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What’s True Now?

 

Health systems and payers alike are scrambling to figure out what the incoming administration means by repealing Obamacare. The payers admitted to having no contingency plans if Trump won. Trump doesn’t have a clear model, and the Republican party has a number of proposals. Some involve changing the names of programs or offering them in a different way. Some involve scrapping large sections of the affordable care act.

Rather than second-guessing what’s to come, at Wellpepper, we are focusing on what’s true now and what will remain true going forward.

We believe these things will continue to hold true:

  • Innovation will continue. If anything we hope that new innovation in healthcare, and technology innovation in particular is driven by market forces rather than legislation which created winners out of what was not always the best technology.
  • Consumer-focus is good. 20M newly insured individuals and high-deductibles helped create a market for new care organizations like local urgent care and patient-focused primary care. This consumer evolution will continue as patients demand that their healthcare dollars deliver good service.
  • Value and outcome focused approaches will be rewarded. Whether it’s traditional payers or self-insured employers, the light has been shone on areas to improve care AND reduce costs. Healthcare organizations have seen investments in outcomes pay off as well.

It’s time for a new patient experience that is real-time, connected, and based on the individual. We need to take advantage of the ability of technology to scale, analyze, and deliver personal experiences to leapfrog the current technology implementations in healthcare and deliver better outcomes and greater value in healthcare.

Posted in: Health Regulations, Healthcare Legislation, Healthcare Policy, Outcomes

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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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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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