Health Data, Workforce Development
A Day in the Life of Three Data Analysts
The Journal of AHIMA recently caught up with a few professionals working in the data analytics space to learn more about what their typical day looks like as data analysts and the challenges and trends in the field. Janae Logan, MSHMI, Allyson Russell, and Larry Mandelkehr recently participated in a webinar series for the Healthcare Data & Analytics Association (HDAA) in partnership with the Rutgers Business School with the aim of attracting the next generation of healthcare analytics practitioners.
What organization do you work for, and what is your title?
I am a Data Analyst II in the Emory Healthcare Network (EHN) Analytics Department at Emory Healthcare.
What is your education background?
In Spring 2017, I graduated from Georgia State University with a Bachelor of Interdisciplinary Studies degree in health informatics. In fall 2019, I graduated from Kennesaw State University with a Master of Science degree in healthcare management and informatics.
What do you like about healthcare analytics?
Healthcare analytics is far more complex yet rewarding than other industries I’ve worked in. It is complex because raw data is oftentimes messy; payer data may not come in the correct format, may be missing some data elements that were there the previous month, a new data element may have been added, or there’s a lag in receiving the data in a timely fashion. There is a lot of cleaning and standardizing you must do for some data sources. However, it is most rewarding when you know the reports and dashboards your team creates are providing impactful insights on how to improve a patient’s life by identifying ways to get them the proper care, education, and resources they need to live a quality life.
What does a typical day look like in your role?
A typical day for us varies depending on if we have available payer data from our data vendor, if we are waiting for the vendor to refresh our data, or where we are in the month. Our department and data vendor typically receive data at the end of the current month/beginning of the following month from our different payer populations for EHN’s attributed members. At the beginning of the month, we will send updated flat file attestations for care coordination and depression screening to one of our payers as well as create an active care coordination list to send to our vendor.
Currently, we are waiting for our data refresh as we have pushed all payer data files to our vendor. This week consisted of our weekly huddle between our team and the medical economics team to discuss high-level reports that both departments are working on, creating/updating standard work documents for our existing report processes, running scripts to receive any available payer data and scripts to send payer data files to our vendor, meeting with Epic to discuss the status of our payer populations being loaded into Epic as well as review current report processes so dashboards can be created in Epic, and working on ad hoc requests from other departments. Once our data is refreshed, we will update our monthly attribution counts across all payers in our monthly attribution report, create our monthly medication adherence report, quality gaps report for MSSP, risk scores for all payer populations (which is always 90 days behind attribution because of the claims needing to be fully adjudicated), and create a physician packet for all EHN practices and their physicians who have member attribution within the reported time frame.
How does your organization leverage analytics to improve operations, patient care, etc.?
We use claims, lab, and pharmacy data to create various reports and dashboards (e.g., care coordination reports, gap reports, medication adherence reports, etc.) to improve patient outcomes. We use various tools such as Excel, Microsoft Access, Tableau, and R to clean and manipulate the data and create the reports. Other departments will reach out to us to retrieve data to answer vital questions on provider performance and targeting certain populations for outreach initiatives.
What are the major challenges healthcare data analysts faces today? What do you foresee as the major challenges in the future?
The time lag in which we receive our data has been one of the major challenges, as it is sometimes out of our, and the data vendor’s, control in how soon we receive payer data. Another challenge, that will be solved with our Epic go-live, is automating reports so we can shift from manual reporting to identifying other actionable opportunities within the payer datasets.
The major challenges I foresee will still be the time lag for certain payer data, keeping up with the newer technologies/trends in healthcare analytics, and creating outreach opportunities for aspiring healthcare analysts so they can shadow or intern in a healthcare analytics department while in school. Many healthcare organizations seek experienced data analysts who have worked in either bedside care, such as a nurse or physician, or worked in data analytics for a certain amount of time, but many analysts do not have a nursing or physician background. Some may have little to no experience in data analytics, as they may be trying to enter the workforce for the first time or are switching careers. This makes it more challenging to recruit educated analysts coming out of school with the fresh knowledge of healthcare concepts and analytical tools.
What are the biggest trends in healthcare analytics you’re seeing today?
The biggest trend I am seeing is the increased use of artificial intelligence (AI)/machine learning (ML). Using AI to create algorithms that analyzes historical data to predict future trends can help to identify needs and make informed decisions more quickly. It is amazing to see how AI/ML can not only improve patient outcomes but the operations of a healthcare entity as well.
What advice do you have for someone interested in a healthcare analytics career?
- Be passionate about healthcare and data analytics,
- Strive to become a lifelong learner, and
- Take a task, understand the why, improve the process where needed, and be able to answer any questions about the report and its process.
Success comes with being passionate about data analytics, a willingness to learn everything you need to succeed in your role, and trying to understand the why behind what you do. In addition to soft skills, such as communicating effectively, the ability to work individually and as a teammate, are key. Creating reports and dashboards on your own can also be fun and rewarding. If you’re on a team, the work you do together makes for a great morale boost and learning experience, as everyone has a different perspective on approaching and analyzing data. There’s always more than one way to solve a problem, but the most efficient way to solve a problem will always be timelier and more accurate.
What organization do you work for, and what is your title?
I am the analytics community and training manager at UNC Health.
What is your education background?
I have a Bachelor of Science in apparel, housing, and resource management from Virginia Tech and certifications, including:
- Cisco Certified Lean Six Sigma Black Belt
- Data Science for Executives Certificate, Columbia University (EdX)
- Data Science for Leaders Certificate, NC State Executive Education
- Candidate for MBA with a specialization in Healthcare Management, UNC Wilmington (expected 2024 graduation)
I have a nontraditional background, but many analysts do! I am intrinsically motivated and rewarded by helping others, whether it’s designing clothes to make people feel beautiful, or by improving business processes to save teammates time at work, or by connecting others to the resources and support to be successful in their roles. Over time, I’ve gained analytics skills through various certificate programs and on-the-job training. It was COVID-19 that inspired me to leave my job at one of the largest technology companies in the world and pursue a career in healthcare analytics.
What do you like about healthcare analytics?
Healthcare analytics is mission-driven work. We have the ability to improve and save lives with data and analytics.
What does a typical day look like in your role?
Every day I work with teammates at all levels across the healthcare system to help them to be successful in their role by leveraging data and analytics, and by connecting them to support and resources. It is a mix of transformational change management, customer service, networking, program management, and analytics. While I have a more formalized role as a champion for healthcare analytics, anyone in healthcare can and should advocate for using data to drive decisions and positive outcomes for patients.
How does your organization leverage analytics to improve operations, patient care, etc.?
UNC Health is a national leader in healthcare analytics. We are one of the first health systems to receive HIMSS Stage 7 certification for analytics adoption in 2018 and the first system in the world to be recertified as a HIMSS Triple 7 organization in 2021. To provide world-class healthcare that is naturally driven by insights, and to continue to lead the way in innovating with healthcare analytics, we leverage and enable the combined analytics skills and capabilities of teammates across the enterprise. There isn’t just one centralized data and analytics function. UNC Health leverages a hybrid-community strategy, with distributed analytics teams across the healthcare system supported by a centralized group within our Information Services Division. This means that our organization leverages analytics in many different ways, all of which are very important to our mission to improve the health and well-being of those we serve.
What are the biggest trends in healthcare analytics you’re seeing today?
The COVID-19 pandemic ushered in a new era for recruiting talent into the healthcare system: The Great Resignation, a mass exodus of the workforce marked by people seeking more money, more flexibility, and happiness. No industry has gone unscathed, but healthcare has been hit particularly hard with burnout from being overworked and underpaid. There are efforts underway across the country to address these shortages, nursing, in particular.
In many ways, COVID-19 was a catalyst that demonstrated the power of data and analytics to healthcare leadership. Now, demands for data, dashboards, reports, analyses, and new data science models are pouring in. On top of the increased demand for data and analytics, our supply of strong data analysts is low due to the Great Resignation. Analysts have transferrable skills and with more employers offering remote work, we now compete for analytics talent globally across all industries.
It's an interesting challenge, yet the mission-driven work of healthcare is often a draw for candidates. More and more candidates are looking at the meaning of their work and how they can contribute to the greater good. Healthcare analytics is definitely mission-driven work. It is important to have a strategic plan for attracting and retaining healthcare analytics talent.
What advice do you have for someone interested in a healthcare analytics career?
While technical skills like data visualization and SQL are important to learn, four skills that are arguably more important to learn are curiosity, critical thinking, problem solving, and collaboration. Ask a lot of questions and wonder how it could be done better. Lean on experts to learn the clinical or business problem, related workflows, and intended outcomes. Lastly, measure improvements and outcomes of projects, celebrate and share successes.
What organization do you work for, and what is your title?
I am executive director of hospital quality and innovation at UNC Health. I have spent my entire career with at least one foot in analytics and still “push my own data” as needed, as well as serve as co-chair of our system’s Data Governance Council.
What is your education background?
I am an electrical engineer by degree (BS and ME from Rensselaer Polytechnic Institute) and spent 12 years in industrial controls (engineering design and project/program/marketing/sales management) before transitioning to quality improvement in healthcare, where I’ve worked for the past 27 years. I have taught at UNC’s Gillings School of Global Public Health in the Health Policy Management Department for 25 years, the first 12 years teaching database design for healthcare applications and the last 13 years teaching healthcare quality and information management in the MHA program (both residential and executive students).
What do you like about healthcare analytics?
It is extremely gratifying to be able to help patients as someone with a nonclinical background. The field also provides the opportunity work with dedicated, caring people and learn something new every day.
What does a typical day look like in your role?
Every day is different, which is another thing that I really like about working in healthcare. My days are a mix of team meetings, one-on-one meetings with my team members, and analytics work (individual and in teams). As department director, I spend more time delegating to my team and supporting their work than analyzing data on my own.
How does your organization leverage analytics to improve operations, patient care, etc.?
We have developed an extensive data repository along with self-service tools, like Tableau, and query and analysis tools. We have developed a wide library of standard reports to speed the process of investigation and understanding (and insure that everyone is looking at data with the same inclusions and exclusions). We have a strong focus on data governance (centralized repository of measure definitions and metadata, identified data stewards/subject matter experts) and a dedicated focus to support our analytics community of developers providing tools, best practices, and consulting support. We have also defined standards for data visualization to improve data literacy and understanding.
What are the major challenges healthcare data analysts faces today? What do you foresee as the major challenges in the future?
Too much data and not enough!
Too much – We have terabytes and terabytes of real-time and historical data points. When you add up all of the operational, financial, value, productivity, quality, and safety metrics—and then add it all the metrics captured by external registries, incentive programs, and public reporting—we are dealing with literally hundreds and sometimes thousands of metrics. Which are most important? To which stakeholders? How do you keep track of them all?
Not enough – Data is sometimes siloed internally or difficult to integrate because we still deal with some proprietary or incompatible systems. Hospitals maintain their own data, as do insurance companies and pharma companies, but they don’t share this data or their findings for many reasons, mostly because of privacy and economic-related reasons. Integrating these expansive data sets and then applying AI and machine learning could lead to development of predictive models across a wide range of applications, saving lives and money.
What are the biggest trends in healthcare analytics you’re seeing today?
Additional focus on predictive measures and tools. Can we identify issues such as developing sepsis and readmission (or being admitted in the first place) before they happen? This is how we improve population health and better manage/reduce costs and utilization.
What advice do you have for someone interested in a healthcare analytics career?
- Develop a broad range of skills – one size doesn’t fit anyone.
- Master data visualization – you can be the best analyst in the world, but if you can’t effectively communicate your message, you will be less successful.
- Find a mentor to improve both your technical and business/content skills – you will spend your entire career learning new things and it’s helpful to have someone to help direct and prioritize
Alexa Schlosser conducted the interviews for this article and is the editor of the Journal of AHIMA.