The rise of value-based care models, including value-based insurance and value-based reimbursement, has been inevitable as employers strive to find innovative strategies that enable them to offer quality, cost-effective healthcare benefits.

Value-based insurance relies upon financial incentives to promote cost efficient healthcare services, enabling health benefit plans to reduce barriers to maintaining and improving health. At the same time, value-based reimbursement requires providers to track and report a host of adverse events and population health measures, including biometrics, patient engagement, and other measures to demonstrate quality performance.

Unlike the traditional fee-for-service model, the emerging value-based care paradigm demands credible data to enable providers to effectively measure quality, determine the overall health of the population, and report outcomes to payers, as well as plan sponsors to demonstrate improvement.

Bloomberg

It’s a tall order, but providers are given incentives to use evidence-based medicine, engage patients, upgrade health IT, and use data analytics to get properly paid for the value they deliver. For patients, a value-based approach requires more coordinated, appropriate and effective care, allowing patients to benefit from greater convenience.

Given the shift towards value in healthcare, employers and their benefits advisers can stay informed by accessing data and information about the care quality, safety and performance of the hospitals and physicians that are delivering care to employees.

In short, quality measures are critical for optimizing the benefits of value-based models.

Finding reliable care quality, safety data

Benefits advisers are well positioned to help employers find the right solutions partner that can help them: evaluate quality care based on reliable population health data and utilization profiles; understand the metrics; isolate this information to gain a clear picture of hospital quality and safety; and dramatically rein in costs.

It’s important to include only high-quality doctors who provide services at the lowest costs and achieve better employee health outcomes. The prevalence of numerous hospital quality rating methodologies can foster confusion. Even the slightest differences in adjustment methodology, data source, time period, inclusion/exclusion rules can produce dramatic differences in hospital or physician ratings. For instance, many of the outlets for hospital ratings reflect substantial differences in hospital performance. While this is expected by those literate in healthcare analytics, it fosters broader confusion for those stakeholders trying to find a single source of truth for discerning value. Many approaches lack the academic and scientific rigor to produce accurate, and reliable, measures of hospital and physician quality.

Even ratings from the government may be misleading. In 2016, CMS star ratings gave 102 hospitals top rating of five stars, and only a few of those were considered as the nation’s best by private ratings sources such as U.S. News & World Report or viewed as the most elite within the medical profession. First tier academic journals like JAMA expressed deep concern about the lack of academic credibility in the methods used to assess performance and aggregate the conclusions into a single rating across many different measures. Ratings approaches that use reputation or self-reported data should be considered less reliable than objective outcomes measures using patient level claims data.

Additionally, hospital overall surveys or patient reported outcomes do not offer a valid basis for comparison. It is also not possible to use a single outcome measure, risk adjusted mortality for example, as a proxy for all outcomes like complications or readmissions as provider performance varies widely across measures. For a comprehensive assessment, all available measures should be incorporated for a specific clinical category. It is possible to create a composite quality score provided you use methods which account for levels of statistical significance and standardize observations. When done properly the conclusions can be precise and very simple to use.

As more employers seek greater value for their healthcare dollars, and as benefits advisers continue to help them reduce staggering healthcare costs, quality ratings have become an essential aspect of improving employee health.

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