The Data Analytics Department recently offered students an opportunity to hear from a prominent leader in healthcare analytics during a live interview with Drew Smith, the Chief Data and Analytics Officer at OhioHealth. With the rapid advancement of new analytics technologies, OhioHealth is working to implement these tools to enhance patient care while addressing concerns about confidentiality and algorithmic bias. Smith shared insights into these processes and discussed where he is focusing his energy as OhioHealth moves forward with these initiatives.
At OhioHealth, Drew’s broad set of responsibilities includes overseeing data collection, management, and usage in analytical tools, including AI platforms. While most of his background is not in healthcare, it is still firmly rooted in data and analytics. Drew was involved in retail before moving to quick-service restaurants, notably Little Caesars. He also worked at IKEA, where he introduced the idea of dynamic pricing, which was new to the brand at the time. Reflecting on that IKEA experience in particular, Drew recalled how challenging it was to bring a brand new pricing structure to an already successful company that had not tried it before. “It can be tough to convince an expert that the data suggests something that contradicts their years of experience,” he said. However, in those situations, Drew welcomes the opportunity to enhance how things are done and learn from the analytics.
Now that Drew works in healthcare, his goals have changed significantly. He mentions three distinct groups to consider when improving current processes: patients, direct care providers, and system administrators who handle tasks like scheduling or locating specialized care for unique patients. Critical to the work of all of those groups is protected health information (PHI), which holds private details about a person’s medical history. Drew is interested in how PHI can be leveraged to address healthcare inequality. He highlighted OhioHealth’s understanding that “not as bad as everyone else” cannot be the benchmark for eliminating care disparities. Factors such as race, gender, wealth, and proximity to a care center are examples of unique personal information that can be useful in these efforts. As Drew expressed, “PHI must be used with caution, but the risks of not using it at all are very serious.” His focus with PHI centers on data privacy, making sure that the analytics do not jeopardize any individual. Although the question of “how can we run things better?” in healthcare often encounters obstacles related to protected information, Drew aims to demonstrate that the improved systems will provide more effective care without compromising anyone’s data.
For anyone looking to be an analytics professional, Drew gave two main pieces of advice. First, find your niche. Figure out where your interests lie, identify a space that needs experts in analytics, and get prepared. Data and analytics is a broad world, and you’ll be more successful when you can put a finger on what you’d like to do. His second piece of advice was to master a few key fundamentals. Anyone going into the field should be able to articulate specific, answerable questions, know where your data comes from, understand basic statistical concepts, and have an idea of how data governance works. Someone with those skills can be effective anywhere.
Drew’s final piece of advice was to keep the human impact of your work in mind, even throughout all of the intermediate steps of a large project. The reason behind your work is always important, and decisions along the way should be made with that in mind. Keep that mentality, and valuable work will follow.
