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In today’s healthcare world, benefits brokers are primed to gain a competitive edge through harnessing the power of big data analytics. With the right analytics engine, brokers can streamline risk analysis to provide their clients with key insights – at micro and macro levels – that shed light on crucial aspects of a member population and generate actionable results (1 Year $1 Million Saved: CEBG). The next major step in healthcare technology is here and ready to assist in the effort to improve population health.

 

Finding the right data analytics risk engine to “wow” clients, however, is another story. Understanding specifically what to look for in an engine will help brokers find the best fit. The right analytics tool will provide brokers with the guidance to work smarter and stay focused without losing the “big picture” perspective.

 

Elements of a top-notch data analytics risk engine include:

 

A Distinct View - A risk engine that provides granular data views and analysis will better help you understand costs, care delivery and quality at the individual level, as a company and compared to other companies or similar industries.

 

Insight at Your Fingertips - Both macro and micro trends within a population, and specific drivers should be at your fingertips; no need to wait for answers you need today to stay on track.

 

Customization - You shouldn’t have to sift through data to find what you need. Every company has unique needs and challenges and the right data analytics risk engine will be able to deliver distinct insights that are easily adjustable to your client’s needs.

 

Advanced Quality and Accuracy - Individual claims data and real-world factors, such as where people live and their behavior patterns, should be used in assigning and updating risk scores to individuals within a given population.

 

Predictive Modeling - It is critical that an engine not only provide actionable insight into a given population, but also be able to calculate conditions, gaps in care, hospital admissions, and re-admissions several months to a year in advance. The right risk engine should be able to identify members that could benefit from care management, compliance with preventive and condition-related best practices, and participation in health activities.

 

Generic analysis and trends are the current standard; using a dynamic healthcare data mining technology that provides customizable, granular and actionable data at your fingertips is not – but should be, considering our health system operates in the information age. The plentiful insights, and cost savings opportunities employers gain are plentiful and unprecedented.