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Machine Learning In Healthcare: How To Avoid GIGO

There’s a commonly used phrase in technology called “garbage in, garbage out” which means that if you start with flawed data or faulty code, you’re going to get lousy output. It results in high-levels of rigor whether that’s in doing user or market research or designing algorithms. Garbage in/Garbage out (or GIGO) is why, although, we are using machine-learning to improve patient engagement and outcomes, at Wellpepper, we’re also slightly skeptical of efforts by big tech (Google, Microsoft, and Amazon) to partner with healthcare organizations to mine their EMR data using machine learning to drive medical breakthroughs. I’ve talked to a number of physicians who are equally skeptical. The reason is that we and especially many physicians are skeptical is that the data in the EMR is frequently poor quality, much of it highly unstructured, and that a major piece of data is missing: the actual patient outcomes. It has what the doctor prescribed but not what the patient did and often what the result was. As well, the data collected in the EMR is designed for billing not diagnosis so it’s more likely the insights will be about billing codes not diagnosis. Why is the data poor quality?

  • A JAMA study found that only 18 percent of EMR notes are original. 46 percent were imported (without attribution) and 36 percent were copied and pasted. Let’s assume that the 18 percent of original notes have no errors, you’re still dealing with 80% of the notes that have a questionable source. This copying and pasting has also contributed to “note bloat” if the data is bad, having more of it will actually hinder the process of finding insights, even for a machine.
  • The data is not standardized. Since so much of the data in the EMR is in these notes, physicians are using different words for the same issue.
  • The dataset from an EMR is biased in several important ways. First, it was entered by physicians and other practitioners, rather than by a broad set of users. The language in healthcare is very different than how patients talk about their health, so these algorithms are unlikely to generalize well outside of the setting where their training data was acquired. Second, data in the EMR has a built-in selection bias towards sick people. Healthy people are probably missing, or at least substantially underrepresented in the dataset. So don’t be surprised if a classifier trained in this setting decides that everyone is sick.
  • Even without copy and paste errors, the data is often just wrong. I once had an intern read back a note to me where she’d recorded my profession as “construction worker”. Yes, I make things, but it’s not nearly as physically taxing and if a physician treating me thought I regularly did heavy labor with my small frame, you can see where over-treatment might be the result.

CNBC’s Christina Farr wrote more about this data problem, the potential for medical errors, and a strange unwillingness to correct the data. A patient quoted in the story understands all too well the problem of GIGO:

“I hope that companies in tech don’t start looking at the text in physician notes and making determinations without a human or someone who knows my medical history very well,” she said. “I’m worried about more errors.”

  • In addition to incorrect data, there are incorrect semantics or examples of physicians using different words for the same issue. In addition to learning medical synonyms which is no small feat, these EMR ML algorithms are going to have to learn grammar too to be truly effective.

Of course, there are solutions to all of these problems and the data quality can be improved with approaches like more standardized input, proof-reading, and possibly using virtual scribes (ironically using machine-learning to speed up input and improve the quality of the data). However the current issues with it make me question whether this is a garbage in/garbage out effort where everyone would be better off starting from cleaner data. The challenge today is that the experts in ML (big tech), don’t have the data, and the experts in the data (healthcare) don’t have the experts in machine learning, so they are partnering and trying to gain some insights from what they have which is arguably very messy data. Another, and possibly more interesting approach is to get a new data set. In 2014, HealthMap showed that you could glean social media data like Twitter, Facebook, and Yelp for health data, and even predict food poisoning faster than the CDC, and now government health organizations have adopted the approach. This is a great example of finding a new data set and seeing what comes of it. At Wellpepper, our growing body of patient-generated data is starting to show insights. In particular we’ve been able to analyze data to find the following, and use this to automate and improve care:

  • Indicators of adverse events in patient-generated messages
  • Patients at 3-times greater risk of readmission from their own reported side-effects
  • The optimal number of care plan tasks for adherence
  • The most adherent cohort of patients
  • The correlation between provider messages and patient adherence to care plan

We also use machine-learning in our patented adaptive notification system that learns from patient behavior and changes notifications and messages based on their behavior. This is a key drive in our high-levels of patient engagement, and can be applied to other patient interactions. While it’s still hard work to find these insights, and then train algorithms on the data sets, we have an advantage because we are also responsible for creating the structure (the patient engagement platform) in which we collect this data :

  • We know exactly what the patient has been asked to do as part of the care plan
  • We have structured and unstructured data
  • Through EMR integration we also have the diagnosis code and other demographic insights on the patient

If you’re interested in gaining new insights about the effectiveness of your own patient-facing care plans delivered to patients outside the clinic, get in touch. You can create a new and clean data stream based on patient-generated data that can start delivering new insights immediately.

Posted in: Clinical Research, Healthcare Technology, patient engagement

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Voice, Podcasts, Partnerships, and Amazon: Wellpepper’s most popular blog posts of 2018

Looking back over the past year, at our most popular blog posts, we suspect that these topics will remain popular in 2019 as well. New technologies and approaches to consumer and digital health have still not reached their full potential, and there’s still lots to learn.

Not surprisingly, a few of our most popular blog posts related to Amazon. In talking with regular people, healthcare organizations, and digital health folks, we find that they are split on whether they want the retail and cloud services giant to get into healthcare, but whatever side of the fence you’re on, there’s no denying they could have a big impact. Right Alexa?

Wellpepper 2018 Blog, Most Viewed Posts

Voice.Health Shows The Promise of Conversational Interfaces

Voice First or Voice And? Dispatches from Voice Summit

This post was actually from 2017, but our CTO’s take on why AWS Lambda serverless architecture is going to be really important for healthcare IT remains a popular topic.

4 Reasons Why the Future of Health IT is Serverless (AWS re:Invent 2017 wrap-up)

We’re also seeing more and more interest in a continuum of care approach: technologies and experiences that span the patient experience, and really help patients and care-givers self-manage, so our announcement of our partnership with Ensocare was also a very popular post.

Ensocare and Wellpepper Streamline Patient Discharge and Engagement

Continual learning is something both technology folks and healthcare folks share, so it comes as no surprise that our round-up of great podcasts for healthcare transformation enthusiasts, was also a popular post.

Podcasts for Healthcare Transformation Enthusiasts

 

 

Posted in: Healthcare Disruption, Healthcare Social Media, Healthcare Technology, Healthcare transformation, M-health, Voice

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Ensocare and Wellpepper Streamline Patient Discharge and Engagement

Ensocare and Wellpepper Streamline Patient Discharge and Engagement

The innovative healthcare companies have partnered to offer care management solutions that enable hospitals to improve the post-acute patient experience.

OMAHA, Neb. – December 6, 2018 – Ensocare, a leading provider of technology-enabled care management solutions, has announced a new partnership with Wellpepper, an award-winning and clinically-validated patient engagement platform used by major health systems to improve outcomes and lower costs of care.

Under the terms of the agreement, Wellpepper’s highly actionable and engaging mobile treatment plans sourced from leading providers such as Mayo Clinic and others will be offered as a supplement to Ensocare’s existing discharge management tool. With Wellpepper, healthcare providers who use the Ensocare Transition application will have the opportunity to customize post-acute treatment plans based on established care protocols enmeshed within the Wellpepper system, creating an unprecedented patient experience.

“Wellpepper was the perfect fit for our organization,” said Luis Castillo, CEO of Ensocare. “One of the biggest challenges we keep hearing about from our hospital and skilled nursing clients is the difficulty of getting patients to adhere to their care plans after leaving the facilities. They’re seeing costly readmissions and care regression that could have been prevented.

“With Wellpepper, we’re able to offer a solution. Their expansive yet endlessly customizable care plans let providers distill complex care into essential components any patient could follow, and I can’t wait to see the positive patient outcomes that occur when our transition software combines with their ingenious treatment plan solution.”

Anne Weiler, CEO and co-founder of Wellpepper, also emphasized the value of the partnership for both patients and providers.

“Partnering with Ensocare was a natural progression of our goals,” said Weiler. “We’re dedicated to helping healthcare providers mitigate the danger of readmission for their most high-risk patients. Ensocare’s transition solutions can be seen as the first step in setting up that treatment plan. If a patient is left to languish in a hospital bed while a case manager struggles to find them a post-acute care setting, that patient is going to immediately be at a disadvantage, regardless of the quality of the care plan. By combining these healthcare IT solutions, a facility can reduce any and all friction that would otherwise occur during the patient’s recovery process.”

Persons interested in learning more about either solution are encouraged to contact Ensocare or Wellpepper to discuss their current situation and explore opportunities to streamline their discharge and patient engagement protocols. Learn more at Ensocare.com and Wellpepper.com.

About Ensocare

Ensocare, a CQuence Health Group company, is a cloud-based solution suite that began as a single care coordination SaaS solution. Today, we are an end-to-end, service-enabled technology platform designed to help hospitals, health systems, physician groups and payers navigate the value-based environment and beyond. Transition, Ensocare’s care placement and referral software, automates the discharge process, effectively transitions patients between care settings and enables coordinated care across the continuum. A growing portfolio of services designed to identify and fill gaps in patient care complement Ensocare’s overall mission to coordinate care, engage patients and positively influence outcomes. For more information, visit www.ensocare.com.


About Wellpepper

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

Contact:

Jill Reeves
Ensocare
jreeves@cquencehealthgroup.com
402-758-2617

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

Posted in: patient engagement, patient-generated data, Press Release

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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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Electronic Patient Surveys Done Wrong

Recently, a family member spent some time in a hospital following an emergency operation, giving me a chance to experience healthcare from the other side. The surgeon did a great job, the hospital staff was uniformly helpful and competent, and the facilities were great. But there was one small part that didn’t measure up.

During our stay, we were asked to participate in a patient quality survey, something which I was happy to do, both because patient surveys are part of the many of the interactive care plans we build at Wellpepper, and because I have an odd affinity for survey-filling, a condition which I’m assured is not yet classified in the DSM-5. Unfortunately, the quality survey was the lowest quality part of our visit, for a few reasons.

Hygiene

The survey was delivered on an iPad outfitted with a soft case and an asset tracking device. Maybe it was because I’d read too many articles about Hospital Acquired Infections, but I kind of gave this device the side-eye in its squishy soft case. I decided that if I had to go out somehow, filling out a survey would at least let me go out as a hero. I’m sure it was fine, but hard plastic and some obvious evidence of disinfection would have made me feel better. There were vendors selling nice UV charging boxes at HIMSS this year – seems like these should just be everywhere at a hospital, even for patients and their families to use with their own devices.

Security vs Usability

Right after the iPad was delivered, a group of docs stopped by to round. By the time they’d left, the iPad had locked itself and prompted me for a PIN. If I was anyone else, I might have just given up here, but I thought I’d be helpful and try the top few most frequent PINS. I didn’t make much progress (+1 for security), so I had the nurse call in some IT person who unlocked it. This person put the iPad in a kiosk (“Guided Access”) mode. However it also prevented the iPad from sleeping. Now I was in a race against the battery to get the survey completed.

Why Do I Have To Tell You This?

It’s weird how our expectations evolve with the medium of communication. If this was a piece of paper on a clipboard, I’d be more understanding about writing down how long we’d been at the hospital and how long I’d been planning this unplanned emergency operation. But on a tablet? Shouldn’t you be telling me this stuff? Imagine if you could only add friends to Facebook by entering their email addresses, DOB, and full name. Instead, they recommend people, even to the point of recommending someone I happened to say hi to at a coffee shop the other day. On the one hand, I know there’s a terrible data silo problem at health systems, particularly for EHR data. On the other hand, getting the admit date and length of stay isn’t a probabilistic graph traversal recommender problem – it’s a one-liner SQL query.

Electronic surveys could be truly helpful with even basic steps to reduce the survey-filling burden. How many times have you written your name and DOB on a hospital form? But sadly the industry hasn’t been able to crack this nut yet.

Connectivity

On sitting number three, I grabbed the iPad – battery now half drained – and tried to resume the survey. This survey, like many, was web based. Unfortunately, the iPad had lost its WiFi connection, and was now asking whether I wanted to resubmit the form. I gambled on “yes”, which was not the right answer, because now I was told I needed some kind of code to get back into my survey. I don’t know if the information I’d completed already was saved, or lost into the ether. In either case, it was clear that I’d gone as far as I could go, so I set the iPad aside and wondered whether someone would stop by to collect it before its battery ran out.

The Future Of Electronic Forms

So, I’m sorry Unnamed Hospital. I really wanted to help. I was going to be your best customer (remember, I like filling out forms). But it was one hurdle too many, between the logistics, the security-over-usability posture, and making me answer questions you knew the answers to. In the end it was your WiFi network that robbed you of my input.

Of course, it doesn’t have to be this way. I’m pretty sure the health IT community is going to figure this out. With a little user-centric design thinking the electronic experience could actually be helpful for patients. A little more critical thought about security vs. usability could reduce user frustration. And eventually hospital WiFi will be consistently awesome. Perhaps eventually I’ll even be allowed to use my own device. It might be covered with germs, but at least they’re my germs.

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Electronic Health Records and Physician Burnout: Fraught with Frustrations

Electronic Health Records (EHRs) have become a scapegoat for physician burnout. A quick google search of “EHR” and “burnout” will yield nearly 350,000 results. Systematic reviews over the last 10 to 15 years look at much of this data and draw a similar conclusion; higher physician burnout rates are correlated to use of EHRs. They point at increased documentation times, decreased user satisfaction, and “clerical burden” as causes of burnout. Data from other sources suggest we may be laying the blame in the wrong place.

At Stanford Children’s Health, in an effort to improve physician satisfaction with EHR use, they have created extensive and personalized education programs. They obtained data from the EHR to develop an efficiency profile, surveyed physicians on their perspective of their efficiency, and performed observation sessions with physicians so support staff could see how physicians used the EHR. With this information, personalized learning plans were developed. Providers were incentivized to participate and they found physician satisfaction with EHR improved as well as their efficiency and less time spent on medical records outside of the hospital.

This suggest that the problem with the EHR is not of the EHR, but rather the onboarding and training process related to it. Most EHRs can be made to work for you, rather than against you, and improve your efficiency with documentation and patient care.

Physician Burnout in the Electronic Health Record Era: Are We Ignoring the Real Cause? Annals of Internal Medicine. July 2018.

Drs. Downing and Bates recently published in JAMA that there may be another underlying cause that is driving physician burnout and dissatisfaction which is being blamed on the EHR. In looking at health systems across the United States and abroad on a similar EHR (Epic Systems), they found that physicians abroad reported higher satisfaction with the EHR and that it improved their efficiency. In other countries, they noted, documentation is briefer, containing only essential clinical information rather than bogged down by compliance and reimbursement documentation. On average, within the same EHR, notes in the United States were found to be four times longer than those abroad. Notes in the United States had documentation requirements from a “clinically irrelevant” number of elements in each part of a note so that fee-for-service components are fulfilled.

Their argument suggest that a key cause of physician burnout which is being blamed on EHRs is actually our “outdated regulatory requirements.” With reform of these requirements, documentation would become only the essential clinical data, rather than notes with strict documentation requirements of a “clinically irrelevant number of elements” in the various components of a note.

A third argument that I would challenge us to consider as a more likely cause of physician burnout rather than the EHR is the cultural state of medicine in the United States. Due to increasing numbers of lawsuits over the last 20 years, physicians are spending a lot of time on “CYA” medicine (Cover Your A**), feeling forced to order unnecessary testing for an unlikely diagnosis “just in case” things do not go according to planned. We also get pulled into the trap of what I refer to as “Burger King” medicine, playing off the fast food giant’s slogan of “Have it your way.” Patients are coming to the physician already “knowing” their diagnosis and requesting specific treatments or testing. If the physician disagrees? No problem, the patient will just go find one down the road who will do what they want.

In an era of electronic health records on the rise and an increase in rates of physician burnout in the United States, it looks easy on paper to show a correlation between the two. What if instead the EHR is not to blame, but any number of other things like lack of physician EHR training and support, documentation regulations, or “Burger King” medicine? Is it more likely that the relationship between EHR prevalence and physician burnout is only a correlation and not a causal relationship? My hope is that in the coming years we will recognize the EHR as a tool to improve patient care and outcomes, increase our efficiency, and return to practicing medicine at the bedside.

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Voice: The most natural user interface for healthcare

There’s so much promise, and such a natural fit for voice in healthcare that unlike electronic medical records, we should not have to mandate its use. If anything, right now we are being limited by the lack of HIPAA controls rather than end-user demand. If the sessions at the recent Voice Summit, which was focused broadly on voice tech, and the upcoming Voice of Healthcare and Voice Summit at Connected Health conferences are any indication, there are many natural use cases, and a lot of pent-up demand.

With so many concerns about documentation and screens getting between patients and physicians, and the ability to deliver empathy, and to rapidly learn from interactions using natural language processing, and artificial intelligence, voice seems a natural fit and unobtrusive interface that could leapfrog traditional interfaces.

The Healthcare track at Voice Summit showed some of this promise, but also pointed out that we are still early days. Many solutions are pilots or prototypes, and I had the distinct impression that some of today’s HIPAA workarounds would not stand up to a detailed audit. Despite Alexa’s sponsorship of the conference, Google’s strong presence, and both companies push into all things healthcare, both were mum on whether or when their consumer voice devices might be HIPAA compliant. Regardless, healthcare organizations and technology vendors alike are charging forward on new scenarios for healthcare, and you can see by the diversity that if even a few of these end up being the “killer app” it’s a big opportunity.

Patient Care

Rooming: Waiting for a physician to see you in an exam room is often a wasted opportunity. A voice interface in the clinic room, could help further pinpoint why a patient is having a visit or educate pre and post visit on medical issues. Or simply having a voice assistant capture the questions that a patient has during a visit might go a long way to improving the visit.

Inpatient stay: The combination of voice assistants, wifi, and tablets could completely replace expensive and proprietary systems for inpatient patient engagement. We’re already seeing use cases for anonymous interactions with voice devices to order food, check the time, or find out the time of the next physician visit.

Long-term care: Alzheimers and dementia care are cited as the poster child for the benefits of voice in long-term care facilities. Unlike human caregivers, voice assistants never get tired of answering the same questions repeatedly. There are so many times you don’t want Saturday Night Live to predict the future, but with this one they got it right.

Patient Engagement

If we define patient engagement as interactions outside the clinic, then the opportunities today fall into three main categories triage (or eventually diagnosis), education, and self-management.

Triage Skills: Today we see some basic triage skills from organizations like Mayo Clinic, and Boston Children’s Hospital where you can check some basic first aid, or ask common questions about children’s health. While there are approximately 1,000 healthcare skills, most likely there will be a few winners or “go-to” experiences here from leading healthcare organization or trusted publishers like WebMD. (Interestingly, the presenter from WebMD was one of the more skeptical on voice experiences for patients at the Voice Summit, possibly because of the complexity of the information they present through text, video, and images on the Web.)

Health Education: Chunking content into manageable bites is currently being touted as the best practice for education material through voice. However, this is an area where the interactivity that’s possible through voice will be necessary for stickiness. If you think about the best podcasts, they use different techniques to both engage you and also impart knowledge: interviewing, verbatim quotes, sound effects, interjections, and expository material. To get engaging and sticky health education content, publishers will have to think about how to test for knowledge, advance explanations, and interact with the end-users. Since we can only remember 5 things at a time, simply chunking content is not going to be enough to make the delivery of health education through voice stick.

Reminders and Interactive Health Tasks: As we’ve seen from our testing, where voice interfaces may have the most impact for patients is in helping them complete health tasks for example, in medication adherence, simple surveys, or check-ins and reminders of basic information. Given that the voice interface is a natural in the home, checking in with a voice assistance on when to take medication, or tracking meals is an easy way to engage with a care plan. As well, cloud-based interactive voice response systems could call patients with reminders and check-ins.

Clinical Notes

Conquering the pain of charting is possibly the closest term opportunity for voice in healthcare. With every increasing workloads, and the need to capture information digitally for both care and reimbursement, the EMR has been blamed for physician burnout and lack of job satisfaction. Microsoft recently partnered with UPMC to use their Cortana voice assistant to transcribe clinical notes during a patient/provider interaction. Others attacking this space include SayKara, Robin, and incumbent, Nuance Communications. With HIPAA compliance, it’s hard not to imagine Amazon and Google looking at it as well.

Hands-free lookup

Voice really shines as an interface when your hands are not free, like driving, dentistry, or when you need to keep your hands clean. Voice is a natural in settings where touching a screen or device can cause contamination or distraction. Simplifeye is tackling this in dentistry to improve charting, and lookup of x-rays, and we expect this to infiltrate all aspects of healthcare.

You may have seen a recent article on why Alexa is not ready for healthcare primetime. With all of these great examples it’s hard to believe it. It turns out that the criticisms in this article basically highlight the current limitations of voice overall (except for HIPAA compliance of course). However, some of the challenges of discovery, context, and navigation, are why we at Wellpepper believe in not just voice, but a “Voice And” future where voice is a key interface that is helped or helps others like screens or even augmented reality. Voice is powerful, “Voice And” will be even better.

Posted in: Behavior Change, chronic disease, HIPAA, patient engagement, Patient Satisfaction, patient-generated data, Voice

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Voice First or Voice And? Dispatches from Voice Summit

The inaugural Voice Summit was held last week in New Jersey, with the hashtag #voicefirst. At Wellpepper, we’re actually in the “Voice and” camp. We love voice interfaces for their convenience, promotion of empathy and connection, and their natural engagement. However, there are times when voice isn’t the best interface for the task or others when voice plus other interfaces are even better, which is reflected in some of our work with the Alexa Diabetes Challenge, which I spoke about at the conference.

People can only remember 5 things at a time, which is a challenge for delivery of complex instructions, education, or information through voice. Add this to the fact that voice is a “headless” navigation. That is, there are often no cues to figure out where you are going. Most of us are visual creatures, and visual cues together with voice or text often provide a richer experience. And believe it or not, the many of the sessions at this inaugural voice conference also seemed to reinforce this idea, in particular many of the consumer sessions, in addition to the healthcare sessions.

Talks by two very different consumer organizations, Comcast and Lego both showed how early we are in voice design, and how when voice is more seamless and ubiquitous we may see the promise of “voice first” but also how “voice and” is possibly the better path forward.

While when you think of giants of voice, you many immediately think of Amazon and Google, did you know that Comcast processed over 6B voice queries last year? My first thought on attending this session was that it was going to be about using interactive voice response trees before you get to a customer service agent, but Comcast has been quietly infusing voice into their entertainment experiences.

Did you know that your Comcast remote has a “voice” interface? You can talk to your TV to find programs, change the channel, or start a show. This is probably one of the best examples of “voice and.” First, voice search is actually found on a physical device. The Comcast design team had originally created a mobile app for the remote voice experience, but found that downloads were a small fraction of their entire subscriber base, so adding a “voice button” to the remote encouraged more searches. Also remember that when you use voice to search it shows you the results on your television screen. This is a “voice and” experience which wouldn’t make a lot of sense as voice standalone. Imagine searching for a movie to watch, say you’re looking for something starring Harrison Ford, and you’ve got to keep in your mind all the titles over his varied career and then choose one. First it’s a lot to remember, and second isn’t it easier to browse titles when you can see pictures and a description to jog your memory? I spoke briefly with the Comcast presenters about why they chose to put voice on the remote, versus directly in the cable box, and they said that it helped their users find the option, which was a big takeaway from the conference for me, although voice is a natural interface, the end-user still needs guidance. (A nice side benefit of the button on the remote is that it’s not always on and listening.)

Lego was another unlikely consumer company playing in the voice arena. Lego “Duplo Stories” is an Alexa skill that tells stories that children can then build using Duplo blocks. While the video was heartwarming, this session in particular highlighted both opportunities for “Voice And” using augmented reality, and also the current discovery limitations of voice.

In the video, a child playing with Duplo blocks asks his mother to start a story. The mother asks Alexa to play a Duplo story. Think about this: the skill had to be discovered and activated before any of this could take place. How would you learn about the skill without something printed on the box that the Duplo blocks came in? While it’s clever, imagine a new scenario where voice and augmented reality are built right into the blocks: a virtual Duplo minecraft. The child builds something with Duplo, and then a voice and visual interface projects the story on the child’s creation.

It’s still early days, and the potential for “Voice And” is still huge. In fact, a lot of the content at this conference reminded me of the early days of web interfaces. There was lots of talk about taxonomy of information, and “chunking” information into manageable pieces. (I used to teach a course on writing for the web, where we practiced this, which is funny as we now are so accustomed to screens that long-form journalism is making a real comeback.)

Similar to the early days of the web, there seemed to be slightly more focus on publishing than on end-user goals: what does the end-user actually want to accomplish, not what is the end-goal of the content publisher. What’s different though is that while during Web 1.0, the answer to question of whether every business needed a website, was a resounding yes, it’s not clear that everyone needs a voice skill. With 30,000 skills already available for Alexa, and new features coming online weekly, the irony is that the Alexa team sends a weekly newsletter to keep us up to date. So, even Alexa knows it’s a “Voice And” world.

Posted in: Behavior Change, Voice

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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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Investing in primary care

The US healthcare system is an underperformer (highest healthcare spending for the lowest health system performance) compared to the other ten economically advantaged countries primarily due to differences in access, administrative inefficiency, disparities in healthcare delivery, and also due to the illogical underinvestment in primary care. Despite evidence by the Dartmouth Atlas of Health that the regions in which a higher percentage of Medicare beneficiaries receive majority of their care from a primary care physician lends to overall lower costs, higher quality of care, and lower rates of avoidable hospitalizations, the US continues to underinvest in primary care relative to other nations. Because of perverse incentives and overall fragmentation that is rampant in American healthcare, conscious and deliberate effort is needed to keep primary care at the forefront of clinical practice and population health improvement, including:

  • Implementation of quality improvement practices that have a theoretical basis
    According to Harvard Medical School’s Center for Primary Care established in 2011, there are five components necessary in improving primary care including evidence-based change concepts and tools, fostering strong relationships within and across practices, simple systems for reflection and feedback, structured time for team discussion and planning, and regular and meaningful engagement of leaders. The general theme is that quality improvement processes that have been validated (e.g. PDSA cycle) and implementation of driver diagrams that break up larger processes into smaller chunks/concepts have value and are worth the time to problem solve.
  • Prioritizing patient-centered care
    Care should be collaborative with patients’ preferences and values in the context of their socioeconomic conditions being respected. If there is less information asymmetry in clinical practice, then patients can be more active participants in their healthcare. Overall quality would improve with cost savings, as patient engagement research has demonstrated. Truly understanding a patient’s capacity and health literacy will improve a primary care physician’s ability to be effective in delivering patient-centric care.
  • Payer reimbursement for provider innovation in preventive and multidisciplinary care
    Primary care prioritization with the US healthcare system depends on heavy investment from payers because of the nature of reimbursement for clinicians’ time and services. In addition to a value-based compensation model that payers like Blue Cross Blue Shield reward providers with, more creative and interdisciplinary measures could be more payer driven. Humana’s Bold Goal program is a partnership between an influential payer and San Antonio Health Advisory board to partner with HEB grocery stores, community clinicians, and the YMCA to increase patients with diabetes’ better nutritional understanding of their choices. Because of the cost savings involved with more investment in primary care, it would make sense that payers would be incentivized towards this trend.
  • Leveraging of non-clinical members of a team to deliver comprehensive, value-based care
    Substantial evidence suggests that patients do not receive all of the preventive and chronic disease care that the U.S. Preventive Services Task Force advises on the basis of its best evidence because clinicians simply don’t have the time. Oak Street Health is a Chicago based network of value-based primary care centers that developed a clinical informatics specialist program 2014 where technical scribes were able to provide evidence-based recommendations and data support which resulted in improved effectiveness metrics, overall operational efficiency, and physician joy of practice.

Investment in primary care is necessary for the US healthcare system to have improved outcomes. Efforts at the community level, reinforced by theoretical models and financially backed by payers, are necessary in making changes that can yield significant population health improvements.

Posted in: Healthcare costs, Healthcare Policy, patient engagement

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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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