Becker's Hospital Review

Health Information Technology ortune 500 21 "When it comes to data analytics, the healthcare industry is just starting to catch up to other sectors that have been successfully using analytics for decades." to data collection, the commitment of leadership to make data-based decisions rather than relying on their personal experience, the organization's focus on the most strategic targets and an analytics staff being developed with the experience to handle the data and with enough career opportunities to keep them in the field. However, a recent survey conducted by the eHealth Initiative and the College of Healthcare Information Management Executives revealed while 80 percent of CIOs and other healthcare executives believe data analytics are important to their organizations' strategic goals, 84 percent said using big data presents a challenge. Less than half (45 percent) of respondents said their organization has a big data management plan, and just 17 percent reported having staff trained to collect and analyze data. Further, those organizations that have begun to employ data analytics have not yet seen results. Just 38 percent of hospital and health system leaders recently surveyed by the Society of Actuaries reported seeing no direct business benefits from using big data, though this survey again revealed a self-reported lack of resources and staff to get the most out of the data they have. Hospital and health systems' struggles to capitalize on data analytics have not gone unnoticed by HIMSS Analytics. Data collected from the country's hospitals by the organization revealed a need for data analytics guidance. "We realized what healthcare organizations were wanting was a maturity model, a framework to understand where they were in regards to analytic maturity, and a roadmap to move forward and apply talent and resources to enhance their analytic abilities and engage in new care-delivery models," says James Gaston, senior director of clinical and business intelligence at HIMSS Analytics. When setting out to develop the model, Mr. Gaston and his team looked to what other industries were using as analytics guidance. "IT companies, banking and retail have all demonstrated the value of analytics and managing information for effective business use," he says. "So why would we create a whole new model for healthcare when there are good models out there that other industries have embraced?" HIMSS Analytics worked with The International Institute for Analytics (which was assisted by Dr. Hughes and SAS) to adapt the DELTA Model, an industry-agnostic scale for data analytics maturity described in Analytics at Work1 for use in the healthcare industry. The standards are the same that have helped the aviation, IT, retail and other industries embrace big data analytics, but the language and examples have been tailored for use by a healthcare audience. The resulting DELTA Poweredtm Analytics Maturity Model focuses on five areas: the availability and accessibility of data, an enterprise approach The model was announced in the spring, and HIMSS Analytics currently has 30 organizations on the model to start developing industry-specific benchmarks. Based on the current industry-agnostic model, Mr. Gaston estimates most healthcare organizations are at about the second of the model's five levels, where data is being collected and used at a very localized level. "Most organizations have some abilities. Some might be higher, but overall they're just beginning to see the benefits of EMRs and the data they collect," says Mr. Gaston. For healthcare organizations, this means the time is now to begin more aggressively pursuing a data analytics program, taking advantage of the large amounts of data contained in a modern healthcare system as well as tools and support from industry organizations like HIMSS Analytics. Some healthcare organizations have already dedicated themselves to getting the most out of their data. Pittsburgh-based UPMC, a system with more than 20 hospitals and more than 4.2 petabytes of data, is actively investing in its data analytics capabilities to deliver the best care to its patient population. However, even Rasu Shrestha, MD, the system's vice president of medical IT, says the system still has a ways to go. "We have lots of aspirations around predictive models of care, and we're working on correlating clinical data to outcomes data, integrating financial data and data on individual physician performance as well," says Dr. Shrestha. "We're still working to connect all the dots." n

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