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Paul Mullen

Addressing the standardization vs. personalization healthcare paradox in acute care

An editorial by Paul Mullen, general manager of GE Healthcare Acute Care

There's a lot of hype today about precision health. From my perspective, it provides a data-driven resolution of the paradox between following the standards of population health and personalizing care to each patient. And some promising work is being done in this area.

Some health care is already personalized. In the United States, women at risk of breast cancer, for example, are screened differently than the rest of the population. But all too often, clinicians have only their own clinical impressions to rely on to personalize a patient's care. Nowhere is this more evident than in treating sepsis.
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In U.S. hospitals, sepsis is the leading cause of death, the number one cost of hospitalization and the top reason for readmissions. If caught early, sepsis can be resolved in a low drama way, with low impact to the patient. But sepsis in its early stages is hard to spot because it often looks like something else. So, caregivers might either wait until it becomes a serious, potentially life-threatening problem, or they might treat without evidence that treatment is needed.

But it's a tough trade-off. Early intervention can be costly if it’s an intervention based on a misdiagnosis. Then there’s the matter of irresponsible stewardship of clinically precious antibiotics that must be used prudently to prevent the rise of untreatable superbugs.

Caregivers must rely on their instincts and their recognition of familiar patterns, while being held accountable to both accepted standards and the expectations of a patient's family, which are often at odds.

Precision health arms caregivers with data-driven insights that help them make personalized care decisions in a standardized way. It informs caregivers about both the cause of a patient’s illness and the patient's likely response to that cause. It frees them from the burden of digging for critical insights, so they can focus on clinical reasoning. It guides their care outside of the guidelines in a prescribed manner.

In the fight against sepsis, for example, GE Healthcare and Roche Diagnostics are working to combine in vivo information, including imaging and vital signs, and in vitro data, such as blood tests and molecular diagnostics, with Artificial Intelligence.

The vision is to help clinicians achieve a more precise, personal and holistic view of every patient.

Early application of basic data science techniques, for example, has enabled the replication of common sepsis predictors, like the SOFA Score and MEWS. As this science matures, these scores will likely be obtained earlier and with greater precision.
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