Analytics in Healthcare

Translating Healthcare Information Into Actionable Insights

March 08, 2021
Four people examining graphs on a computer around a table at work.
Healthcare analysts uncover patterns and trends in healthcare data and draw reliable and meaningful conclusions from it.

Big data has the potential to make a significant impact on the healthcare sector, from improving daily operations and management to informing executive-level decisions to influencing marketing and communication strategies and more. The ability to translate healthcare information into actionable insights is vital to unlocking the power of big data in healthcare. This is the primary focus of healthcare analyst jobs.

What is health data analysis?

In general terms, analysis is the process of converting something whole into separate parts, then examining those parts in detail to understand its essential qualities or characteristics. In the healthcare sector, health data analysis uncovers patterns and trends in healthcare data and draws reliable and meaningful conclusions from it. This involves using both quantitative methods that are numerical and measurable and qualitative methods that are observational and descriptive.

Problem solving with health data analysis

Using historical and current — even real-time — data sets from internal and external sources, healthcare data analysis allows health providers and organizations to do the following:

  • Assess a situation and evaluate or calculate its results. For example, insurance companies can assess an applicant’s health status based on his or her medical history to calculate an individual health insurance premium and underwrite a health insurance policy.
  • Compare healthcare data to identify similarities and differences between two or more options and determine the best option for a particular situation. For example, a physician can compare the effectiveness of different medications and dosages used to treat certain health conditions and apply that data to develop and monitor a personalized treatment plan for a particular patient.
  • Estimate numbers or the extent of something to make informed judgments. For example, healthcare systems can operate more efficiently by estimating the number of patients they’ll admit at any given time throughout the day and allocate personnel and medical resources accordingly.
  • Predict future trends and consequences. For example, organizations can identify, manage and control the outbreak and spread of disease. During the global coronavirus pandemic, medical experts pulled health data related to COVID-19 variants, such as the UK variant and the South Africa variant, to predict how these variants of the disease will affect the U.S. population. The healthcare sector has also predicted the spread and total number of deaths in upcoming months due to COVID-19 based on weather data, the number of confirmed cases and deaths from previous months and many other factors.
  • Test the performance, quality or reliability of something before putting it into practice or widespread use. For example, pharma companies can test the efficacy and side effects of new prescription drugs to perfect their chemical formula before taking them to market.
  • Improve something to produce better results and outcomes. For example, analytics in healthcare can be used to identify gaps in service areas and improve outreach and care in specific locations. Or, health data analysis can lead to the development of health intervention and disease prevention programs.

Big data analytics in healthcare can be used in a wide variety of other cases to understand a patient, organization or community.

Predictive analysis in healthcare

Predictive analysis in healthcare has emerged as an important subfield of data analytics in healthcare, especially at the enterprise level. In a recent survey from the Society of Actuaries, more than half of respondents reported that their healthcare organization has adopted predictive analytics, with a significant number of them experiencing improved patient satisfaction and cost savings.

Health systems use predictive analytics to learn from historical data and make reliable predictions about the unknown. For example, predictive analytics has been used to monitor and analyze patient vital signs and identify who is most likely to need an intervention in the immediate future. This has enabled critical caregivers to respond early and proactively to changes in a patient’s condition.

Data analysts also use predictive analysis in healthcare to make sense of behavioral, biometric and psychosocial data that was once hard for healthcare data analysts to manage. For example, predictive analysis in healthcare has helped detect early signs of deterioration in patients with data transmitted from wearable biosensors. These medical devices enable care providers to monitor patients remotely, which has proven to be an effective way to carry out clinical surveillance of COVID-19 patients.

Predictive analysis in healthcare is often combined with related branches of biomedical science such as clinical medicine and epidemiology for larger data sets and more effective results.

Healthcare analyst jobs

Healthcare analyst jobs focus on providing actionable insights to healthcare organizations. Data analysts in healthcare design and develop health data analysis procedures and techniques using programming languages such as R, Python and SQL. Then, they demonstrate conclusions using business intelligence suites and data visualization tools such as dashboards. Healthcare analysts work closely with healthcare data managers, who prepare health data for analysis, and health informatics specialists, who apply the information and insights to make strategic decisions and changes.

Degrees in data analytics

Well-designed degrees in data analytics may prepare you for any of the fields mentioned above: healthcare analytics, health data management and health informatics. The difference at Touro is our strength and reputation in technology and healthcare education.

Our 10-course, 30-credit online program curriculum prepares you to kickstart, change or advance your tech career, especially in the healthcare sector. You’ll gain in-depth knowledge of healthcare operations while developing advanced technical skills in data analysis tools and methods. For example, the Analytics Data Modeling and Strategic Decisions course combines interactive lectures with hands-on labs to teach you how to apply various data modeling and data analytics concepts using state-of-the-art tools and technologies.

The data analytics in healthcare master’s degree program also prepares you for the Certified Health Data Analyst certification from the American Health Information Management Association. The hands-on experience and technical work are designed to give you a competitive edge over other candidates for healthcare analyst jobs with degrees in data analytics.

Explore Touro’s data analytics in healthcare master’s degree program and find out how you can help transform the future of healthcare while working in healthcare analyst jobs.