Other challenges that will confront healthcare IT executives as they implement health data analytics tools, according to the report, include:
-- High implementation and licensing fees. Implementation and subscription/licensing fees for advanced analytics are just one more financial burden and can add to the budgetary woes faced by many hospitals today. Advanced health data analytics systems can cost over $100,000 for implementation and about the same for annual subscription/licensing fees, making it difficult for hospitals to justify spending, at least in the short term when they are so focused on implementing EHRs and upgrading revenue cycle management (RCM) systems.
-- Communication barriers in hospitals that slow information sharing. Many hospitals have siloed departments and service lines that operate as independent units. They have not previously had to share data across multiple departments within the same hospital, much less across an entire IDN.
-- Lack of standardized health data that affects analytics use. Inconsistency in capturing and defining data limits the use of clinical data for patient care metrics. Hospitals are increasingly working to integrate and standardize data across various operational units. However the lack of robust and consistent data standards will likely limit the uptake of advanced health data analytics to some extent.
-- Continued use of existing basic analytics tools that restrict the implementation of newer solutions. Many hospitals, particularly small and rural hospitals, continue to rely on their existing, rather basic, legacy business intelligence systems--think Excel and Access. These tools are often only used at the department level and likely use only retrospective data to develop reports.
According to Fabozzi, many hospitals intend to continue using business intelligence tools that focus mainly on financial and administrative data, but change is inevitable.
"Realistically, a lot of hospitals will continue to use these processes for some time because of all the other aforementioned barriers to changing over to newer systems," Fabozzi said. "Legacy business intelligence tools will be seen as "good enough for now" until it just becomes too inefficient to continue."