Why is Healthcare Data Analytics Important?
For those of you who have been reading our coverage of data in the healthcare world, it’s no surprise that we put a premium on data analytics in healthcare. Healthcare data analytics encompasses both macro and micro trends in the healthcare field, whether it’s using data to gauge the spread of a disease or aiding a clinician in detecting an anomaly in a cancer scan.
Like all data analytics fields, the term refers to the use of large amounts of data to give organizations or professionals actionable insights, applied here to the healthcare field. As healthcare spending continues to ramp up, cost saving measures from healthcare data analytics offer hospitals and healthcare systems an easy way to cut costs while improving outcomes.
Given the trillions spent on healthcare worldwide, it’s no surprise that “by 2025 the market for health-related analytics will increase to about $28 billion” (Healthworld.com).
Descriptive Analysis: This is the most basic of all analysis. This examines an event that happened in the past. For example, a healthcare data analyst might track data at a hospital over the past five years to look for seasonal patient admission trends.
Diagnostic Analysis: This type of analysis is used to investigate why an event happened. For example, a healthcare provider might ask “Why is there an increase in patient dissatisfaction this month in our post-visit surveys?”
Predictive Analysis: This form of analysis is used to forecast something that will happen in the future. For example, a hospital might predict, based on trends observed over the past decade, that incoming cardiac patients will most likely increase by 20% this year.
Prescriptive Analysis: This is possibly the most important form of analysis in healthcare and the trend that is growing quickest. This form of analysis takes pre-existing data and implements treatment plans. For example, a healthcare provider might use a smart device to automatically analyze a patient’s vital signs, preemptively alert them that they’re at risk for developing a medical condition, and instruct them to visit their healthcare provider.
Below are three examples of how healthcare data analytics have affected the healthcare industry.
If there’s one thing we learned from the COVID-19 pandemic it’s that there are a finite amount of hospital beds. While the pandemic might be considered a black swan event, being able to predict hospital bed usage is vital for any working healthcare system. In a form of predictive analysis, French hospitals used an analytics program created by Intel to predict emergency room visits and hospital admissions.
