When combined with a suite of business analytics tools and data visualization, health analytics helps managers perform better, providing real-time insights that can inform decisions and deliver actionable insights. With the richness of information provided by healthcare data analytics, providers and administrators are now empowered to make better healthcare and financial decisions, all the while providing ever-improving quality patient care. For hospitals and health care managers, healthcare data analytics provides a mix of financial and administrative data along with insights that can help with the efforts to provide patient care, improve services, and enhance existing procedures. Using health data analytics allows improvements in patient care, faster and more accurate diagnoses, prevention measures, more individualized treatments, and better decision-making.
It is not only providers, but legislators and researchers, that are turning to big data analytics and predictive models to help assign resources, anticipate spikes, improve care and outcomes, and implement preventive measures. Despite these challenges, a handful of new technical improvements are enabling the transformation of health data into useful, actionable insights. Global health systems are increasingly embracing data-backed decision-making tools to improve outcomes and patient experiences. Undoubtedly, embracing use of healthcare’s Big Data could change the health industry, moving it from a fee-for-service model toward value-based care.
Growth in the global marketplace is driven in large part by factors like rising VC funding, public efforts to increase the usage of EHRs, increasing pressures to lower healthcare costs and improve patient outcomes, increasing relevance of real-world data, as well as the value-based care, as well as growth of Big Data analytics. The visibility of health analytics has grown due to multiple factors, such as stakeholders’ hunger for information; the need for managing massive, heterogeneous data; growing competition; increasing regulatory complexities; and advances in technology within healthcare. As more data becomes available from sources like EHRs, claims, wearable health devices, social media, and patients themselves, analytics may help more and more detect patterns in the information, provide actionable insights, and allow autonomous systems to predict, extrapolate, and envision alternatives that may not be apparent otherwise. Building analytics capabilities can help healthcare organizations leverage big data to generate actionable insights that can be used by providers, hospital, and health systems leaders, and people across the public and private sectors of healthcare delivery to enhance outcomes, providing value for people served by providers.
To improve the performance of current health systems, integrating big data into healthcare analytics may be one of the main factors; however, complex strategies must be developed. This critical use case of big data in healthcare is indeed evidence of medical analytics being life-saving. Through the data-driven analysis of genetic information, and also the reactive predictions within patients, big data analytics in health care could be crucial to developing groundbreaking new drugs and future-proof therapies. In fact, by 2030, global health care spending is estimated at a staggering $15 trillion.1 Digital health brings together a wide range of industries, including genomics, injectables and implants, wearables, sensors, retailers, social media, artificial intelligence, analytics, clinical data, and electronic health records.
