How Real-Time Data Is Affecting Healthcare

How Real-Time Data Is Affecting Healthcare

Medical devices are becoming increasingly connected and are able to relay real-time data to analytics systems that can produce actionable information where it counts.

This blog post was published on before the merger with Cloudera. Some links, resources, or references may no longer be accurate.

Real-time data is one of the most promising applications of big data in the healthcare industry. 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 actionable insights on a minute-by-minute basis.

Medical devices are supporting this use case because they are increasingly connected and able to relay data to centralized patient management systems. The nature of these devices is also changing. Smart wearables are already enabling healthcare providers to monitor patients both during their hospital stays and after they have returned home.

A System in Need

The combination of real-time data and big data analytics promises to breathe new life into U.S. healthcare—and the system could certainly use the help. According to the Commonwealth Fund’s 2017 report that evaluated 11 countries, the U.S. received the worst overall healthcare ranking, while also spending the most. For every dollar that the U.S. produces, more than 16 cents goes to health-related spending.

Healthcare costs are rising as the system faces an influx of older patients with greater needs and an increasing portion of the population with chronic conditions. Concurrently, the industry is seeing a gradual move to value-based payments, in which healthcare providers focus on outcomes rather than solely on fee-based services.

According to McKinsey, physicians are also being asked to focus on evidence-based medicine, which means systematically reviewing clinical data and making treatment decisions based on the best available information. However, heavy patient loads—along with an unprecedented flow of new data from these connected devices and electronic medical records (EMRs)—make that difficult.

A Deeper Understanding of Patient Needs

Real-time data will be a crucial asset as the industry tackles these problems. It can give a deeper understanding of individual patient situations at the point of care. This understanding can help us to lower costs and improve outcomes. No wonder, then, that BIS Research saw a $14.25 billion market for big data in healthcare in 2017, and predicts that it will grow to over $68.75 billion by 2025. According to the report, the fastest-growing subcategory in this market is clinical analytics.

Analyzing patient vitals in real-time and monitoring patient care plans, provides the opportunity for providers to proactively care for patients. Combining analyses of large data sets with current patients’ medical records can help identify high-risk patients who may need extra attention at bedside or remote home healthcare sites.

Applications like these are driven by a wealth of new data coming from a variety of sources, ranging from connected medical equipment to EMRs. Healthcare organizations must ingest data from these new sources while supporting existing software and databases that provide useful financial and operational data. Distilling all this information into actionable intelligence takes considerable IT, data science, and domain expertise.


Clearsense is one company that has been using real-time data to advise medical staff about patient conditions. The company uses the HL7 medical messaging standard to gather data from IoT devices around hospitals. Anything from a bedside alarm to a heart-rate monitor to an insulin reader can provide information that is a valuable indicator of patient health.

Clearsense takes data from hospitals around the U.S., creating a corpus of information that its analytics systems can use to identify trends that support future decisions. It helps healthcare providers in three main areas:

  1. Financial: It helps track key performance indicators and in keeping healthcare providers within their financial targets.
  2. Operational: It monitors data in the field to ensure that healthcare staff and processes are meeting expectations, and to find potential areas for improvement.
  3. Clinical: It uses real-time information on a mission control dashboard to detect patient deterioration and avert serious medical problems before they happen.

In one case, Clearsense has been able to use real-time information to warn healthcare staff of patient deterioration 12 to 48 hours before it occurs. Additionally, cost efficiencies from cloud-based services have enabled Clearsense to offer healthcare predictive analytics to 2,000 rural providers that otherwise wouldn’t have access.

As the industry’s ability to digest and process real-time data improves, healthcare organizations stand to gain significantly from the latent information that already exists in their administrative systems, monitoring equipment, and patient management solutions. Making the most of big data analytics can not only improve the quality of patients’ lives, but potentially save them.

Learn more about how Clearsense has revolutionized patient healthcare with real-time data.

Cindy Maike
VP Industry Solutions
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