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The Healthcare of the Future: Equity and Access

If the sold-out “Healthcare of the Future” event presented by Puget Sound Business Journal, is any indication, Seattle is ready for healthcare transformation. Last week’s event at the Fairmont Olympic featured prominent local healthcare leaders discussing equity and access to care, and why Seattle is the right community to deliver.

Healthcare of the Future

Interesting, the panel discussion started with a definition of access, framed as not just being able to receive care, but also to navigate and understand care. Speakers mentioned that in the transition from uninsured to insured, people might now have access to care but not enough health literacy to receive care. This was exemplified when one of the panelists, a physician herself talked about a recent experience with getting care for her son where she navigated multiple providers and care settings, and all the while had a firm handle on who she was talking to, why her concerns were important, and the eventual diagnosis.

You can see examples of this everyday on #medtwitter when physicians or other healthcare professionals talk about how hard it was for them to navigate the system as caregivers for their families. Now, just imagine that you’ve never had healthcare coverage before. How do you know what your options are, how much you may have to pay, or when and where to see a doctor?

Panelists also felt that in addition to access, health equity needed to include helping patients make decisions based on their own values, not the values of the system. Again, a difficult situation to navigate for someone new to the system, or potentially being intimidated by the ‘white coat.’ Equity also looks at whether anyone is being left behind in the system, which could be from a myriad of reasons: language, cultural, or even geographical barriers. Given the problems of staffing rural clinics and hospitals, are people in remote areas able to receive the same level of care as those in the cities?

Unsurprisingly, panelists were bullish on Seattle’s ability to deliver, both from the collaborative nature of the healthcare organizations in the region, and from our stronghold of technology. Tech and healthcare partnerships were cited as the best opportunity to shorten the 17 year cycle from research to clinical practice, with technology disruption in the areas of big data, AI, and cloud infrastructure from local tech giants Microsoft and Amazon pushing the healthcare industry forward. (Let’s hope they can also solve the interoperability of data problems, as one speaker equated having the largest Epic installation at Providence as being a substitute for data portability and interoperability.)

All in all, this was a great event, and discussions at my table ranged from best practices for oncology care, especially with patient-facing tools outside the clinic, to how smart hospital room design includes sensors in the furniture to predict patient falls. That the room was buzzing before 7:30 on a Friday morning shows that we have a lot of great momentum for solving hard problems in healthcare in Seattle.

Posted in: Healthcare costs, Healthcare Disruption, Healthcare Technology, Healthcare transformation

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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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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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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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Investing in primary care

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

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

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

Posted in: Healthcare costs, Healthcare Policy, patient engagement

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Pointing Fingers at Healthcare Problems

I’m only halfway through Elizabeth Rosenthal’s “An American Sickness: How Healthcare Became Big Business and How You Can Take It Back” which means that I haven’t gotten to the “what you can do about the problem” part. It’s a slow read, not because it’s not compelling but because it’s too compelling, and if like the current President, you were surprised at how complicated healthcare is, this book will do nothing to dissuade you. It’s really really complicated.

So far, I have two main takeaways from the book, that are easily illustrated through my recent experience of breaking and dislocating my finger: a simple, non-life-threatening problem, that unearthed a couple of key dysfunctions and unintended consequences.

My first takeaway is that everyone is complicit, and yet seem to manage to finger point at everyone else. Rosenthal spares no punches in unearthing decisions that are not made with the best interest in of the patient at heart. Providers, healthcare organizations, payers, pharma, and employers all are complicit in the mess that is our current healthcare system.

This past fall, I broke and dislocated my finger. It wasn’t a big deal, but because it happened on a Saturday night, my only option for care was at the ER. Last week I received a letter in the mail from my insurance company, that according to the envelope required my urgent reply. In the letter, the insurance company suggested that perhaps someone other than them may be on the hook for my ER bill. While I understand they wanted to make sure this wasn’t a worker’s compensation claim, the form was basically for me to tell them whose fault my injury was so that they could go after another insurance company to pay. This was a sports injury in a game of Ultimate Frisbee, a game so granola-like that there are no referees: players call fouls on themselves. . No one was at fault, and even if they were, I would never have considered suing. However, the form didn’t give me that option: only gave me the option of saying whether I had settled my claim. I created a new box that said “NA” and checked it.

When I received the letter, I couldn’t help but think back to Rosenthal’s book, and also consider the amount of effort and cost that was going into finding someone else to blame and pay. Just imagine what this effort and cost would have been if there were legal action….

The second takeaway is that the original intention of a decision always has much farther reaching implications than anyone who agreed on what seemed like a reasonable decision though. Again with the finger, I was asked a number of times if I wanted a prescription for OxyContin. I did not. As has been well publicized we have an opioid addiction problem in North America. While my finger hurt, aside from morphine during inpatient for an appendectomy, I hadn’t had opioids, and really didn’t think that it was necessary, which I explained to the physician. It wasn’t. Tylenol worked fine—however, it seemed that it was very important that I be the one to make this call, not the physician.

One of the unintended consequences of patient satisfaction scores may be the over prescription of pain medication, as many of the questions on the HCAHPS are about whether the patient’s pain was well managed. In Rosenthal’s book, I was also surprised to learn that a finger fracture where an opioid is prescribed has a different billing code than if it is not prescribed, and that with the fracture plus opioid billing code, hospitals get paid more. Now, if you are wondering how this may be the case, if you think about it, a fracture that requires an opioid must be more severe than one that doesn’t and therefore the billing code reflects the severity. This is exactly where the unintended consequences of billing codes can result in exactly the wrong behavior for patient care and safety.

It’s quite possible that the physicians on duty were not aware of either of these two drivers for prescribing, especially the billing code one. They may have just been told “this is our standard of care” and were following guidelines.

If a simple finger fracture and dislocation can shine a light on two key problems in our healthcare system, just imagine what else is out there. Actually, you don’t have to, just get a copy of Elizabeth’s book yourself, and let’s compare notes when I get to the part about what the fix is. It’s going to take all of us.

Posted in: Health Regulations, Healthcare costs, Healthcare Disruption, Healthcare Legislation, Healthcare Policy, Healthcare transformation, Opioids

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EvergreenHealth: Evolving Care Outside The Clinic for Better Outcomes

In 2016 we formally announced our collaboration with EvergreenHealth to deliver interactive care plans for Total Joint Replacement.

“Across our organization, we strive to be a trusted source for innovative care solutions for our patients and families, and our partnership with Wellpepper helps us deliver on that commitment,” said EvergreenHealth CEO Bob Malte. “Since we began using Wellpepper in 2014, we’ve seen how the solution enhances the interaction between patients and providers and ultimately leads to optimal recovery and the best possible outcomes for our patients.”

EvergreenHealth is an integrated health care system that serves nearly 1 million residents in King and Snohomish counties in Washington State, and offers a breadth of services and programs that is among the most comprehensive in the region. More than 1,300 physicians provide clinical excellence in over 80 specialties, including heart and vascular care, oncology, surgical care, orthopedics, neurosciences, women’s and children’s services, pulmonary care and home care and hospice services. With expansion into more rural areas, and a catchment area that serves Seattle’s ‘eastside’ home to Microsoft and other major technology companies, delivering virtual care is both an imperative for an an expectation of EvergreenHealth patients.

Since our initial announcement, we’ve seen thousands of patients complete care plans and outcome surveys, and expanded within the musculoskeletal service line to include preventive care, spine surgery, and general rehabilitation.

User Experience

EvergreenHealth has a white labeled version of the Wellpepper patient application called MyEvergreen and available in Android and Apple App Stores. Clinicians use the Wellpepper clinic portal, and receive alerts to their email inbox if patients report any issues or unexpected outcomes.

EvergreenHealth has deployed care plans based on their own clinical best practices. 

Outcomes

  • Thousands of patients have used Wellpepper interactive care plans at EvergreenHealth
  • Interactive care plan users show higher scores on standardized outcome reports than those tracking outcomes without an interactive care plan
  • EvergreenHealth patients show a higher engagement level than Wellpepper’s overall 70% engagement

I would not want to have another knee surgery without the app. I was 81 and it wasn’t hard for me at all!

Total Knee Replacement Patient at EvergreenHealth

Technology

This deployment used a white labeled Android and iOS application for patients, and a clinic portal for clinicians. Patient invitation is synched with the Cerner medical records software using an ADT feed. Clinicians are notified of patients requiring additional help with an email alert. Wellpepper’s entire HIPAA secure platform was leveraged for this implementation, and EvergreenHealth deployed custom care plans based on their own best practices. They continue to add innovative features as they are added to the Wellpepper platform.

Posted in: Exercise Physiology, Healthcare costs, Healthcare Technology, HIPAA, Interoperability, M-health, Outcomes, patient engagement, Prehabilitation, Seattle

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