The healthcare industry has experienced much progress in data management and analysis. This includes more than a decade in the large-scale digitisation of medical records, as well as the aggregation of research and development in electronic form. In addition, governments have also accelerated the move towards transparency, making stored data more accessible to the industry as a whole.
These shifts towards greater data liquidity—the ability of patient data to move throughout the healthcare system securely and usefully—is promising newfound knowledge that can transform healthcare outcomes via Big Data and predictive analytics.
Discussed extensively, now what?
Big Data and predictive analytics have been discussed extensively in healthcare, and many healthcare organisations have invested in various Big Data initiatives.
According to a survey from PwC, 95% of healthcare CEOs said they’re exploring better ways of using and managing Big Data. But large gaps remain in what they’ve accomplished toward their goals. As an illustration, only 36% made any headway in getting to grips with Big Data.
So, how can healthcare providers and professionals maximise the value of Big Data analytics in achieving patient outcomes? How can healthcare leaders harness a data-driven approach to run the organisation more efficiently and effectively?
With the buzz shifting towards how the healthcare industry can use new technologies such as artificial intelligence, robotics, and virtual reality, it is particularly pertinent for healthcare organisations to review this area.
The crux of data’s value: Speed
Data’s value can only be truly unlocked when healthcare organisations are able to analyse it quickly and push it digitally to all appropriate parties. While data collection is important, it is the agility in integrating disparate sources of data, and the swiftness that the data is forwarded to those who need it that will make the difference.
Data needs to get into the hands of healthcare practitioners so that they can improve patient outcomes. It also needs to get to healthcare administrators so that they can gain cross-functional visibility and collective insights into quality and cost-saving measures. And medical researchers need to access and analyse—in real time—large volumes of healthcare data from diverse sources to advance opportunities for personalising medicine for each patient.
Data needs to get into the hands of healthcare practitioners so that they can improve patient outcomes.
This is often challenging as the healthcare industry generates extremely complex data over an increasingly larger footprint of care settings. But speed is crucial, and leading healthcare organisations understand it.
Leading healthcare organisations: Learning from their successes
In fact, their actions show it.
Mercy is one such example. Mercy, a U.S. healthcare provider with more than 40,000 employees, serves millions of patients at its 43 acute-care and specialty hospitals and 700 physician practices across Arkansas, Kansas, Missouri, and Oklahoma. The organisation wanted to provide its physicians and clinical teams with more accurate and timely information at the point of care to improve patient outcomes. It also wanted to reduce variations in clinical care across hospitals and physician practices to standardise best practices and increase operational efficiency. This led to Mercy’s Big Data analytics business transformation, which allowed it to achieve breakthrough outcomes.
Mercy eliminated three hours from the time needed to administer critical medications to patients suffering from heart failure and pneumonia. This helped Mercy reduce mortality rates to less than half the national average. In addition, Mercy realised US$65 million in additional revenue by improving clinical documentation to ensure physicians properly capture a clinical diagnosis. The organisation also saved US$9.42 million by eliminating or minimising use of specific surgical products, reducing variation in surgical protocols, and establishing best practices across surgical departments to ensure quality in postoperative results for patients.
As a result, Mercy won the HIMSS Nicholas E. Davies Award of Excellence in 2016, which recognises healthcare organisations that use health IT to improve patient care while also reducing costs. It received the Gartner 2016 Healthcare Supply Chainnovators Award for saving upwards of $9 million last year in surgery-related costs. Mercy also won the Analytics Wizard Category at the SAP HANA Innovation Awards at SAPPHIRE NOW in 2016 by showing how real-time analytics helped them save millions while empowering the workforce and their patients.
2. Seoul National University Bundang Hospital
The Seoul National University Bundang Hospital (SNUBH) offers another excellent example. First in the Asia-Pacific region to have a fully digitalised paperless hospital, SNUBH is the digital cornerstone of the South Korean national healthcare system. Since starting to operate its data warehouse in 2004, data query times were slow and inconsistent. SNUBH needed to manage more data in less time. The organisation also wanted to improve management and monitoring of 350 clinical indicators to stay competitive, as well as provide physicians and researchers access to relevant data in real time.
These objectives drove its data-driven business transformation. SNUBH now takes less than 2 seconds to analyse quarterly data, a process that previously took one to two months. The hospital also achieved 700 times faster retrieval on up to ten years of research data. And according to PwC, SNUBH will attain a 147% return on investment within five years.
The data advantage
Many trends drive innovations in healthcare, and it is important to watch all of these. But it’s also important to remember that healthcare organisations can do much more when they deepen their capability in driving data-driven innovation.
Taking advantage of in-depth data analysis, predictions, processing complex events, and combining data from a variety of sources into one integrated platform can result in significant cost savings, dramatic improvements in patient outcomes, and a path to precision medicine.
How can healthcare organizations reap the data advantage? Download these resources for the healthcare industry to find out more.
This blog originally appeared in the Digitalist.