Christopher J. Donovan: Leveraging Data for Enterprise Business Initiatives
Christopher DonovanData governance and discipline are keys to building a modern, maximally efficient enterprise business intelligence (EBI) platform for health care. The actual technology must be secondary to the organizational activities that go into building an EBI platform designed to serve the business information needs of the organization. The data, not the technology, should be the point of control. Those were some of the main points of a recent presentation by Christopher J. Donovan, executive director of fiscal services at Cleveland Clinic, Cleveland, Ohio, and Kathryn A. Whitmore, managing principal of STS Consulting Group, a technology solutions provider based in Sparks, Maryland, at the recent 2013 HIMSS Conference and Exhibition in New Orleans, Louisiana. According to Donovan, the key lesson Cleveland Clinic has learned (and continues to learn) in its efforts to build the best EBI platform is how to provide the right tools to the right people at the right time, across the organization, to help people do their jobs. “We’re data- and metric-driven,” he explains. “The physician perspective permeates what we do. We use our business intelligence to support performance management. We need to know where the organization is going, strategically and tactically, and its imperatives.” Cleveland Clinic’s guiding principles—continuous innovation, effective governance, proactive and adaptable execution, and consistent process utilization—must be visible to employees and executives, and so must performance metrics. Keeping the CEO Up at Night The initiative to build an improved EBI platform started as “an initiative to understand what was keeping the CEO up at night,” Donovan says. “We needed to identify the gap in our ability to accurately measure performance.” The platform, Donovan notes, is a business program supported by technology. People, process, and governance are the main foci; if governance isn’t in place, technology won’t solve the problem. “Effective data governance requires standard definitions, if the right data are to show up on the executive dashboards,” he says. The EBI platform is governed by a three-tier structure. The leadership team, made up of executive directors from IT, finance, and medical operations, manages the resources and program overall. A strategic council of representatives from several clinical and operational areas meets regularly with the leadership team to provide project ranking recommendations. The leadership team also meets monthly with a team of three C-level executives. The strategic council, as well as patients, provide the leadership team with information on how the market is changing and what their priorities are; the leadership team uses that information to determine what needs to be done, and feeds that information to the executive team. The efficient use of operating rooms is key to the overall operation of Cleveland Clinic, Donovan notes. Thus, input from OR personnel about what information they needed on their dashboards was an essential component. EBI Goals Among the goals that Cleveland Clinic wanted to achieve through its EBI platform were to drive down number of days a new patient would wait to be seen, and to drive up patient satisfaction. To achieve those goals required a linkage of business and clinical analytics. “We organized a central database for financial, operational, and clinical data,” Donovan says. “Over time, we’ll have to change from providing information across this spectrum, to providing analytics across this spectrum. That means thinking of them as one thing.” Analytics are gaining importance, Donovan explains, because of several new challenges facing the health care industry: health care reform, value-based reimbursement, changing expectations, and the need to provide both value and transparency. “Currently, our work is understanding, analyzing, and optimizing existing processes,” he says. “Going forward, the skill sets will have to evolve so we can develop strategies. We need to think of new ways of approaching business, rather than looking back and optimizing our existing processes. Our traditional information strategies won’t bring much value. We need to evolve our competencies to deliver information in a distributive manner. It has to be more browsable. The change in our industry over the next five years will be historic: from a volume-based to a value-based organization.” EBI strategy must align with, support, and inform organizational strategy, Donovan adds. The objective must be to provide analytics that shape strategy, rather than analytics that support existing strategy. Historical Analytics Are Passé Whitmore asserts that there has never been a better time to implement such an EBI platform. The necessary technology has become far more user-friendly in recent years—by 2014, 40% of related programs will be bought by consumers—and a much lower overhead of technological expertise is required to work with it. “We must be more agile and nimble to survive and thrive,” she adds. “Historical analytics are passé. Cleveland Clinic is well aligned with its strategic imperative, but it needs increased analytical competency to innovate and excel, as well as to satisfy increasing consumer demand for information.” Strategy, Whitmore says, must be about performance management excellence, not technology. A less centralized analytics model is needed, as well as an individual empowerment strategy, the ability to have a hands-on approach, and near-time if not real-time data. “How do you empower the front line with information that they can trust?” she asks. “Data governance will help us get there, and Cleveland Clinic is well-positioned with a good data governance foundation. Data governance is not a committee, and it’s not an IT back-office function. It’s an evolving discipline, a coordinated set of processes. It’s data cascading down, data no longer owned by an individual; it’s a matter of transforming data into a corporate asset that’s shared and leveraged. It includes people, procedures, policies, a cascading top-down governance model that transforms data into a corporate asset that’s shared. Transparency and quality of data are essential to empower.” Today’s EBI capabilities, Whitmore says, include remarkable advances in data processing and analytics. Today’s mathematical models can sometimes produce answers before the question is asked. However, she warns, it’s sometimes difficult to separate the value from the hype, which is being driven by the current media focus on analytics, the market demand for it, vendor growth, and accelerated research and development. Planks in the Platform To build its EBI platform, Cleveland Clinic broke its requirements down into five segments: enterprise data warehouse (EDW) infrastructure; integration; information delivery; analysis; and advanced analytics. To meet its needs in each segment, the EBI platform included mobile device support (a new but very important requirement), a full complement of tools for data governance, and interactive visualization with statistical and predictive modeling. The platform addresses volume, velocity, variety, and value. The system delivers a predefined exploration path, making it easier to have conversations on what is driving performance. “It sometimes takes time to refine the dashboards,” Donovan admits, “but we’re willing to pay that price to get what we need.” The platform might, for example, measure on-time standards for treating patients at a given facility, incorporating volume, frequency of late starts, and degree of lateness—and draw comparisons among different facilities. This facilitates discussions about what is driving performance, good or bad. Context-sensitive reports, designed for department managers, might drill deeper. Standardization of the navigation process, dashboard to dashboard, is also important. The data, not the tool, are the point of control. Users of the platform look at the data within parameters defined by the leadership team; thus, they have the data they need but don’t get sidetracked. Such a system, Donovan says, is most useful for relatively small data sets. “We control the definitions, the parameters of that data, so employees can see it but can’t provide their own definitions,” he explains. “Clinical, financial, operational data; real time info on clinical outcomes; historical performance of treatment; costs of treatments: Our platform allows us to analyze all this and inform our decisions, which will be critical, going forward, to providing real-time data to our clinicians and maximum value to our customers.” Joseph Dobrian is a contributing writer for HealthCXO.