Have You Considered a Career in the Field of Healthcare Data and Analytics?

By Brian Krumholz and Haluk Demirkan, PhD, PMP

The job market in the field of data and analytics—which includes data science, business analytics, business intelligence, and data engineering—is growing exponentially. In 2020, the World Economic Forum published its predictions for the future workforce through 2025.1 In this report, data analyst has the highest “increasing demand” globally in almost all industries, and healthcare data analyst is the most emerging role.

If you are starting your career in the data analysis domain, a career as a healthcare data analyst may be an option for you.

What does analyzing healthcare data involve?

Data is one of the most valuable assets that an organization owns. Having professionals on staff who are trained to properly collect, store, retrieve, and present data that supports clinical and business decisions is vital. In the context of the healthcare system, which is increasingly data-reliant, data analytics can help derive insights on systemic wasting of resources, track individual practitioner performance, and even track the health of populations and identify people at risk for chronic diseases. Data, analytics, and smart digital solutions can increase the efficiency and effectiveness of healthcare services by increasing the utilization of resources, providing better telehealth, reducing costs, increasing quality care of patients, providing better healthcare services, reducing readmissions, improving processes, and more. It’s all about using healthcare data to drive decisions.

Why is it a growing field?

The passage of the Health Information Technology for Economic and Clinical Health Act (HITECH Act) and COVID-19 accelerated the digitization of medical records.2 All healthcare providers, from large hospitals and clinics to small individual practices, produce a massive amount of digital medical data. Healthcare providers are required to demonstrate meaningful use of electronic health records (EHRs) to avoid significant reimbursement penalties from government insurance payers.

This rapid expansion of available digital medical records created an information resource that gives healthcare leaders unprecedented depth of insight to help guide decisions regarding the delivery and the business of healthcare.

What is a healthcare data analyst?

Healthcare data analysts—sometimes called healthcare business analysts or health information management (HIM) analysts—apply their specialized knowledge of data acquisition, management, analysis, and interpretation directly to healthcare data, providing actionable insights that physicians, clinical researchers, operations, administration, decision-makers, and others can use. It’s a great career choice for those who want to apply healthcare knowledge and expertise in a novel and innovative way.

Healthcare data analysts gather and interpret data from a variety of sources (e.g., the EHR, insurance claims, cost reports, and patient satisfaction surveys) to help organizations improve the quality of care, lower the cost of care, and enhance the patient experience. Their role has become increasingly important as organizations look for ways to capitalize on big data and its various applications, including how it can be used to drive healthcare quality improvement.

Healthcare data analysts may help hospitals, health systems, and physician groups decide whether to add a new service line, merge with other medical groups, or join an accountable care organization. They also provide data insights that drive clinical process improvement, such as reducing readmissions and hospital-acquired conditions. In addition, healthcare analysts help insurers, vendors, and others synthesize data that guides decision-making, population health management, cost containment, and quality improvement.

The main role of the healthcare analyst is to:

  • Collect and interpret data from multiple sources like cost reports or EHRs with the help of big data and its applications
  • Understand hospital functionalities and systems to support in the decision-making process
  • Provide end-to-end database management, including collection, storing, retrieving, and securing the healthcare data
  • Create reports and dashboards to deliver the required information to the stakeholders in the healthcare sector
  • Coordinate data exchanges between hospitals, clinics, pharmacies, and the patient
  • Automate existing labor-intensive workflows to free up staff and physicians
How do I become a healthcare data analyst?

In order to become a healthcare data analyst you must have at least a bachelor’s degree. It is best for that degree to be in in business analytics, HIM, health IT, statistics, data science, information technology, computer science, or industrial engineering. Employers also prefer to hire those with healthcare experience, such as experience working with clinical or other types of EHR data.

Aspiring healthcare data analysts may also want to consider obtaining the Certified Health Data Analyst (CHDA) credential from AHIMA. According to AHIMA, the CHDA denotes one’s ability to “acquire, manage, analyze, interpret, and transform data into accurate, consistent, and timely information, while balancing the ‘big picture’ strategic vision with day-to-day details.”

The best healthcare data analysts maximize their value to the organization by using their problem-solving skills to become a partner for clinical and operational improvement. Due to the nature of business, some of the emerging skills are:3

  • Active learning and learning strategies
  • Emotional intelligence
  • Creativity, originality, and initiative
  • Leadership and social influence
  • Resilience, stress tolerance, and flexibility
  • Reasoning, problem-solving, and ideation
  • Service orientation
  • Complex problem solving
  • Troubleshooting and user experience
  • Persuasion and negotiation
  • Technology use, monitoring, and control
  • Technology design and programming
  • Quality control and safety awareness
  • Critical thinking and analysis
  • Coordination and time management
What is their thinking pattern?
  • Strategic thinking—problem or opportunity identification: First, the top healthcare data analyst asks many questions that seek to understand, “What is the problem we’re trying to solve?” and, “Why does it matter?” This deliberate questioning helps to tease out the best opportunities.
  • Tactical thinking—converting data to information: Next, data analysts ask, “How will we solve that problem or address that opportunity?” and, “What information would be needed to help solve this problem?” Top analysts turn data into information, so what they’re getting at is, “What data do I need to begin to address the issue, and where do I find it?”
  • Operational thinking—analytics and technical skills: After finding the data, the healthcare data analyst asks questions such as: What insights can we gather from this data? How does this data need to be organized, analyzed, and presented to address the problem? Who, when, and how (format and tool) do I need to present this information to so they can make a timely decision?
  • Technology and methodological adoption: Technology and data analysis methodologies are evolving rapidly. It is extremely important to know which technologies to collect, store, and analyze data, and what methods to analyze data. Healthcare analysts must have technical aptitude coupled with knowledge of healthcare data and operations (see Table 1).
Table 1: Sample list of healthcare IT trends with challenges and opportunities
Healthcare IT TrendsChallenges and Barriers to Adoption of New Technologies
  • Artificial intelligence (e.g., machine learning, neural networks, NLP)
  • Clinical automation
  • Business process management
  • Big data and analytics
  • Home base medical service
  • Medical imaging
  • Remote access
  • Health information exchange
  • Increased regulation
  • Mobile solutions, internet of things, connected devices
  • Text, image, and voice processing
  • Encryption and cyber security
  • Cloud computing
  • Lack of flexibility of the regulatory framework
  • Skills gaps in the local labor market
  • Inability to attract specialized talent
  • Shortage of investment capita
  • Complexity
  • Capacity
  • Compliance
  • Availability
  • Performance
  • Security
  • Convenience
  • Privacy
  • Culture change

As a result of the COVID-19 pandemic, the need and importance of health data analysts are increasing rapidly. The impact of COVID-19 on companies has included adopting strategies to provide more opportunities to work remotely, accelerate the digitization of work process, accelerate automation of tasks, accelerate the digitization of upskilling/reskilling, and temporarily reassign workers to different tasks.4

Where will a health data analyst be employed?

The healthcare data analyst can start their career in different areas, such as:

  • Government healthcare departments
  • Private hospitals or public sector hospitals
  • Analytics team of multinational companies
  • Diagnostic centers
  • Health insurance companies
  • Healthcare software vendor companies
How many jobs are out there?

A simple search for “healthcare data” in the US on the Careeronestop job finder brings back over 100,000 search results as of January 4, 2021.

Some data analysts may also be promoted to healthcare management positions. Searches for jobs in this category on the same website yielded similar results.

What are the current trends in healthcare analytics?

COVID-19 has accelerated several emerging trends in healthcare data analytics. As hospitals look for ways to reduce costs and recruit talented analysts, more remote work positions are being offered. Many hospitals have recently sold their offices as a sign that remote work arrangements will be prevalent for at least the near future.

The deluge of decision points in healthcare has made it impossible to hire enough people to review every decision needed for efficient management. Decisions about which insurance denials to write off or which patients should be invited to research trial are now sometimes being made by computer systems without human review. Hospitals and software vendors have begun introducing machine learning–  and artificial intelligence–based decision systems into these workflows. Hospital leadership is currently looking for the pioneers to integrate these new technologies into healthcare.

For example, can you imagine the current complexity of managing a hospital census (hospital bed capacity management)? Hospitals need to keep a certain amount of empty-bed capacity to admit urgent COVID-19 patients, but in the meantime they still need to continue offering other types of acute and nonacute health services to their patients. How can they predict the number of full, empty, or available (because of maintenance of rooms and/or availability of nurses and doctors based on acute level) beds for tomorrow, when last year’s numbers are useless in today’s complex COVID-19 days?

Hear directly from someone working in healthcare analytics.

Brian Krumholz is a master’s student studying business analytics. He is the claims analyst team lead at UC San Francisco Medical Center. He has been working in a healthcare analytics role as part of the medical centers and healthcare software vendors for more than 15 years. Hear Brian talk about his career in this YouTube video.

Notes
  1. World Economic Forum. “The Future of Jobs Report 2020.” October 2020. http://www3.weforum.org/docs/WEF_Future_of_Jobs_2020.pdf.
  2. Stanfill, Mary H., Giannangelo, Kathy, and Susan H. Fenton. “Health Information Management Best Practices for Quality Health Data During the COVID-19 Global Pandemic.” Journal of AHIMA. July, 7 2020. https://journal.ahima.org/health-information-management-best-practices-for-quality-health-data-during-the-covid-19-global-pandemic/.
  3. World Economic Forum, “Jobs Report.”
  4. Ibid.

Brian Krumholz ([email protected]) is the Epic claims team lead at the UCSF Medical Center and a business analytics graduate student at the Milgard School of Business, University of Washington – Tacoma.

Haluk Demirkan ([email protected]) is the assistant dean of analytics innovations and the director the Center for Business Analytics at the Milgard School of Business, University of Washington – Tacoma.

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