Published in Circulation: Heart Failure, a recent study conducted by Northwestern Medicine researchers found that adding social determinants of health (SDOH) data into machine learning models led to less bias when predicting outcomes for heart failure patients. Healthcare bias can lead to detrimental outcomes for patients. For example, in April, a study published in PLOS digital health found that digital health…
During the pandemic, health care providers and institutions ramped up innovative, sustainable and increasingly digital ways to improve population health outcomes, and I expect this trend to continue. For over 20 years, I’ve advised health care provider teams across the U.S. on leveraging and incorporating digital technology and tools like patient portals, health trackers and…
When I graduated from medical school and took the Hippocratic Oath, I vowed to not just treat the illness on a patient’s medical history form but to treat the person behind the diagnosis. To do this well, clinicians need to understand the whole person and the context in which they live — their race, gender…
DOWNLOAD SLIDES The CDC reports that 6 in 10 adults in the US have a chronic disease and 4 in 10 have two or more. With the prevalence of chronic diseases in mind, it’s no surprise that they are the leading driver for the nation’s $3.8 trillion in annual healthcare costs, and the diabetic population…
Many healthcare systems have made creating high-quality and value-based care a top priority. Southwestern Health Resources (SWHR) used clinical data and predictive analytics to put a total cost of care plan in place to provide affordable and quality care to thousands of patients in North Texas and cost-effective care for their employers. Oftentimes in the healthcare market, purchasers…
The pace of change in the healthcare industry is accelerating with new therapies promising cures to previously debilitating or deadly diseases. Aging populations, and public health crises, such as addiction to opioids, are putting pressure on provider workloads and increasing patient safety risk and negatively affecting patient experience. Healthcare providers must rise to the challenges…
Machine learning is getting better at predicting things. There are now algorithms that improve the detection of diabetic retinopathy, predict the onset of sepsis, and help determine a critically ill patient’s risk of dying. But a piece of wisdom from Warren Buffet comes to mind: “Predicting rain doesn’t matter. Building arks does.” Even the most…
There is increased recognition for better methods to measure, predict and adjust for social risk factors in healthcare and population health. Current performance and quality measures generally do not take SRFs into account in the bonus/penalty structure, nor are SRFs generally included in most risk adjustment formulas. This can lead to unintended consequences, including the…
Imagine the future when you go to your doctor to be treated for some sort of ailment. After collecting and entering key data into an app, she’s presented with a clinical diagnosis and optimal course of treatment, including the correct medications. While she’s there to talk “human-to-human” to the patient, it’s a predictive model and…
Humans have been interested in artificial intelligence for as long as you or I can remember. If you’re a science fiction fan you’ll have seen it in both good (i.e. Star Trek’s Lt. Commander Data and Star Wars’ C3P0) and bad forms (i.e. The Terminator or Hal 9000 from 2001 – A Space Odyssey) since the 1980s. Suffice to say, we’re still…