Heard recently, “Our organization has lots of analytics, but we really don’t really know what to do with them.” This is a common dilemma. Analytics (data analysis) are abundant, they are presented in annual reports and published in colorful graphics. Too often the effort ends there. Nice information, but how does it change operational flow, claim outcomes and profitability?
Obviously, the basic ingredient for analytics is data. After that comes skill, ingenuity, and creativity. Business intelligence and knowledge are severely limited without data. Fortunately, the last thirty years have been primarily devoted to data gathering.
Over the past thirty years or more, all industries have evolved through several phases in data collection and management. Main frame and mini-computers produced data and with the inception of the PC in the 80’s, data gathering became the business of everyone. DOS systems were clumsy and there were significant restrictions to screen size and data volume.
Recall the Y2K debacle caused by limiting the year to two characters instead of four. The two digit year was made necessary in early computing because of restricted capacity.
Happily for the data gathering effort, progress in technology has been rapid. Advancement was enhanced first by local and wide area networks, then by the Internet along with ever more powerful hardware and lower costs. Data gathering has been overwhelmingly successful.
Now we have truckloads of data, often referred to as Big Data. In fact, a new industry has developed around understanding and managing huge data volumes. Once Big Data is corralled, analytic possibilities are endless.
The Workers’ Compensation industry has also collected enormous volumes of data. Now, much is being done in the industry to actualize the analytics to produce knowledge that support reductions in costs and improved outcomes.
Imbed analytic intelligence
The best way to apply analytics in Workers’ Compensation is to create ways to translate and deliver intelligence to the operational front lines, to those who make critical decisions daily. Knowledge derived from analytics cannot change processes or outcomes unless it is imbedded into the work of adjusters, medical case managers, and other key personnel. These professionals make decisions that affect the course of claims and they need electronic knowledge tools to assist them.
Consulting graphics for guidance is cumbersome, interpretation is uneven or unreliable, and the results cannot be verified. Therefore, intelligence must be made easily accessible and easy to interpret and apply. Front line decision-makers need online tools designed to support decisions and direct actions.
To effectively imbed analytic intelligence into operations, all claims data must be continuously monitored electronically. Data in claims must be monitored continuously so the system can identify claims that contain conditions cautioned by the analytics. The interpreted information is then linked to operations.
By electronically monitoring all claims for high risk events and conditions informed by analytics, high risk and migrating claims cannot slip through the cracks.
Personnel can be alerted of all claims with risky conditions identified through analytics. Additionally, the analytic delivery system should automatically document itself.
The system that is developed to deliver analytic knowledge to operations should automatically self-document. That is, it should keep its own audit trail to record to whom the intelligence alert was sent, when, and why.
Without self-documentation, the analytic delivery system lacks authenticity. Those who receive the information cannot be held accountable for whether or how they acted on it. When the system automatically self-documents, those who have received the information can be commended for, or held accountable for their part. Management is able to review current status at any time.
A system that is self-documenting can also self-verify, meaning results of delivering analytics to operations can be measured. Claim conditions and costs can be measured. Moreover, further analyses can be executed to measure what analytic intelligence is most useful, in what form, and importantly, what action responses generate best results.
The analytics-informed knowledge delivery system monitors all claims data, identifies claims that contain risk elements, and creates knowledge tools for front-line workers. The data becomes a work-in-process information and decision-support tool while analytics are linked directly to outcomes and savings are objectively measured.
Karen Wolfe is the founder and President of MedMetrics®, LLC, a Workers’ Compensation, analytics-Informed medical management and technical services company. MedMetrics offers online apps that link analytics to operations, thereby making them actionable and measureable. firstname.lastname@example.org