Data analytics is the science of using various quantitative and qualitative processes to improve productivity and therefore enhance gain in business. Electronic health records and its widening scope is helping to generate big data in the healthcare market. The emergence of cloud storage assists this byreducingthe cost of data technology and tools like data mining, data orchestration, and the analysis of structured and unstructured data. All this means that the data generated can be stored for long periods of time, analyzed, and integrated into healthcare services.
Big Data Analytics in Healthcare
The increasing popularity of smartphones, health apps on smartphones, wearable health devices, and eHealth services has boosted the amount of available data. By 2020, healthcare data is expected to exceed 2,314 exabytes. Most major hospitals and medical providers are using data derived from electronic health records for data analytics. Clinical analytics, for example, helps to reduce medical errors and improve population health management.Financial analytics contributes a larger share of data analytics as it provides healthcare organizations the ability to enhance revenues, lower operating costs and increase shareholder value. It uses specialized software for billing, tracks various claim processes and the revenue generated from different sources.
Healthcare organizations are also using data analytical tools, artificial intelligence and machine learning techniques to receive insights on how to reduce costs of healthcare, improve revenue streams, personalize medicine, and proactively manage patient health.
Demand for Personalized Health Records
The demand for personalized health records is also helping data analytics expand. Patients are learning to store their medical information online, and scheduling appointments using smartphone apps or health provider websites. This is helpful not only for the patients but also for healthcare providers, who can track patient’s medical histories, past surgeries, and healthcare issues and personalize information gathered frompatients.
E-prescriptions is a developing trend, which eliminates the need for paper-based medical prescriptions. Electronic health records can store virtual format materials, which can be accessed by healthcare providers anywhere and everywhere, andmodified or updated as per treatment requirementsforeach individual patient. E-prescriptions also reduce cost duplication and medical errors.
Value-based Patient-Centric Healthcare
The increasing trend towards value-based patient-centric healthcare is also driving data analytics in healthcare. Insurers and other public health-based systems like Medicare are trying to provide patient-centric care with the help of digital technology, electronic health records, and data analytics. Analyzing patient spending patterns, responses to particular treatments, and transparency of billing and health insurance processes are also possible through data analytics. Insurers can also identify anomalies, detect insurance fraud, and target patients needing care using data analytics.
Use of Mobile Apps and Wearable Health Devices
The use of mobile apps and wearable health devices spawned the real-time monitoring of patient health conditions,creating another growth opportunity for data analytics in healthcare. A patient’s vital signs, blood glucose levels, and more can be monitored using readily available real-time sensors. Data patterns generated from this information can help to trigger appropriate responses and treatments by healthcare providers. In remote regions, this can even be a life-saving opportunity.
The global health market for data analytics is expected to reach more than $43 million by the year 2023. In 2017, North America was the largest market for data analytics in healthcare and will continue to be the largest contributor to the data analytics market for some time to come. However, the reduction in the cost of cloud storage, growing digitalization, expanding internet services, and increasing adoption of data analytics in healthcare worldwide is resulting in an unprecedented global expansion. Soon the Asia-Pacific region is expected to grow at a much higher rate, largely due to improvements in their development of data infrastructure and applications.
Most of the key vendors in the healthcare data analytics market are currently focusing on ramping up their software, integrating their hardware, and learning technology to improve their data analytics. Artificial intelligence and machine learning techniques are other technologies being incorporated into healthcare data analytics. The challenges for global data analytics in healthcare include connectivity and linking between databases, security measures to comply with HIPPA and collaborative research. Continuous research and new software development with assistance from hardware and artificial intelligence will help drive and enhance the growing trend of global data analytics.