Emergence of Big Data in healthcare and its impact on healthcare analytics market growth and set to exceed USD 18,250.8 million by 2025
There has been a significant paradigm shift in recent years pertaining to the collection, storage, maintenance, management and analysis of data. Over the years, bolstered by the wave of digitalization sweeping across the globe, data collection is transitioning gradually from paper-based charts to digital real-time analytics systems.
This new data ecosystem is designed not just to enhance disease prevention rates but also to improve medical diagnostics, administer medications securely and augment overall treatment processes. Consequently, healthcare offerings are evolving from a one-size-fits-all approach to more patient-centric, customized treatment plans.
The rising prevalence of big data owing to digitization of analytics is promoting the adoption of electronic health records or EHRs for patient’s health data collection, which is likely to add great impetus to global healthcare analytics market expansion.
The evolution of the healthcare landscape is generating immense demand for advanced healthcare data analytics.
Healthcare analytics or clinical data analytics entails the use of EHRs to garner actionable insights into patient’s health condition and develop suitable treatment plans.
As the number of patients seeking healthcare solutions continues to surge and resources continue to deplete, conventional claims-based analytics systems are unable to accommodate the rapidly arising healthcare issues. This combined with the immense capacity of clinical data in EHRs is a major driving force behind the popularity of advanced healthcare analytics.
Considering the prolific expansion of the healthcare industry, numerous industry players are making persistent efforts towards enhancing health data analytics systems to streamline patient care.
For instance, InterSystems has recently partnered with digital engineering expert Virtusa in a bid to advance healthcare data analytics capabilities in vLife, Virtusa’s cloud-based life sciences platform.
The system comprises a robust, HIPAA-compliant data repository with multiple sources of data. Additionally, the platform features pre-built APIs as well as AI and machine learning-based models.
Prediction to Prevention – The Significance of Predictive Analysis in Healthcare Applications
Predictive analytics is a sophisticated healthcare data analytics tool that leverages historical data and real-time information in order to forecast potential outcomes. Considering the healthcare landscape, predictive analytics can be applied to consumer, claims or patient data through which healthcare workers can predict patterns or trends which can help enhance patient care or outreach programs.
To illustrate, according to a 2017 study, the University of Pennsylvania utilized a predictive analytics tool integrated with machine learning and EHR information to detect severe sepsis or septic shock in on-track patients, nearly 12 hours before the condition manifested.
Burgeoning need for Real-Time Healthcare Solutions
Empowered by the digital revolution, a large number of healthcare management systems are now leveraging real-time, event-driven data feeds.
Since healthcare is a real-time activity, the ability to accumulate health-related data in real-time is a great boon for healthcare workers and clinicians. It gives them the ability to make point-of-care lifesaving decisions and reduce the dependency on resources, thereby cutting back treatment costs to a significant extent.
Real-time analytics demonstrate great potential in various healthcare-related scenarios; for instance, in the case of a patient’s blood pressure signifying an alarming increase, the healthcare analytics will send a real-time report to the doctor, who can immediately act on administering suitable measures to counteract the condition.
Many prominent industry players are working towards adopting real-time monitoring into their product innovations. For example, Apple has just revealed a new Apple Watch Series 4 with an integrated EKG (electrocardiogram) features, which helps users track their cardiovascular information in real time and alert them to any undiagnosed conditions.
Healthcare Analytics Transformation through Big Data
The emergence of big data has brought about a tremendous shift in the way data is collected, analyzed and used in a plethora of industries. Big data comprises large quantities of data generated through digitization of myriad sources, which is then merged and analyzed by specialized technologies. When used in healthcare analytics, big data makes use of population or individual-specific health data which can potentially mitigate the risk of epidemic, treat maladies and reduce costs, among other benefits.
In light of the changing healthcare spectrum, more and more physicians are basing their decisions on ample quantities of clinical data instead of simply asserting their professional theoretical opinion.
With the healthcare industry swelling and more and more data being collected, professionals need a support system to ensure proper management and application of data. This is perhaps why the demand for big data analytics across the healthcare sector is witnessing such tremendous growth.
The U.S healthcare analytics market is currently making immense strides in big data analytics, by ensuring the adoption of EHRs across nearly 94% hospitals. A major industry player in the U.S market is Kaiser Permanente, who has developed and integrated a novel system called Health Connect. This system allows data sharing across multiple facilities and streamlines the use of EHRs.