Healthcare Research

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

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

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

Care Plan Intervention

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

Motivational behavior change through an m-health intervention

Outcomes

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

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

More Information

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

Study Announcement Press Release

Study Methodology and Description

Published Study

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

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Healthcare Summer Reading: Invisible Women

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

Machine Learning in Healthcare: How To Avoid GIGO

Self-Driving Healthcare

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

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

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

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

Examples include:

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

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

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

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

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

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Transforming Health at Montana HIMSS Annual Spring Conference

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

 

 

 

Here’s a small review of what attendees experienced:

Voice Technology

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

Security

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

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

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

Finding Money for Innovation

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

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

Consumer Experience

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

Building a State-Wide Healthcare IT Strategy

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

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

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

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

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

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

Dr Toby Cosgrove at Cleveland Clinic

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

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

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

 

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

Patient Stories

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

How Walmart Started a Movement of Engagement

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

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

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

Nebraska Medicine’s Situational Interviewing

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

Geisinger Longitudinal Patient JourneyGeisinger’s Longitudinal Patient Record

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

Wellpepper Digital Intervention for Seniors

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

Financial Impact of Care

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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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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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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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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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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Mary Meeker’s 2017 Healthcare Trends Report Shows Opportunity

An annual highlight of Recode’s CodeConf is Mary Meeker’s internet trends report. Last year, I had the pleasure of hearing her in person, and I’m not sure I’ve ever heard a presentation with so much good data, presented so quickly. This year, I wasn’t able to attend, but she also ran out of time for some of the most important slides for a healthcare entrepreneur like me. Based on a quick run-through of the deck, these three slides struck me. (If you want to see the full section on healthcare, it starts at Slide 288.)

Not surprising that consumers expect digital health services, or that Millenials lead in most categories. It’s also not surprising that Boomers have sought the most remote care–they have probably sought the most care overall. It might be interesting to see this pro-rated by care usage. That Boomers are not looking at online reviews is very interesting given how much attention the surgeons we work with give to them.

 

 

 

 

 

 

 

 

 

 

 

 

Even with all their consumer device troubles, Samsung squeaks above Apple, and Facebook and Amazon both with a tremendous amount of data about you, are still reasonably well trusted. Both Microsoft and Google have tried and failed previously to own your personal health record, but they are well positioned to do so. What would also be interesting is to see these trust levels against traditional healthcare companies like GE or Johnson & Johnson.

 

 

 

 

 

 

 

 

 

 

 

 

EHR adoption is not surprising since it was mandated through meaningful use. It’s a bit depressing to look at the 2004 stats, and think back to which parts of your life weren’t digital in 2004, and compare that to your medical records. However, the biggest opportunity we see in this slide is dramatically expanding the data points available by tracking patients outside the clinic. Physicians are making decisions with only a few data points when there is so much richer information available through patient-entered and patient generated data.

Posted in: Healthcare Research, Healthcare Technology, Healthcare transformation

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T2 Telehealth aka ATA 2017 aka ATA 23: Part 1, The Eye of the Hurricane

While there is a focus on transformation, value, and outcomes going on, if the keynotes are any indication it may be a rough road ahead for telemedicine.

“It’s the 23rd year for the American Telemedicine Association conference, why are we still talking about how to get paid?”, admonished Pamela Peele, PhD economist and Chief Analytics Officer of UPMC during the opening keynote of the annual conference of the American Telemedicine Association.

Pamela Peele at ATA2017

Pamela Peele at ATA2017

“Especially since, as this audience knows, telemedicine is the best thing since sliced bread?

Why indeed? Well, it’s complicated. The problem is that each person in the value chain, the payer, the physician, the healthcare organization, the patient, and the patient’s closest adult daughter (aka primary caregiver), only see the value of one slice of that loaf of bread, and we collectively as purveyors of telemedicine have to sell the entire loaf. There’s no clear solution to this problem. However, with unsustainable costs of healthcare, and increasing consumerization we have got to figure it out. The taxpayer is bearing the brunt of the costs right now, and Peele characterized the shift of baby boomers to skilled nursing facilities as a hurricane we are unprepared for. One way out is to keep people at home, and for that we need Medicare to fund a cross-state multi-facility study to determine efficacy, value, and best practices. Fragmentation of trials is keeping us from wide scale adoption.

The Adaptation Curve

The Adaptation Curve

“We have got to figure it out” was also the theme of best-selling author and New York Times columnist Tom Friedman’s keynote promoting his new book “Thank-You For Being Late.” Friedman claimed to be more right than the rightest Republican and suggested abolishing corporate taxes and at the same time more left than the leftist Bernie Sander’s supporter suggesting we need an adaptable safety net. His major thesis is that we are undergoing 3 climate changes right now: globalization, climate, and technological. To survive and thrive in this new world, we need to adapt and evolve, and take our cues from Mother Nature, not from some sort of top-down regulation. Like Peele on the previous day, Friedman also sees a hurricane coming and suggests that the only way to survive is to find the eye of the storm not by building a wall.

Adapting and evolving will come in handy with the harder times for healthcare investment ahead predicted by the venture investing panel in the day 3 keynote. Tom Rodgers of McKesson Ventures, and Rob Coppedge of the newly formed Echo Health Ventures pulled no punches, as they tossed of tweet worthy statements like “Don’t tell me you’re the SnapChat of healthcare” and “it seems like there are only 3 business models for telemedicine.” The later was Coppedge’s comment on walking the tradeshow floor. (The models are direct to consumer, platform, and as a combined technology and service.) Rodgers had no love for direct to consumer models or anything that targeted millennials who he deemed low and inconsistent users of services. Platform vendors were advised to surround themselves with services: video was seen as a commodity.

So where does that leave us? Value, value, value. The challenge is that the value is different depending on the intervention, the patient, the payer, and the provider. Preventing readmissions, aging at home, decreasing travel costs, all provide benefits to one or more of the key stake holders. Can we figure out how to reimburse based on slices of value? How do we get together to realize that value? And how do we do it before the hurricane hits?

Posted in: Behavior Change, Healthcare Disruption, Healthcare Policy, Healthcare Research, Healthcare transformation, Telemedicine

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Telehealth 2.0: Our picks for Orlando

File-2016-3478-2017_ATATradeshow_1920_25I am really looking forward to heading to Orlando for the American Telemedicine Conference, aka Telehealth 2.0. Seattle has been under a rain cloud this entire year, and I want to see the sun. I’m also looking forward to sharing our findings in using asynchronous mobile telehealth for remote rehabilitation with patients recovering from total joint replacement. I’ll be speaking with our colleagues from Hartford Health, Reflexion, and Miami Children’s Hospital on Sunday during the first breakout sessions. Hope to see you there!

In addition to the topics about legislation and regulations, it’s great to see these sessions on value, quality, and new treatment models. Here are some of Wellpepper’s picks for the conference.

Sunday

Monday

Tuesday

Now with all this great content, networking and a talk to prepare, when will I see the sun?

Posted in: Adherence, Behavior Change, Health Regulations, Healthcare Disruption, Healthcare Legislation, Healthcare Policy, Healthcare Research, Healthcare Technology, patient engagement, Telemedicine

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Better Living Through Big Data

This week I had the opportunity to participate on a lively panel at General Assembly Seattle organized by Seattle Health Innovators, and moderated by Corinne Stroum of Caradigm. Fellow panelists included Randy Wise formerly of Group Health and now at EveryMove, Ang Sun of Regence/Cambia, Lifesprite founder Swatee Surve, and Daniel Newton of Accolade.

Corrine sent us a series of great questions in advance, and we had a rich discussion and so many questions from the audience that we didn’t even get to half of them. It’s a big topic, and with payers, providers, and technologists on the panel there was a lot of opportunity for broad perspectives. There’s a discussion of having a follow-up to this panel to continue the conversation—stay tuned for more on that. The general themes of the discussion included the value of big data to influence individual health with examples like the quantified-self movement, but more generally how our ability to collect and analyze can lead to more personalized and better healthcare. img_3265

At Wellpepper, we have a lot of data to analyze. As Wellpepper CTO Mike Van Snellenberg pointed out in his Stanford MedX talk and I’ve also talked about in this paper in The Journal of MHealth, having data provides an opportunity to get answers faster than using the traditional scientific method. Rather than formulating a hypothesis, setting up an experiment, collecting data, analyzing the data, and then going back to the drawing board if your hypothesis is not born out, data enables you to ask a series of questions and get immediate and sometimes surprising answers.

The panel kicked off with the sharing of some surprising things that we’ve found from the data,  ranging from which mental health tools were favored by different populations to the ability to predict hospital readmissions. In addition to finding trends from explicit patient input, we also discussed the ability to draw insight from activities including social media and mobile usage patterns. Swatee mentioned the Instagram analysis that showed color scheme on photos was a predictor of depression.

The ability to combine both passive and active patient-generated data, and draw conclusions from broad date sets these data sources can help to deliver better care – resulting in what Daniel Newton referred to as “small data.” That is, I’m going to learn as much as I can about you, and then tailor care to you, which is the approach Accolade takes.

As with any talk on tracking and data, questions of privacy came up. While all the panelists thought that there have become standard terms for people to opt-in to sharing health data, describing the use of that data was deemed important. At this point, Ang Sun from Cambia (who admitted that, as a healthcare plan, they had a heck of a lot of data on people), mused that he wished his physician knew as much about him as Google did. Generally, there was consensus that, if the purpose of the data sharing was for connecting people with the appropriate healthcare services, people would opt in.

Our panel was pretty aligned on the idea that there is big value in big data for healthcare, but that the general applications and usage are still in early days. First, there are the privacy concerns and even laws. Second, current healthcare organizations using this first generation of EMRs have limited ability to look at aggregate data for trends. However, with new technology and personalized approaches to care, we see great promise in big data and predictive analytics for healthcare.

Posted in: Clinical Research, Healthcare Research, Research, Seattle

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MHealth and Big Data Are Catalysts for Personalized Patient Care

Although there are many complexities wrapped around our healthcare system, Stanford University’s 2016 Medicine X Conference starts finding solutions to improving patient care by focusing on increasing patient engagement and transforming how patients are treated in the system.

Wellpepper CTO Mike Van Snellenberg, who spoke at MedX in September with digital health entrepreneur and physician Dr. Ravi Komatireddy, addressed several important aspects of big data collection.

“Collecting big data is like planting trees. You need to plant the seed of the process or tooling,” says Van Snelleberg. “Over time, this matures and produces data.”

Mr. Van Snellenberg, who has collected and analyzed patient data at Wellpepper, discovered several key aspects of data collection that could improve care continuity for both patient and providers. He shared this to his MedX audience.

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“Wellpepper has already uncovered new understandings about which patients are most adherent as well as indicators of readmissions,” says Van Snellenberg. “That’s very valuable information.”

“We’ve discovered that, as you collect patient-generated data, these types of insights as well indications about the effectiveness of certain clinical protocols will be available to you. This will help allow for providers to encourage positive patient behavior,” he stated.

Mr. Van Snellenberg spoke further at an interview in October about collecting and using patient-generated data.

 

Question: What groups can benefit off the collecting of big data?

Snellenberg: Collecting patient-generated data can ultimately produce better outcomes and patient care for hospital and clinics as well as the patients themselves. The more in quantity and detail, the better it is to help produce good results. Data collection has tremendous value that can allow hospitals and clinics to learn more about their patients in between hospital visits, thereby filling in missing gaps in patient information. We also realized that collecting big data can potentially prevent complications or readmissions by identifying warning flags before the patient needs to return to the clinic.

And as mentioned, analyzing big data has provided us insights about which patients are most adherent. For example, we have found that patients with 5-7 tasks are adherent while patients with 8-10 tasks are not.

 

Q: What are some things you have discovered using patient-generated data?

MS: We were able to make observations on the patterns. We also discovered a strong linear correlation between the level of pain and difficulty of patients.

Traditionally, patient data remained in the hospital. This often left big gaps in knowledge about the patient in between hospital visits. By collecting and data in between visits to the hospital, you can discover important correlations that would not have been discoverable without data.

 

Q: What are some possible methods to collect patient data?

MS: Dr. Ravi Komatireddy, who worked in digital health, suggested several programs such as Storyvine and AugMedix.

Usually, data is collected by patients recording symptoms and experiences on a daily basis in a consistent manner and then managed afterwards. For example, patients themselves tend to keep track of their progress in diaries or using the FitBit to record the number of steps and heart rate.

 

Q: What are some of the most unique aspects about this year’s MedX?

MS: One unique aspect about the MedX Conference is that it provided more opportunities for diverse voices to be heard in addition to health professionals – including a mix of health patients, providers, and educators.

The mindset was also encouraged to change. Some of the convention’s most progressive talks on stage happened when phrases such as “How might we…” and “Everybody included” are brought up in the discussion.

The term “Everyone included” came up most often, pushing for more perspectives outside of JUST the physicians. MedX’s solution-oriented focus proves to be heading down a successful route to improving patient care in the healthcare system as well as acting as the initiative to open doors for new voices to be heard.

Posted in: Clinical Research, Healthcare motivation, Healthcare Research, Healthcare Technology, Outcomes, patient engagement, Research, Seattle

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A CJR Primer

Recently, I had the opportunity to attend a CJR Bootcamp put on by the Healthcare Education Associates in Miami, Florida. The boot camp setting was intimate, collegial, and well targeted. With the exception of a trio of cardio folks who wanted to get ahead of their bundles, all attendees were directly responsible for implementing bundles at their health systems . The two days were jam-packed with information ranging from understanding the legislation to influencing surgeon behavior to assembling a great team to implement CJR. I recommend that if you’re on the hook for bundles in your organization that you check out this or a similar training yourself.

There is too much to recap in a single blog post, so I’ll share some high-level takeaways:

Bundles Are Complex

Even advanced organizations had gaps in their knowledge and understanding when it comes to the complexity associated with bundles. CMS continues to evolve the requirements and guidelines, causing some implementation approaches to have to rely on predicting what’s going to stick.

For example, the original PRO guidelines were for HOOS and KOOS, which have now been changed to HOOSJR and KOOSJR. If you’re concerned about requirements changing, consider adopting requirements that will benefit you even if they change. Organizations that started tracking HOOS and KOOS have a leg (or knee or hip) up because they have historical outcome data and have hopefully streamlined their processes.

Bundles Require Multi-Disciplinary and Multi-Organizational Teams

Within an organization, you’ll need a multi-disciplinary team that includes clinical, administrative, operational and finance, technology, procurement and so on. You’ll also require an executive sponsor who will make sure senior leadership is aware of and supporting your initiative.

A recommended working group looks like this:

  1. Executive Sponsor(s)
  2. Physician Lead
  3. Project Manager(s)
  4. Care Navigator/Care Coordination Lead
  5. HER/IT Lead
  6. Data Analytics & Quality Leads
  7. Compliance Lead
  8. Legal Lead
  9. Communications Lead
  10. Gainsharing Program Support

You’ll need to be skilled in both project management as well as the ability to influence change. Consider all the stakeholders that need to be influenced – who are the best people to influence them and how?

Think about the rhythm of communication to different stakeholders. Too much and you overwhelm. Too little and people aren’t part of the process.

 Influencing Surgeons

One of the sessions focused on how to change behavior of surgeons. It was presented by Claudette Lajam, M.D. Assistant Professor of Orthopedic Surgery Chief Safety Officer at NYU Langone Orthopedics, who had the task of decreasing costs for implants and improving quality by getting Langone’s to use the right selection criteria. Dr. Lajam studied behavior change theory to implement the change, but it came down to understanding surgeon behavior. She presented them with data, and encouraged competition: each surgeon was able to see in a weekly report where they stood with respect to costs and quality against everyone else in the department.

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In the new model, hospitals are responsible for gain sharing with both upstream and downstream partners where they have less influence and insight. Understanding your top performing orthopedic and skilled nursing partners is key to a successful bundle. In some areas, this risk-and-gain sharing is causing consolidation where orthopedic groups are joining hospitals.

Note that with CJR, different from BPCI, conveners are not allowed. That is, hospitals can only share risk with orthopedic groups and skilled nursing facilities. Organizations that offer to manage your program and share the risk are not allowed to participate in any gain sharing.

Bundles Need Data: But People Don’t Have It

If you need to improve outcomes and lower costs, you need to know where you’re starting from.  To know where you’re starting from, you will need lots of data so that the impact of outliers is harmonized. Not many organizations have this level of detail across their entire pathway, either from organizational challenges or challenges of the system.

Sometimes, this is from a variation of care. For example, one surgeon has most of the complex cases, or another surgeon uses a different combination of implants and auxiliary materials.

Sometimes this is from the challenges of inter-organizational communication. For example, the handoffs between hospital and skilled nursing are notoriously bad – usually with hospitals not knowing where their patients ended up and skilled nursing not knowing why they are there.

Add to this that you can’tthis on top of not being able to find out if a patient is even in the CJR bundle for a period until the CMS data comes back.

So, you’ve got a complex challenge, with large and heterogeneous teams and organizations, and a lack of data. What do you do? Give up? Of course not.

First, attend a boot camp like this one.

Then, treat every patient like they are in a bundle and work on improving outcomes.

Finally, take a look at your position, risk, and low hanging fruit. Even if you only have a few patients in the bundle today, the private payers and self-insured employers are monitoring this closely.

There is Low Hanging Fruit

There are a few areas that have been identified as opportunities to lower costs without impacting quality:

  • Inpatient rehab has been targeted, and often cut. Patients need to get moving soon after surgery, but they may not need as many sessions with a PT directly. We have patients who are following their PT care plan through Wellpepper even in an inpatient setting.
  • Standardization and optimization of implants. Often the implant companies charge separately for each component for the implant and try to upsell on items like screws. Negotiating a standardized bundle can decrease costs here, as can evaluating patients for the best joint for their situation rather than using the surgeon’s favorite. (This was the project undertaken at NYU Langone.)
  • Decreasing the length of inpatient and skilled nursing stay. Equipping patients to be more self-sufficient with joint camps, educational materials, and mobile care plans can enable them to go home faster.

You are Here

Possibly because it’s early days and people are still figuring this out, there isn’t a consistent, phased approach to rolling out the CJR bundle. In fact, you can start anywhere. Or maybe you don’t have to.

First off, make sure you’re in one of the X areas where the bundle is being rolled out. If you are, find out who else is in your region. Your cost accountability is for the average for your region. If there are big spenders in your region, you may already be delivering total joints more effectively than others and may not need to change much besides starting to collect PROs.

Also, take a look at your Medicare population for joint replacement. If it’s low, you may only have a few patients that qualify for the bundle each year – which doesn’t mean that you shouldn’t strive to improve, but it may impact the amount of effort you put in initially.

Figure out where you are today and plan your efforts accordingly. Don’t try to do everything at once and understand that both your process and the information available will continue to improve.

Good luck!

Posted in: Behavior Change, Clinical Research, Healthcare Legislation, Healthcare motivation, Healthcare Research

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Finding Change and Honesty at Mayo Transform Conference 2016

mayo-clinic-logoAlthough the theme of this year’s Mayo Transform conference was “Change,” it might as well have been dubbed “Honesty.”

From keynotes to breakout sessions, there was a raw sense of honesty and acceptance of the fact that change is hard, and we’ve reached a point where the evolution in healthcare doesn’t seem to be happening fast enough.

When you’re as successful as Mayo, it might be easy to brush failure under the rug – which made this session, “We Made This Thing, But It Didn’t Go as Planned. Now What?” unique. Now that some of the initial hype for digital health has died down, we are in a phase of realistic optimism where sharing both wins and misses represents a realistic way forward.

This interactive session in three parts by Steve Ommen, MD, Kelli Walvatne, and Amy Wicks unfolded a bit like a mystery. Questions were posed to the audience at each phase for our input on what might have gone right and wrong. Not surprisingly, the attentive audience proved as capable as the presenters, and some of the most valuable insights came from the audience questions.

The case study in this session was a three-year process to develop a new interface and workflow for the cardiology clinic. Dr. Ommen and the other presenters did not tip their hands to whether the project was successful or not, and we had to tease out the wins and losses that occurred during each phase.

The presenters shared stories, but did not show any artifacts of the process such as flow diagrams, screenshots, or personas. This methodology was effective because, instead of getting bogged down in critique of particular elements, we were able to see the bigger picture of challenges that could apply to any innovation or clinical change.

At the end of the session, the presenters summarized their top takeaways as:

  • Not having enough credibility and evidence

Much of the Transformation team were experts in design, but not necessarily the clinical experience for this service line. There were some misunderstandings between what could work in theory and in practice, although the team did identify areas of workflow improvement that saved time regardless of whether the technology was implemented.

  • Change fatigue (or “Agile shouldn’t be rigid”)

The team tried to use a lean or agile methodology with two-week product sprints: iterating on the design and introducing new features as well as interface changes biweekly. This pace was more than what the clinical users – especially the physicians – could handle, but the design aimed to stay true to the agile process. In this situation, the process was not flexible to the needs of the end users and possibly exacerbated the first point of lack of credibility.

  • Cultural resistance

The team lost champions because of the process. It also seemed like they may have spent too much effort convincing skeptics rather than listening to their champions. One physician in the audience wondered aloud whether the way physicians were included in the process had an outsized impact on the feedback the team received about what was working and wasn’t working. From his own experience, he noticed that a physician’s authority is often a barrier to collaboration and brainstorming.

From audience observations, it seemed like there may have been some other challenges such as:

  • Scope/Success Definition

There wasn’t a clear definition of success for the project. While the problem was identified that the current process was clunky and the technology was not adaptive and usable, not all parties had a clear understanding of what constituted success for the project.

Looking back, Dr. Ommen suggested that rather than trying to build a solution that addressed all co-morbidities, they should have chosen one that worked for the most common or “happy path” scenario. The too-broad scope and lack of alignment on goals made it challenging to conclude success.

  • Getting EPIC’ed

When the project started, the team was largely solving for usability problems created by having two instances of Cerner and one of GE used in the clinical workflow. During the course of this three-year project, Mayo made the decision to ink a deal with Epic, rendering the current problem they were solving for obsolete.

Going for a smaller win early on might have delivered value to end users before this massive shift in the underlying medical records software.

So what happened?

You can probably tell from the recap that the project was shelved. However, the team did have some wins, certainly in their understanding of how to better run a project like this in the future as well as in helping the clinical team optimize their workflow.

What should you take away?

Know your users, iterate, and move quickly to deploy quick wins – but not so quickly as to alienate your stakeholders.

Finally, ask your peers: we’re facing similar problems and can learn together.

Posted in: Clinical Research, Healthcare motivation, Healthcare Research, Healthcare transformation, Outcomes, Research, Uncategorized

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Health Care Innovators’ Uphill Climb

The Healthcare Innovators Collaborative and Cambia Grove have joined forces to present a series of talks on our evolving healthcare challenges.

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This series was run out of University of Washington last year, and this year’s sessions, subtitled “Under the Boughs” are held at Cambia Grove – where a new Sasquatch In Residence (SIR) ensures that the patient voice is present in the conversations.

September’s session took off with Dr. Carlos A. Pellegrini, Chief Medical Officer of UW Medicine, discussing the shift to value-based care. Pellegrini defined UW’s transformation as a process with 6 key goals:

  1.  Standardization

Standardization improves efficiency and is key to reducing cost and improving outcomes. Today, surgeons performing surgery at different hospitals may have varying tasks per hospital. Patients may receive different instructions depending on which physician or department they interact with. As a result, it is difficult to compare outcomes or optimize clinical workflow without a form of standardization.

      2. Population Health Management

Using system data to anticipate patient needs before they become major problems can both improve care and lower costs.

       3. Medical Home 

Implementing the medical home model can allow providers to be more aware of all of their patients and manage them proactively in measurable groups.

       4. Clinical Technology

Better use of clinical technical systems and of technology generally will enable more efficient and proactive patient care.

Dr. Pellegrini suggested they need to identify which patient was calling and suggesting the care they needed. For example “It’s Linda Smith, and she’s due for a mammogram.”

       5. Risk Management

“The Healthy You” – Sending better information to clinicians can help keep patients healthy, such as regarding activity level for obese patients.

        6. Smart Innovation

In contrast to standardization, consider opportunities to   customize experience/treatment for patients to deliver personalized and targeted care.

Understanding and measuring outcomes is also seen as key to approaching this evolution. Still, it was pointed out that providers, payers, and patients all understand a positive outcome differently. For example, for a provider the outcome is usually functional, for a payer or employer the outcome is financial, and for the patient it is often quality of life.

Only when these three outcomes are considered at once can we have true value-based experiences.

While Dr. Pellegrini and interview Lee Huntsman lamented the fact that US healthcare is ten times as expensive as other models, like the UK’s system, at present only 3% of UW Medicine’s revenue comes from value-based models, and it costs them $200M per year to maintain EPIC.

With numbers like this, the shift to value-based care has some big uphill battles. Keep fighting the good fight everyone, we know that the burgeoning health community in Seattle and the Cambia Sasquatch will!

Posted in: Healthcare Research, Healthcare transformation, Meaningful Use, Outcomes, Patient Advocacy, Seattle

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