Analyzing Electronic Health Records (EHRs)

Aggregate and analyze data for trends that can reduce healthcare costs. Sharing data between physicians and healthcare providers as they examine patients can reduce duplicate tests and improve patient care.

Analyzing Hospital Networks

Analyze trends in hospital care by using big data. For example, the administration might be able to determine that one surgeon was prescribing post-operative antibiotics that were less effective against infection.

More Efficient Medical Practice

 Using big data, the practice  analyze more  processes and procedures. As a result, the practice is able to streamline workflow, shift clinical tasks from doctors to nurses, reduce unnecessary testing, and improve patient satisfaction. Big data made it clear where processes could be improved.

Protecting Patients’ Identity

 Insurers  use big data analytics in order to detect medical fraud and identity theft and predict which types of treatment plans are more likely to succeed.

Reducing Hospital Readmissions

Using big data analytics in order to identify at-risk patients based on past history, chart information, and patient trends, hospitals can identify at-risk patients and provide the necessary care to reduce readmission rates.

Control Data for Public Health Research

Using big data,Medical offices and hospitals submit data about medical conditions and immunizations. Using analytics normalizes, raw patient data to fill gaps in public health records that can affect regulations as well as provide better care.

Evidence-Based Medicine

 Big data assimilates information from different sources and normalizes the data, so one record that describes “high blood pressure” maps to another that describes “elevated blood pressure.