How Big Data Is Improving Health Outcomes for Seniors
In health care, big data is a popular topic. With electronic medical record (EMR) use in full swing and advances in a variety of sensor-based technologies, there is a growing wealth of health data available to help improve care. For seniors, the optimized collection and use of such data can make a significant difference in meeting health care’s Triple Aim of improving the health of populations, enhancing the care experience, and reducing the cost of doing both. Here, we’ll examine how big data is helping to improve health outcomes for older Americans.
Collecting Health Data
There are a number of methods in which data is being collected across the health care system, including EMR systems, health surveys, administrative enrollment and billing records, social media, health apps, wearable devices, various medical devices and remote monitoring systems. Although seniors are often perceived as being less tech savvy, a Pew Research report published in 2014 indicates otherwise, finding that 59 percent of adults 65 or older use the internet, 47 percent have a broadband connection, and 77 percent have a cellphone. Although results indicated that tech usage decreases significantly beyond 75 years of age, and was lower for those with disabilities that made such use difficult, seniors who do adopt technology seem to stick with it: “When it comes to technology, most seniors who become internet users make visiting the digital world a regular occurrence.”
The type of data collected varies depending upon the application in use. EMR systems gather a plethora of clinical data points, as well as demographic, financial and other data. In addition to data obtained through the EMR, real-time data related to chronic diseases — such as blood sugar, blood pressure, heart rate, weight and sleep patterns — can be obtained and transmitted wirelessly via wearable devices with embedded sensors and other remote monitoring devices. This provides a variety of benefits for seniors, including the ability to receive care at home, timely alerts of symptoms to support early intervention and the reduction of costs for providing care.
Using Health Data
Health data is stored in a variety of formats, and covered entities who create, receive, use or maintain such data are responsible for security and adhering to legal regulations. Legacy systems have typically relied on server-based storage, but as the volume of data grows exponentially and the need for more integrated care increases, more health care providers are adopting Cloud technology to house it. In addition, there is a growing recognition of the benefits of more coordinated efforts for data sharing, as well as open access to anonymous data to support better care and innovation—which is why the federal government has several initiatives in place to do just that.
In a recent interview, Sam Hanna, director of The George Washington University’s online masters in health informatics program, discussed the great benefits that can be achieved when health care systems begin to use the wealth of available health data to its full potential:
“The data’s there and only a sliver of that data is being really touched or massaged in a way that enables better decisions, because [health care systems] don’t really know what to do with it. There are so many different ways you can slice and dice this data. You can use it for clinical trials, you can use it for research, you can use it for pharmaceutical research.
We have so much information that we are not using, and I think that’s where the next frontier is. By having a better-educated workforce in informatics, they’ll be able to look at this and say, you know, we’ve made this decision based on this limited set of data or facts that we know, but what if we knew 10 more data points? Are our decisions going to be better? Are they more improved? That’s where the industry’s going.”
As health care systems become increasingly savvy about how best to use data, predictive analytics for decision-making will expand beyond the business office to the bedside as clinical analytics assume a greater role in care. As the authors of “Big data analytics in healthcare: promise and potential” note,
“By discovering associations and understanding patterns and trends within the data, big data analytics has the potential to improve care, save lives and lower costs…. When big data is synthesized and analyzed — and those aforementioned associations, patterns and trends revealed — healthcare providers and other stakeholders in the healthcare delivery system can develop more thorough and insightful diagnoses and treatments, resulting, one would expect, in higher quality care at lower costs and in better outcomes overall.”
Improving health outcomes for seniors
For seniors, optimal use of big data can help to improve health outcomes in a number of ways. The health of many seniors is fragile, and the use of predictive models and evidence-based care that can be achieved through clinical analytics may support earlier intervention for individuals who may be more prone to rapid decline. In addition, this population is especially vulnerable to health care-acquired infections and chronic conditions, making the ability to receive care at home with the support of remote monitoring an attractive alternative — in addition to improving quality of life. Finally, seniors experience especially high rates of chronic disease, which is especially responsive to frequent or continuous remote monitoring of specific data points to inform early diagnosis and treatment; that also helps to limit disease progression and recurrent hospitalizations.
These are just a few ways big data can improve health outcomes for seniors. As health care systems continue to learn how to make the most of what big data has to offer, the benefits for older Americans will continue to grow. To learn more about optimizing big data to its full potential in your organization, you can start by accessing resources available through the Office of the National Coordinator for Health Information Technology (ONC) and the National Institute of Health’s (NIH) Precision Medicine Initiative.
Author Bio: Sue Montgomery, RN, BSN, CHPN is the CEO of Sue Montgomery & Associates. She has been a nurse and healthcare leader for over 31 years in a variety of settings. She is also an entrepreneur and provides communications consulting and other services through her company. She is a regular contributor to the MPH@GW and MHA@GW blogs.
