Big data is now commonly used in the financial and health care industries. It encompasses massive quantities of complex, variable, high-speed digital information, the sheer size and content-disparity of which compels use of innovative technologies for storage, management and use. Data evaluation is crucial to its application, particularly for design and delivery of core and voluntary benefits.

Big data analytics and associated reporting tools collect, analyze and interpret information. Under pressure to do more with less, insurers are pushing data analysis to new heights. Insurance carriers apply the results to a growing number of enterprise priorities.

In general, the overriding objective is isolating pertinent relationships among data, converting the information into business intelligence (BI) to improve health care benefits administration. More particularly, big data analytics can enhance outcomes for:

  • Policy go-to-market/underwriting outcomes
  • Consumer engagement
  • Risk and performance assessment
  • Cost reduction

Most health insurance providers engage data analytics as an integral component of their benefits administration because they recognize its ability to generate better, more efficient healthcare at substantially lower expense. Cost savings emerge for providers and health care consumers, both individual and corporate.
Analytics and reporting tools stimulate enhanced benefits administration for corporate clients, with respect to such aspects of coverage as:

Product performance

One condition that complicates benefit administration for insurance carriers is the diversity of insurance products required by corporate customers. Each will seek a coverage arrangement suitable to the precise needs of their firm and workers. Designed to improve the quality of BI, analytic and reporting tools can generate exceptionally accurate real-time appraisals of each coverage-product's performance, in relation to its intended purpose and competitor’s products. Big data generates an entire range of relevant numbers, statistics pertinent to annual performance, as well as quarterly, regional and demographic measurements, evaluated by customer or industry. These data can be used as a basis to modify strategies according to analytical outcomes and directives.

Employee medical history

Big data analytics combine acquired and stored information regarding patients from their medical records and available research databases to suggest more accurate diagnostic and treatment options to physicians. Moreover, analysis of patient claims history can determine how closely they adhere to treatment guidelines laid out by their physician. Reporting these data can be particularly important for patients suffering from such chronic conditions as heart disease or diabetes, where the objective is better disease management through preventive care. Patients identified as likely to be noncompliant then receive tailored interventions to help overcome their specified medical problems. Such factors as the patient's age, medical/prescription history and their specific economic, educational and occupational background, as well as current living circumstances, enrich the quality of data analyzed, to inform insurers’ benefits administration decisions. Lower policy and treatment costs are a typical result.

Client HR function

Analytics focus on selected aspects of each client health care program. Both the insurance provider and the client HR department require access to data concerning employee demographics/participation rate, benefit selection, hospital/health care use, time-to-complete the enrollment process and cost of treatment-per-employee or service. These data can be used to modify benefits administration processes and the content of policies themselves, to provide better-quality, less costly health care.

Consumer engagement

Analyzing and reporting big data is useful for measuring not only the overall use and effectiveness of employer private exchange policies in the workplace, but also employee acceptance of them and their exercise of self-select care options. Interpretation of data shows which treatment options employees are using and how well they're working, providing a basis for policy modifications that better reflect consumer healthcare needs while lowering the cost of their delivery. Assessing health plan utilization, participation and results helps employers identify initiatives that work, as well as those draining resources with no quantifiable return on investment. 

Health care data analysis for benefits administration is not confined to insurance providers for their B2B clients. Third parties also generate professional assistance tracking and reporting trends in health-risk assessment, developments in treatment/prevention, claims analysis, policy effectiveness, medical innovation and, most importantly, consumer engagement. Dedicated to benefits analysis for health care insurance, their contribution to the insurance industry should continue to grow at a rate commensurate with big data application. If you’re interested in further data analysis in your benefits enrollment, a guide to ideal enrollments is available here.

Freund, CFP, ChFC, CLU, is president of Common Census, Inc. Reach him at daniel.freund@commoncensus.com.

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