MN Perspective: Big Data & Healthcare

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A recent article on the Star Tribune by Joe Carlson brought the conversation about healthcare and big data analytics close to home. Several Minnesota-connected companies led discussions on working across the industry to utilize data from insurance, hospital, pharma and medical device sources to drive better patient outcomes and manage rising costs.  Working with big data analytics tools has been key to making this possible.

The first example comes from Medtronic and UnitedHealth. Many might think medical device and insurance companies might not always have the same goals in mind but not true.  The two companies partnered together to discover the value of the features of a Medtronic insulin pump vs. other pumps on the market.  Mr. Carlson reports they discovered that there was a decrease in hospitalizations due to complications from diabetes when the Medtronic pump was used, thus decreasing overall insurance costs.  This led to a change of thinking.  Dr. Richard Migliori, chief medical officer of UnitedHealth explains in the article, “It caused us to stop looking at line-item cost figures and start looking at, what is the total value? Because we saw a total value, we then began to wonder; shouldn’t we be (paying) on the basis of total value?” In 2016, UnitedHealth announced that Metronic would be its preferred insulin pump provider.

In Mr. Carlson’s article, he also gains insight from Mayo CEO John Noseworthy.  Mr. Noseworthy adds that the industry has changed in the last five years and the atmosphere is one of “partnership, trust and transparency” in order to work together to bring down rising costs and improve patient outcomes.

Finally, St Jude Medical is working on a solution to reduce chronic pain by using a medical device versus pain medications. According to Mr. Carlson’s article prescription opioid painkillers are not only addicting but they lead to 15,000 deaths per year.  Using big data analytics, St. Jude is looking to make the case for using its device which has a larger upfront cost but may reduce overall costs long term.

The power of big data analytics and a great spirit of partnership has helped make these connections possible.

What’s Next for Big Data in Healthcare

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“Big Data will leave no sector untouched as it continues to change the way we think about everything from sales to human resources, and medicine and healthcare are no different,” writes Bernard Marr for Forbes.

Handling data is nothing new to the healthcare industry.  But, in recent years, increased abilities to share and access data plus new data from sensors and wearables has created not only more data but better data according to Mr. Marr.  In his article he outlines several ways big data will make an impact:

Prevention.  Mr. Marr writes, “smartphones and other popular smart devices including Jawbone, Fitbit and others, now have the capacity to help people track their progress towards a healthier lifestyle. Apps and devices to help track and monitor physical fitness but also chronic ailments like diabetes, Parkinson’s and heart disease are also being developed.”  Not only do these devices track more data but this data can be more reliable than traditional patient led tracking and reporting methods.

Diagnosis. Improvements are being made to how big data is stored and shared in the healthcare industry with the goal of  bringing medical providers more access. Systems, such as IBM’s Watson, are also looking at test results, recognizing patterns and learning in order to aid in diagnostics and improve early detection.

Treatment.  To get to more personalized medicine and better patient  treatments you first have to start big, as in big data.  The results of big data analytics, predictive modeling and new systems crunching vast amounts of information will help to better inform doctors about the needs of each patient.

Big data is definitely a “game changer” for the healthcare industry both now and in the future.

2015 Review – Big Data in Healthcare

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Jennifer Bresnick put together an interesting take on how big data is taking shape in the healthcare industry for Health IT Analytics. She writes, “Even in a decade filled with milestone events for the healthcare industry, 2015 must certainly stand out as one of the most eventful years for the big data analytics world. From the raging controversy over the timing of Stage 3 meaningful use, the less-dire-than-expected ICD-10 conversion, and the increasing pressure on vendors to make EHR interoperability a priority to the advent of the Internet of Things and a system-wide push to put population health management into action, the past twelve months have been packed with progress, change, and even a few disappointing setbacks.”

Let’s check out what leading trends developed this past year:

Internet of things (IoT). Using devices to track healthcare data allows for more personalization of patient care. Ms. Bresnick writes, “IoT devices have the potential to improve patient safety, make chronic disease management simpler, and provide healthcare organizations with the detailed data they need to engage in effective population health management programs. While the associated influx of data may seem like trouble to overwhelmed clinicians still struggling to wrestle their EHRs into submission, IoT developers are putting plenty of effort into designing interfaces that ease the burden of sifting through reams of data from sleep trackers, diet apps, heart monitors, and smartwatches.”

Precision medicine. Ms. Bresnick comments that precision medicine is moving from theory to everyday practice. Several initiatives are coming together currently to not only build data sources but also to put findings into the hands of practitioners.

Overdose of Ambien (alone or in combination with other CNS depressants, including ethanol), led to the development of disorders of consciousness (up to coma and more severe symptoms, including death). Treatment: if there has been less than one hour after the overdose, and the patient is still conscious, you should try to induce vomiting. If it is impossible to induce vomiting or if the patient is unconscious, gastric lavage should be carried out.

Big data-driven care. As the healthcare industry is pushed to be more effective, while continuing to provide quality innovative patient care, big data use could be the key to success. Ms. Bresnick explains, “big data has the potential to help healthcare organizations balance their competing initiatives and equip providers with the tools they need to leverage their EHRs for better care rather than feel overwhelmed by them. The trick is to understand how big data can be valuable, how it intersects with mandated reporting requirements, and why it’s so important to improve the way the healthcare system measures its progress and evaluates its weaknesses.”

In the healthcare industry yourself? Share your thoughts on key big data transformations in 2015.

Automated Analytics in Healthcare

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Today let’s take a look at a healthcare analytics use case from IBM involving automated reporting and optimized analytics operations for athenahealth.

Paula Williams from IBM’s Big Data Hub explains the challenge companies face with healthcare analytics. “New government rules and regulations—such as the Health Insurance Portability and Accountability Act (HIPAA), Medicare and Medicaid, The Affordable Care Act, and so on—continually affect healthcare organizations. The ability to respond to these legislative mandates requires much agility. For organizations such as athenahealth, having an information technology infrastructure that is flexible enough to accommodate growth while allowing it to address healthcare industry market changes is a must.”

Athenahealth provides cloud based services to doctors, providers and large hospitals across the country.  As they grew their healthcare analytics solution started to fall short and analysts were finding themselves spending more time gathering the data rather than analyzing it. Business leaders also found themselves with little opportunity to get at the data themselves creating a bottle neck within the analytics team.  Sound familiar? This is a common occurrence at any-sized business but given the volume of healthcare data and sources, finding a solution to automate can be a game changer to how you serve your customers.

Athenahealth came to IBM looking for a solution that allowed them to provide the same level of healthcare analytics and back-end support to each of their customers, no matter the size. Not only did they want to save time but they also wanted to empower business leaders by providing self-service options. Since implementation they have gained efficiency and improved access for business leaders. Some processes have gone from days to minutes and analysts are seeing a real gain in the time they now have to analyze the data to better serve their customers.

What pain points is your company facing as its data and sources of data continue to grow?

Integrated Big Data Solutions for Healthcare

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We have all seen the headlines around what big data can do for the healthcare industry and patient care. Today let’s take a step back and look at what a successful architecture might look like with every day healthcare data sources in mind.

Krish Krishnan breaks down data sources for IBM’s Big Data & Analytics Hub. He writes, “Big data is information that is both traditionally available (doctors’ notes, clinical trials, insurance claims data, drug information), plus new data generated from social media, forums and hosted sites (for example, WebMD) along with machine data.”  He breaks down these data sources among Volume, Velocity and Variety or the three Vs of Big Data.

  • Volume: data sizes are varied and range from “megabytes to multiple terabytes”
  • Velocity: “the data production by machines, doctors’ notes, nurses’ notes and clinical trials are all produced at different speeds and are highly unpredictable”
  • Variety:  data produced in different formats but not necessarily with the same standards

The key is to harness the data in an integrated solution that reduces complexity and latency as well as allows for scale, collaboration and agile analytics. Of course, the solution should also be “useful,” Mr. Krishnan explains, “getting the right information to the right resource at the right time.”

Mr. Krishnan also underlines the benefits of using metadata, “Using metadata-based integration of data and creating different types of solutions—including evidence-based statistics, clinical trial versus clinical diagnosis types of insights, patient dashboards for disease state management based on machine output and so on—lets us generate information that is rich, auditable and reliable. This information can be used to provide better care, reduce errors and create more confidence in sharing data with physicians in a social media outlet, thus providing more insights and opportunities.”

Getting started with big data may seem daunting at first, but a trusted, experienced business partner can guide you down the path so your organization (and patients!) can soon start to realize the benefits of big data.