Andrew Johnson is CTO for AIMed with responsibility for database management, web development along with client management. A highly experienced publishing executive with a passion for technology.
Founded in 2016, the Center for Perioperative Intelligence, in the Department of General Anesthesiology of Cleveland Clinic, has a mission to advance surgical patient management by utilizing real-time data and analytics to provide value-based, high quality and efficient care.
Intraoperative mortality (deaths occurring during surgeries) have reduced significantly over the past decades but postoperative morbidity (medical conditions occurring during, relating to or denoting the period following a surgical operation) remains high. While there are many models in the market predicting complications, the fact that they were built using only data from electronic health records (EHRs) limit their accuracy and generalizability.
In addition, traditional medicine only takes action when a medical episode begins and efficacy of new interventions tend to be assessed via randomized control trials. Yet, in the real-world setting, treatment success is determined at patient level.
However, Dr. Kamal Maheshwari, the Center’s Director believes technology can turn a reactive care management system into a proactive one to prevent harm occuring in the first place. Thus, the Center is able to establish a synergy between healthcare providers, tech vendors, and patients; combining EHRs and the best available evidence to provide real-time decision support that accounts for the patient level differences. This empowers physicians with crucial knowledge including; which patients would benefit most from surgeries, when surgeries should be performed and what anaesthetic technique and perioperative pathway will be most effective for each patient.
“This is a new area which I feel gets left out in a lot of discussions when we are talking about care of surgical patients,” says Dr. Maheshwari. “When a patient undergoes surgery, we are not just talking about when they were in the hospital but before and after their stay too.”
Right now, the Center is leveraging big data and AI to address three key areas: Identification of at-risk patients; early detection of complications, and offering timely and targeted treatment. “AI helps guide appropriate and effective treatment decisions for a patient, realizing the goal of precision medicine,” Dr. Maheshwari wrote in a commentary published in the Journal of Clinical Monitoring and Computing.
For example, in a pilot study involving 7000 colorectal surgery patients, the Center accumulated resources and information across Cleveland Clinic to establish a platform which categorizes patients into nine groups based on their principal diagnosis; surgical approach; readmission rate; healthcare cost; IV fluid management, and the use of Ketorolac, a form of pain relief. Clinicians are then able to analyze and compare these statistics at the click of a button.
According to Dr. Maheshwari, they found that patients given Ketorolac and less than two litres of IV fluid had more favorable outcomes, lower healthcare cost and fewer complications. It also became apparent that patients with other pre-existing conditions like diabetes or emergency surgery status, rectal resection and those given more than three litres of IV fluid were most likely to be re-admitted and clearly warranted further attention.
“What we are doing is going into the very leading indicators at a physiology level so if required, we can immediately change something in patient management,” explains Dr. Maheshwari. “The ability to show clinicians the information right away on whatever questions they have, is vital. Backing every statement that you are making with hard data – that’s the real value going forward.”