We need a new health outcomes equation
For as long as there have been humans, there has been an understanding of why people become ill, and how to help them. I imagine the earliest man to have known the basics: fire = burns, falling from a tree = injury, snow or ice = reduced swelling. The very young and the very old are generally more susceptible to illness and injury. Prevention is more effective than treatment.
We didn’t always get it right. We attributed illness and disease to supernatural causes. Then, for a while, we considered the four humours responsible for most illnesses. We would alter the temperature of the diet, give laxatives, or drain the patient’s blood to restore balance to the humours.
As our understanding of disease grew, we realized a familial tendency toward some illnesses. That certain attributes like weight could impact disease outcomes. That how and where we lived could make us more likely to become ill. And yet, when diseases like plague would tear through a community, it often seemed like all humans were equally insignificant in the face of death.
Germ theory, development of inoculations, the discovery of antibiotics, and similar advancements in science increased our understanding of disease. We began to stratify patients by their likelihood of becoming ill or recovering from disease. We identified hereditary conditions. We calculated the risk of exposure to caustic agents.
For centuries, we considered the likelihood of a patient having a good health outcome to be based on their intrinsic health status and the things happening to them, both harmful and protective. The equation was:
(entity) + (threats or threat mitigation) = outcome
In more modern medical development, we have begun to understand that a third element significantly impacts the outcome equation. Often, these are hidden or difficult to quantify influences in a patient’s life, that increase a patient’s risk of a poor outcome. The vulnerability factor. This includes vulnerabilities like lifestyle choices, activity level, and the environment as well as those under the broader umbrella of Social Determinants of Health (SDOH)—health literacy, access to secure nutritious food sources, social supports and connectedness. Now we view the health outcome equation as:
(vulnerability) + (entity) + (threats or threat mitigation) = outcome
I call it the VETO model.
And what’s intriguing to me as a physician is the way this model begins to redefine patient care.
A patient’s genetic risk factors and health history are not modifiable.
Decreasing threats or increasing threat mitigation can only go so far, and only some threats are not able to be mitigated.
But, by addressing vulnerability, we are significantly influencing outcomes.
This is why I have devoted myself to using the Jvion CORE™ to accurately predict patient and community level vulnerability, so that providers, health care organizations, and payors can take meaningful action to improve outcomes.
Before developing vulnerability predictions in the Jvion CORE, my time in practice was filled with tools like LACE and Braden. These tools attempted to risk stratify patients and predict outcomes. And in some cases, they can do it well—the tools are accurate in stratifying patients in the likelihood of a poor outcome.
The problem though is that these tools focused on the (entity) and (threat and threat mitigation) factors of the outcome equation while ignoring the (vulnerability) factor.
Take the LACE tool. This simple, quick calculation is accurate in predicting who is at highest risk for readmission. But the tool uses (entity) characteristics like the length of stay, history or disease, and entry point into the hospital to risk stratify the patient. These are non-modifiable characteristics. So,
while accurately risk stratifying the patient, the tool doesn’t help clinicians identify actions that can impact the drivers of risk.
The Braden Score has a similar problem. The tool focuses on the (threats and threat mitigation) factor of the outcome equation: activity and mobility level, moisture, and friction with (entity) factors: nutrition and sensation. There is no opportunity to address the (vulnerability) factor.
Jvion’s CORE creates predictions that include all three factors. By incorporating (vulnerability), we have incorporated the most modifiable and impactful drivers of poor outcomes. The insights we provide aren’t just about risk, they are about risk mitigation and reduction.