It is estimated that medical knowledge is now doubling every few months. Perhaps AI will eventually save us from this accelerating information avalanche. In the meantime, clinicians are tasked with knowing everything from continuously evolving professional society guidelines to how a patient’s genetic markers translate into adjusting medication dosing.
It’s no wonder that in this increasingly complex and expensive healthcare environment, the focus on reducing clinical variation and enhancing patient outcomes has never been more important. Yet, the tools we regularly deploy in our pursuit of these goals, such as the electronic health record systems (EHR) and specifically, order sets, often go unexamined for efficiency and effectiveness. As a clinician and CEO deeply entrenched in the healthcare technology landscape, I've seen firsthand how these tools, when curated and adopted appropriately, can dramatically move patient care for the better.
The average Phrase Health partner has about 700 order sets. This is a testament to the complexity and breadth of modern medical care, but also how content within the EHR continuously accumulates over time. In essence, IT and informatics teams “close the ticket” after building a new EHR intervention and then move onto the next ticket. Ultimately, the challenge with managing a large library of electronic content lies in the methodical, data-driven review of its messaging and performance. Without it, labs, medications, and other orders will almost certainly push clinicians towards decisions that are not only wasteful but potentially inappropriate.
The economic implications of lab supplies weren’t discussed in medical school. However, we did learn about the downstream emotional and financial toll of unnecessary tests. The chain reaction from a single false positive result exemplifies the downstream impacts that can go unnoticed: a cascade of further testing and procedures, a longer length of stay, heightened patient anxiety, and more. The reality is that every test ordered, whether needed or not, carries a cost that often goes well beyond the one test in question.
The ongoing evolution of medical guidelines necessitates regular reviews of order sets (and really any protocolized ordering tool or nudge) to ensure compliance and relevancy. Beyond regulatory adherence, there's a tangible opportunity to pinpoint cost-drivers inherent to these tools. Take, for instance, a partner organization that uncovered an opportunity to reduce wasteful lab ordering for pneumonia patients by over $700,000. It’s also worth noting that this accounted only for direct lab supply costs and not any downstream costs. This discovery came from a diligent, data-oriented review of protocolized orders, highlighting the substantial financial implications of unoptimized ordering workflows that nudge specific behaviors.
Despite the clear need for rigorous review, the reality is that the majority of healthcare institutions find themselves under-resourced to undertake such a monumental task for all “knowledge” built into the EHR. I've engaged with hundreds of organizations, each echoing a similar sentiment: there's a profound gap between the necessity for comprehensive EHR tool analysis and the available staffing to execute it in an effective way. This is where technology steps in to bridge the divide.
Tools like Phrase Health are at the forefront of automating and streamlining the review process, enabling healthcare providers to uncover potential savings while elevating the standard of patient care. By deploying advanced analytics and leveraging the power of automation, technology can support organizations struggling to keep pace with the demands of modern healthcare.
The journey towards reducing clinical variation and enhancing patient outcomes is multifaceted, requiring a deep dive into the tools that shape daily medical decisions. The examination of EHR tools, particularly order sets, is not just a matter of regulatory compliance or financial savings; it's a fundamental component of providing high-quality and patient-centered care.
I’m a firm believer that the keys to successful execution of this informatics and quality domain relies on people, process, and technology. As long as this is an institutional priority and framework in place to achieve more robust EHR content evaluations, then technologies like Phrase Health can catalyze the execution by allowing teams to do more with less. Organizations that dedicate the resources to this work will not only unlock potential savings but also, and more importantly, ensure that our patients receive the best care possible.
If you’d like to read the case study mentioned above, you can access it here or reach out to me directly!