In part one of the series on Clinical intelligence (CI), I covered analytics and performance management. Today’s discussion focuses on CI and data management.
CI results from the use of querying, reporting, analytical processing and alerting that help answer event-based questions such as: “What happened?”, “How many times?”, “How often did it happen?”, “Where exactly is the problem?” and “What actions are needed to resolve it?” CI is best for gaining insight into current activities and events, as well as understanding what has happened and how those events have affected the patient status. CI answers the question, “What works best for whom?” the cornerstone of best practice.
Data management is the development and execution of architectures, policies, practices and procedures designed to help properly manage the collection, quality, standardization, integration, aggregation and governance of data across the organization. Data management primarily involves looking backward and figuring out how to learn from the past to improve the present and the future. There are multiple drivers of investments in information technologies. First, IRFs collect vast amounts of information about their clinical activities and patients through generated patient care transactions, billable events and electronic reporting systems. However, this discrete information doesn’t provide an integrated view across the hospital. The problem of data is literally growing out of control, and the lack of a holistic view will begin to cripple many IRFs in the not-too-distant future.
Compliance leads the push for better clinical analytic capabilities. Analytics tools are key enablers to support regulatory requirements. Costly as it may be, most IRFs have no choice but to implement these tools in order to adhere to compliance measures and to monitor and mitigate risk.
Increased performance and competitive demands are intense drivers of improved clinical analytic capabilities. The need to remain competitive compels IRFs to invest in the knowledge tools that improve insight into clinical and market information, which in turn can enable more informed and proactive decisions. Rehabilitation hospitals lag far behind most knowledge dependant companies utilizing comprehensive performance management systems to deliver information to decision-makers to improve insight and outcomes.
Why is CI necessary? Clinical analytics will shift the knowledge paradigm. Currently, IRFs are investing in EMR systems to automate and streamline their record keeping and care delivery processes. This has resulted in a significant increase in organized data; however, the focus has shifted from simply organizing data more efficiently toward analyzing information to improve performance. Clinical analytics can help IRFs move from answering the question, “What do I need to do?” to answering the more complex question of, “What do I need to know?”
This paradigm shift is the wave of the future. Most IRFs know what they need to do. To stay ahead of the competition in the future, they will need to slice and dice their data in myriad, increasingly complex ways, in order to understand what they need to know about their clinical practice to improve its effectiveness. One way to gain this knowledge is to leverage CI to gain foresight as well as insight. Hospitals that are best able to leverage clinical analytic capabilities will certainly be better positioned to thrive in an uncertain future.