Why you should consider a career in healthcare analytics—and what you need to know to get started

headshot of online healthcare analytics instructor Erin Griffin

Novel COVID-19 is unprecedented. As its name implies, it’s new, not something we have ever seen before. With this new virus comes an almost-overwhelming amount of new, constantly evolving healthcare data. And we’re also seeing a new level of discussion revolving around this data: It’s not just healthcare leaders and professionals who are analyzing it, it’s consumers and the general public, too. We’re all trying to make sense of what the data means and how it affects us.

We sat down with epidemiologist Erin Griffin, a research scientist at UC Davis School of Medicine and an instructor in UC Davis Continuing and Professional Education’s Healthcare Analytics Certificate Program, for insight on why quality healthcare data is so important.

“The ability to analyze data requires ethics, general EQ, team work, responsibility, trust, transparency and a very high level of professionalism.”

Here are a few takeaways—and what you need to know if you’re considering a career in the industry.

Quality healthcare data is essential for evidence-based practice.

Quality data and analytics are the essential tools for understanding predictors of health outcomes, surveillance, trends, and risk and protective factors. We can’t get that subjectively, anecdotally or without accounting for the many influences that contribute to health outcomes. As an applied data scientist and researcher, my interest is in continuous quality improvement to inform progress. I like to think of it as a life cycle—asking a question, gathering appropriate data, conducting analyses, then telling the story. The story helps us understand where and how changes to programs or interventions make sense, which leads to new questions. 

Data literacy is key.

Data literacy is a core competency for healthcare leaders. The Data Literacy Project says that only one-third of us can confidently understand, analyze and argue with data. Healthcare leaders need the skills to quickly and reliably interpret, explain and draw conclusions from data and analyses. The data do not ‘say’ anything; people do. Evidence-based conclusions always come with limitations and context that must be clearly and accurately communicated to ensure that subsequent actions and investments are justified and on point.

Be a student of the data.

COVID-19 has been tricky for epidemiologists. While a lot is known about how epidemics tend to behave, less is known about pandemics, and even less about this pandemic. Statistical modeling is a powerful tool for increasing understanding of phenomena we have seen before. For novel outbreaks like COVID-19, we begin with little knowledge and no real-time data. As data accumulate, we increasingly understand the role of risk and protective factors, the effectiveness of interventions—such as social distancing, masks and hand hygiene—how to leverage testing to inform public health interventions and how to care for patients.  

Data analytics is booming.

This is an opportune time for healthcare leaders to increase data literacy. There is great need. For the analytically inclined, there are literally endless opportunities to develop and enhance skills. Entry points include traditional routes of statistics, statistical programming and presentation, in addition to rapidly evolving specialties in data visualization, GIS, AI and more.  Blending these approaches is extremely gratifying, as we are moving beyond simple tables and charts to dynamic, intuitive methods for communicating vast amounts of information in ways that are engaging and thought provoking.

Be a change maker.

The UC Davis Continuing and Professional Education Healthcare Analytics Certificate Program provides an excellent introduction to the field. It teaches you about macro data and getting out in the world and using it. These are boots-on-the-ground analysts who need competency, good communication skills and data literacy. The certificate program gives you the foundation to become a really good generalist or puts you on the path to become an expert and specialize in statistics or data visualization. It positions students to start a career that will never ever be static.

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