
5 benefits of data analytics in healthcare
- Artificial intelligence (AI) and machine learning (ML) tools
- Cloud computing platforms
- Medical IoT devices
- Health information exchange (HIE) systems
- Blockchain networks
- Descriptive analysis: This involves examining and describing events that have already happened. For example, medical researchers were able to determine how contagious COVID-19 was based on the rate of positive tests among different populations.
- Diagnostic analysis: This approach focuses on discovering the cause or causes of an event. After collecting and analyzing a patient’s symptoms, AI technology can be used to diagnose the illness or injury.
- Predictive analysis: A common practice among businesses in all industries, predictive analytics involves collecting historical data, trends, and other actionable insights to make intelligent projections for the future—then adjusting organizational efforts and allocations based on those findings. Researchers are constantly analyzing healthcare data to forecast the upcoming seasonal spread of viruses like the flu and COVID-19.
- Prescriptive analysis: This process aims to identify actions an organization can take to achieve a certain outcome. When implementing preventative treatment plans for patients, doctors will assess various types of clinical data, such as the patient’s pre-existing conditions and their family’s medical history, as well as relevant historical trends and insights within the medical field.
Superior patient experiences and outcomes
More informed decision making
Real-time updates and alerts
Fraud reduction
High operational efficiency
Partner with Codal to experience the benefits of data analytics in healthcare
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