Big Data has transformed the way we handle, analyze, and make use of data in any industry. One of the areas where its application has immense importance is healthcare. The healthcare industry faces various challenges, including maintaining optimal operational efficiency, securing health records, real-time monitoring of health, etc., and big data analytics help in solving them. Today, we are witnessing the role played by innovative technologies such as Artificial Intelligence in the Healthcare Industry. Big Data has a highly significant role in this area, and it enables the healthcare sector players to offer more efficient insights and operations into the patients and their health condition.

With a massive volume of data like clinical, financial, administration, R&D, operational, and financial data available in the healthcare sector, big data analytics can derive meaningful insights to enhance the operational efficiency of the industry. The evolvement of the healthcare data analytics sector also signifies the quick adoption of big data in the healthcare sector. There is an incredible number of potential applications for big data in healthcare, and this article explains the significant ways this industry can leverage big data.

Looking forward to a career as a Hadoop Developer? Check out the Big Data Hadoop Certification Training Course and get certified today.

Big Data in Healthcare

1. Improving Operational Efficiency

The significance of big data in the healthcare industry is highlighted by the fact that healthcare organizations utilize it as part of their BI (Business Intelligence) strategy. For example, the shift managers face the problem of how many people should put on staff at any given point in time. They may experience unnecessary labor costs if they put too many people, and there is also a risk of having poor customer outcomes if they put very few people, which can be fatal for patients. 

So, by analyzing historical patient admission rates and examining the efficiency of staff, shift managers can optimally allocate healthcare personnel to a specific shift without having to understaff or overstaff. Predictive analytics is significant in attaining the goal of cutting down on health care costs and providing better care simultaneously.

2. Electronic Health Records (EHRs)

EHRs are patient-centered and real-time records that make information available securely and instantly to authorized users. They store the treatment and medical histories of patients electronically by replacing the traditional paper-based health records. These records enable healthcare practitioners to have much easier access to data and help them in providing quality care.

EHRs provide timely information that healthcare practitioners require to create customized reports. You can control data access making sure that only the authorized personnel can view sensitive patient information. The other opportunities for EHRs include a quick understanding of the causation and progression of a disease, improving existing models of care and research with greater efficiency, triggering reminders and warnings when a patient should get a lab test done, minimizing medical error by enhancing the clarity and accuracy of medical records, reducing delays in treatment and duplication of tests, etc.

Although EHR is a great idea, many nations are still struggling to implement them thoroughly. While the main objective of EHRs is to obtain meaningful, significant data insights from the health workflow, only a few healthcare practitioners are able to exploit widely analytic tools. This is attributed to the fact of having to handle multiple steps and systems, which discourage them from involving more. However, a rapid increase in the annual adoption rates of EHRs was witnessed after the HITECH Act. A report on the significant data healthcare by McKinsey states that “The integrated system has better outcomes in cardiovascular disease and attained an estimated $1 billion in savings from decreased lab tests and office visits.”

3. Real-Time Alerts

A real-time application known as the Clinical Decision Support (CDS) can provide a prescription after examining the patient’s medical data. This helps doctors monitor the health conditions of their patients on the spot and revert when needed. 

To avoid in-house treatments that involve high cost, doctors want their patients to stay away from hospitals. Personal analytics devices will collect the health data of patients continuously and send it to the cloud. Also, this data will be accessed to the database on the state of the general public’s health, which will enable doctors to compare this information in the socioeconomic context and alter the delivery strategies accordingly. The care managers and institutions utilize sophisticated tools to monitor this huge data stream and react whenever the results are disturbing.

For example, if a patient is suffering from blood pressure issues, then the doctor can receive an alert when the patient’s blood pressure rises alarmingly so that he/she can take necessary action to lower the pressure.

Big Data Hadoop Certification

4. Improve Patient Engagement

Consumer interest in smart devices that record heart rate, hours slept, steps are taken, and other data daily reveals that introducing these smart devices as a physician aid could help enhance patient engagement and outcomes.

For example, a high heart rate and chronic insomnia can signal a risk for heart disease in the future. Patients are involved directly in monitoring their health, and health insurance incentives can enable them to lead a healthy lifestyle(for example, giving the money back to people utilizing smartwatches). 

Another way to improve patient engagement comes with new wearables under development. These wearables can track particular health trends and relay them to the cloud where the healthcare practitioners can monitor them. That is quite helpful for everything starting from blood pressure to asthma and helps patients stay independent and reduce unneeded doctor visits. 

Conclusion

In today’s world, big data has become an essential tool since its use cases are going broader than we initially thought possible. It is helping businesses, be it healthcare or social media, to obtain higher productivity. Big data has provided a new way for the healthcare industry to boost up the outcomes, organize their future vision, reduce time to value, and develop actionable insights. The applications mentioned above of big data in healthcare will enable physicians to serve the needs of healthcare consumers better.

Recommended Reads