Top Challenges to Analytics in Healthcare? Not Technology
A variety of challenges stand in the way of successfully implementing analytics in healthcare organizations. Not surprisingly, the top issues dont always involve technology.
A variety of challenges stand in the way of successfully implementing analytics in healthcare organizations. Not surprisingly, the top issues don’t always involve technology.
This finding became clear in a study conducted by the Healthcare Center of Excellence this summer, which sought to determine what are perceived to be the top challenges facing analytics.
The study reveals the importance of executive leadership skills in bringing about support of analytics and the extent to which findings from analytic efforts are incorporated into how organizations change and adapt. This aspect of leadership, while learnable, needs to happen quickly if organizations want to achieve the desired incomes from their forays into analytics.
Methodology of the Study
During a workshop at Health Data Management’s Healthcare Analytics Symposium, held in Chicago in July, participants were asked what they believe to be the top challenges they face in implementing analytics at their healthcare organization. They each were asked to identify as many as five challenges they face, and then were put into groups to develop three solutions to overcome those challenges.
The challenges were classified into 10 categories – analytic tools, change management, costs, data management, education, integration, leadership, process, talent and technology. While the challenges facing healthcare analytics implementations may not surprise anyone, the order of magnitude, related to the number of times they were mentioned may be surprising.
The top three categories were leadership, mentioned by 29 percent; data management, mentioned by 18 percent; and talent, mentioned by 14 percent. The technology and tools weren’t perceived as being a problem – in fact, technology was mentioned by only 5 percent, analytics tools and process, both at 3 percent.
Leadership included common terms and phrases, such as lack of priority, lack of vision, need for buy-in from staff and lack of direction, but it also included disparate EHR systems, siloed systems and teams not working together – problems that also can be resolved through strong leadership.
Terms that were included in the data management category included the lack of data standardization, lack of data stewardship, lack of definition of key variables to study, a lack of agreement on where the data resides, and issues involving the quality of data.
Talent components include the lack of adequate analytics talent, hiring the right people, lack of skills, not enough qualified staff and retaining talent.
Who Identified Deficiencies
The sources of these comments were really surprising to the researchers. Participants were asked to include their title on the surveys, and the titles were summarized into general categories that indicated responses from all levels of the organizational hierarchy, ranging from C-level executives to analysts.
Titles were matched back to the challenges listed by individuals, to determine if there was any disparity between responses based on organizational level. In addition, levels were further summarized by span of control – those with a wide span of control included positions at the director level and above. All others were included in the narrow span of control group.
Of the total challenges categorized as leadership problems, the “wide span” participants pointed to leadership issues (27 percent) almost as frequently as “narrow span” participants (31 percent).
The only challenges where the disparities were significant were in integration and processes, probably due to perspective. “Wide span” executives are anxious to see results achieved for their investments through data integration; by contrast, “narrow span” participants prefer more, and better, processes, to make their jobs easier. Of the solutions developed by the small workgroups, some 54 percent addressed leadership issues, the largest by a wide margin.
Implications for Leadership
Although the results weren’t surprising, the strength of the argument for better executive leadership skills in healthcare was obvious. Many of those outside of healthcare organizations can see this problem, and those within organizations are likely to wholeheartedly agree. It’s the 800-pound gorilla that no one really wants to identify, but as soon as it’s mentioned, everyone starts nodding in agreement.
These results aren’t intended to disparage healthcare leaders – they’ve been dealt a tough hand. No other industry has been asked to make so many dramatic changes in such a short period of time. It’s like asking an electronics retailer to also become a fine French restaurant in 12 months.
Most healthcare executives have not been trained to handle the scope of the business shift now being demanded of healthcare organizations, and that impact trickles down to those in the analytics department. The good news is that this type of leadership can be learned; while it can’t be achieved overnight, this leadership transition in analytics must happen quickly if success is the desired outcome.
J. Bryan Bennett is a predictive analytics subject matter expert and adjunct professor for Northwestern University’s School of Professional Studies Predictive Analytics Certificate Program. He also teaches healthcare marketing for Loyola University’s master’s program and leadership classes for Judson University’s organizational leadership graduate program. He is the director of the Healthcare Center of Excellence, http://www.healthcarecoe.org/.
This finding became clear in a study conducted by the Healthcare Center of Excellence this summer, which sought to determine what are perceived to be the top challenges facing analytics.
The study reveals the importance of executive leadership skills in bringing about support of analytics and the extent to which findings from analytic efforts are incorporated into how organizations change and adapt. This aspect of leadership, while learnable, needs to happen quickly if organizations want to achieve the desired incomes from their forays into analytics.
Methodology of the Study
During a workshop at Health Data Management’s Healthcare Analytics Symposium, held in Chicago in July, participants were asked what they believe to be the top challenges they face in implementing analytics at their healthcare organization. They each were asked to identify as many as five challenges they face, and then were put into groups to develop three solutions to overcome those challenges.
The challenges were classified into 10 categories – analytic tools, change management, costs, data management, education, integration, leadership, process, talent and technology. While the challenges facing healthcare analytics implementations may not surprise anyone, the order of magnitude, related to the number of times they were mentioned may be surprising.
The top three categories were leadership, mentioned by 29 percent; data management, mentioned by 18 percent; and talent, mentioned by 14 percent. The technology and tools weren’t perceived as being a problem – in fact, technology was mentioned by only 5 percent, analytics tools and process, both at 3 percent.
Leadership included common terms and phrases, such as lack of priority, lack of vision, need for buy-in from staff and lack of direction, but it also included disparate EHR systems, siloed systems and teams not working together – problems that also can be resolved through strong leadership.
Terms that were included in the data management category included the lack of data standardization, lack of data stewardship, lack of definition of key variables to study, a lack of agreement on where the data resides, and issues involving the quality of data.
Talent components include the lack of adequate analytics talent, hiring the right people, lack of skills, not enough qualified staff and retaining talent.
Who Identified Deficiencies
The sources of these comments were really surprising to the researchers. Participants were asked to include their title on the surveys, and the titles were summarized into general categories that indicated responses from all levels of the organizational hierarchy, ranging from C-level executives to analysts.
Titles were matched back to the challenges listed by individuals, to determine if there was any disparity between responses based on organizational level. In addition, levels were further summarized by span of control – those with a wide span of control included positions at the director level and above. All others were included in the narrow span of control group.
Of the total challenges categorized as leadership problems, the “wide span” participants pointed to leadership issues (27 percent) almost as frequently as “narrow span” participants (31 percent).
The only challenges where the disparities were significant were in integration and processes, probably due to perspective. “Wide span” executives are anxious to see results achieved for their investments through data integration; by contrast, “narrow span” participants prefer more, and better, processes, to make their jobs easier. Of the solutions developed by the small workgroups, some 54 percent addressed leadership issues, the largest by a wide margin.
Implications for Leadership
Although the results weren’t surprising, the strength of the argument for better executive leadership skills in healthcare was obvious. Many of those outside of healthcare organizations can see this problem, and those within organizations are likely to wholeheartedly agree. It’s the 800-pound gorilla that no one really wants to identify, but as soon as it’s mentioned, everyone starts nodding in agreement.
These results aren’t intended to disparage healthcare leaders – they’ve been dealt a tough hand. No other industry has been asked to make so many dramatic changes in such a short period of time. It’s like asking an electronics retailer to also become a fine French restaurant in 12 months.
Most healthcare executives have not been trained to handle the scope of the business shift now being demanded of healthcare organizations, and that impact trickles down to those in the analytics department. The good news is that this type of leadership can be learned; while it can’t be achieved overnight, this leadership transition in analytics must happen quickly if success is the desired outcome.
J. Bryan Bennett is a predictive analytics subject matter expert and adjunct professor for Northwestern University’s School of Professional Studies Predictive Analytics Certificate Program. He also teaches healthcare marketing for Loyola University’s master’s program and leadership classes for Judson University’s organizational leadership graduate program. He is the director of the Healthcare Center of Excellence, http://www.healthcarecoe.org/.
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