DATA ANALYTICS. The Importance of. for Self-Insurers by Robin Gelburd

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1 The Importance of DATA ANALYTICS for Self-Insurers by Robin Gelburd 4 September 2013 The Self-Insurer Self-Insurers Publishing Corp. All rights reserved.

2 Rising health costs in the United States have increased the financial burden of healthcare coverage for all parties especially employers and employees. To combat this continuing trend, everyone must be more strategic about how they manage healthcare costs. Many employers see the Patient Protection and Affordable Care Act s (ACA) exemptions for self-insurers as an opportunity to take greater control of the cost of their employee health benefits. Even while changes continue to be made to the ACA, meaning that the ultimate impact of the decision to self-insure remains unclear, many employers are revisiting the option to self-insure. According to research by the Employee Benefit Research Institute, one fact remains clear: selfinsurance is an increasingly popular option for employers in an era of high and escalating premiums. With this trend comes premium relief but also increased risk for predicting and managing employee health costs. In order to fully comprehend these costs and strategize accordingly employers need access to regional market information on benefits utilization and health risks. This data can help self-insured organizations better understand, and mitigate, short- and long-term risk through smart plan design and clear, actionable benefits communication. Self-insured employers have access to the claims data of their workforce, but current employee information is not the only data with which they should be concerned. Broader market information is crucial to support health plan design and offerings. Understanding how a plan population s utilization patterns differ from that of the general population in the area can inform a host of decisions from network makeup, to investments in training and ergonomic equipment, to wellness program features and incentives. For example, analyses of the most and least common diagnoses or procedures and their associated costs in a region can provide valuable insights that help companies make educated decisions regarding their offerings. Such understanding can be an important commodity in an era when healthcare costs are continuing to rise, but employers and consumers are eager to reduce their payments while maintaining employee health and satisfaction. Below are several samples of market-level healthcare data in action: how data can provide key insights into benefit costs and utilization, network adequacy, risk management through wellness programs, the evaluation of fee schedules and claims adjudication and fraud detection. Cost and utilization trending One smart way for employers to design cost-effective healthcare and dental plans is to analyze utilization and billing patterns in zip codes where employees currently receive care. With this analysis, employers can construct offerings, incentives, coverage levels, networks and co-pays to drive smart short- and longterm health behavior. This cost and utilization data also helps employers make smart plan and network design decisions, which keep employees healthy and productive. In dentistry, for example, the administration of topical fluoride is a procedure performed on high-risk patients to guard against tooth decay the figure below shows the locations for selected states where the lowest to highest percentages of topical fluoride applications are reported. Analysis of plan data in comparison to data for multiple insurers within the state can help evaluate if plan members needs are being met. Potential actions that could result from this study might include communications to plan members about the benefits of fluoride treatments and/or educating network providers about the importance of identifying high-risk patients for whom this procedure would be appropriate. Why Big Data and data analytics? When self-insuring for medical and/or dental care, it is critically important that employers understand the profile of their plan population. Data that provides a window into both the cost and utilization patterns of their plan population can support analysis and research that generates insights resulting in better-tailored benefit design. Self-Insurers Publishing Corp. All rights reserved. The Self-Insurer September

3 Network adequacy Claims data provide a critical tool for understanding network composition which, in turn, helps employers design plans that cover employees adequately and cost effectively. The below example demonstrates patient utilization with respect to emergency department visits across New York during The data raise a number of interesting questions regarding network adequacy. Do zip codes with the highest emergency department visits suggest inadequate primary care networks? How mobile is your wellness service? Take us with you! Let us show you how Call: info@attunelife.com visit attunelife.com to learn more Attune Health Management, Inc Preston Rd, Suite 220 Plano, Texas Alternatively, does high emergency room utilization suggest the absence of sufficient emergency rooms in the surrounding areas? How do the business hours of primary care practices impact the utilization of emergency room visits in those high utilization areas? For self-insurers with employees receiving care in regions with high emergency department visits, it s essential to (1) expand primary care networks (or operating hours) to enhance care management and thereby reduce emergency room utilization; (2) provide greater coverage relating to emergency department visits and (3) educate employees about their options such as access to urgent care facilities for non-emergency services. Wellness and disease management programs Data can also help self-insured employers understand the needs of a patient population more fully, which helps companies design wellness and disease management programs that impact their bottom line. Chronic conditions are among the highest in cost and place employers under the highest risk when self-insured, not to mention the time lost when these employees miss work. Preventative measures may be essential to lower employer risk and increase employee health. Such programs should not have a one-size fits all approach, but should mirror the needs of the employee population being served. For example, an employer might choose to compare its claims data to overall regional data to determine differences that suggest the need for certain educational and/or preventive services. Thus, if a company sees a high incidence of carpal tunnel surgeries in its workplace, programmatic SIIA-DisplayAd-2013-v5.indd 1 7/2/2013 4:43:22 PM 6 September 2013 The Self-Insurer Self-Insurers Publishing Corp. All rights reserved.

4 overall experience of the privately insured population provide a stronger base for decision making. Market data can be used to create usual, customary and reasonable fee schedules for outof-network reimbursement and ensure that allowed charges don t exceed the needs of the local market. Smart use of data can empower decision makers to run their plans efficiently. interventions can be developed. The company might consider introducing certain work routines, rest breaks or other measures as strategies to reduce injuries caused by repetitive tasks. Further, to evaluate whether a wellness routine is having its intended benefit, employers might decide to track carpal tunnel surgery utilization against the larger market over time. Fee schedules and claims adjudication Data can be an important aid to managing reimbursement risk. While self-insured plans have access to their own claims data, insights into the Fraud and abuse Another interesting use of data can be to identify charge outliers to detect possible instances of fraudulent billing practices. Billed charges for a particular procedure in a given area generally follow a bell curve, which can also be compared to the plan s experience for the same procedure. While the curve for billed charges may vary to a higher degree for some procedures than others, as demonstrated by the figure below, outliers charges that vary widely from the curve may warrant further investigation. Assistance for Stop Loss Coverage At BenefitMall, we know that some employer groups benefit most from treating their medical plan as an investment rather than an expense. Our self funded team of experts represents numerous direct writers of medical stop-loss. We can help you succeed by offering: Marketing Billing & Premium Collection Licensing, Commission & Bonus Programs Claims Expedition Compliance Services (888) BenefitMall. All rights reserved. BenefitMall, the BenefitMall Logo, the BenefitMall ALL TOGETHER, BETTER Logo, the ALL Logo, ALL TOGETHER, BETTER, CompuPay and Self Funded Products and Services are trademarks or registered trademarks of Centerstone Insurance and Financial Services, Inc. d/b/a BenefitMall or its affiliates in the U.S. California License # *All other trademarks are the property of their respective owners. Self-Insurers Publishing Corp. All rights reserved. The Self-Insurer September

5 The charges on the right side of the graph clearly fall outside of the normal distribution of charges. Research into these charges may show that there were extraordinary circumstances involved with the provision of these services; however it might highlight a single practice that is consistently overbilling for the procedure. Companies can harness the power of data by comparing their plan s experience to the overall market area to save costs and ensure the smooth operation of their benefi ts programs. Using data to support more informed - and satisfied - employees Data analyses provide great tools to ensure that self-insured plans meet the needs of both employers and employees. But a good plan is just the beginning. Self-insured employers need to invest in employee education to keep satisfaction high and costs low. To help employees make smart choices (and avoid surprises), employers need to provide clear plan information and decision support tools. With issues such as in-network and out-of-network fee schedules, as well as varying reimbursement rates, there is great potential for employees to incur unexpected out-of-pocket costs, which can lead to dissatisfaction, reduced productivity and compromised health outcomes. Data can help in this regard as well. Many companies are incorporating out-of-network cost estimation and transparency tools into member portals to help their employees make informed decisions when choosing providers. As more employers decide to selfinsure, they need clear, accurate data to manage risk and make smart choices. Data gives employers a window into utilization and billing patterns that can be a guide for plan and network design. Equally important, data helps employers develop smart communication and disease management programs, and ultimately achieve better, more affordable health outcomes. n Robin Gelburd is President of FAIR Health, Inc., a national independent, not-for-profi t corporation whose mission is to bring transparency to healthcare costs and health insurance information through comprehensive data products, consumer resources and research tools, all powered by the nation s largest collection of medical and dental claims data. 8 September 2013 The Self-Insurer Self-Insurers Publishing Corp. All rights reserved.