As healthcare becomes more data-driven, it is now more important than ever for health informaticists with particular areas of domain expertise (pharmacy, nursing, medicine, public health) to also acquire skills in the area of data science and health analytics.
1. Data Analytics Provide Actionable Insights: It is not just about what you know, but what you can actually do with that knowledge. Decisions regarding healthcare strategy and operations are no longer based on conventional wisdom, gut instinct, or the “squeakiest wheel,” but instead on leveraging data analytics to provide actionable insights. These insights help healthcare organizations to set strategic priorities for larger goals such as quality improvement, patient safety, patient engagement, growth, and managing risk. Operational decisions for staffing and patient acuity are also based on analytic algorithms. Health informaticists, with the right skills, can make important contributions to analytic projects by participating in project design, analytic plan development, and data collection.
2. A Shortage of Informaticists with Data Analytics Expertise: Research indicates that there is a gap between demand and supply related to data analytics expertise. According to McKinsey (http://bit.ly/2kqmopD), “there is a shortage of 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data.” One of the biggest barriers that companies face in realizing value from data and analytics is due to not having access to individuals with analytic skills. This includes all members of an analytic team—not only data scientists but also business analysts, statisticians, technical experts, and leaders who are data savvy. LinkedIn research (http://bit.ly/2xldWOI) has revealed that only 180 out of 6,000 data scientists in the U.S. work in healthcare, making this an opportunity to build data science expertise within the healthcare industry.
3. Informaticists Must Keep up With Improving Analytics Capabilities: Healthcare organizations are continuing to mature their capabilities in using analytics. They are going beyond simply describing what happened (descriptive analytics) to answering questions about what will happen (predictive analytics) and then ultimately arriving at how we can make something happen (prescriptive analytics). Building analytic capability drives more need for informaticists with data science and analytic skills.
4. Allowing Informaticists to Participate in an Innovative Field: This is a time of discovery and innovation fueled by the application of data science to healthcare. As entrepreneurial energy increases, opportunities for new and exciting career paths for health informaticists emerge (http://healthinformatics.uic.edu). This makes it an opportune time to look beyond traditional informaticist roles for opportunities to apply new skills to work in areas such as mobile health, big data and artificial intelligence, and cognitive computing.
To leverage your health informatics knowledge, focus on building competencies such as:
- Ability to identify relevant health data sources and explore the data
- Integrating data sources and preparing data sets
- Applying systems thinking to analytics
- Present and communicate data—storytelling and visualization
- Developing and managing data products
Developing these competencies will lead to a successful shift into a career in health data science.