Posted by: Jenny Laurello
Data analytics, Hard skills, Health care analytics, Soft skills
Guest post by: Trevor Strome MSc, PMP, Informatics Lead, Winnipeg Regional Health Authority; Assistant Professor, Department of Emergency Medicine, Faculty of Medicine, University of Manitoba
One of the questions I am asked the most by readers of my blog is, “what kind of skills are needed to work in the field of health care analytics?” This question is especially relevant now as there is evidence of a talent shortage in the field of analytics that may be limiting the potential of organizations to leverage information as effectively as possible for decision making.
Throughout my career, I have seen many different types of people, with many different backgrounds, excel in healthcare analytics. I believe that it is the strong diversity of backgrounds and skills that analytics professionals possess that make analytics indispensable for healthcare quality and performance improvement initiatives.
A few common traits
There is an abundance of opinions on the web highlighting various qualities and attributes of “data scientists,” business intelligence professionals and analysts. Most of the discussion I have seen, however, is about either the “math,” “data” or “technology” skills perceived to be important. Because my focus is on the application of analytics for quality and performance improvement, the qualities I view as ideal for analytics professionals involved in these activities typically are within the intersection of IT, the business and the quality improvement goals of the health care organization (HCO).
With this in mind, several of the traits I view as important for healthcare analytics professionals (working in quality and performance improvement) are as follows:
As more healthcare data becomes available via the proliferation of electronic health records, there is much to be learned about the data available and. in turn, much to be learned from what the data tells us. Healthcare analytics professionals should be naturally curious and revel in asking “what” and “why”, realizing that these questions do not “expose ignorance” but are truly the only way to gain full understanding of a problem.
Healthcare quality and performance improvement initiatives require a great deal of innovation to identify more efficient and effective workflows and processes. To help achieve the required levels of innovation, healthcare analytics professionals must see analytics not as “report development,” but to build the “information tools” necessary to solve pressing health care issues. They are willing, able and excited to leverage all the technology and information available to maximum extent (whether it’s experimenting and adopting new visualizations or trying novel analytical approaches). They strive for effective, yet creative, solutions that provide efficient access to the right information to the right people when it is needed.
Improving healthcare quality and performance requires a strong and thorough understanding of processes and workflows. Analytics used to support QI initiatives must align with and provide insight into the business of providing care. This is why health care analytics professionals must be focus on business, striving to know the pertinent details of the health care domains in which they work. After all, it is these details of the business that add the necessary context to data that help it become “information.”
In many ways, analytics operate at the heart of healthcare information technology (HIT) given that analytical solutions typically integrate data from multiple data sources (such as clinical and financial systems). Many systems and steps are involved in getting data from source systems into a location and format available for effective analysis. Having said that, however, an experienced healthcare analytics professional doesn’t need to be a tech jockey (that is, they don’t need to be a hardcore programmer or serious database administrator). But they should be comfortable and proficient with the current and emerging technologies, such as business intelligence platforms and data cleaning, analysis and visualization tools. This means being comfortable in using more than just a spreadsheet.
Effective healthcare analytics projects depend upon having effective analytics teams. This means working well with other members of health care analytics and quality improvement teams, all while respecting the differing points of views that professionals in other disciplines (such as nurses, physicians, laboratory technologists, etc.) bring to the discussion. It also means communicating well; healthcare analytics professionals must both listen to and understand what others are saying, and articulately convey their own opinions and knowledge to others who may not be analytics experts.
Healthcare quality improvement is now a multi-disciplinary effort, involving a range of experts including clinical, administrative, technology and process engineering professionals. Due to the different roles and teams in which healthcare analytics professionals may find themselves, a strong mix of technical, interpersonal and analytical skills is essential to successfully operate in today’s challenging healthcare environment.
About the author:
Trevor Strome MSc, PMP, is the Informatics Lead for the Winnipeg Regional Health Authority, and is Assistant Professor at the Department of Emergency Medicine, Faculty of Medicine, University of Manitoba. You can visit Trevor’s blog at http://healthcareanalytics.info, or contact him by email at firstname.lastname@example.org.