Mayo Clinic initiative takes analytics to the enterprise level
Assessment finds information gaps leading to organizational changes that expand the use of predictive analytics throughout the system.
Implementing an enterprise analytics organization at the Mayo Clinic has not been an easy journey, but it’s starting to pay dividends for one of America’s most respected healthcare organizations.
Mayo Clinic’s analytics capabilities are fast becoming one of the largest and most sophisticated in the nation. However, that hasn’t always been the case, according to Joe Dudas, division chair of enterprise analytics, who has been leading efforts to tap into Mayo’s database of more than 5 million patient records and healthcare partners that provide access to more than 100 million.
Nonetheless, “big data is not about the data—it is about the analytics,” Dudas said during an address at HDM’s Healthcare Analytics Conference in Chicago. “Instead of just telling what happened, we need to tell what’s going to happen and, more importantly, why it’s going to happen. That’s really a role for advanced analytics.”
Among the advanced analytics at the Mayo Clinic are a model that can predict 12-month mortality and a cancer cost-of-care calculator that can accurately project six-month costs for patients, as well as ongoing work on claims denials.
About 18 months ago, the Mayo Clinic conducted a comprehensive assessment that found organizational gaps in the information necessary for the organization to achieve its goal of delivering the highest value care. Based on leadership and staff interviews, he said the assessment concluded that the organization was “data rich and information poor,” while “way too much time and energy was being spent on data and not enough time on analytics.”
The analytics shortfalls that the Mayo Clinic identified were in two specific areas: clinical operations and patient-centered care. In particular, only 17 percent of the Mayo Clinic’s leadership felt that the needed service level could be delivered by its current analytics capabilities. Further, just 12 percent of the organization’s staff indicated that the current analytical tools were actually being shared enterprise wide.
“On the one hand, we’re being told we’re not delivering enough. And, on the other hand, we’re not using what we have,” remarked Dudas. “If you have tools that are good tools and they’re not being used, that’s an easy way to scale.”
To help with the scaling of these analytical tools at an enterprise level across its three U.S. regions, the Mayo Clinic has dedicated more personnel to the effort, with more than 70 staff designated for analytics consulting, design, development and operations, as well as data management.
Another focus area has been improving data quality and enabling self-service, according to Dudas. “This really boils down to three things: proactive positioning of data, the reliability and quality of information, and—last but not least—supplying tools that users like to use,” he said.
One of the key areas of transformation was the Mayo Clinic’s move from project management to product management, observed Dudas, whose organization is responsible for providing seven analytics product lines. “Product management is a proactive process,” he said. “Instead of waiting for a request, we anticipate what’s going to be needed. This is a fundamental change...You can’t wait for the demand to come to you. You just don’t have time.”
Gone are the days of custom development, Dudas concluded, adding that analytics tools must have a purpose. “What is the question you’re trying to answer with the data?”
Mayo Clinic’s analytics capabilities are fast becoming one of the largest and most sophisticated in the nation. However, that hasn’t always been the case, according to Joe Dudas, division chair of enterprise analytics, who has been leading efforts to tap into Mayo’s database of more than 5 million patient records and healthcare partners that provide access to more than 100 million.
Nonetheless, “big data is not about the data—it is about the analytics,” Dudas said during an address at HDM’s Healthcare Analytics Conference in Chicago. “Instead of just telling what happened, we need to tell what’s going to happen and, more importantly, why it’s going to happen. That’s really a role for advanced analytics.”
Among the advanced analytics at the Mayo Clinic are a model that can predict 12-month mortality and a cancer cost-of-care calculator that can accurately project six-month costs for patients, as well as ongoing work on claims denials.
About 18 months ago, the Mayo Clinic conducted a comprehensive assessment that found organizational gaps in the information necessary for the organization to achieve its goal of delivering the highest value care. Based on leadership and staff interviews, he said the assessment concluded that the organization was “data rich and information poor,” while “way too much time and energy was being spent on data and not enough time on analytics.”The analytics shortfalls that the Mayo Clinic identified were in two specific areas: clinical operations and patient-centered care. In particular, only 17 percent of the Mayo Clinic’s leadership felt that the needed service level could be delivered by its current analytics capabilities. Further, just 12 percent of the organization’s staff indicated that the current analytical tools were actually being shared enterprise wide.
“On the one hand, we’re being told we’re not delivering enough. And, on the other hand, we’re not using what we have,” remarked Dudas. “If you have tools that are good tools and they’re not being used, that’s an easy way to scale.”
To help with the scaling of these analytical tools at an enterprise level across its three U.S. regions, the Mayo Clinic has dedicated more personnel to the effort, with more than 70 staff designated for analytics consulting, design, development and operations, as well as data management.
Another focus area has been improving data quality and enabling self-service, according to Dudas. “This really boils down to three things: proactive positioning of data, the reliability and quality of information, and—last but not least—supplying tools that users like to use,” he said.
One of the key areas of transformation was the Mayo Clinic’s move from project management to product management, observed Dudas, whose organization is responsible for providing seven analytics product lines. “Product management is a proactive process,” he said. “Instead of waiting for a request, we anticipate what’s going to be needed. This is a fundamental change...You can’t wait for the demand to come to you. You just don’t have time.”
Gone are the days of custom development, Dudas concluded, adding that analytics tools must have a purpose. “What is the question you’re trying to answer with the data?”
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