23-03-24
What is healthcare data analytics?
At its heart, healthcare data analytics is the uncovering of patterns and insights from raw healthcare data like patient histories, bloodwork and genetic trackers to help healthcare providers determine the best course of treatment.
This field leverages technologies like machine learning and data visualization to enhance medical practices, optimize resource allocation, and drive evidence-based decision making in the healthcare industry. In short, healthcare data analytics seeks to transform vast amounts of raw data into meaningful, actionable knowledge.
How to make healthcare data analytics fit for purpose
There are various subsets of healthcare analytics, each serving a distinct purpose:
- Medical data analytics is conducted using data from electronic health records, medical imaging, laboratory tests, and wearable health devices of individual patients. The objective is to gain insights into patients' health conditions and clinical outcomes to enhance healthcare delivery on a patient-specific basis, encompassing diagnosis, treatment planning, and monitoring.
- Clinical data analytics involves analyzing data gathered from clinical care activities, such as patient interactions, medical procedures, and healthcare interventions. The goal is to identify patterns that could enhance clinical workflows.
- Hospital data analytics specifically pertains to the examination of data produced within hospital environments, encompassing administrative data, operational metrics, and financial performance indicators.
While medical data analytics, clinical data analytics and hospital data analytics all target specific facets of healthcare, they each empower healthcare professionals to make well-informed decisions that can lead to revolutionary improvements in patient care and healthcare management.
Four types of healthcare data analytics explained
When looking at the more technical side of healthcare data analytics, we can discern four fundamental types of analytic techniques:
- Descriptive analytics is the initial phase that creates a historical narrative of healthcare events.
- Diagnostic analytics goes a little deeper to identify trends and explain them.
- Predictive analytics uses past and current data to forecast future events. As such, predictive analytics in healthcare is medicine’s attempt at a crystal ball.
- Prescriptive analytics is the final stage. By suggesting actions in response to the predictions made, this analytics process seeks to find a strategy. When done well, it is key to driving informed and data-driven decision making.
