As it’s been made clear time and time again, there is no easy fix for increasing value in healthcare, which is measured by improved quality of care and lowered costs. In our industry, bottlenecks and constraints are everywhere, driven by mixed incentives over diverse regions in a highly regulated, human centered and excessively variable industry.
Even for industry leaders, there remains a lot of work to be done. With the release of recent regulatory reforms, it seems that clinicians will have more flexibility in optimizing their work flow. On the health IT side, we refer to this work as part of EHR+ or The Post EHR Innovation Era.
The cascade of events after the ACA went into effect is an interesting case study of how highly impactful legislation has informed the overall, day to day behavior of its biggest constituents over a relatively short period of time. It is an absolute understatement to claim that the ACA was the single most important factor in the lightning speed of EHR adoption nationwide. And this very jump to light speed has dropped us here, where we are now actively reevaluating what the exchange of health information entails, how it should be paid for, and its respective place in the health care universe. Due to the outsize role healthcare plays in each of our lives coupled with the perpetually accelerating advancement of digital technology everywhere, there are technically, billions of ways to make it all better: delivery, cost, outcomes, social determinants, financial sustainability, etc.
Now that we are all technically “online” and “leveraging data to improve care” using a first, second or even third iteration of EHR and associated systems, the most innovative healthcare systems in the country are using every framework under the sun to stay ahead. An interesting idea is that those that see success of any innovation across a diagnosis group or a service line are trying to automate those approaches over a multiplier i.e., if that new intervention or process worked well, let’s tweak it a little bit and try it over multiple cohorts with minimal deployment or significant workflow changes. In a controlled environment, an advanced learning system on the back end should constantly improve delivery in incremental yet exponential ways. As Nick Marko of Geisinger Health System has stated, “So it’s not just, what one answer can I get to one question based on meta-analysis, but, how can I do this all the time?” This is the sign of the age of EHR+.
So what does EHR+ involve exactly? It combines a few elements. First are analytics that embody the highest standard of clinical algorithms and knowledge to build a holistic portrait of the patient at multiple touch points within the healthcare system. Second, these insights need to be completely informed – incorporating every available and relevant data point to provide a personalized level of care. And third, this human and machine intelligence must follow and be interactive with the patient beyond their initial encounters to maintain their health and keep them out of the hospital. Only these types of initiatives will significantly improve outcomes and lower costs over the long term.
Marrying machine learning with the practice of medicine can produce exceptional value for the healthcare provider and the patient. However, this requires bringing together a cascade of reliable and executable components to help providers embrace value through intelligent informatics. We believe that the key to this feat is a nuanced combination of human insights on one side and learning technology on the other, coupled with an underlying understanding that results are only as significant as the time, place and context of an application. In the EHR+ era, this careful balance requires deep domain expertise in both medicine and engineering – something that few companies today are doing very well.
Everyone wants clinicians to execute on a patient risk score, not just visualize it. We want to improve the clinical encounter, not just be present within it. And we want to be purveyors of knowledge so that every clinician can deliver the best clinical results and financial performance.
These are a few of the “hard solvables” within the new era of EHR+ that must be alleviated to turn individual longitudinal data into personalized clinical assessments for each and every patient. The goal of the healthcare industry is and will continue to be improving clinical, operational, and regulatory efficiencies both on the front lines and in the executive board rooms. With EHR+, we are now ready to move this goal from aspiration to realization.