Healthcare, Big Data, and Option Value: Lessons from HIMSS 2014
Attitudes towards technology in healthcare are changing rapidly. At this year’s Health Information and Management Systems Society (HIMSS) conference, the enthusiasm for Big Data was clear in the confluence of traditional industry actors, large IT vendors, and startups all jockeying for attention on the mile-long showfloor with their Big Data architecture, infrastructure, mobility, and software solutions. However, for all the agreement about direction and vision, there was little discernable perspective on the status of data-driven capabilities in healthcare IT today and how to fully measure the opportunity offered by innovation.
While keynote speaker Hillary Clinton emphasized evidence-based medicine as the goal above all else, I was looking for proof that the community has evaluated how to align evidence to truly transformational health outcomes in the foreseeable future. I was trying to find indication that vendors and customers have corroborated a strategy beyond the minimum requirement of meaningful use of electronic medical records (EMRs) and electronic health records (EHRs) established by the 2009 HITECH Act.
Specialized IT: Health Outcomes vs. ROI
Over the course of the conference’s five days, I had a variety of conversations with customers, industry actors, and other vendors about their priorities for becoming more information-driven, primarily falling into six categories:
- EMR and EHR Storage, Integration, and Management
- Data Governance and HIPAA Compliance
- Business Intelligence and Operational Efficiency
- Patient Segmentation and Population Management
- Predictive Analytics and Machine Learning
- Visual Modeling and Strategic Communication
However, the prevailing notion at HIMSS 2014 was that the entirety of any healthcare industry actor’s IT roadmap could only fall into one of those categories, since return-on-investment would be the opportunity cost of a multi-tactic strategy. The unfortunate truth is that vast majority of healthcare IT solutions are extremely specialized, not only for the industry, but also for the provider or payer, and for only one of the priorities listed above. This usually makes scale a tradeoff on option value and completely forestalls any true notion of healthcare transformation.
The EDH Drives Healthcare Transformation
Cloudera’s mission for healthcare data is different. An enterprise data hub (EDH) with Hadoop at its core is a more flexible, forgiving, and faceted solution that brings a wide—and growing—variety of processing engines and compute tools to data of any size and format. Because capital outlay for an EDH is up to 99% less than a traditional data warehouse accommodating the same volume of data, opportunity costs actually diminish as scale increases.
Even more importantly, the EDH is built to accommodate—or even encourage—all of the objectives on the healthcare IT wishlist: Big Data management, integration, security, descriptive analytics, data science, and visualization. And there’s no need to remove or replace current systems because Cloudera’s ecosystem of over 800 partners enables healthcare actors to both extend their preferred tools into the EDH and rationalize their existing architecture through better performance.
Adverse effects and prescription errors will decline as trial data becomes accessible on thousands of drugs, millions of compounds, and countless individual genetic variations. Healthcare will become personalized to minimize unnecessary emergency room visits by streaming data from wearable and implanted sensors. And newly acquired patient data will add color to an already-robust library of health records and genome sequencing that will not only help to address the specific patient’s current malady, but also help predict proper action to prevent illness and improve quality of life throughout the entire population.
Cloudera is also helping healthcare actors address Big Data challenges and opportunities by learning from clients across other industries. Retailers are using the EDH to get a 360-degree view of their customers and incent certain behaviors among specific customer profiles—similar to the healthcare objective of cost management through preventative health behaviors among key patient segments. Telecom companies combine and transform telemetry data in real time to deliver value-added services to customers and optimize network performance—similar to the opportunity in healthcare to collect massive amounts of multi-structured data from machines and labs or remotely from medical devices. Both government agencies and financial services have successfully deployed the EDH to detect security anomalies while complying with privacy requirements—similar to the advanced fraud detection and regulatory compliance goals in healthcare.
Ultimately, the role of Big Data in healthcare is not simply to aggregate digital records and comply with HIPAA, but to address the larger objectives of healthcare access, quality, affordability, and outcomes by becoming information-driven. The first step is to afford decision-makers a longitudinal view of all their data and the option to ask bigger questions that truly impact population health and the ability to sustainably provide and pay for it. With an enterprise data hub built on Apache Hadoop at its core, healthcare has a proven resource for Big Data management at scale that, deployed today, eliminates the cost tradeoffs of specialized solutions and provides a platform for the types of transformational systems and analyses that had previously been outside the scope and budget of the industry.
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