The use of big data in healthcare has the potential to greatly improve patient treatments. As more organizations, providers and researchers use and exchange healthcare data, physicians can more easily anticipate and treat illnesses with the aid of health information systems. The healthcare field is growing rapidly, and it needs professionals who can help physicians, nurses and practitioners use big data to improve patient treatments.
What Can Big Data Do for Healthcare?
Big data in healthcare can improve patient treatments by enabling pattern analysis across segments of the population. By compiling patient healthcare information and using analytical software, a physician can look for patterns among his or her own patients, or a hospital could use their health information systems to watch for patterns across their greater patient population. Algorithms can send notifications when certain triggers appear, meaning providers know when to do more individualized research into larger trends.
Faster responses to emergent healthcare patterns can save lives, and it can help hospitals, clinics and individual practitioners lower their costs and reduce waste by reaching diagnoses sooner with fewer tests. With powerful analytical tools at their disposal, providers can save patients time and money while avoiding the negative consequences of delayed treatment.
A Case Study
Healthcare researchers are already using big data to improve patient treatments during the annual flu season. Researchers from Johns Hopkins University have worked with Twitter in recent years to detect trends in the spread of flu both nationally and regionally. As people post tweets related to their health, researchers can pinpoint their locations, indicating where the flu is on the rise and where it is likely to emerge next.
For example, a team of researchers from Johns Hopkins and George Washington University were able to narrow their analysis to tweets in the greater New York City area and compare this information with big data from healthcare providers in the region. By narrowing their analysis to a very specific geographic region, researchers help healthcare providers prepare better treatments, ensure hospital bed availability and provide adequate vaccination in the face of outbreaks.
Challenges to Big Data in Healthcare
The development of better analytical systems for big data in healthcare faces several challenges in its current state. In order to provide the best results, software systems need to analyze the largest datasets possible. Often the data is limited due to difficulties in coordinating providers, insurance companies, researchers and government agencies. As health information researchers are better able to aggregate data from a wide variety of sources, both their analyses and patient outcomes will improve.
Big data also faces the challenge of increasing concern for patient privacy. As more people hear about digital security breaches, patients and hospitals alike push harder for protections against healthcare information sharing. Researchers and innovators in health information systems must assure patients that their health information will remain private.
Using big data in healthcare to improve patient outcomes is becoming increasingly common. Finding data-driven solutions for healthcare systems has piqued the interest of a growing number of joint venture companies in recent years. With an aging population in the U.S. and an increasing demand for transparency in healthcare, the number of technology companies investing in healthcare data solutions will only rise. More interest from businesses and more investment in health information systems means more innovation, more growth in the healthcare sector and ultimately more improvement in treatments for patients.
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