With new challenges cropping up seemingly every day, what technology advancements can hospitals and clinics use to improve patient care? Big data technology has made improving care for high-cost patients, readmissions, triage, and decomposition possible.

• Improving High-cost Patient Treatment

It is estimated that 15 percent of patients account for about 50 percent of health care spending in the U.S. One way to reduce costs is to identify those patients and find ways to manage their needs more effectively. This can be accomplished by using big data to help case managers better understand the medical history of patients as they work to improve their care. Although they are high-cost patients, big data can help doctors better understand the type of treatment that each patient needs. Programs that manage high-cost patients can be expensive, however, the use of big data can tailor care to the patient’s needs for a reasonable price. That combined with medical billing and coding classes online means greater efficiency so hospitals can focus on the most important things.

• Detect Readmissions

Big data and analytics have created a system that can identify patients that may need to be readmitted. One method includes monitoring patients (with their permission) and keeping track of how many calls, texts, and emails they receive. These statistics can help doctors identify if patients are suffering from depression or other issues that may lead to readmission. Patients can also wear a device that monitors their physiological parameters such as heart rate or rhythm. This data can be most effective in helping doctors make healthcare decisions as long as they are processed with analytics.

• Triage

Triage assigns different degrees of urgency to patient illnesses and wounds to determine in what order which patients will receive treatment. The use of big data can help this estimation by analyzing the risk of complications for each patient. It can help manage staffing and resources, learn if a patient needs to transfer to a different unit, and develop specific strategies to help each patient. By integrating triage into big data, this alliance can help inform caregivers what type of care needs to be administered. When a doctor knows the type of work or the specific treatment that each patient needs, they can dedicate their time to the most critical patients.      

• Decompensation

The stress of a disease can cause certain organs to fail. It’s possible that physiological data, or big data, can determine if the patient is at risk for decompensating. Intensive care units have determined certain patients who are considered critically ill and should be monitored to avoid decompensation.The analytic systems of big data use multiple data streams to help detect whether a patient is as risk of decompensation. With big data analytics, this system can be used throughout the hospital. New technologies, including big data, have become available to be used to better monitor patient stress levels and mental stability.

Essential to keeping healthcare costs down is correctly managing patients. As advanced as this new technology is, there is still need for more research in certain areas. Unfortunately, the lack of access to health records has also limited the use of big data to help treat patients. Electronic health records have helped hospitals improve patient care immensely while also helping health professionals with their ACLS recertification, but with the addition of big data, healthcare can increase opportunities to analyze and interpret quantities of patient information to manage patients more effectively.