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Wellpepper Deployment Options

Health Systems have 3 ways to deploy Interactive Treatment Plans at their organization:

  1. Using Wellpepper templates
  2. Leveraging the best practices from Mayo Clinic
  3. Custom Care Plan based on own best practices

Wellpepper Templates

We have a partnership with University of Georgia Medical School, that allows residents to join us on rotation for a month. Through this partnership, and with our excellent research partners, we’ve been able to build care plan templates based on best practice templates for over 30 chronic and acute conditions.

Health Systems may choose to implement these Wellpepper Templates, with minimal effort, which makes this deployment option the quickest.

Mayo Clinic Best Practices

At HIMSS 2018, we announced a partnership with Mayo Clinic to make their best practices available on the Wellpepper platform (here). This allows for health systems to leverage interactive care plans developed with Mayo Clinic content. This is also a very fast deployment and only requires a few configuration decisions from the health system.

Custom Care Plans

The third and most commonly selected option, especially for comprehensive care plans, is to develop an interactive treatment plan based on the Health System’s own best practices. These implementations typically take a bit more time to deploy. One of our tenants is if we can’t do better than paper, then we shouldn’t be doing it. Because of this, we’ll spend additional time going through the existing care plan documentation/discharge instructions and provide guidance and recommendations for how to deliver content digitally in context of where the patients are in their care.

EMR Integration

For initial deployments, we’ll typically see Health Systems choose to start without EMR integration. This is due to competing priorities with IT and allows the Health System to get up and running more quickly.

Shortly after that initial deployment, or in parallel with, we will start to map out what EMR integration looks like, with the goal of streamlining the clinical experience. The graphic below shows several ways that we integrate with EMRs, with the first step frequently being single sign on for patients and clinicians, followed by an ADT feed to onboard patients.

For more information on how to get the most of your deployment, please email me at luke@wellpepper.com.

Posted in: Healthcare Technology, Interoperability, patient engagement, Using Wellpepper

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Engaging Patients and Impact to Clinical Workflow

One of our goals at Wellpepper is to enable patients to self-manage and we know that if given the right tools, they will do so. While we strive for that exceptional patient experience, we also put a lot of effort into streamlining clinical workflow for onboarding and monitoring patients.

Patient Onboarding

The process for inviting a patient is meant to be simple with a minimal impact to clinical workflow. Capturing basic patient demographics and assigning the appropriate care plan(s); a process that takes 30 seconds to complete. Typically, a scheduler, navigator or health coach will invite patients when they have been identified for an interactive care plan. Ideally, this is done prior to the patient coming into the clinic, but depending on the care plan, this can place at the front desk or in the patient’s room. EMR integration is another way Wellpepper can help streamline this process. You can read a bit more about some of our EMR Integration options in my post about deployment options (here).

Patient Monitoring

Our professional services team will work with your clinical teams to understand all the scenarios where you want to know what your patients are doing when they’re not in the clinic. Using Alerts & Notifications and Machine Learning, we can help make sure that you’re focusing your time on the patients that need help.

Alerting & Notifications

Our sophisticated rules engine enables health systems to build out simple or complex alerting scenarios. These alerting scenarios will generate an alert and notify the care team.

Patients reporting a symptom or side effect is the most commonly used alerting scenario. Our analysis has found that in surgical scenarios, patients that report a symptom or side effect within 3 days after surgery are 3 times as likely to readmit within 30 days. By alerting the care team that a patient is experiencing a symptom or side effect, a care team member can take action and possibly prevent a readmission.

Other Alerting scenarios may include things like patients not doing their exercises, or reporting a blood sugar reading out of the target range.

Machine Learning

One of the areas that we apply machine learning to help streamline clinical workflow is in our HIPAA-compliant messaging system, which allows communication between patients and their care team. Our analysis has shown that 98% of the messages that patients send are not urgent, and 70% of them don’t need a response. Our message classifier looks for the 2% that are urgent and escalates those to the care team.

It’s important to understand all of the points where patients may reach out for help and optimize workflow accordingly. This is another area where integrating with the EMR can help.

For more information on how to streamline clinical workflow while still providing a great patient experience, please email me at luke@wellpepper.com.

Posted in: Healthcare Disruption, Healthcare motivation, Healthcare Technology, Healthcare transformation, Interoperability, Managing Chronic Disease, patient engagement

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Boston University Study Demonstrates that mHealth-Supported Exercise Program Benefits People with Parkinson Disease

Boston University Study Demonstrates that mHealth-Supported Exercise Program Benefits People with Parkinson Disease

Boston, MA – February 7, 2019 – The randomized controlled pilot study used the Wellpepper patient engagement platform to examine the comparative effectiveness of mobile-health-supported exercise compared with exercise alone for people with Parkinson disease.

Key Points:

  • The comparative-effectiveness study, which took place over a 12-month period, was published in the February 2019 issue (Volume 99, Issue 2) of the journal Physical Therapy.
  • It is among the first randomized controlled studies to clinically validate the use of digital health tools in supporting improved patient outcomes.
  • The study positively demonstrated the impact of a digital intervention on people with Parkinson disease who were evaluated as sedentary during study enrollment. People with Parkinson disease who were less active when they entered the study, and who used the Wellpepper application during the 12-month period, showed a statistically and clinically significant improvement in their overall mobility scores compared to similar individuals in the control group without the digital intervention.
  • The study was led by Terry D. Ellis, PT, PhD, Department of Physical Therapy and Athletic Training and Sargent College of Health and Rehabilitation Sciences at Boston University with a research team from Boston University, the University of New England and Brigham and Women’s Hospital at Harvard Medical School (see full list of authors below).
  • Ellis is continuing research in this area at two sites with an NIH-funded clinical trial to further determine the effectiveness of a “connected behavioral approach” against a control group in increasing real-world walking activity in persons with Parkinson disease. The study is onboarding the first subjects this month (February 2019).

“Behavioral change strategies provided through mHealth applications such as those delivered by Ellis and colleagues provide a promising theoretically based and practical approach for helping people with PD (and possibly other chronic disabling conditions) to successfully engage in sustained exercise behavior over the long term,” said Alan M. Jette, PT, PhD, FAPTA and editor in chief of Physical Therapy in an editorial. “As the rehabilitation field shifts from traditional approaches to digital platforms in delivering behavior change interventions, an mHealth application like the one examined in the Ellis et al study holds promise in increasing the reach and scalability of physical therapist services in the digital age.”

This VIDEO demonstrates how the technology was used.

Background:

Declining physical activity commonly occurs in people with Parkinson disease (PD) and contributes to significantly reduced functional capacity and overall quality of life. Previous studies have demonstrated the benefits of exercise and physical activity in reducing disability and enhancing quality of life in people with PD.

This study was designed to explore the effectiveness, safety and acceptability of a mobile-health-mediated exercise program in promoting sustained physical activity in people with PD. Essentially, the Wellpepper mobile patient engagement application became a tool for motivating and monitoring behavior change.

There were 51 participants in the study, all of whom had mild-to-moderately severe Parkinson disease. They were divided randomly into two groups – mHealth and active control – and each group was further subdivided into those who were more active when they came into the study and those who were more sedentary.

Over the course of one year, the mHealth group’s outcomes were compared with those of an active control group, looking at daily steps, moderate-intensity minutes and other measures of activity and mobility. Evaluations were made at the beginning and again at the end of 12 months and exercises were provided by physical therapists with expertise in PD.

  • mHealth: The mHealth group participated in a technology-mediated exercise program that included walking with a pedometer and engagement in exercises. The Wellpepper mobile patient engagement application was used to provide the take-home exercise instructions (along with videos of each person doing their own exercises in proper form), ongoing text-based communication and support (e.g. changing exercises over time to accommodate progress or health changes) and tracking of physical activity and adherence. Ttracking was visible to participants to monitor their own progress and to researchers.
  • Control: The active control group walked with a pedometer, received paper-based exercise instructions and tracked their activity in a paper calendar.

Outcomes:

At the end of one year, both groups had increased their daily steps, moderate-intensity minutes and 6-Minute Walk Test, however the Parkinson Disease Questionnaire 39 mobility scores among the subgroup who were less active prior to the study demonstrated a statistically and clinically meaningful improvement.

An abstract of the study is available HERE and the full study can be made available to media upon request. Editorial overview of the study is also available.

Study Authors:

Terry D. Ellis, PT, PhD, Department of Physical Therapy and Athletic Training, Sargent College of Health and Rehabilitation Sciences, Boston University; JamesT. Cavanaugh, PT, PhD, Department of Physical Therapy, University of New England, Portland, Maine; Tamara DeAngelis, PT, DPT, Department of Physical Therapy and Athletic Training, Sargent College of Health and Rehabilitation Sciences, Boston University; Kathryn Hendron, PT, DPT, Department of Physical Therapy and Athletic Training, Sargent College of Health and Rehabilitation Sciences, Boston University; Cathi A. Thomas, RN, MS, Department of Neurology, Parkinson’s Disease and Movement Disorders Center, Boston University; Marie Saint-Hilaire, MD, Department of Neurology, Parkinson’s Disease and Movement Disorders Center, Boston University; Karol Pencina, PhD, Research Program in Men’s Health, Aging and Metabolism, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts; and NancyK. Latham, PT, PhD, Research Program in Men’s Health, Aging and Metabolism, Brigham and Women’s Hospital, Harvard Medical School.

About Boston University Center for Neurorehabilitation

The vision of Boston University Center for Neurorehabilitation is to lead the development of evidence based, innovative, theory-based approaches to the rehabilitation of persons with Parkinson disease and other neurological conditions and to disseminate this information on a global level. Lead by Director and assistant professor Dr. Terry Ellis, PhD, PT, NCS, the center is part of the College of Health and Rehabilitation Sciences, Sargent College, Boston University.

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.

Media Contact:

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

 

Posted in: Press Release, Uncategorized

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The HIMSS Flu

As usual HIMSS was an overwhelming whirlwind of meetings, opportunities, and information. We had a great show at Wellpepper, and were impressed by a few things. First we heard a lot less about wanting the EMR to do everything. People have realized that especially for all of the patient-facing digital experience, that there need to be interoperable solutions, that are designed with the needs of the end-user in mind. Another thing we noticed was less hype that any one technology (AI, blockchain) was going to be the savior of healthcare. It seems like the market is maturing and there’s an understanding that technology is a key underpinning but only when it’s solving real problems for patients and clinicians. John Moore from Chilmark, who was attending his 11th HIMSS has a great take on this.

Each year, we come away from HIMSS with something we didn’t expect. While it’s usually new leads, partnerships, or competitive intelligence, this year for me, it was the HIMSS flu. Being in a conference center full of technology to diagnose, manage, connect with, and treat sick people, made it seem like a solution should be close by. Ironically, I had meetings with a number of physicians who said that it looked like I had the flu, but couldn’t treat me because they weren’t licensed in Florida. Also, my primary care physician couldn’t help me for this reason as well.

After seeing CirrusMD tweet at my friend and fellow patient-centered care advocate Jan Oldenburg with an offer of a consult, I thought that telemedicine might be the answer.

MDLive came through with a visit code, and I signed up. The sign-up process was pretty painless although an option to clarify where I was physically versus where I lived might have been helpful.

Once I signed up, the app told me it would notify me when it found a physician. This was the slightly confusing part, as when I exited the app and opened it again there was no record that I was in a queue for an appointment, so I started trying to sign up again. Eventually, a video visit came through while I was trying to re-register.

My doctor looked like she was taking calls from home, from the video. Unfortunately, video didn’t work very well from the HIMSS floor—not surprising given the status of the network, so we switched to phone. After a 10 minute conversation, she concluded I had the flu (she was right), and prescribed Tamiflu.

As Jan also found out when she had her asthma attack, the pharmacies near the convention center weren’t actually pharmacies, that is they didn’t offer prescription medication. For Jan it was an expensive Uber to pick up her prescription. For me it was finding a pharmacy that would be open between Orlando and Tampa where were were headed for customer meetings on Friday. By the time I got the prescription, it was 7 hours later, and with Tamiflu the timing matters.

While I was thankful to get care, here are a number of points of friction that made it more difficult than it needed to be, and also show how healthcare really hasn’t adapted to the needs of people:

  • State-based licensure makes telemedicine prohibitive. It also means that you can’t get care from your primary care or other specialists if you’re traveling. Kind of ridiculous that because the patient is physically in Florida suddenly the physician is not licensed to practice.
  • Pharmacies need more delivery options. Even locally, I’ve ended up at pharmacies that don’t take my insurance. Driving around when you’re sick is annoying, and showing up in person when you’ve got the flu is unhelpful for everyone else there.

On the licensure, it’s slow going, but states are starting to have agreements to solve this. On the delivery options, Amazon-drone delivery can’t come fast enough. Overall, the experience wasn’t terrible, and the technology worked but it certainly wasn’t seamless or convenient, and I probably infected a bunch of people while trying to get care. I’d like to apologize to anyone I may have passed the flu along to. I’m not the type to work when sick, but when you’re on the road it’s hard not to.

Also, we’d like HIMSS and all conferences to consider pop-up urgent care. The bandaids in the first-aid room weren’t enough.

Posted in: Healthcare costs, Healthcare Disruption, Healthcare Technology, HIMSS, M-health, patient engagement, Telemedicine

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See you at HIMSS19

HIMSS19 is a couple weeks away and we have a lot to be excited for!

Stop by and see us in the Personalized Health Experience, Booth 888-96. Alongside our great partners at Ensocare, we will be showcasing our latest product updates, discussing ROI for patient engagement platforms, promoting care plans based on Mayo Clinic best practices, and sharing our vision for the future of patient engagement.

We have a long list of booths to visit and sessions to attend. Below are some of the topics that we’re particularly interested in this year:

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

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

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Calculating Return On Investment For Interactive Care Plans

Patient engagement and education is perhaps one of the most under-utilized resources in the care continuum. Patients who are engaged in their care cost healthcare systems [cost] 8% less than non-engaged patients in their base year, and 21% less in future years.[1]

Interactive treatment plans deliver return on investment in three key ways:

Improving patient satisfaction and outcomes

  • Patients look for quality and convenience when they choose a provider organization. They want to be able to interact with their healthcare organization on the same terms as everything else in their lives. Improving outcomes also increases patient satisfaction.

Increasing access to care

  • By monitoring what patients are doing outside the clinic and enabling patients to self-manage, you can increase access to care by seeing the right patients, seeing more patients, and improving recall. Making sure patients are prepared for surgery decreases no-shows and increases utilization and access to care.

Reducing costs

  • Cost reductions are the most dependent on model of care since a readmission or ED visit could be a source of revenue. However, you can look for reducing hard costs of seminars and handouts as well as costs of readmissions, extra visits in capitated models, and of complications. For patients poor outcomes increase costs both out of pocket and in quality of life. Manual labor costs of administering surveys and follow up questionaries can also be avoided with automated systems.

Long-term impact

Patient engagement can have a much stronger long-term impact, including reducing:

  • Hidden costs of variability in care delivery
  • Hidden costs of lack of standardization and manual processes
  • Costs of poor patient outcomes that result in worsening patient problems

As well, as an industry have only begun to scratch the surface of the types of clinical and behavioral insights that will be derived from patient-reported data, that will enable more efficient and effective treatment based on predictive models, and stronger patient participation in their own care.

For our full whitepaper, and ROI economic models contact sales@wellpepper.com or call (844) 899-7377 and press 1 for Sales.

[1] Health Affairs, 32, no.2 (2013):207-214 What The Evidence Shows About Patient Activation: Better Health Outcomes And Care Experiences; Fewer Data On Costs

Posted in: Adherence, Healthcare Legislation, Healthcare transformation, patient-generated data, Return on Investment

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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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