9 tips for getting started with big data
With big data promising enormous clinical and financial rewards for healthcare, but posing just as many technical and strategic challenges, the Institute for Health Technology Transformation (iHT2) has published a study mapping the way forward for providers at the starting line.
"Health care providers face significant obstacles in implementing analytics, business intelligence tools and data warehousing," writes iHT2 CEO Waco Hoover in the report. "Health data is diverse, comprising structured and unstructured information in a range of formats and distributed in hard-to-penetrate silos owned by a multitude of stakeholders.
Moreover, he writes, "each stakeholder has different interests and business incentives while still being closely intertwined."
The white paper, "Transforming Health Care Through Big Data," is meant to offer providers some models for "innovative uses of data assets that can enable them to reduce costs, improve quality, and provide more accessible care."
Drawing on the expertise of leaders from Kaiser Permanente, IBM, Sharp Community Medical Group, Newton Medical Center and University of Manitoba, the report seeks to help hospitals and health networks overcome the headaches and hurdles on the way to the big goal of big data, says Hoover: "to make better, evidence-based decisions."
And there are plenty of challenges. The industry is still in its infancy when it comes to data collection, for instance, 43 percent of providers say they're unable to collect sufficient data to improve care.
The data that is collected is often untrusted – or at least unstructured, which makes it all but useless to even the best analytics technology. Moreover, data fragmentation – scattered as it is among EHRs, lab systems and financial software, makes it hard to draw meaningful conclusions about organizations' holistic health.
Infrastructure is another big issue, of course. iHT2 shows how legacy systems and new technologies have trouble interfacing, and that lack of interoperability remains "a significant obstacle to many organizations’ efforts to leverage big data." Providers' options for upgrading, even if they could afford it, are limited.
Ever-present privacy and security concerns only complicate things further.
The iHT2 white paper lays out nine strategies for those looking to make an earnest attempt at making use of big data.
Implement a data governance framework. "A carefully structured framework for enterprise-wide data governance is arguably the first and most critical priority to ensure the success of any effort to leverage big data for health care delivery," according to the report.
Engage providers. It's crucial to make physicians active partners in any initiative. One strategy is to spotlight the importance of big data at department-wide meetings and reward docs "when they meet standards for data collection and improvement of quality metrics."
Foster competition and transparency. Healthcare organizations "are attaching monetary incentives to measuring and looking at data," the iHT2 study reads, "displaying peer and colleague data with respect to patient satisfaction and quality metrics and using dashboards, all in an effort to leverage competition and improve performance among clinicians."
- Bake analytics into training. Hospitals must understand that physicians and nurses need analytics training to understand how big data tools add value to healthcare. Medical schools such as University of North Carolina at Chapel Hill and the University of Washington-Seattle are cited as proactive thinkers in this regard.
- Provide for flexibility in information transference. "There is a growing recognition that work and learning styles vary among clinicians; facilities are demonstrating a growing willingness to deliver data in multiple ways based on clinician preference and style," according to iHT2.
- When possible, choose in-house solutions over vendor-generated solutions. Inflexibility can be a big roadblock to big data success, and overly-rigid vendor offerings can be the worst offenders. "Organizations are increasingly recognizing that some of the most successful solutions to their challenges can sometimes be developed with in-house' input and expertise," according to the report.
- Use tools such as dashboards for clinicians to visualize incoming data. As big data moves toward real-time processing often at the point of care, "organizations should strive to update processes and develop capabilities to enable tool use, and focus on real- or near-real time clinical decision support."
- Don’t scale up, scale out. While some organizations may be tempted to replace older servers with bigger and more powerful machines, today’s trend is to “scale out,” according to the study – "to improve performance and scalability of a system by adding nodes for processing and data storage." Such an approach helps make systems easier to manage and expand.
- Close the quality loop. iHT2 researchers write that, "Data analytics teams must work in lockstep with quality improvement teams so that analytics tools and techniques can be integrated into the various quality-improvement methodologies which, together, can provide a framework that drives the front-line and administrative changes necessary for achieving desired improvements to health care outcomes and efficiency."
"It must be emphasized that the healthcare industry remains well within its infancy of leveraging big data for business and clinical use," writes Hoover.
All the same, providers are clearly curious about the best uses of analytics, and as they learn how do harness them together, the industry should mature quickly – and catch up to other industries, that are much further ahead of the game.
Access iHT2's "Transforming Health Care Through Big Data" here.
[See also: IBM offers tips for doing big data right]