“Big Data” is a big buzzword days. The topic has been making waves in other industries for some time, but its applications in healthcare are still in their formative stages. The use of big data shows exciting promise for improving health outcomes and controlling costs, as evidenced by some emerging use cases, but the practice seems to be defined somewhat differently by each expert we ask.
The concept refers to vast quantities of data—created by the mass adoption of the Internet and digitization of all sorts of information, including health records—too large or complex for traditional technology to make sense of. New big data technologies, however, hold promise for consolidating and analyzing these digital treasure troves in order to discover trends and make predictions.
I wanted to understand what big data will mean for healthcare, so I turned to big data analytics and healthcare informatics expert Dr. Russell Richmond to discuss what the future holds. Dr. Richmond is a leading healthcare technology authority whose experience includes building large data analytics companies and advising health system executives as a consultant at management consulting firm McKinsey & Company.
More Precise Treatments
According to Dr. Richmond, one of the most exciting implications for big data in healthcare is that providers will be able to deliver much more precise and personalized care. With a more complete, detailed picture of patients and populations, they’ll be able to determine how a particular patient will respond to a specific treatment, or even identify patients at risk before a health issue arises.
“More information yields more granular diagnosis, which creates the opportunity for more precise treatment,” Dr. Richmond explained to me. Dr. Richmond got me wondering about companies that are already making use of big data to influence health outcomes. He recently joined the board of directors for one such company, Explorys. So I decided to take a closer look at Explorys and other organizations utilizing big data today.
Who’s Using Big Data Today?
Explorys is a Cleveland Clinic spinoff company that leverages big data to provide tools for clinical support, at-risk patient population management and cost of care measurement. Dr. Richmond joined their board in May of this year.
Explorys has developed one of the world’s biggest healthcare databases. Laid over that they’ve created applications that tap into the more than 100 billion data points in their database. Their solutions help clinicians analyze troves of data from disparate sources, such as electronic health records (EHRs) and payor financial data, in real time.
Mining the data with Explorys’s analytics tools can help providers pinpoint how variations among patients and treatments influence health outcomes. Based on these insights, providers can determine more precise treatment plans for individual patients or patient populations.
For example, according to Dr. Richmond, in a world with big data, “general asthma” may no longer be a sufficient diagnosis. Big data’s granularity may allow us to detect and diagnose five or six variants of asthma, with different treatment pathways for each. Data mining could point physicians to the precise treatment plan called for by each patient’s unique case.
Propeller Health (formerly Asthmapolis)
Dr. Richmond’s asthma example led me to discover another company focused on asthma management, this one on the prevention side (rather than the treatment side). Propeller Health (formerly Asthmapolis) uses sensors for asthma inhalers, along with mobile applications and advanced analytics, to help providers identify at-risk asthma patients before an attack occurs. Their sensors record date and time of use, and pair with GPS-enabled devices like smartphones to track location data.
The Propeller Health app provides individual patients and their providers with a profile of that patient’s inhaler usage, which helps them understand trends and predict (and thereby prevent) attacks. But Propeller Health also collects weather data, air quality data, and is even working on EHR integration. Their goal is to be able to predict the risk-level for any given area. They’ve recently partnered with the city of Louisville, Kentucky and its local Walgreens pharmacies to map asthma exacerbations in that city and identify risk factors.
Genomics, as Dr. Richmond pointed out in our discussion, is the next frontier of medicine. The cost of genome sequencing is falling; you can sequence your complete genome for a couple thousand dollars these days, down from around $100 million a decade ago. As a result, the volume of genomics data is growing rapidly—and so is our ability to take advantage of that data.
NextBio uses data about the human genome to aid providers in making personalized medical decisions. Their big-data technology uses both public and proprietary molecular and genomic data, as well as clinical information from individual patients which is uploaded by the provider into a HIPAA-compliant secure domain.
Emory University and the Aflac Cancer Center recently partnered with NextBio to study data related to medulloblastoma, the most common malignant brain tumor among children. Medulloblastoma currently has a uniform treatment approach: radiation therapy. Emory and Aflac are using NextBio to look at clinical and genomic data to discover biomarkers that can help predict the metastases of cancer in young patients. Providers, in turn, will use this information to pinpoint targeted therapy approaches based on the biomarkers of their individual patients.
The University of Pittsburgh Medical Center (UPMC) is another organization utilizing genomic data to advance personalized solutions. In 2012, UPMC invested in creating a data warehouse and analytics platform that integrates clinical, financial, administrative and genomic data from more than 200 sources.
They’ve begun with a focus on breast cancer and are already seeing promising results. In June, researchers announced that UPMC’s data warehouse had enabled the electronic integration – for the first time – of clinical and genomic information on 140 breast cancer patients. This allows researchers to make important connections that previously wouldn’t have been made because of the disparate nature of the various types of data. To start, researchers investigated pre- and post-menopausal breast cancer and found notable molecular differences.
Studying these differences, they hope, will enable the development of cancer therapies targeted to be more effective for each group, so that providers can personalize treatment based on a patient’s menopausal status.
InterSystems is a 35-year-old software company focusing its accumulated expertise and technology to tackle big data applications such as mapping the Milky Way with the European Space Agency.
For healthcare providers, its HealthShare Active Analytics tool is aimed at improving cost savings and outcomes in population health management. HealthShare’s technology enables the collection, aggregation, and normalization of data across siloed health system databases, while Active Analytics provides near-real-time analytics tools.
The state of Rhode Island has partnered with InterSystems to aggregate and analyze patient data on a statewide level. Their Quality Institute used HealthShare tools to determine that some 10 percent of major lab tests performed in over 25 percent of the state’s population were medically unnecessary – a discovery that will help Rhode Island reign in spending as well as improve quality of care.
Personalizing Care and Controlling Costs
We’re probably a few years away from the average medical practitioner at a small to mid-sized practice realizing the benefits of big data in a meaningful way. Dr. Richmond summarizes the challenge: “We’re spending an awful lot of time putting information in [to digital systems like EHRs], but we haven’t yet harnessed the insight that comes from using that information once it’s in.”
But investors see big data as a big moneymaker, and more investment will lead to more solutions. In a few years, Dr. Richmond expects big data and the personalized medicine it facilitates to help eliminate “one-size-fits-all” approaches to treatment. And importantly, he says, this ability to better manage care should result in lowered health costs as well.