Introduction
Patients’ adherence to medications sharply declines as the number of prescribed medications increases. Specifically, adherence begins to decline once patients are prescribed five medications, a pattern that has consistently been observed in numerous studies. Why then, would we ever recommend that physicians prescribe a complicated guideline-directed medical therapy (GDMT) regimen involving more than five medications to their patients? Traditionally, healthcare in the United States has been guided by a philosophy of maximization, encouraging physicians to prescribe the maximum number of medications and services. However, this approach disregards important factors such as patient preferences, needs, behaviors, and the desire to maintain normalcy in everyday life. Consequently, it's no surprise that only 7% of heart failure patients adhere to their GDMT.
The problem does not stem from physicians not doing enough or patients not wanting to be better. Rather, it underscores the need for a shift in thinking towards an optimization approach in healthcare, rather than a maximization approach. Such a shift would mean considering all of the cognitive, physiological, and financial influences and constraints that affect patients' adherence to medication, and ultimately lead to better health outcomes in the long run.
Emerging technologies offer promising solutions to reconcile these factors and perspectives with physicians' medical expertise and intuition, making it possible for physicians to tailor their GDMT regimens to individual patient needs. In other words, making a meaningful change in healthcare will not solely arise from increased physician education or awareness of new therapies, but will require solutions that integrate the natural constraints of everyday life and patient preferences into clinical decision-making processes — making recommendations that are not only effective but also likely to last.
Maximization philosophy
The maximization philosophy is characterized by an "all-in" approach to healthcare. It involves treatment strategies that involve prescribing numerous medications, ordering extensive diagnostic tests, recommending specialist consultations, and generally, reacting to health issues as they arise rather than proactively identifying and addressing underlying risk factors and taking preventive measures. Most healthcare systems and payment structures incentivize high-volume care by rewarding healthcare providers based on the number of procedures performed, tests ordered, or patients seen, rather than the quality or outcomes of care delivered.
An optimization approach
The call for optimization in healthcare is not a call for compromise but a shift in focus to the quality or outcomes of care delivered. Optimization seeks to achieve the best possible outcomes within these constraints, ensuring that care is not only effective but also accessible and equitable.
Technology to support the shift toward an optimization approach
In clinical practice, the cognitive, physiological, and financial constraints mentioned above make it really difficult for physicians to do the right thing, even when they know what the right thing to do is. This is where the promise of digital medicine comes in. When we talk to our cardiology friends, they often grasp these methods intuitively and are capable of evaluating many clinical factors at once; however, it is difficult to aggregate that intuition and test whether, in fact, it is correct. Are physicians intuitively prescribing the right medications in the right combinations, and in the right sequences? The rise of real-world evidence (RWE) and sophisticated mathematical modeling now allows for the empirical assessment of these approaches. This advancement can provide physicians with a whole new set of tools over the next 5-10 years, to fully integrate advanced scientific evidence into care decisions.
The nimbleness required to move with the RWE that is being generated in every moment of every day
Medical guidelines are notoriously slow to be adopted in clinical practice. In fact, it is not uncommon for new evidence from clinical trials to be delayed by a full 17 years before it becomes the new “norm.” Medical societies are learning to leverage their technology partners to achieve the nimbleness required to close this gap between evidence and practice. However, one of the things to be cautionary about when it comes to clinical decision support (CDS) is that it is not enough to point out to physicians that they haven’t done the right thing — especially as they are already bumping into constraints. Rather than saying, “you’re missing these 3 GDMT,” effective technology solutions must be able to also say, “ this is the one that is going to have the most impact for your patient — and by the way, it is the one they can afford.” Until CDS systems can do this, they are only infuriating physicians and contributing to burnout.
The path forward
We need to take a step back and design systems around what we are trying to accomplish in healthcare, which is ultimately, the best wellbeing for each individual patient. This includes considering their cognitive, physiological, and financial constraints. Currently, much of the medical field is focused on maximization, striving to do everything possible for each patient. The path forward should recognize the actual, determinative realities of real human beings making real choices.
Authored by
Cassandra Broadwin, MPH, Rajesh Dash, MD, PhD
This article is inspired by a Beyond the Chart podcast conversation with Brendan Mullen.
