Healthcare data analytics instructor, marking first year, says blend of multiple focal points are differentiator for new program
When Nicole Danaher-Garcia was studying dolphin behavior during her doctoral studies in biology, little did she know it would be the perfect foundation for what she’s doing today – a fulltime faculty member of healthcare data analytics at the MGH Institute.
“Dolphin behavior is very unusual,” said Danaher-Garcia. “So, you need to have pretty complex statistics and modeling to accurately analyze it and understand their relationships.”
Along the coast of the Bahamian island of Bimini, Danaher-Garcia and her team studied the movements and sounds of Atlantic spotted dolphins for five years. Because none of the graduate courses she took prepared her to deal with unusual behavioral data, Danaher-Garcia says she taught herself.
“I look at who spends time with whom, what kind of interactions they have,” explained Danaher-Garcia. “What postures they exchange, what body contact they have.”
Her team discovered that two large groups of dolphins once separated by 100 miles actually came together and formed new friendships, a rarity in a world where territoriality and the fight for resources are king. The published findings caught the attention of media outlets like the New York Times, Science and Newsweek. Today, Danaher-Garcia is marking her first year as an Assistant Professor of Healthcare Data Analytics in the School of Healthcare Leadership. She finds a number of correlations between dolphins and what she teaches.
“There are a lot of assumptions in statistics that observations are independent,” she said. “And obviously, if individuals are interacting with each other, they're no longer independent. Their behaviors depend on the individuals around them. So, there are more complicated statistical models that deal with that. A lot of students are going to be looking at behaviors, learning outcomes, and issues that don’t fulfill many statistical assumptions.”
Danaher-Garcia has developed and is teaching three technical courses in the Master of Healthcare Data Analytics program, which began in September 2022. She sees her students thinking more critically, framing things in a more quantitative way, and not getting stuck when they hit obstacles.
“If they’re working on an assignment and it's something that wasn't explicitly taught in the textbook, they can still figure out, ‘How do I work around this problem?’” says Danaher-Garcia. “The great thing about data analytics is that there's no one right way to get to the solution.”
The beauty of the Healthcare Data Analytics program, she notes, is the blend of technical, leadership, interprofessionalism, and ethics courses – the very areas a healthcare system rests on.
“It’s not just, you are handed data. You have to work with the team to figure out what data need to be collected,” she says. “And then they need to understand why they're collecting it. Once you have results, you have to understand how to communicate back to them so that they can make effective decisions. So, it's the merger of the two sides. The technical and non-technical are what make our program specific to healthcare data analytics.”
Dr. Shuhan He says the program is lucky to have someone with Danaher-Garcia’s skills and expertise.
“Nicole’s background is in network analysis – looking at how people communicate - which is a really interesting technique,” said Dr. He, the program’s director. “It's an advanced-data analyst technique that really gives you interesting insights to multiple pieces of data. Our faculty are actually world class in being able to apply this to healthcare, very specialized in not just data science, not just data analytics, but that we're doing this with a healthcare lens which is so important. Our faculty understand how this is being applied to healthcare, which is really critical.”
In this fast-growing field, Danaher-Garcia says system fluency is key, as is modeling a scenario that targets the people who need the help while maximizing a clinician’s time.
“Being able to model, ‘How many people do we expect in the ER over the next month, and what times of day? And, you know, what days of the week?” asks Danaher-Garcia. “These types of things so that you can maximize who’s there to staff those times, and make sure that your clinicians are getting their rest. So that type of thing is really big right now - predictive modeling for the greater purpose of understanding how a system works."
“Data analytics is constantly growing and evolving,” she adds. “I think that we are on the front line of realizing that you need specific guidance to be able to work in healthcare. Any data analyst could walk into a hospital and help. But what's the best way? How do you train a data analyst who is actually going to maximize your investment in them and their time working with you? That’s what we are doing at the IHP.”