You’re in the health information field, but you want to expand on your expertise or explore other fields… Are you the type to geek out over numbers, equations, and statistics? Do you frequently question existing assumptions and processes? If the answer to either or both of these questions is ‘yes,’ then data science—an interdisciplinary field that focuses on the use of data to inform decisions and make new discoveries—may be a good fit for you.
What exactly is a data scientist?
“A data scientist is somebody who is inquisitive, who can stare at data and spot trends. It’s almost like a Renaissance individual who really wants to learn and bring change to an organization,” says Anjul Bhambhri, vice president of big data products at IBM.
Data scientist is one of the five best technology jobs, according to the 2022 US News Best Jobs report. Not only is the job in demand, but it’s also highly lucrative.
According to the U.S. Bureau of Labor Statistics, it is projected that the employment of data scientists will grow 36 percent from 2021 to 2031, approximately creating 13,500 job openings. And increasingly, these companies are in the healthcare sector. As big data continues to grow commensurate with electronic health records, data scientists are the ones who utilize healthcare analytics to manage and merge data sources, create visualizations, build mathematical models, and present insights—all with the goal of producing answers, predictions, and calculations as quickly and accurately as possible.
A simple search for “healthcare data scientist” on LinkedIn generates more than 300,000 jobs nationwide, many of which require previous healthcare experience and knowledge of patient data.
According to Glassdoor, data scientists earn an average annual salary of $114,067. The need for big data skills continues to lead to pay increases— approximately 20 percent as of 2021, according to Burtch Works. It’s probably fair to assume that those working in healthcare—and who possess a formal health information management education—may earn even more due to their specialized knowledge.
Advancing your career
According to AHIMA’s Career Map, many employers actually require—or strongly prefer—a master’s degree for certain types of data-related positions such as informatics researcher, data analyst, research and development scientist, project manager, director of clinical informatics, or chief clinical informatics officer. A master’s degree in data science certainly fulfills these requirements.
Even if you don’t intend to advance your career in the immediate future, a degree in data science can make you a more effective health information management professional. By building a solid foundation in healthcare analytics, computer science and applications, communication, modeling, statistics, analytics and math, those with a working knowledge of data science are able to:
- Collect and report on complex data
- Communicate findings to both business and IT leaders
- Apply data to business problems
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Relevant healthcare topics in data science
The following data science coursework is also particularly helpful for individuals currently working in health information management:
- Data warehousing. Health information management professionals can use data warehousing skills to collect, clean, and prepare data stored in the electronic health record and various other electronic systems. Being able to evaluate data in terms of its source, volume, frequency, and flow is an important part of ensuring effective health information exchange.
- Big data computing. Health information management professionals can use big data computing skills to answer important questions, such as: How can the organization reduce readmissions or prevent hospitalizations? What is the root cause of certain denials? Can the organization justify expanding a particular service line? Should it join an Accountable Care Organization or purchase a physician practice? A 2011 study by MGI and the McKinsey Global Institute found that the healthcare sector could create more than $300 billion in value annually if it were to use big data and healthcare analytics to creatively and effectively drive efficiency and quality.
- Data communication. Health information management professionals can use data communication skills to educate decision makers about the nature, structure, and interpretation of coded data—including ICD-9 vs. ICD-10 as well as a whole host of other clinical and non-clinical data.
- Data mining. Knowledge of data mining can benefit health information management professionals frequently who frequently generate reports necessary for clinical and operational improvement. Accessing and analyzing unstructured data helps health information management professionals create a more well-rounded and insightful clinical picture.
- Ethics of data science. Being able to discuss the privacy, intellectual property, security, and integrity of data is important aspect data management, release, and exchange in an increasingly electronic health information management environment. Those who are well-trained in the ethics of data science can contribute intelligently to these types of conversations and drive change within their organizations.
Finding the time to benefit your field
Obtaining a master’s degree in data science will invariably help health information management professionals tackle these ongoing challenges within the industry:
- Raise awareness of the intersection between health information management and big data
- Justify a seat at the decision-making table
- Capitalize on the power of healthcare analytics in the electronic health record
As a working adult, though, it can be hard to find the time to pursue a graduate degree. Fortunately, the University of Wisconsin Master of Science in Data Science was designed with adult learners in mind. It’s 100 percent online, making it easier to fit into an already-busy schedule. Visit the UW MS in Data Science page to learn more about this degree and find out if it’s right for you.