These days, it seems like most of us can broadly agree on how healthcare needs to fundamentally change.
Basic shifts like rewarding early detection and prevention, the use of data analytics to reduce risk/generate value and avoiding costly, unnecessary events like hospital acquired infections and readmissions. A countless amount of companies, CMS reforms, provider initiatives and yes, blogs, have targeted these issues and others as part of the collective war on the 20th century healthcare system. But why is it so hard to change? And how can we make this change go faster?
Now, more than ever, information is the currency that can lead to success or failure in our industry. The right information at the right time with the right patient can sometimes mean the difference between life and death1 and is critical if we are going to achieve the holy grail of lower costs and better outcomes for all.
If information is the currency, then the patient must be the consumer – seamlessly navigating the system with their preferences in mind and receiving the best care simply as a result of market forces. So, how do we empower the systems, patients and the hard working clinicians to deliver the best care armed with the best information? We thought that the easy answer was the digitalization of health records and the cascade of change that would result soon after. But, as even CMS is keenly aware, “At present, evidence on EHR benefits in either improving quality of care or reducing health care costs is mixed. This is not surprising since the adoption of EHR as a fully functioning part of medical practice is still in its infancy.”2 At the same time, medicine is only becoming more complex – in a good way. The world’s scientists and clinicians are understanding human health and disease more and more each day, adding exponential layers to the universe of captured knowledge. We have been trying for years to bring those latest developments to the point of care – good intentions, but met with limited success.
How can we tackle these constraints (and others) while injecting more value into a naturally imperfect product? How can we encourage creativity for the clinician and freedom for the patient in the age of “checking boxes” for quality and performance metrics?
For one, we can build a comprehensive, adaptive and scalable information network with an initial focus on concrete clinical elements that are universal and easily understandable such as identification of medical errors and clinical gaps in care that result from a lack of information exchange, chronic care management and universal preventive measures like screenings, vaccinations and annual wellness visits. From there, we can build more sophisticated functions that are scalable and accessible that will aid the system to catch up to its full technological potential3.
Going forward, it is critically important that CMS and other public entities continue to lead by trial and error. Uncle Sam is the only dominant player that has the resources and wherewithal to fail and learn continuously. But, as John Halamka has observed4, the information groundwork laid by the Fed is nearly complete and the private sector must now emerge and continue the work of building a sustainable system. With the entire tech industry ablaze with the promise of artificial intelligence, including machine learning and natural language processing, it is imperative that we consider these tools for relevant functions such as precision coding, patient empanelment and most importantly, to assist the wondrous work that case managers and care coordinators are doing with their patients.
Our current technological advancement provides the capability to operationalize incentives and adapt to the natural variations that occur constantly over the course of patient care. But first, we need to learn how to leverage the data we already have while being more interconnected and to sort through large datasets very fast, without missing critical information. Once this information network gains momentum, we can build a system that is: accountable, transparent and patient centered with less medical errors and bankruptcies. We can then apply learnings from big data using evidence based guidelines to lower costs, streamline provider workflows and improve patient outcomes.
This won’t happen overnight, but we have reached a point5 where these initiatives have never seemed more possible. Let’s pessimistically observe all that is wrong while optimistically knowing that we can actually clean up the mess.
1 https://blogs.scientificamerican.com/guest-blog/the-real-cause-of-deadly-medical-errors/
2 MACRA proposed rule: https://s3.amazonaws.com/public-inspection.federalregister.gov/2016-10032.pdf
4 http://geekdoctor.blogspot.com/2016/07/do-we-need-more-or-less-healthcare-it.html
