Four Humours and the 'humor of it'
Black bile, yellow bile, blood, and phlegm. Hippocrates believed that all disease was the direct result of an imbalance of these four liquids, or humours. Diagnosing an illness required assessing which humour was out of balance, and treatment focused on restoring equilibrium by adjusting diet, lifestyle, or completely removing the out-of-balance humour from the body.
His scientific observation notwithstanding, Hippocrates had only part of the picture. Though he came to the correct conclusion that illness had natural causes, he incorrectly believed the cause to be generalized and the result of one of four fluid variables.
Even with modern day advances in medicine where successful treatment begins with understanding the individual patient, current practices still hold sacred a ‘one size fits all’ approach to many branches of healthcare. Many chronic diseases are diagnosed with a single blood test or a simple physical exam. These methods might diagnose a majority of the demographic, but it also leaves a sizable pool of undiagnosed individuals who simply do not fit into the preconceived mold of disease.
With Artificial Intelligence, we can reimagine health.
Artificial Intelligence (AI) in healthcare is the use of complex algorithms to emulate human cognition in the analysis, interpretation, and comprehension of medical and healthcare data. The rise of complex data in healthcare means that artificial intelligence (AI) can and WILL increasingly be applied to augment human ingenuity in transforming healthcare. We have an opportunity to dramatically advance broad-based health by improving diagnosis and interventions, uncovering and mitigating latent risk, optimizing healthcare investments, and streamlining patient experiences.
Dare to end the cost curve by addressing the hidden ‘rising-risk’ pool of patients.
While effective management of high-risk patients is the universal starting point for cost containment, the basis remains in reducing cost by minimizing utilization of costly services. The strategy, however, ignores a large population of rising-risk patients that represent the greatest opportunity for improving the health and cost curves. Typically, 35% of the population is the hidden rising-risk pool, and each year 18% of the rising-risk members escalate to the high-risk category when not managed.
Complex chronic diseases are healthcare’s hidden rising-risk! Chronic diseases such as heart disease, kidney disease, and diabetes are the leading causes of death and disability around the United States and around the globe, and according to preliminary studies, AI could be the key to catching these illnesses years in advance.
To successfully manage this emerging challenge, healthcare leaders will need a better understanding of the intricate care needs associated with complex chronic diseases. Identifying rising-risk patients must be the focus. With AI, we are able to look for insights that improve our overall knowledge of complexity and multi-morbidity, and the potential implications on cost in combination with other health resources. Diagnosis and prediction of the rising-risk cohort is a major opportunity area for identifying potential or hidden detrimental symptoms associated with complex chronic diseases. Early detection and onset prediction allows for a timely and efficient care approach. These insights provide healthcare leaders with a never-before-seen scope to optimize outlays towards enhancing care experience, and most importantly – stay ahead of the cost curve.
Public and & workforce health is under the microscope now, and will be central to policy planning in the coming years. A global argument towards more sustainable economic models promoting health and welfare is gaining traction.