Providing personalized medicine for HIV patients or identifying a person’s risk of suffering a heart attack: Big Data technology uses sophisticated analytics to deliver better health outcomes for patients.
Every single day, gargantuan streams of data pass through networks and data centers all over the world. In the healthcare sector particularly, vast amounts of data are generated as a result of medical tests and examinations ― including patient records, radiology images, and digitalized lab results. PHEMI, a supplier of systems for analyzing patient data, offers solutions that simplify the challenge of turning information into actionable insight.
Calculating risk with SAP HANA and predictive analytics
The Big Data warehouse from SAP and PHEMI aims to improve clinical care for patients and help medical facilities cut their costs. For example, by using predictive analytics in SAP HANA to analyze data collected from heart attack victims, SAP HANA can calculate predictive values and gives clinicians a risk score so that they can determine a patient care plan. These are used to identify patients who are particularly at risk of suffering a repeat heart attack and need to be kept under observation and those who have a low risk and can be discharged from the hospital.
“Patient re-admissions are a major cost factor for clinics, and heart attack is one of the 10 most common reasons for readmission,” says Adam Lorant, Vice President Marketing and Product Management at PHEMI.
Predictive analytics in SAP HANA uses historical data collected from a large number of patients and takes account of hundreds of clinical parameters to calculate risk values. Physicians can use the predictive values calculated by SAP HANA as a basis for assessing a patient’s health risk. This not only helps reduce the number of hospital readmissions, it also provides patients with a greater degree of reassurance.
Personalized medicine delivers greater success
In the case of HIV patients, DNA sequencing helps enable personalized medicine. In this procedure, algorithms are applied to genetic material from patient blood samples in order to select the most appropriate drug for a particular strain of HIV. The results of DNA sequencing provide insight into which is the best treatment plan for an individual patient and the ideal drug combination and dosage for that patient.
The Big Data warehouse from SAP/PHEMI provides the ideal location for storing, mining, and comparing the data obtained from DNA sequencing and clinical results. And thanks to SAP HANA DNA sequencing is now speedier and can be performed on massive volumes of data ― because the analysis takes place in real time. Which means that patients benefit from personalized medicine much faster.
According to the current state of research, personalized medicine promises to be extremely effective in reducing the risk of spreading HIV and keeping the level of virus in the patient’s blood as low as possible. As such, every patient benefits from receiving their very own personalized drugs.
As well as offering powerful technology, the Big Data architecture must ensure compliance with data protection laws. The PHEMI Central data warehouse stores, archives, and monitors clinical data while adhering to data protection requirements. When clinics need data for research and developmental purposes, they have to be sure that no associated private information is passed to unauthorized parties. PHEMI’s healthcare database incorporates “Privacy by Design” principles, which means that, when reading data, it can remove associated private data automatically. Read authorizations are based on user attributes, access guidelines, or legal provisions.
Gaining insight with the Big Data warehouse
Medical facilities need to access multiple, disparate datasets and data sources that are highly complex to manage.
“More than 70 percent of healthcare information is unstructured and difficult to mine for relevant insight using traditional methods,” says Dr. Paul Terry, CEO of PHEMI Health Systems.
The Big Data warehouse from SAP and PHEMI gives enterprises access to hundreds of different sources of information. By curating that data, it helps hospitals and clinics get the most out of the information they possess. It aggregates both structured and unstructured datasets and transforms unstructured information into actionable data.
“New data sources can be added 35 percent faster than with a conventional enterprise data warehouse,” says Lorant.
Within the data warehouse, PHEMI Central, a kind of digital data library, is responsible for pulling information from the various clinical sources, cleansing, and curating it. It then feeds the curated data to the SAP HANA platform for data modeling and analysis. The aim is to analyze data faster and with a greater degree of automation so that scientists and medical professionals can benefit rapidly from valuable information that would otherwise be locked into terabytes of unstructured datasets. This automatic analysis saves health organizations money and frees up medical personnel to spend more time with their patients — which means better healthcare all around.
Based in Vancouver, Canada, PHEMI is a member of the SAP Startup Focus program, which helps fledgling enterprises in the Big Data, predictive, and real-time analytics space develop new applications on SAP HANA and accelerate market traction.
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