Little by little, improvements are coming to healthcare systems around the world that are having a real, positive impact on the overall wellness of populations, the quality of individual outcomes, and costs.
Bringing predictive analytics to healthcare is one such development, and it will have a lasting, large-scale impact on the parameters of healthcare that concern us.
Predictive analytics are already used in many industries to streamline business processes and improve decision making. If you’ve applied for a loan or submitted an insurance claim, your submission was likely screened by predictive analytics to vet your application or automatically pay your claim. Predictive analytics are being used in industry to identify machines that are beginning to show early signs of failure. This enables a company to schedule downtime for repairs when it’s more convenient, rather than having a machine fail in the middle of a production run.
A couple of trends are helping bring predictive analytics to healthcare. First is the movement of systems and solutions from legacy systems to platform-oriented, cloud-based technologies. This move is helping unite isolated patient data that existed in many different systems. Second, the volume of data itself is growing. Data collection devices such as the Fitbit and smartwatches, coupled with smartphone apps for fitness, weight loss, sleep and other health-related applications, are just a few of the sources that are generating more personal data that can be fed into predictive analytics to aid in early disease detection, life-style management and other wellness programs.
Analytics can also be used to provide aid in public health emergencies such as the opioid epidemic in the United States. George Mathew, MD, MBA, the chief medical officer for the North American Healthcare organization at DXC Technology, describes how analytics can be used to help fight the evolving epidemic in his white paper, “Fighting the Opioid Crisis with Data, Analytics and Waivers — A Coordinated Approach.”
Dr. Mathew says the Centers for Disease Control (CDC) has been funding several analytics-based initiatives to help states fight the opioid crisis using reporting and analytics. The Prevention for States (PfS) program uses analytics to, among other things, evaluate prescribing patterns to address fraud, waste and abuse, and to identify provider overprescribing (“pill-mills”).
The Data-Driven Prevention Initiative (DDPI) improves data collection and analysis of opioid use, abuse and overdose. It also assesses how to change behaviors that lead to opioid abuse and build community-based prevention programs. The Enhanced State Opioid Overdose Surveillance (ESOOS) program is designed to improve reporting of nonfatal opioid overdoses, using surveillance of emergency departments and emergency medicine services, and to improve reporting of fatal opioid overdoses.
Progress toward saving and improving lives often seems uneven, and always too slow. No one person has exactly the right answer to address all of the issues we face. But with the steady rise of unified systems, more data and the ability to analyze it more effectively, we’re certain to deliver significant health and wellness improvements for everyone.
For more on the role of data and analytics in achieving a proactive real-time approach to a growing healthcare challenge, see DXC’s paper, “Fighting the Opioid Crisis with Data, Analytics and Waivers — A Coordinated Approach.”