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7 Big Data Use Cases for Healthcare

October 08, 2017

7 Big Data Use Cases for Healthcare

Big data is all about delivering big insights: gathering information from disparate sources and analyzing it to reveal trends that are not accessible in any other way. Of all the industries that are finding value from big data analytics, healthcare has the potential to realize the greatest returns. Not only can big data show healthcare providers how to increase profitability and improve operational efficiency, big data also has the potential to uncover trends that can directly improve people’s well-being.

The Centers for Disease Control and Prevention (CDC), for example, has been using big data as a defense against Ebola and other pandemics. The CDC has a pilot big data program, BioMosaic, which merges population data, health statistics, and population migration in real time in order to track epidemics. The agency has successfully used BioMosaic as a tool for forecasting, testing, and targeting diseases for tracking potential disease outbreaks and recommending proactive measures to stem a potential epidemic.

This is just one of the many applications for big data in healthcare. Here are some of the most common that we have been seeing in healthcare, both for business operations and health management:

1.   Analyzing Electronic Health Records (EHRs) – Doctors sharing EHRs can aggregate and analyze data for trends that can reduce healthcare costs. Sharing data between physicians and healthcare providers as they examine patients can reduce duplicate tests and improve patient care. Most EHR data is siloed, largely for security and regulatory compliance reasons, but finding a secure way to mine patient data can improve the quality of care while reducing costs.

2.   Analyzing Hospital Networks – Consider the power of analyzing trends in hospital care. For example, centralizing analysis of medical instruments in a pediatric ward can isolate possible infant infection trends earlier. Or consider the case of one hospital that was able to reduce post-operative staph infection: by using big data, the administration was able to determine that one surgeon was prescribing post-operative antibiotics that were less effective against infection.

3.   Control Data for Public Health Research – The medical profession is drowning in data. Medical offices and hospitals submit data about medical conditions and immunizations, but without big data, those data are meaningless. Using analytics normalizes raw patient data to fill gaps in public health records that can affect regulations as well as providing better care.

4.   Evidence-Based Medicine – Most hospitals and emergency rooms practice “cookbook medicine,” where a patient is admitted, and the physician uses the same battery of tests in order to identify the cause for symptoms. Using evidence-based medicine, the doctor can match symptoms to a larger patient database in order to come to an accurate diagnosis faster and more efficiently. Where big data plays a role is assimilating information from different sources and normalizing the data, so one record that describes “high blood pressure” maps to another that describes “elevated blood pressure.”

5.   Reducing Hospital Readmissions – Hospital costs are rising partially because of high readmission rates within 30 days of patient release. Using big data analytics in order to identify at-risk patients based on past history, chart information, and patient trends, hospitals can identify at-risk patients and provide the necessary care to reduce readmission rates.

6.   Protecting Patients’ Identity – Insurers like UnitedHealthcare are using big data analytics in order to detect medical fraud and identity theft. The company uses analytics on speech-to-text records from calls to the call center to identify potential fraudsters. The insurance company also uses big data in order to predict which types of treatment plans are more likely to succeed.

7.   More Efficient Medical Practice – As medical practices grow, accommodating more doctors and more patients becomes more challenging. Consider Westmed Medical Group in Westchester County, New York. This practice grew from 16 physicians in 1996 to 250 physicians today seeing 250,000 patients, with annual revenue of $285 million. As the practice grows, it needs to be more efficient in order to succeed. Using big data, the practice was able to analyze more than 2,200 processes and procedures. As a result, the practice was able to streamline workflow, shift clinical tasks from doctors to nurses, reduce unnecessary testing, and improve patient satisfaction. Like any business, big data made it clear where processes could be improved.

These are just seven areas where big data is having a big impact on healthcare. The more data that are available to physicians and hospital administrators, the easier it is to identify trends, normalize patient data, and identify bottlenecks in patient care. Medical practitioners can apply big data analytics in the same way they are applied in any other business. The only difference is that the stakes are higher and the insights from big data may help save people’s lives.