Want to know how big data and personal stories can be used together to improve patient care? Follow this thread as we share the story of Dr. Suresh Bhavnani, his mother’s hip replacement and the unexpected connections found through visualizations like this one

Dr. Bhavnani, a biomedical informatics researcher @UTMB_PrevMed, is used to dealing with detailed medical data, spreadsheets full of numbers and complex statistics. However, when his mother fractured her hip a few years ago, the anonymous numbers suddenly became personal.

As his mother was generally healthy with well-controlled pre-existing conditions, Bhavnani did not think she would have any problems with her hip surgery, and she didn’t. The problems started after the operation while she was at a rehab facility.

When his mother ended up back in the hospital for nonsurgical reasons, he was concerned. For an older patient, to be readmitted within 30 days after a hip fracture surgery can mean increased risk of infection or death, as well as increased costs for patients and hospitals.

When she was discharged and readmitted two more times, Bhavnani knew he needed to figure out what was going wrong.

He knew that figuring out which subgroup of patient are at a higher risk of readmission could help doctors and nurses design better recovery treatment plans. However, current models of risk assessment are not designed to provide such insights, he said.

So Bhavnani partnered with physicians, rehabilitation specialists, nurses, and data scientists to look at his mother’s case as well as data from more than 33,000 other patients with hip fractures.

“It turns out that my mom’s readmission experience is not unique,” Bhavnani said.

Using Bhavnani’s visual analytical method, the team was able to identify subgroups of patients with hip fractures who shared pre-existing conditions - renal failure, diabetes, arrhythmia - and mapped combinations of conditions that could lead to a higher risk of readmissions

“A hip fracture patient with renal failure or diabetes has a certain risk for readmission but if you combine that with another condition such as congestive heart failure, stroke, COPD, the risk jumps up,” Bhavnani said.

In a paper published in @jmirpub Medical Informatics, the team was able to show how a combination of certain pre-existing conditions could make an otherwise healthy person become a higher risk patient needing specialized care https://medinform.jmir.org/2020/10/e13567/ 

Bhavnani observed this firsthand when his mother was at the rehab unit, which focused mainly on making sure her surgical wound was healing and getting her back on her feet through physical therapy.

However, due to the new surroundings, medications, and unfamiliar diet, her prior conditions were exacerbated, landing her back in the hospital, Bhavnani said.

But by knowing which high-risk pre-existing conditions interact and affect a patient’s risk of readmission, health care providers could be better prepared and better treat their patients after a hip fracture surgery

The research team was also able to come up with some seemingly simple and practical solutions. Discharge notes and order sets could be designed to alert a physician if a patient has pre-existing conditions that would make a patient have a higher risk.

By visualizing the data and finding connections unnoticed before, Bhavnani and team could help patients stay out of the hospital and allow doctors, nurses and therapists fine tune the care they provide. Read more here https://www.utmb.edu/newsroom/article13588.aspx

Bhavnani's mother was able to recover from her hip surgery and her experience, combined with data from thousands of other patients, will, hopefully, help improve care for others. Bhavnani, meanwhile, continues to look for connections hidden in the tangles of complex data.

Bhavnani is now looking at how pre-existing conditions interact to increase the risk in older patients with COVID-19. More to come on that when the research is done. You can learn more about his Team-Centered Informatics approach here

And for more about Bhavnani and his Discovery and Innovations through Visual Analytics Laboratory (DIVA Lab), go to http://www.skbhavnani.com/DIVA/contact.html