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Big Data Analytics Can Prevent Healthcare Fraud. Here’s How.

By on April 8, 2015

**This post originally appeared on VentureBeat**

Catching and preventing health care fraud is more important than ever.

The industry has undergone massive transformations with breakthroughs like the adoption of online health records, remote patient care and data-driven care. While these changes have created a more efficient health care system, improved patient outcomes, and boosted bottom lines, they have also given rise to a host of challenges that, if poorly addressed, could mean skyrocketing costs, breached privacy, and even patients’ lives.

According to the Association of Certified Fraud Examiners, 2015 is the year that technology will give fraudsters an edge. Yet, while technology is contributing to the sophistication of fraud schemes, it is also providing organizations and government investigators with powerful weapons to catch and prevent perpetrators. As data analytics rises to the top as the weapon of choice against health care fraud, the association states that gleaning insights from unstructured data will be the most notable use of analytic tools.

As sophisticated data-analytics tools become more accessible, we can expect to see the use of them make progress in two areas: securing patient privacy and mitigating prescription fraud.

Data analytics prevent health care data breaches

The past year was dim for cybersecurity with major data breaches like those at Sony, Target and eBay reinforcing the importance of protecting sensitive information. Unfortunately, health care organizations are not immune to these data attacks. In fact, a 2014 analysis of Standard & Poor’s 500-stock index companies by BitSight Technologies found that health care and pharmaceutical companies fare worse than retailers in terms of security performance with poor practices and slow response times.

For health care organizations tasked with the responsibility to protect patient details and medical information, data is their best friend. It can be used to not only address security, fraud prevention and compliance problems, but also to anticipate and proactively address these issues.

With the health care security landscapes and compliance requirements constantly evolving, organizations must be able to act quickly. And doing so requires unlocking trends, patterns, and outliers buried in log, sensor, and machine data –– both structured and unstructured types of data.

Collecting, preparing, and analyzing this fragmented data is no small feat, but with the help of sophisticated data analytics, it’s possible. Big data analytics is the most powerful weapon in this fight because it allows organizations to combine, integrate, and analyze all of their data at once — regardless of source, type, size, or format — and identify patterns needed to address fraud and compliance-related challenges. For example, organizations can analyze public websites, tracking pages, and application programming interfaces to catch attacks early on or analyze log files to spot abnormal server access patterns and perform security forensics.

Data defers prescription drug abuse

Not only can data analytics help protect patient data, it can also help protect patient lives. According to the Centers for Disease Control and Prevention (CDC), more than half of the 43,982 overdose deaths in 2012 were related to pharmaceuticals, and this prescription drug abuse costs the nation more than $55 billion annually. If doctors and pharmacies have quick access to controlled substance history information at the point of care, it will help them make better prescribing decisions and identify potential prescription drug abuse.

With the ability to combine multiple data sources, analyze data and quickly deliver insights, pharmacies, doctor offices, and hospitals can track abnormal activity to mitigate prescription drug abuse. Currently, California has a Prescription Drug Monitoring Program (PDMP) system, which allows health care workers eligible to prescribe and dispense controlled substances to access timely patient history information. More and more states are calling for secure databases like this that use big data analytics to detect patterns of fraud or misuse. Using data analytics tools that simplify the process and deliver digestible data visualizations empower everyone, not just data scientists, to use data for the benefit of all. Rather than just delivering raw data to health care professionals, sophisticated databases like California’s will give health care professionals a larger picture that allows them to address why, where, when, and how these issues are arising.

In the fight against health care fraud, it’s clear that data analytics will play a crucial role. As more organizations adopt analytics tools that make big data simple for everyone, we’ll start to see its benefits spread across all aspects of health care.

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Stefan Groschupf

Stefan Groschupf

Stefan Groschupf is a big data veteran and serial entrepreneur with strong roots in the open source community. He was one of the very few early contributors to Nutch, the open source project that spun out Hadoop, which 10 years later, is considered a 20 billion dollar business. Open source technologies designed and coded by Stefan can be found running in all 20 of the Fortune 20 companies in the world, and innovative open source technologies like Kafka, Storm, Katta and Spark, all rely on technology Stefan designed more than a half decade ago. In 2003, Groschupf was named one of the most innovative Germans under 30 by Stern Magazine. In 2013, Fast Company named Datameer, one of the most innovative companies in the world. Stefan is currently CEO and Chairman of Datameer, the company he co-founded in 2009 after several years of architecting and implementing distributed big data analytic systems for companies like Apple, EMI Music, Hoffmann La Roche, AT&T, the European Union, and others. After two years in the market, Datameer was commercially deployed in more than 30 percent of the Fortune 20. Stefan is a frequent conference speaker, contributor to industry publications and books, holds patents and is advising a set of startups on product, scale and operations. If not working, Stefan is backpacking, sea kayaking, kite boarding or mountain biking. He lives in San Francisco, California.