Thanks to improved healthcare services, today, the average human lifespan has increased to a great extent. While this is a commendable milestone for humankind, it also poses lots of new and diverse challenges for health care providers (HCPs). They face increasing amounts of challenges in delivering healthcare services to patients. This is where Big Data comes in the scenario.
Big Data in healthcare pertains to the massive amounts of healthcare data gathered from multiple sources such as pharmaceutical research, electronic health records (EHRs), healthcare wearables, medical imaging, genomic sequencing, and other such processes. The digitization of healthcare information and the increase in demand for value-based care are the primary reasons behind the rapid rise in Big Data in healthcare. As the ever-increasing pile of healthcare data continues to pose new challenges for HCPs, it calls for the adoption of Big Data technologies and tools that can efficiently collect, store, and analyze large datasets to deliver actionable insights.
Rise of Big Data in Healthcare
The adoption of Big Data in healthcare has been quite slow compared to other industries (manufacturing, BFSI, logistics, etc.) due to reasons like the sensitivity of private healthcare data, security issues, and budget constraints, among other things. However, a report by the International Data Corporation (IDC) sponsored by Seagate Technology maintains that Big Data is likely to grow faster in healthcare than in sectors like media, manufacturing, or financial services. Furthermore, estimates suggest that healthcare data will grow at a CAGR of 36% all through till 2025.
As of now, 2 primary trends have encouraged the adoption of Big Data in healthcare.
- The first push came from the transition from the ‘pay-for-service’ model (it offers financial incentives to HCPs and caregivers for delivering healthcare services) to a ‘value-based care’ model (it rewards HCPs and caregivers according to the overall health of their patient population). This transition has been possible because of the ability of Big Data Analytics to measure and track the health of the patients.
- The second trend is where HCPs and medical professionals leverage using Big Data Analytics to deliver evidence-based information that promises to boost the efficiencies of healthcare delivery while simultaneously increasing our understanding of the best healthcare practices.
Bottomline – the adoption of Big Data technologies in healthcare holds the potential of transforming the healthcare industry for the better. It is not only allowing HCPs to deliver superior treatments, diagnosis, and care experiences, but it is also lowering healthcare costs, thereby making healthcare services accessible to the mass.
Applications of Big Data in Healthcare
- Health Tracking
Along with the Internet of Things (IoT), Big Data Analytics is revolutionizing how healthcare statistics and vitals are tracked. While wearables and fitness devices can already detect heart rate, sleep patterns, distance walked, etc., innovations in this front can now monitor one’s blood pressure, glucose levels, pulse, and much more. These technologies are allowing people to take charge of their health.
- Episode Analytics
HCPs are always struggling with offering quality healthcare services at marginalized costs. Episode Analytics and Big Data tools are helping solve this dilemma by allowing HCPs to understand their performance, to identify the areas that offer scope for improvement, and to redesign their care delivery system. Together, all of this helps to optimize the processes as well as reduce the costs.
- Fraud detection and prevention
Big Data Analytics and tools come in very handy to detect and prevent fraud and human errors. These can validate the patient data, analyze his/her medical history, and point out any out of place errors in prescriptions, wrong medicines, wrong dosage, and other minor human mistakes, thereby saving lives.
- Real-time alerts
Big Data tech allows HCPs and medical professionals to analyze data in real-time and perform accurate diagnoses. For instance, Clinical Decision Support (CDS) software can analyze medical data on-spot, thereby offering crucial medical advice to healthcare practitioners as they diagnose patients and write prescriptions. This helps save a lot of time.
- Telemedicine
Thanks to Big Data technologies, we are now able to make full use of Telemedicine. It allows HCPs and medical practitioners to deliver remote diagnosis and clinical services to patients, saving them both time and money.
In the future, the healthcare sector will see a lot more of Big Data applications that will revolutionize the healthcare industry one step at a time. Not only will Big Data help streamline the delivery of healthcare services, but it will also allow HCPs to enhance their competitive advantage through smart business solutions.
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