Kindled Hope of Boosting Healthcare through Big Data and Predictive Analysis
“As data piles up, we have ourselves a genuine gold rush. But data isn’t the gold. I repeat, data in its raw form is boring crud. The gold is what’s discovered therein.”
Since childhood we have been studying history and the sole reason behind it
is, it teaches a lesson which helps us in making right decisions in the future. Similarly big data has a lot to tell & predictive analysis utilizes that knowledge of big data, it studies, history of data and comes up with patterns which will help you predict the future events, it helps us in leveraging technology to make the world a better place to live, and for this, healthcare is the best example to count on.
Beside fixing misapplication of overhead and bettering profits, healthcare is using Big Data for predicting epidemics, recovery of diseases, preventive health care lifestyle to inhibit preventable deaths.
Let’s see the ways in which Big Data and Predictive Analysis are helping hospitals through Real Life Examples:
Ensuring Quality, Patient Experience and Safety through EHR
- Researchers at the University of California, Davis are using data collected through EHR as the fodder for building up an algorithm that gives an early warning about sepsis, which has 40% of mortality rate and is difficult to detect until it’s too late. “Finding a precise and quick way to determine which patients are at high risk of developing the disease is critically important,” said study co-author Hien Nguyen, Associate Professor of Internal Medicine and Medical Director of EHRs at UC Davis.
- Predictive Analytics is also on a roll these days. Recently, an analytics system called QPID system in Massachusetts General Hospital has been in vogue, which responsibly maintains finicky patient data during the process of treatment. It also predicts any surgical risk beforehand and suggests best suited program for the patient. “The system automates searches using national guidelines, and then it essentially shows the results in a dashboard with a red, yellow, or green risk indicator for the surgeon to see” explained Dr. David Ting, Associate Medical Director of Information Systems at the Massachusetts General Physicians Organization.
Precision Medicine: Trying to Find Out the Roots of the Complication
“Precision medicine” entered the healthcare industry’s lexicon in a big way earlier this year during President Obama’s State of the Union address. Now it is showing notable progress in the field:
- Oncology– Corey wood, a young woman, inspired many by her story. She was diagnosed with lung cancer, via a Foundation Medicine test, to have a mutation for which a category of targeted therapies was available.
- Mendelian Disease– Consider the inspiring story of Bill Elder Jr., a patient (and medical student) with cystic fibrosis caused by a relatively unusual mutation, for which a targeted therapy (Vertex’s ivacaftor) is available.
- Infectious Disease– Osborn, a 14 year old boy from New York was identified and treated for a life-threatening occult infection caused due to a pathogen which was spotted by a genetic testing approach pioneered by UCSF’s Charles Chiu; he recovered completely. Chiu recently received funding from the California Precision Medicine Initiative to expand this approach (disclosure: DNAnexus is involved in the effort).
Abating Hospital Readmissions
Analytics is helping many hospitals at the time of financial pinch to reduce readmission. Texas hospital noticed the change after usage of EHR data analytics by five percent by drawing on nearly 30 data elements included in the patient’s chart. “This is one of the first prospective studies to demonstrate how detailed data in EMRs can be used in real-time to automatically identify and target patients at the highest risk of readmission early in their initial hospitalization when there is a lot that can be done to improve and coordinate their care, so they will do well when they leave the hospital,” said Ethan Halm, MD, MPH, Professor of Internal Medicine and Clinical Sciences and Chief of the Division of General Internal Medicine at UT Southwestern.
There is pool of opportunities for big data in healthcare industry, although huge investments are required to manifest in real time, many big names are emerging as investors in this enterprise.
Even after crossing the investment pit, there remains a substantial problem of the protection of privacy of the patient and the security of all that data. Easy access to so many different people will ease access to controversial patient data, therefore, privacy and security have to be on top of the list for any healthcare organisation that wants to move into the big data era.
If you know any other real time utility of Big Data and Predictive Analysis in healthcare or any other industry, please share with us.