Tableau Software, IBM, Apple and others are building a future where analysis of clinical data guides personalized medicine, fuels research, and helps reduce healthcare costs
Use of big data in healthcare is poised to become a big business. That’s because new players in data analytics have begun to help providers and accountable care organizations (ACOs) effectively use data to improve their business operations, personalize care for patients, and/or discover new medical insights.
Because more than 70% of a typical patient’s permanent medical record consists of clinical laboratory laboratory test data, pathologists and medical laboratory scientists have a stake in the growth of big-data analytics, which are a core component in healthcare’s journey toward personalized medicine.
Stanford University Instructors Form Company to Make Data Accessible to All
• Christopher Stolte, PhD, then a PhD candidate in computer science;
Operating in Seattle, Tableau Software’s goal of making data understandable to ordinary people has helped the company to become a leading force in data-visualization software.
Tableau went public on the New York Stock Exchange in 2013 and today has more than 35,000 customer accounts worldwide, according to a November 2015 company statement on its third-quarter results. In 2014, its revenue grew to $412.6 million, a 78% increase over the previous year.
While Tableau’s software is being used across 21 industries to tell stories with their data, healthcare is its fastest-growing market. According to Modern Healthcare, “Tableau claims its software can build a data dashboard in eight minutes or less and can combine data from disparate data sources with a quick drag and drop.”
Dashboards Reveal How Patients Use Healthcare Following Discharge
Community Health Center Network (CHCN) in the San Francisco area serves about 200,000 patients and manages care for roughly 127,000 of these patients. Tableau’s dashboards have enabled the parent healthcare system “to paint a clearer picture of how patients interact with the healthcare system once they leave the health centers,” Modern Healthcare reported.
CHCN says Tableau’s easy-to-use tools have contributed to “a 37% increase in the number of patients seeing a primary-care physician after a hospital admission, a 12% reduction in emergency department visits, and a 14% drop in hospital readmissions.”
“It actually [has] turned the business analyst into a hero,” Andy De, MBA, MS, Tableau’s Managing Director for Healthcare and Life sciences, told Modern Healthcare.
A 2014 Healthcare Information and Management Systems Society (HIMSS) survey found that Tableau was the most commonly used data-visualization software among 1,800 respondents, with 20% currently using the product and another 20% planning to in the future.
Other similar tools, such as Information Builders, QlikTech, and TIBCO Spotfire each were used by no more than 15% of those surveyed. A more basic analytic tool, Microsoft Excel, continues to be used by roughly 60% of respondents.
Tableau also offers a free tool known as Tableau Public that enables anyone to connect to a spreadsheet or file and create interactive charts and graphs, maps, live dashboards, and other data visualizations for the Web.
“Fifteen years ago, it was a dream to do the kind of things that I do today,” Martinez told USA Today in a recent story. “Other tools that existed out there were very difficult to use, and for an audience that was specialized.”
Big Data at Forefront of Personalized Healthcare
Forbes reports that medical and data professionals also are partnering to use data from various sources “to draw a comprehensive picture of the patient as an individual, in order to offer a tailored healthcare package.”
One such partnership is the Pittsburgh Health Data Alliance, a collaboration among Carnegie Mellon University (CMU), The University of Pittsburgh (PITT), and the University of Pittsburgh Medical Center (UPMC), to leverage big data generated by patient information in the electronic health record (EHR), diagnostic imaging, prescriptions, genomic profiles, insurance records, and wearable devices to provide deeper insights into disease.
“The complementary strengths of the alliance’s partner institutions will allow us to reimagine healthcare for millions of people in our shared, data-driven world,” Subra Suresh, PhD, President of CMU, said in a statement. “Through this collaboration, we will move more rapidly to immediate prevention and remediation, further accelerate the development of evidence-based medicine, and augment disease-centered models with patient-centered models of care.”
The new research centers at CMU and PITT will be funded over the next six years by UPMC and also will benefit from several hundred million dollars in existing research grants at all three institutions.
Apple, IBM, and Others Collaborating to Develop Big-Data Health Platforms
The biggest players in information technology recognize the revenue potential of healthcare big data. For example, Apple and IBM are collaborating on a big-data health platform that will allow iPhone and Apple Watch users to share data to IBM’s Watson Health cloud healthcare analytics service, potentially generating real-time activity and biometric data from millions of potential users, Forbes stated in a feature about healthcare big data.
In an effort to accelerate cancer research and personalized medicine, Flatiron Health, a healthcare technology company formed in 2012 in New York, is creating OncologyCloud, a cloud-based data platform for oncology that would aggregate datasets from cancer patients with the goal of powering a national benchmarking and research network.
“In America, most of the learning that occurs in healthcare is in clinical trials,” Flatiron co-founder Nat Turner told Fortune. And yet, a full 96% of patients don’t participate. “It’s a huge problem. If 100 patients walk in the door, we’re only learning from four of them.”
Clinical Laboratories Also Collaborating on Big-Data Projects
Laboratory medicine’s role in big data analytics is not going unnoticed. Quest Diagnostics Incorporated and Medivo, an early player in clinical laboratory test data analytics, announced in November that they are teaming up to analyze laboratory data in an effort to improve outcomes for patients.
Under the agreement, Quest Diagnostics will provide clinical and bioinformatics expertise and de-identified laboratory data to Medivo, which will combine the information and other datasets to identify physicians whose patients may be candidates for these therapies, according to a Medivo statement.
The Quest Diagnostics database consists of laboratory test results on a wide range of conditions such as diabetes, cholesterol, oncology, pregnancy health, and other clinical areas.
“Medivo’s analytic solutions are designed to transform lab data into actionable information. While we currently service the majority of the top 15 pharma companies, analyses based on the addition of Quest’s 20 billion laboratory test results allows us to provide solutions for more conditions to more brands,” said Medivo CEO Sundeep Bhan in a statement.
In fact, Medivo’s business model includes helping medical laboratories and pathology groups earn revenue in return for providing the de-identified lab test data that it analyzes in ways that have value for health insurers, pharmaceutical companies, and other healthcare providers.
Our sister publication, The Dark Report, just published an intelligence briefing about Medivo’s revenue-boosting opportunity for labs in its December 28, 2015, issue. This business arrangement is an early example of how labs can use their lab test data to build new streams of revenue as the era of healthcare big data moves forward.
—Andrea Downing Peck