Key Applications of Big Data and Analytics in Healthcare
healthcaretechoutlook

Key Applications of Big Data and Analytics in Healthcare

Healthcare Tech Outlook | Friday, June 18, 2021

A genuinely data-driven healthcare analytics solution can integrate all data sources and analyze structured, unstructured, and real-time data. 

FREMONT, CA: Healthcare providers identified data and analytics, as well as AI/machine learning, as the most game-changing technology. Big data and analytics are affecting numerous industries, and one of the most visible areas where big data is transforming procedures is healthcare. New patient data sources can provide significant insights to help healthcare providers enhance care quality and streamline operations. Breaking down data silos to merge medical data from different sources and acquire a holistic perspective of your business from one source, rather than various, fragmented sources, is one of the most challenging difficulties of big data in healthcare.

Examine electronic health records (EHRs)

Electronic health records are one of the most common applications of big data in healthcare. EHRs manage and record your patient's health data, including pre-existing conditions and allergies, eliminating unnecessary testing and the expenditures that come with them. Sharing patient data among healthcare practitioners while treating patients can help eliminate duplicate tests and improve patient care.

Lower hospital readmissions

Hospital costs rise due to increased readmission rates within a month following discharge. Healthcare professionals can detect at-risk patients using big data by analyzing patient trends, medical history, diagnostic information, and real-time data from medical equipment. Hospitals can provide lower readmission rates to these patients, allowing them to focus on their treatment rather than their healthcare costs.

Implement evidence-based medicine

Doctors perform tests when a patient is admitted to the hospital to determine the symptoms and the underlying ailment. Evidence-based medicine allows healthcare providers to collect evidence of a patient's health and compare it to a more extensive patient database, allowing for faster, more accurate, and better diagnosis and treatment. Big data aids in consolidating and analyzing information from this massive patient database derived from various divergent sources.

Improve supply chain processes

Big data is essential throughout the healthcare supply chain, from order placement to order fulfillment and billing. Real-time visibility into supply chain processes can assist hospitals in avoiding supply round-tripping and wastage, which are both costly and impact care delivery. Supply chain data analytics automates typical procurement operations, freeing up staff to focus on strategic objectives.

Fraud detection and prevention

Fraud in healthcare can range from actual billing errors to fake claims that result in incorrect payments. Hospitals must store and sort large amounts of shares, billings, and other data. Detecting fraud and gathering evidence for legal action takes time and can result in significant financial damages for the company. Big data analytics may assist spot anomalies considerably faster and tell you immediately, significantly reducing the risk of healthcare fraud.

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