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Health systems are using data analytics to optimize patient care

With 2022 upon us, it feels like it’s the moment for the field of health care data analytics akin to the start of the development of the smartphone in the mid-2000s, says Christopher Bondy, a professor at Rochester Institute of Technology. 

“It feels like we will look back and ask, ‘How did we operate so primitively without health data?’ ” says Bondy, the program coordinator of the master’s program in health informatics at RIT and a visiting professor at the Golisano College of Computing and Information sciences. 

“Health informatics really is the collision of computer science and the emerging need for data for healthcare,” Bondy continues. “You can see, as we became more reliant as consumers and the health industry on data, we just need so many things related to data. Everything in the entire data supply chain is being reengineered around this notion of real time monitoring and feedback. The industry itself is in its infancy, maybe 10 years in the making.” 

The University of Rochester Medical Center has been investing in using data analytics to improve patient services and outcomes since at least 2015, says Dr. Judy Baumhauer, associate chair of academic affairs and a professor in the Department of Orthopaedics at UR.  

One of the main ways that UR Medicine has done so is by participating in the Patient-Reported Outcomes Measurement System (PROMIS) developed with National Institutes of Health (NIH) funding, says Baumhauer, who is the medical director of PROMIS for the UR Health Care System as well as current president of the national PROMIS Health Organization,  

According to the U.S. Department of Health and Human Services, PROMIS “is a set of person-centered measures that evaluates and monitors physical, mental, and social health in adults and children.” 

Baumhauer says that this data collection helps clinical care providers know how their treatments are working through feedback from patients so that healthcare resources can be allocated most appropriately to patients. 

“We only want patients to get better with the best outcomes,” Baumhauer says.  

Approximately 60 percent of the UR health system’s divisions and departments are participating in PROMIS, Baumhauer says. 

Patient-reported outcomes are questions that are asked of patients at every interval of care and responses directly populate into their electronic health records. 

One benefit of directly asking patients about their symptoms is that it eliminates bias from a clinician interpreting the data, Baumhauer says. 

The PROMIS databank has data from over 300,000 unique patients and over 5 to 6 million data points, according to Baumhauer. 

Patient-reported outcomes for physical function, for depression and for how pain interferes with their lives are tracked over time at every outpatient visit on iPads on which patients enter their answers to relevant questions. This measures how a treatment decision intersects with patient outcomes, Baumhauer says. 

Patients also can get a picture of their progress because the URMC-designed interface displays their pain, mood and function scores over time as line charts, Baumhauer says. 

“We’re doing it as site of service so that we can use that data to help us with the care during that visit,” Baumhauer says.  

When that data is aggregated, Baumhauer says that it can inform providers about what types of treatment are the best for patient outcomes. 

In a review of procedures done to “snug up” the ligaments of UR Medicine patients vulnerable to instability in their ankle and vulnerable to chronic ankle sprains, it was found that doing those procedures using fiber tape augmentation cost more but had the worst outcomes, Baumhauer says. When that data was presented to the orthopedic surgeons, it gave them an opportunity to change their care in a way that would benefit patients, she says. 

Baumhauer also says that there is a national trend for governmental payers like Medicaid and Medicare to evaluate patient-reported outcomes in terms of authorizing reimburse payments. 

“It’s a national trend for payment for quality, for just good patient care,” Baumhauer says. “I think it’s unstoppable.”  


The Finger Lakes Health system has been using data analytics to improve patient outcomes by participating in disease-specific programs for treating stroke and chest pain set out by the Joint Commission, which is an independent nonprofit that sets standards for measuring patient safety and quality, Dr. Matthew Talbott, chief of emergency medicine, says. 

Finer Lakes Health has a performance improvement team that collects data to help improve patient care and outcomes, Talbott says. 

“We are able to use the metrics that are reportable to our accrediting organizations and we create dashboards and continuously monitor the data monthly specific to chest pain and stroke,” Talbott says. 

The data is reviewed at departmental meetings focused on chest pain and strokes, Talbott says. 

Talbott notes that it takes a multidisciplinary team to improve patient outcomes; having emergency medical services, nurses, patient techs, pharmacists, diagnosticians, doctors, physicians assistants and nurse practitioners buy in to use data to improve patient outcomes is essential to ensure the best patient care possible. 

While Finger Lakes Health cannot provide catheter-directed therapy for strokes, it can do IV-based therapy, Talbott says. The goal is to start IV-based therapy within 60 minutes of a patient arriving to the emergency department, and the deployment of data analytics has ensured Finger Lakes Health is staying on top of meeting that goal, Talbott says. 

Finger Lakes Health also is participating in a Rochester region initiative to advance a system of care with patients facing the acute events of heart attacks and stroke, Talbott says. It’s part of a national effort launched by the American Heart Association called Mission Lifeline. 

Bondy says that one of the challenges for having data analytics benefit patient outcomes is how to optimize the work flow of data in health care. He notes that there is “small data” collected from individual patients from health devices like Fitbits and Apple Watches and there is “big data” generated from mammoth datasets because electronic health records are required by the federal government. 

Small data and big data is converging, and skilled employees are needed to visualize that data so patients can get a first-hand view of their own health data and how that data aggregates in comparison to other people with similar profiles, Bondy says. 

As part of this new wave, RIT is partnering with Rochester Regional Health in a clinical informatic fellowship program that trains physicians in data analysis as they earn a master’s in health informatics. 

“Imagine where that is going to take the contours of health care,” Bondy says. “We can focus on the right remedy at the right time.”  

Amaris Elliott-Engel is a Rochester-area freelance writer.  


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