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Innovaccer Launches Perioperative Optimization Platform for Surgeons

by Jasmine Pennic 08/18/2020 Leave a Comment

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Innovaccer Launches Perioperative Optimization Platform for Surgeons

What You Should Know:

– Innovaccer launches a perioperative optimization solution for surgeons to realize clinical and financial goals with patient-risk analysis.

– The solution redefines surgical planning and post-surgical recovery with machine learning-based patient stratification for optimized surgery experience and personalized patient care management.


Innovaccer, Inc., a San Francisco, CA-based healthcare technology company, recently launched its perioperative optimization solution for health systems. The solution optimizes surgeries and ramps up volumes by identifying high-risk patients for pre-surgical intervention while reducing the length of stay, readmissions, and cost. The solution uses advanced analytics and machine learning-based algorithms to proactively identify patients at greater risk for post-surgical complications. Patients are then referred to the pre-surgical optimization clinic for pre-surgical strategies which are personalized for individual patients and specifically designed to minimize post-surgical complications.

Impact of COVID-19 on Elective Surgeries, Non-Essential Medical Care

COVID-19 has challenged traditional healthcare delivery systems and caused the postponement of elective surgeries and other non-essential medical care. As patients wait for their surgeries, it is likely their conditions could deteriorate and/or patients would return to clinics during a pandemic surge. Health systems will need to be prepared to address the potential for more complicated patient health conditions with careful risk assessment.

Pre-Surgical Optimization Platform Features

Innovaccer’s “Pre-Surgical Optimization” solution guides patient prioritization based on an algorithm that factors medical history, patient demographics, allergies, chronic conditions, history, and social determinants of health. Based on the previous data on these patients from the electronic medical record, claims, and the individual’s risk factors, the algorithm estimates the future cost of care for the patient. The algorithm also assigns patients to appropriate case managers using a smart rule engine that assesses a variety of factors including the number of appointments, and the surgeon’s expertise to map the patient to the provider. This approach helps hospitals identify high-risk patients and focus on the patients that will benefit most from pre-surgical interventions. 

Return on Investment Model for Healthcare Organizations

Innovaccer has also incorporated a refined return on investment model designed to make the optimization process revenue positive for healthcare organizations. The three key pillars of the exclusive model are sensitivity analysis tools, deep data insights, and performance analytics. Using this solution, hospitals can track their return on investment in real-time on a customizable dashboard with metrics including reduced readmissions, reduced length of stay, and emergency department visits with their associated costs. 

“With about 28 million surgeries canceled worldwide, non-COVID medical care has suffered tremendously. Canceled elective surgeries have impacted patient health conditions and the economic sustainability of health systems,” says Abhinav Shashank, CEO and Co-founder of Innovaccer. “As health systems plan to resume surgical procedures, care managers will need to engage the patient remotely for pre-surgical interventions. Our solution is created to redefine the entire process of optimizing surgery planning and to become more patient-centered and adaptable to the changing care environment. We want to ensure exemplary pre-optimization and post-discharge engagement to reduce readmissions and improve the hospital’s financial impact using the pre-surgical optimization process.”

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Tagged With: algorithms, care management, electronic medical record, Health Systems, healthcare delivery, healthcare technology, Innovaccer, Machine Learning, model, Patient Care, patient stratification, risk, SAN FRANCISCO, Social Determinants of Health, Surgery Platform

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