. We used this to train our image classifier to look for foot ulcers, and compare results to human detection, and also to test the voice service. We used an anonymous voice service as Alexa and the Lex services are not currently HIPAA-eligible.

We gathered feedback from diabetes educators, clinicians at KP Washington, and across the country, and from people with Type 2 diabetes. While not everyone wanted to use all aspects of the solution, they all felt that the various components: voice, mobile, and device offered a lot of support and value. As well, we determined that there is an opportunity for a voice-powered scale and scanner in the clinic which could aid in early detection and streamline productivity. Voice interactions in the clinic are a natural fit.

Judges and Competitors: Alexa Diabetes Challenge

The great thing about a challenge is the constraints provided to do something really great in a short period of time. We’re so proud of the Sugarpod team, and also incredibly impressed with the other entries in this competition ranging from a focus on supporting the mental health challenges faced by people newly diagnosed with Type 2 diabetes to a specific protocol for diet and nutrition, to solutions that helped manage all aspects of care. We enjoyed meeting our fellow competitors at the bootcamp and the final, and wish we had met in a situation where we could collaborate with them. We also appreciated the thoughtful feedback and questions from the judges, and would definitely have a lot to gain from deeper discussions with them on the topic.

Stay tuned for more on our learnings through this challenge and our experiences with voice.

Posted in: Healthcare Disruption, Healthcare Technology, Healthcare transformation, M-health, Managing Chronic Disease, Outcomes, patient engagement, patient-generated data

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Who Defines Value?

Pharma companies have recently jumped on the value bandwagon with proposals for value-based drug pricing based on outcomes and effectiveness. They have started to enter contracts with payers for specific drugs based on the impact the drug has on the condition the drug is treating.

This is a step in the right direction, and much better than pricing based on maximizing shareholder value, but value is in the eye of the beholder, and the patient is a key stakeholder. Shared decision making does a good job defining what’s important to a patient. The goal of shared decision making is to choose courses of care that offer the best outcome to the patient, and can consider some of the following:

  • Is this procedure my only option? What are alternative types of treatment?
  • What are the possible outcomes and side effects of each option, including the option of doing nothing?
  • What is the estimated cost of the procedure and any related follow-up care or medication?

Source: Center for American Progress

Simply, value can be defined by the following.

The challenge of the equation is in the definitions of acceptable outcomes and costs. Here are a few things that people might consider when evaluating a drug or a course of care.

  • Inconvenience or effort: How much does this disrupt their life? Does it prevent the person from doing other things?
  • Cost: How much does it cost? This could be in monetary terms, time, side effects, or quality of life.
  • Outcome: What is the expected outcome and how closely does it align with the outcome that’s important to me?

You can see that based on these factors, that healthcare can be a market of one. My idea of value and acceptable outcomes could be very different from yours. And, unfortunately, the patient is not a consumer in a free and transparent market. That said, it is possible to make consumer-like decisions in healthcare.

Let’s look at the value decision I tried to make this past weekend. I fractured and dislocated a finger while playing Ultimate Frisbee. I was pretty sure the finger was dislocated, which shouldn’t be a big deal, so tried to go to urgent care where I expected value based on time, outcome, and cost. Well guess what? Urgent care is not open on a Saturday night. I had a feeling that emergency care would not meet my value criteria of effort, since I expected a long wait, and I got it. On the cost, I did know that the provider I went to was in-network so that wasn’t a big issue, but I still don’t know the total cost if I’d had to pay out of pocket.

Waiting in ED

Waiting

Outcome was great, and the level of care was great. What was not great is that it took 4 hours to get x-rays, pop my finger back in, and splint it. If I had been choosing as a consumer, I’d never have chosen this. With higher deductibles and co-pays, people are making decisions as consumers which is why hospitals advertise wait times, and some are looking at how to completely overhaul the ER, both of which would get us closer to value.

Let’s look at an example on value-based drug pricing. Back when I had the Cadillac of US healthcare plans when I was working at Microsoft, I was prescribed a topical psoriasis drug. The expected outcome was no psoriasis lesions. The cost was $800 for a 60g tube. Since I didn’t have to pay anything out of pocket, I got the prescription. Did it work? Yes. Was it worth it to me? No. I had other creams that cost much less, and worked almost as well. I didn’t end up getting it again—I wouldn’t have paid $800 for it myself, so why should my employer? If cost is not part of the equation, people are making decisions with only partial information, and can’t possibly judge value. Co-pays and transparency can help guide people to consumer-like behavior in healthcare, even in an imperfect market.

What’s the upside? The upside is that we’re having these discussions, and that we can see a shift to value and consumer focus, even without legislation, which is really how it needs to happen. The other thing to remember is that people want to deliver excellent and quality care. Everyone I met during my finger ordeal, from the admitting staff to the x-ray tech, to the resident who was excited to see a dislocation he’d never seen before was excellent, and that defines quality in my mind. Maybe we have less far to go than we thought.

Posted in: Healthcare Disruption, Healthcare Legislation, Healthcare motivation, Healthcare Policy, Outcomes

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But Will It Fly? What Airlines and Healthcare Organizations Have In Common

What do airlines and healthcare systems have in common? Quite a lot it turns out, from a recent power breakfast featuring Rod Hochman, CEO of Providence St. Joseph Hoag Health system, and Brad Tilden, CEO of Alaska Airlines. In addition to the Pacific Northwest roots of both organizations, both have also undertaken mergers to gain market share and increase physical territory. Both serve a large cross-section of the population, and both are in highly-regulated industries that are not necessarily known for customer service that are grappling with new always connected user experiences and expectations.

The wide-ranging discussion included early inspiration for Hochman and Tilden’s early careers, how to motivate and engage a wide range of employees, and how to deal with competition and lead change. Both leaders had early influences on their career direction. Hochman knew he wanted to be a doctor at 16 when assisting on surgeries (!), and Tilden grew up beside Seatac airport watching planes while his peers were watching girls. Tilden grew his career at Alaska, while Hochman is a practicing rheumatologist, who has worked his way from small clinic to major system. Hochman joked that a rheumatology specialty is much more suited to success in administration than say surgery, equating running a hospital to the patient required in managing chronic diseases.

Airlines and health systems have similar challenges with employee experience. Both types of organizations have highly skilled staff, pilots and physicians, who demand a lot of autonomy. Mistakes in both professions can cause loss of life. The difference is that aviation has moved a lot faster in instituting standard procedures and checklists to improve safety and outcomes. Tilden frequently referenced an Alaska Air crash 17 years ago that impacted their approach to safety, and talked about the ways pilots and co-pilots double check settings. Hochman talked about his hope for quality improvements and better collaboration from the younger generation of physicians who have grown up in a world of checklists and standardization, and said that the ones who only care about being left alone to make decisions will retire.

They also have large teams of people who “get stuff done.” Hochman has banned the term ‘middle management’ since he sees those people as the ones who are making things happen, instead he calls them “core team”, a term that Tilden quipped he’d also start using.Rod Hochman & Brad Tilden

Customer experience was also top of mind for both execs. Tilden talked about Alaska adopting Virgin’s mission of being the airline people love. While he seemed to find some of Virgin’s approach to be a bit edgy compared to Alaska, he said you couldn’t find a better mission. Both grappled with the ease of sharing bad experiences on social media, and indicated that social media monitoring has become a key tool in managing consumer expectations. Hochman, also noted that it all comes back to the individual experience when he described that his staff hate when he has his own annual physical, because his expectations as a patient are much higher than what he experiences, especially with respect to convenience and information flow.

Both are optimistic and passionate leaders who genuinely care about the consumer and employee experience, and had as good a time interviewing each other as the audience did listening to them. This event was sold out, so if an opportunity like this comes up again, sign up early.

Posted in: Healthcare Disruption, Healthcare Technology, Healthcare transformation, M-health

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Introducing Sugarpod by Wellpepper, a comprehensive diabetes care plan

We’re both honored and excited to be one of five finalists in the Alexa Diabetes Challenge. We’re honored to be in such great company, and excited about the novel device our team is building. You may wonder how a team of software folks ends up with an entry with a hardware component. We did too, until we thought more about the convergence happening in technology.

We were early fans of the power of voice, and we previewed a prototype of Alexa integration with Wellpepper digital treatment plans for total joint replacement at HIMSS in February 2017. Voice is a great interface for people who are mobility or vision challenged, and the design of Amazon Echo makes it an unobtrusive home device. While a mobile treatment plan is always with you, the Amazon Echo is central in the home. At one point, we thought television would be the next logical screen to support patients with their home treatment plans, but it seems like the Echo Show is going to be more powerful and still quite accessible to a large number of people.

Since our platform supports all types of patient interventions, including diabetes, this challenge was a natural fit for our team, which is made up of Wellpepper staff and Dr Soma Mandal, who joined us this spring for a rotation from the University of Georgia. However, when we brainstormed 20 possible ideas for the challenge (admittedly over beer at Fremont Brewing), the two that rose to the top involved hardware solutions in addition to voice interactions with a treatment plan. And that’s how we found ourselves with Sugarpod by Wellpepper which includes a comprehensive diabetes care plan for someone newly diagnosed, and a novel Alexa-enabled device to check for foot problems, a common complication of diabetes mellitus.

Currently in healthcare, there are some big efforts to connect device data to the EMR. While we think device data is extremely interesting, connecting it directly to the EMR is missing a key component: what’s actually happening with the patient. Having real-time device data without real-time patient experience as well, is only solving one piece of the puzzle. Patients don’t think about the devices to manage their health – whether glucometer, blood pressure monitor, or foot scanner – separately from their entire care plan. In fact, looking at both together, and understanding the interplay between their actions, and the readings from these devices, is key for patient self-management.

And that’s how we found ourselves, a mostly SaaS company, entering a challenge with a device. It’s not the first time we’ve thought about how to better integrate devices with our care plans, but is the first time we’ve gone as far as prototyping one ourselves, which got us wondering which way the market will go. It doesn’t make sense for every device to have their own corresponding app. That app is not integrated with the physician’s instructions or the rest of the patient’s care plan. It may not be feasible for every interactive treatment plan to integrate with every device, so are vertically integrated solutions the future? If you look at the bets that Google and Apple are making in this space, you might say yes. It will be fascinating to see where this Alexa challenge takes Amazon, and us too.

We’ve got a lot of work cut out for us before the final pitch on September 25th in New York. If you’re interested in our progress, subscribe to our Wellpepper newsletter, and we’ll have a few updates. If you’re interested in this overall hardware and software solution for Type 2 diabetes care, either for deploying in your organization or bringing a new device to market, please get in touch.

Read more about the process, the pitch, and how we developed the solution:

Ready When You Are: Voice Interfaces for Patient Engagement

Alexa Voice Challenge for Type 2 Diabetes: Evolving a Solution

 

Posted in: Behavior Change, chronic disease, Healthcare Disruption, Healthcare Technology, Healthcare transformation, M-health, Managing Chronic Disease, patient-generated data

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In Defense of Patient-Generated Data

There’s a lot of activity going on with large technology companies and others trying to get access to EMR data to mine it for insights. They’re using machine learning and artificial intelligence to crawl notes and diagnosis to try to find patterns that may predict disease. At the same time, equal amounts of energy are being spent figuring out how to get data from the myriad of medical and consumer devices into the EMR, considered the system of record.

There are a few flaws in this plan:

  • A significant amount of data in the EMR is copied and pasted. While it may be true that physicians and especially specialists see the same problems repeatedly, it’s also true that lack of specificity and even mistakes are introduced by this practice.
  • As well, the same ICD-10 codes are reused. Doctors admit to reusing codes that they know will be reimbursed. While they are not mis-diagnosing patients, this is another area where there is a lack of specificity. Search for “frequently used ICD-10 codes”, you’ll find a myriad of cheat sheets listing the most common codes for primary care and specialties.
  • Historically clinical research, on which recommendations and standard ranges are created, has been lacking in ethnic and sometimes gender diversity, which means that a patient whose tests are within standard range may have a different experience because that patient is different than the archetype on which the standard is based.
  • Data without context is meaningless, which is physicians initially balked about having device data in the EMR. Understanding how much a healthy person is active is interesting but you don’t need FitBit data for that, there are other indicators like BMI and resting heart rate. Understanding how much someone recovering from knee surgery is interesting, but only if you understand other things about that person’s situation and care.

There’s a pretty simple and often overlooked solution to this problem: get data and information directly from the patient. This data, of a patient’s own experience, will often answer the questions of why a patient is or isn’t getting better. It’s one thing to look at data points and see whether a patient is in or out of accepted ranges. It’s another to consider how the patient feels and what he or she is doing that may improve or exacerbate a condition. In ignoring the patient experience, decisions are being made with only some of the data. In Kleiner-Perkin’s State of the Internet Report, Mary Meeker estimates that the EMR collects a mere 26 data points per year on each patient. That’s not enough to make decisions about a single patient, let alone expect that AI will auto-magically find insights.

We’ve seen the value of patient engagement in our own research and data collected, for example in identifying side effects that are predictors of post-surgical readmission. If you’re interested, in these insights, we publish them through our newsletter.  In interviewing patients and providers, we’ve heard so many examples where physicians were puzzled between the patient’s experience in-clinic or in-patient versus at home. One pulmonary specialist we met told us he had a COPD patient who was not responding to medication. The obvious solution was to change the medication. The not-so-obvious solution was to ask the patient to demonstrate how he was using his inhaler. He was spraying it in the air and walking through the mist, which was how a discharge nurse had shown him how to use the inhaler.

By providing patients with useable and personalized instructions and then tracking the patient experience in following instructions and managing their health, you can close the loop. Combining this information with device data and physician observations and diagnosis, will provide the insight that we can use to scale and personalize care.

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

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