[{"@context":"https:\/\/schema.org\/","@type":"Article","@id":"https:\/\/share-dev.upmc.com\/2019\/06\/answers-for-today\/#Article","mainEntityOfPage":"https:\/\/share-dev.upmc.com\/2019\/06\/answers-for-today\/","headline":"Answers for Today \u2026 and a Platform for the Future","name":"Answers for Today \u2026 and a Platform for the Future","description":"Learn how UPMC is now expanding use of machine learning technology to lower readmission rates and improve patient outcomes in other hospitals. ","datePublished":"2019-06-05","dateModified":"2025-06-27","author":{"@type":"Organization","@id":"https:\/\/www.upmc.com\/","name":"UPMC","url":"https:\/\/www.upmc.com\/","sameAs":"https:\/\/share-dev.upmc.com\/upmc\/","parentOrganization":"UPMC"},"publisher":{"@type":"Organization","name":"UPMC HealthBeat","logo":{"@type":"ImageObject","@id":"https:\/\/share-dev.upmc.com\/wp-content\/uploads\/2019\/04\/UPMC-HealthBeat-Logo.png","url":"https:\/\/share-dev.upmc.com\/wp-content\/uploads\/2019\/04\/UPMC-HealthBeat-Logo.png","width":600,"height":60}},"image":{"@type":"ImageObject","@id":"https:\/\/share-dev.upmc.com\/wp-content\/uploads\/2019\/05\/upmc_next_machine_learning_3.jpg","url":"https:\/\/share-dev.upmc.com\/wp-content\/uploads\/2019\/05\/upmc_next_machine_learning_3.jpg","height":540,"width":1920},"url":"https:\/\/share-dev.upmc.com\/2019\/06\/answers-for-today\/","about":["Health Topics A-Z"],"wordCount":542,"articleBody":"UPMC\u2019s Health Services Division is harnessing machine learning for better day-to-day outcomes.It\u2019s not unusual for a leading-edge health care research organization like UPMC to invest in high-powered computers, a world-class data center, and a small army of statisticians and data scientists to study patient outcomes. What differentiates UPMC\u2019s approach to patient analytics is its use of data \u2014 not just for study, but for action that improves day-to-day patient outcomes, and not off in the future, but right now.One recent example is an analytics platform and a machine learning algorithm developed by UPMC\u2019s Clinical Analytics Department that gave doctors the information they needed to identify patients who were at the highest risk of being rehospitalized within seven days of discharge. This enabled them to reduce rehospitalizations by about 50 percent in the unit where the algorithm was piloted at UPMC Presbyterian.A million-case databaseThe project used health record data pulled from 1 million hospital discharges to design a proprietary algorithm that helps doctors identify patients at highest risk of rehospitalization within seven and 30 days of discharge. Built with advanced machine learning technology, the algorithm correlates patient clinical data with home location, social determinants of health, referring hospital, and other information. Armed with this tool, UPMC doctors have a better chance of spotting high-risk patients and arranging appropriate post-hospitalization follow-up care.After development and testing, the algorithm was approved for use within the UPMC system, beginning with a pilot program conducted last year in a UPMC Presbyterian cardiology unit. It features a computer \u201cdashboard\u201d that tracks current hospitalized patients, providing doctors a view of the entire patient population by unit, condition, and risk level. The risk level also is included in individual electronic medical records so doctors are aware of their patient\u2019s risk. \u201cWe can use our data to figure out which actions are associated with better outcomes,\u201d says project lead Oscar Marroquin, MD, chief clinical analytics officer, UPMC Health Services Division.Delivering better care \u2026 right now.Following the successful pilot, the program was expanded and is now being used by nearly half the hospitals in the UPMC system \u2014 a number that continues to grow as more doctors use the system to drive better outcomes every day. \u201cEvery large healthcare system claims to have a lot of data and analytical capabilities,\u201d says Dr. Marroquin. What\u2019s different about us \u2014 and perhaps a few other systems \u2014 is that unlike the majority who have built infrastructure mostly for research purposes, we have made the investment to have a team dedicated to delivering better care for our patients right now. Our goal is to be a learning health system, where we develop, train, test, and validate our models in the real world.\u201dOnly the beginningChris Carmody, senior vice president of UPMC Information Services, says UPMC is just beginning to tap the value of clinical analytics. \u201cThe genius of Dr. Marroquin is that his team takes very practical approaches to the data,\u201d he says. \u201cThey\u2019re not creating just one algorithm to solve one problem; they\u2019re creating a platform to solve many problems. The insights that he and his team are garnering are simply awesome.\u201dEditor's Note: This article was originally published on June 5, 2019, and was last reviewed on June 27, 2025."},{"@context":"https:\/\/schema.org\/","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"2019","item":"https:\/\/share-dev.upmc.com\/2019\/#breadcrumbitem"},{"@type":"ListItem","position":2,"name":"06","item":"https:\/\/share-dev.upmc.com\/2019\/\/06\/#breadcrumbitem"},{"@type":"ListItem","position":3,"name":"Answers for Today \u2026 and a Platform for the Future","item":"https:\/\/share-dev.upmc.com\/2019\/06\/answers-for-today\/#breadcrumbitem"}]}]