Real-time data is one of the healthcare industry’s most promising applications of big data. While batched data can provide powerful insights by identifying medium and long-term trends, healthcare providers can combine streaming data with real-time processing to create minute-by-minute actionable insights. Medical devices support this use case as they are increasingly connected to centralized patient management systems and are able to relay data. These devices ‘ nature is also changing. Smart wearables already enable healthcare providers to monitor patients both during and after their hospital stay.
Clearsense is one company that used real-time data to advise patient conditions to medical staff. The company uses the HL7 medical messaging standard to collect information about hospitals from IoT devices. Anything from a bedside alarm to an insulin reader’s heart rate monitor can provide information that is a valuable indicator of patient health. Clearsense takes data from hospitals around the U.S., creating an information corpus that can be used by its analytics systems to identify trends that support future decisions. In three main areas, it helps healthcare providers:
Financial: It helps track key indicators of performance and keep health care providers within their financial goals.
Operational: It monitors field data to ensure that the expectations of healthcare staff and processes are met and to identify potential areas for improvement.
Clinical: It uses real-time dashboard mission control information to detect deterioration of the patient and to prevent serious medical problems before they occur.
In one case, Clearsense was able to use real-time information to warn patient deterioration medical staff 12 to 48 hours before it occurred. In addition, cost efficiencies from cloud-based services have enabled Clearsense to provide predictive healthcare analytics to 2,000 rural providers who would otherwise have no access.
As the ability of the industry to digest and process real-time data improves, healthcare organizations are gaining significantly from the latent information already available in their administrative systems, monitoring equipment, and solutions for patient management. Making the most of the analytics of big data can not only improve, but potentially save, the quality of life of patients.