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Big Data Applications in Healthcare

Big Data Applications used to refer to data sets that are too large or complex for traditional data-processing application software to adequately deal with. Other concepts later attributed with big data are veracity and value. Big data analytics is the often complex process of examining large and varied data sets or big data to uncover information including hidden patterns, unknown correlations, market trends and customer preferences that can help organizations make informed business decisions.

Big Data Applications in Healthcare

The application of big data analytics in healthcare has a lot of positive and also life-saving outcomes. There is a large amount of data coming in from healthcare systems either from billing systems. There is certainly a large variety of data coming from different sources, in different formats driving the need for a big data approach to tackling all this.

Electronic Health Records (EHRs) can trigger warnings and reminders when a patient should get a new lab test or track prescriptions to see if a patient has been following doctors’ orders. it is the main application of big data in healthcare. Every patient has his/her own medical records such as laboratory tests results, medical reports, lists of medicines, etc. EHRs make it easier to maintain the data and have access to such data.

Real-Time Alerting Clinical Decision Support (CDS) software analyzes medical data on the spot, providing health practitioners with advice as they make prescriptive decisions. Healthcare Systems are looking forward to offering better treatments to their patients by constantly monitoring their health in real-time. Many tools are there which analyze the data of the patient and advice the doctors to take respective actions.

Big data can help cure cancer Medical researchers can use large amounts of data on treatment plans and recovery rates of cancer patients in order to find trends and treatments that have the highest rates of success in the real world.
To make this successful, patient’s database from different health institutions need to be linked up keeping in mind the confidentiality of patient’s data.

Predictive Analytics In Healthcare The goal of healthcare business intelligence is to help doctors make data-driven decisions within seconds and improve patients’ treatment. Predictive analysis leads to patient’s safety and quality care. It keeps doctors informed about the patient’s medical histories and helps predict results for the future.

Prevention of ER visits Hospitals wants to reduce the number of ER visits or Emergency visits of patients. Saving time, money and energy using big data analytics for healthcare is necessary. the system lets ER staff know things like

  • If the patient they are treating has already had certain tests done at other hospitals, and what the results of those tests are.
  • If the patient in question already has a case manager at another hospital, preventing unnecessary assignments.
  • What advice has already been given to the patient, so that a coherent message to the patient can be maintained by providers.

Telemedicine has been present on the market for over 40 years, but only today, with the arrival of online video conferences, smartphones, wireless devices, and wearables, has it been able to come into full bloom. The term refers to the delivery of remote clinical services using technology. It is used for primary consultations and initial diagnosis, remote patient monitoring, and medical education for health professionals.

Healthcare Intelligence Big Data can be used for healthcare Intelligence application. This will help hospitals, payers and healthcare agencies augment their competitive advantages by developing smart business solutions.

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