Serendipity of survival: The democratization of healthcare

“Chronic diseases and conditions—such as heart disease, stroke, cancer, type 2 diabetes, obesity, and arthritis—are among the most common, costly, and preventable of all health problems,” according to the CDC.

In fact, about half of all adults in the US suffer from one or more chronic diseases; and 86 percent of the nation’s $2.7 trillion annual health care expenditures are related to chronic illness and mental health conditions.1

What may be even more alarming than the cost impact is the fact that patients afflicted with these acute and chronic conditions are often not receiving optimal care. One study referenced in the New England Journal of Medicine (NEJM) found that almost half—46.3 percent—of chronically ill participants “did not receive recommended care.”2

Why does this happen, despite the proven results of accepted evidenced-based guidelines? There’s no simple answer; rather it’s a result of a combination of pressures including: the transition from fee-for-service to value-based care, time-consuming regulatory and documentation requirements, information overload, and an explosion of knowledge in the industry. And, the ability to ingest, process and retain enormous volumes of data and then translate that information to actionable, patient-specific interventions is a challenge that tests the limits of even the best and brightest of human minds.

Efficiency vs Efficacy
Whatever the cause, the effect is that, for the nearly half of all patients who don’t receive the best course of treatment, costs increase and quality outcomes decrease. Future adverse events and flare-ups will lead to readmissions, avoidable surgeries, and a host of additional costs down the road. Efficient delivery of ineffective care won’t correct poor outcomes.

Evidence supporting the need for efficacy and efficiency of care can be found across all chronic conditions. For example, a study in the March 2017 issue of the Journal of the American Medical Association (JAMA) found that, of nearly 95,000 patients with a known history of atrial fibrillation (AF) who had acute ischemic stroke, an astonishing 83% “were not receiving therapeutic anticoagulation.”3 To be clear, this was not a case of patient non-adherence, but rather of physicians never having prescribed the medication in the first place. Consider the potential savings of avoiding these strokes, had the patients been receiving blood thinners as guidelines recommend. The efficient delivery of flawed care would not have helped these patients.

The Haves and the Have-Nots
The unfortunate reality of today’s healthcare system is that your care is dependent upon: 1) what your doctor knows, and 2) who you know. No doctor – or human being, for that matter – is capable of retaining all of the most up-to-date scientific evidence for every medical condition, let alone consistently distilling this knowledge into the optimal interventions during the very limited intervals they have to examine a patient’s conditions. And, very few patients have access to the most educated and experienced physicians, centers of excellence or high-quality care for every possible health condition. The reasons for this inequity are nuanced, and include both socioeconomic factors as well as sheer proximity to experts.

In addition to factors such as where you live or your financial means, the healthcare you receive can also largely depend on who you know. For example, if you work in New York City, you have a higher probability of knowing someone who works at a renowned institution like Mount Sinai, Weill Cornell, or Memorial Sloan Kettering than someone in Iowa would. That means you might have a friend or relative who is a nurse, doctor, technician, or even a scheduling or billing staff member at one of the top hospitals in the country. Likewise, if you work for a major health insurance company like Aetna or Blue Cross and Blue Shield or in the health industry yourself, chances are, you know someone who knows someone, who can get you a recommendation, referral, or expedited appointment to see the right doctor for the best possible care.

But what if you don’t?

Timing is Everything
I have been approached more times that I can count by family, friends, colleagues, patients and acquaintances who are faced with a medical crisis and have no idea where to go and what to do with their diagnoses. They are often consumed with fear, unanswered questions and no plan of action. I’ve been fortunate throughout my career to have amassed a large network of experts in nearly every area of medical science, and thankfully, I can make a call and quickly connect those facing medical uncertainties to one of the best-in-class physicians within a particular specialty. By making these connections and expediting the process, my friends and colleagues receive the best possible medical treatment.

As grateful as I am to help, this is yet another example of how the US healthcare system is broken. The average American doesn’t always have access to the nation’s leading specialty healthcare experts. And why is it a matter of chance at all? Why can’t we all have access to the best possible care from the brightest medical minds–-with the latest evidence-based guidelines—at any time and from any location?

Finally. A Technology Solution with the Potential to Democratize Healthcare
“The first step toward a solution is acknowledging the profound mismatch between the human mind’s abilities and medicine’s complexity,” write Ziad Obermeyer, and Thomas H. Lee, MDs, in an NEJM perspectives article titled, “Lost in Thought — The Limits of the Human Mind and the Future of Medicine.”6 They outline the problem as follows:

“Medical knowledge is expanding rapidly, with a widening array of therapies and diagnostics fueled by advances in immunology, genetics, and systems biology. Patients are older, with more coexisting illnesses and more medications. They see more specialists and undergo more diagnostic testing, which leads to exponential accumulation of electronic health record (EHR) data. Every patient is now a “big data” challenge, with vast amounts of information on past trajectories and current states … If a root cause of our challenges is complexity, the solutions are unlikely to be simple … But there is hope. The same computers that today torment us with never-ending checkboxes and forms will tomorrow be able to process and synthesize medical data in ways we could never do ourselves. Already, there are indications that data science can help us with critical problems.”

Obermeyer and Lee have it exactly right. With the coordination of medical technology and the right (real-time) patient data, there is opportunity to equitize care across the country. We now have technology that offers the ability to deliver insights based on the latest scientific research and approved guidelines. By collecting granular data from a specific patient and interpreting the data against guidelines, we can dramatically lower healthcare costs and improve patient outcomes, saving lives.

Let’s look at an analogy to help explain how this technology works. Major commercial jet engine manufacturers now create “digital twins”, or electronically replicated versions of each of their jet engines. The company looks at factors that an engineer would want data on, such as wind speed, oil pressure, external obstacles like birds and other planes in the sky, and so on, and sends that data to an analytic platform in real-time. This digital twin, helps to anticipate service needs, prevent an unexpected failure and extend the engine’s useful life. Without this real-time data and the resulting recommendations, the company would be “flying blind,” so to speak, and the probability of costly, catastrophic negative events would increase exponentially.

In healthcare, then, we need to create a similar “digital replica” of each patient, using data from electronic health records, insurance companies, and even information from remote monitoring technology (devices that are wearable or implantable, or can be used in the home), such as blood pressure readings for cardiac patients and blood sugar tests for diabetics. From there, using cloud-based technology, the data collected about specific patients can be compared against the latest accepted evidence-based guidelines, and a customized, real-time recommendation can be delivered instantaneously to the physician or other care giver, alerting them to the likelihood of acute events, and, most importantly, offering actionable recommendations for care to help prevent those events, allowing physicians to intervene before the event occurs.

democratization

How Do We Make Abstract Guidelines Actionable – and Available to the Masses
We already have everything we need at our fingertips: enough information and computing power to provide an analytical bridge between medical guidelines and high-risk patients with chronic conditions. The result is actionable diagnostic and treatment interventions tailored to individual patients. The missing link, however, is the ability to deconstruct and digitize these scientifically-based guidelines into an evidentiary machine learning platform. This platform applies the guidelines and real-world evidence from medical experts to an individual patient’s data and health history and is continually monitoring the patient’s data. The result is prescriptive diagnostic and therapeutic solutions for physicians to incorporate into their treatment plans. The impact is preempted strokes, heart attacks, blindness, kidney disease and amputations, and lives saved. Our mission is to disseminate this information across the care continuum in an easily digestible manner so that all patients have access to the best care available.

As a result of my own personal experience and our early, compelling results, I’m convinced that we as an industry can work together to truly change the way medicine is delivered and provide our patients with the highest quality, evidence-based care available.

References:
1. https://www.cdc.gov/chronicdisease/overview/index.htm
2. http://www.nejm.org/doi/full/10.1056/NEJMsa022615#t=article
3. https://www.ncbi.nlm.nih.gov/pubmed/28291892
4. http://www.who.int/social_determinants/sdh_definition/en/
5. https://www.chartisforum.com/wp-content/uploads/2017/05/The-Rural-Relevance-Study_2017.pdf
6. http://www.nejm.org/doi/full/10.1056/NEJMp1705348#t=article

The views, opinions and positions expressed within these guest posts are those of the author alone and do not represent those of Becker's Hospital Review/Becker's Healthcare. The accuracy, completeness and validity of any statements made within this article are not guaranteed. We accept no liability for any errors, omissions or representations. The copyright of this content belongs to the author and any liability with regards to infringement of intellectual property rights remains with them.

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