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Rethinking the Uses and Value of Employer-Sponsored Biometric Screening

Sherman, Bruce W. MD; Addy, Carol MD, MMSc

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Journal of Occupational and Environmental Medicine: November 2016 - Volume 58 - Issue 11 - p e362-e365
doi: 10.1097/JOM.0000000000000877
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Population-based biometric screening and laboratory testing has been a popular component of workforce wellness programs for many years. Current employer survey data indicate that biometric screenings are the most highly valued of all wellness program offerings.1 Businesses have traditionally viewed employee participation in this offering as a means to promote individual awareness and understanding of results outside the normal (“ideal”) range that may be indicative of increased health risk, with the overarching goal being to prompt appropriate self-referral or self-management of identified health risk concerns.2 As with other health benefits offerings, some employers have opted to use financial incentives in progressively increasing amounts to boost suboptimal participation rates and to encourage employee utilization.3 In the past few years, a number of employers have refocused their use of financial incentives to reward outcomes rather than simply participation in biometric screening. The rationale for this outcomes-based approach is to foster individual engagement seeking professional medical care and self-management, where appropriate, of health issues identified via biometric screenings, including hypertension, hyperlipidemia, obesity, diabetes, and metabolic syndrome.

During the past 2 years, different viewpoints have been expressed regarding the value of biometric screening and its role in health promotion. Proponents assert that the tests help individuals to understand their health status and provide education for and, ideally, motivation for taking action,4 while detractors allege that the testing exceeds United States Preventive Services Task Force (USPSTF)-recommended treatment guidelines, causes discomfort and inconvenience, may lead to additional unnecessary testing, and all in the absence of a compelling value proposition.5

The goal of this commentary is to provide a review of some key considerations regarding biometric screening program outcomes and to propose an alternative use for biometric results that may afford greater value to all stakeholders.


For years, “know your numbers” biometrics awareness campaigns have been a mainstay of employer health promotion programs, with the traditional approach including incentive-based completion of a health risk assessment and biometric screening.6 The general assumption has been that awareness of biometrics results indicative of increased health risks would prompt individual corrective action. Indeed, biometric screening programs have identified a significant proportion of individuals with newly identified conditions or health risks.2 However, for these results to be meaningful, individuals must take action. To do so, they may benefit from a discussion with their primary care practitioner. Unfortunately, data are lacking as to what proportion of individuals have their biometrics results reviewed by their primary care physician or health care team, what percentage of those with a result indicative of increased risk actually meet to discuss the issue with their health care provider, and finally, what proportion of those implement a change in either a lifestyle or medication to address the identified concern.

What insights have we learned about individual health-seeking behaviors following an abnormal population-level health screening result for other conditions? Spirometry screening has not been shown to be an effective independent adjunct to promote smoking cessation in four of five reviewed studies.7 Publicly available ambulatory ultrasound screenings for carotid plaque have not been demonstrated to have an impact on management of risk factors for cardiovascular disease, including smoking.8 Accordingly, although biometric screenings provide quantitative results for individuals, behavior change outcomes from other population-level screening programs would suggest that the health impact for biometric screenings may not be significant.

Unfortunately, efforts to find published evidence regarding the impact of biometric screening on individual behaviors have proved surprisingly fruitless. Intuitively, it would seem that individuals who learn they have biometric results outside of normal ranges from a credible source would have interest in addressing those abnormal findings. However, at an individual level, other factors likely impact individuals’ responses to biometric screening, including, but not limited to health benefit design, access to care, health care consumerism activation or engagement status,9 and socioeconomic status.10 A detailed discussion of these contributors is beyond the scope of this commentary.


If biometric screenings are used to identify individuals with health risks, then it would make reasonable sense to test with a frequency in accordance with evidence-based clinical guidelines. In that context, the recommended screening frequency for adult populations at an average risk for common biometric tests is noted in Table 1.

Current Recommendations for Biometric Screening for Adults From the United States Preventive Services Task Force (USPSTF)

On the basis of these frequency parameters, annual population-level biometric testing for populations of average risk individuals clearly exceeds evidence-based medicine and expert guidance. As such, although the test results may be instructive for individuals regarding identification of health management priorities, we were unable to find any research demonstrating a link between individual biometric test results and health-seeking behavior. Certainly, many individuals with biometric values outside of the normal range may strive to self-manage their particular concern and not seek medical care. That said, it is likely that biometric testing vendors may be in possession of both biometric screening and claims data, but may not have the resources to perform a more rigorous statistical analysis of program impact.

A specific concern relates to lipid profile testing. The 2013 American College of Cardiology/American Heart Association (ACC/AHA) guidelines have prompted a shift away from low-density lipoprotein (LDL) target goals as a basis for treatment, and instead guide practitioners to manage primarily on the basis of predicted heart disease risk.11 Accordingly, in the current framework, measurement of lipid levels alone may not provide sufficient guidance for evidence-based treatment.


Yet in the setting of chronic conditions, these same biometric values have evidence-based support for use in monitoring treatment outcomes, as summarized in Table 2. The four conditions in question, hyperlipidemia, diabetes, hypertension, and obesity, are among the most prevalent chronic diseases in the US adult population. All are associated with disease-specific complications, including heart and vascular disease, certain cancers, and joint degeneration that can significantly increase health care expenditures.

Chronic Condition Prevalence and Treatment Effectiveness for Adults in the United States

Some limited population-level data may be available from health plans regarding the effectiveness of condition management, generally from Healthcare Effectiveness Data and Information Set (HEDIS) measure reporting. Unfortunately, when it comes to an understanding of population-level treatment to clinical goals, most employers have little, if any, information. This knowledge deficit has substantial implications for employers, where outcomes data can be used to more meaningfully structure benefit design in order to increase the likelihood of realizing evidence-based treatment goals. Simply put, if employers are able to shift their tactical approach from cost containment to treatment effectiveness, they may well derive financial benefit from both improved workforce health and performance, as well as a reduced risk of disease-specific complications.


In light of the prior discussion, it seems both evident and reasonable that biometric data can be used as a means for employers to monitor the effectiveness of chronic condition management. By doing so, benefits personnel can become more effective stewards of the health of their benefits enrollees for a number of reasons. First, from a benefit design perspective, outcomes data can help employers to better understand the effectiveness of their benefits tactics and identify opportunities for better alignment with treatment goals. The findings may also help to inform outcomes-based partnerships with health care delivery system entities. Second, the outcomes data can help to more comprehensively evaluate condition management vendor performance, with outcomes representing a potential basis for performance guarantees. Third, at an individual patient level, employers can facilitate sharing of these outcomes data between vendors to help prioritize opportunities for vendor outreach and engagement to individuals who are suboptimally controlled.

As such, the use of biometric testing results in population health management represents enhancements over the current approach. In addition to the noted employer benefits, chronic condition management vendors can use the testing data along with other data sources to refine their messaging approach to individual patients. For example, if two individuals have elevated hemoglobin A1c levels at 8.0%, and one has been adherent to medication while the other has not, the management approach is necessarily different. The first individual will benefit from therapeutic intensification, while the second may need support to improve medication adherence. Personalized communications or messaging platforms that integrate claims data with other data sources will find these test results particularly helpful in generating appropriate algorithm-based, individualized messaging. Finally, implementation of worksite biometric testing programs improves access and convenience for employees, and may increase compliance rates with evidence-based, disease-specific monitoring guidelines, particularly among individuals with high deductibles who may be avoiding care due to out-of-pocket cost concerns.12

The potential for both tactical and pragmatic limitations exist with this approach. First, from a tactical perspective, programs that rely on fingerstick may need to consider adopting venipuncture collection to obtain higher diagnostic accuracy. Second, testing should be performed by entities skilled in performing the specific tests, with processes in place for repeat or serial testing, particularly for blood pressure, to ensure accurate results. Lastly, there is a critical need for the data from this testing to reach the hands of the health care team, to ensure that appropriate therapeutic intervention is provided for those whose conditions are not optimally controlled. In contrast to the biometrics screening scenario wherein many individuals appear to use their biometric screening as a proxy for a preventive visit, it is vital that results from individuals with suboptimally controlled chronic conditions are shared with their health care practitioners for modification to the treatment plan.

From a more pragmatic perspective, the question remains as to whether sufficient cost-effectiveness and value can be derived from population-level testing that targets sizeable subpopulations with chronic conditions. This point is certainly an arguable one. However, considering the potential benefit for chronic condition management as previously described—as well as identification of previously undiagnosed individuals—perhaps this approach has merit. Indeed, concerns remain regarding overuse of testing and the associated implications. Yet, this approach may generate net value for employers, given the evident challenges to effective chronic condition management at the present time. Employer incentives strategies may also warrant reevaluation in this setting. Furthermore, this approach may also create net value for health care delivery systems, particularly those moving toward population-level outcomes-based payment models. Irrespective of the approach, biometric and laboratory testing programs that fail to leverage the acquired data to build new and better interventions and hold accountable the health management programs are missing a substantial opportunity.


We appreciate that opportunities exist to improve the current process for both biometric screening and chronic condition monitoring. Directed use of primary care practitioners (PCPs), while certainly a sensible approach, has failed to achieve the desired level of testing compliance or outcomes. PCP access is an issue for many, for a multitude of reasons, including out-of-pocket cost, access and scheduling challenges, as well as other, nonhealth personal priorities. As a means to improve access to care, worksite clinics afford the opportunity for more targeted testing, either based on self-identified chronic conditions, or perhaps by using obesity as a leading indicator of risk for other comorbid conditions. Alternatively, if biometric testing can be performed in a way that protects individual privacy, perhaps a brief questionnaire can help to distinguish those who will most benefit from laboratory testing from those who are low risk and/or do not warrant testing based on USPSTF screening guidelines.


The current approach to biometric testing exceeds recommended screening frequency based on evidence-based guidelines, yet does help to identify individuals with increased health risks and previously unappreciated health conditions. Furthermore, evidence supporting the clinical impact of annual testing appears limited. However, for those with hypertension, hyperlipidemia, diabetes, and obesity, a thoughtful approach to annual testing can add value for employer-sponsored population health efforts, by providing an objective basis to inform employer benefits strategies, as well as increase the likelihood that individuals reach their identified treatment goals.


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