How Big Data is Optimising Healthcare

Big data has proven to be immensely beneficial in the optimization of numerous processes in various sectors. Healthcare is one such sector where Big data is aiding in advancements of current procedure and providing new perspectives as well. Big data analytics have the potential to significantly reduce treatment costs, predict outbreaks of epidemics, avoid preventable diseases.

Big data analytics helps doctors to understand the patients well and take preventive measures well in time. Following are the ways Big data analytics has playing a significant role in optimizing healthcare Industry.

Better staffing with patients footfall prediction

One of the challenges Hospitals face today is to predict the patient’s footfall for various time slots and put the staff on duty accordingly. Shift managers face this critical issue every day. If too much staff is assigned on duty, it results in higher costs while the opposite will result in poor customer service and in case of emergencies it can turn out to be disastrous.

Big data come to the rescue to this problem, hospitals which are part of the Assistance Publique-Hôpitaux de Paris have been using big data collected from a variety of sources to analyze with daily and hourly predictions of how many patients are expected to visit and put staff on duty accordingly.

Real-time symptom analysis and cure

Big data analysis plays a crucial role in the real-time analysis and cures it by real-time alerting. Real-time alerting can prove to be a life-saver in critical circumstances. For example, If a patient’s blood sugar increases to a dangerous level, the system will alert the doctor in real time enabling them to take action to reach the patient and administer measures to lower the blood sugar.

Predictive-analysis in Healthcare

Optum Labs a US-based research firm analyzed electronic health records of over 30 million patients and created a database for predictive analytics tools that will help doctors make data-driven decisions within seconds and improve patients’ treatment. This is extremely useful for patients with complex medical history and for the patients who are at a higher risk of life-threatening or life-altering disease. New tools would also be able to predict disasters and give advise to make use of additional screenings or and preventive measures.

Prevent Opioid abuse

Opioid abuse is a problem about which Medical practitioners are concerned today. The situation is getting critical as opioid abuse is increasing. Here again, Big data analytics can provide the solution we are looking for.

Data scientists at Blue Cross Blue Shield with analytics experts are working at Fuzzy Logix to form a logic where a person having a high risk of opioid can be identified. Using years of insurance and pharmacy data, Fuzzy Logix analysts have made a list of 742 risk factors that indicate a high risk of opioid abuse. The preventive measures can be taken beforehand to eliminate the occurrence of opioid abuse.

Reducing the cost of the treatment

Knowledge extracted from the analysis of big data enables healthcare providers to gain insights not otherwise available. For example, The Mayo Clinic is utilizing big data analytics to identify patients with more than one chronic condition (comorbidity)and are likely to benefit from early interventions at care homes. It will save them unnecessarily from visits to the emergency department.


Big data is undoubtedly proving to be a boon for the healthcare sector. In the times to come, we will be able to witness many more applications of big data as Big data analytics is still unfolding many more ways it can save human life.


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