Discussion
Our analysis showed the risk of progression from pre-diabetes to diabetes was significantly lower for persons with pre-diabetes in employer groups offering the DHP. Employees and covered dependents from DHP employer groups had an 8% lower absolute predicted probability of incident diabetes over 3 years of follow-up after baseline compared with those from employer groups offering standard benefit plans. Our finding of an 8% absolute reduction, translating into a 21% relative reduction compared with the 37% incidence rate among the comparison group, can be measured against the effect size observed in the intensive lifestyle arms and metformin arms of the DPP study. In 2002, this randomized controlled study demonstrated that intensive lifestyle intervention reduced incidence of diabetes by 58% and metformin reduced the incidence by 31%, as compared with placebo over 2.8 years.4 In contrast, the DHP is a relatively light touch approach that still manages to have a meaningful effect size. More importantly, DHP-like insurance benefit designs are implementable on a national scale since 60% of US adults are currently insured through employer-sponsored insurance programs.21
The mechanism by which a disease-specific health insurance benefit design, such as the DHP, may help prevent or delay development of diabetes is likely twofold. First, since pre-diabetes is an explicit DHP eligibility criterion, our findings may result in part from the increased awareness of a pre-diabetes diagnosis afforded by the DHP. Patients who otherwise might not be aware of their diagnosis know they are being offered the DHP based on their pre-diabetes diagnosis and studies have shown that pre-diabetes awareness can activate patients to engage in health promotion activities.5 8 The DHP also incorporates features to increase compliance with recommended preventive care, such as quarterly scorecards that are mailed to patients reminding them of recommended care (eg, annual visit with their primary care provider). Since education alone may not be enough to lead to behavior change, the DHP also enhances access to evidence-based pre-diabetes care, possibly making it easier for patients to engage in the recommended care. This includes free or reduced cost sharing for follow-up HbA1c testing, as well as access to in-person or online lifestyle intervention programs and/or metformin, which are the mainstay of pre-diabetes treatment and diabetes risk reduction.9
The proposed patient activation by the DHP is nicely demonstrated by the differential rates of follow-up glucose lab testing between DHP and control employers. We identified at least one A1c/FPG/OGTT follow-up test for 89% of individuals from DHP groups compared with only 66% from standard benefits/controls in any of the three postbaseline years (p<0.001). Thus, our data show that participants from DHP groups were much more likely to have recommended follow-up glucose testing in accordance with most national care recommendations for repeat annual diabetes screening for those with pre-diabetes.9 Although this increased testing creates a potential detection bias towards ‘higher’ rates of progression (ie, increased rates of testing may increase the chance of diagnosing incident diabetes), our unadjusted results showed lower rates of incident diabetes among employees and dependents covered by the DHP. It is likely that rates of incident diabetes among the control population were even higher than reported but went undiagnosed as these patients were never tested during the follow-up period. We used multiple imputation to address this differential in the availability of the primary outcome, and our results lean towards more conservative estimates of the difference between the two comparison groups. Our intent-to-treat design, which included all DHP employees and dependents with pre-diabetes whether or not they enrolled in the DHP, also leans towards more conservative estimates.
Overall, our findings should be of broad interest since 37% of US adults are currently estimated to have pre-diabetes.1 To our knowledge, this is also one of the first studies to examine the impact of a disease-specific health insurance benefit design on outcomes for patients with pre-diabetes. Our findings indicate that health insurance benefit designs that help increase pre-diabetes awareness by devoting resources to identify and inform patients of their pre-diabetes diagnosis, incorporating features to increase adherence with recommended care, and providing incentives and/or reduce barriers to recommended care may be a viable means of preventing or delaying incident diabetes for working-age adults with pre-diabetes. The DHP places strong emphasis on the importance of prevention and regular use of primary care services, highlighting the importance of aligning incentives and payment structures for effective delivery of preventive care services for persons with pre-diabetes. Our findings may help inform future benefit design and/or national policies surrounding pre-diabetes care. In many ways, the DHP is a test case of a concept of disease-specific benefit design that deserves further study. This concept is akin to personalized medicine at the benefit level and can also be tested in other costly chronic conditions where there are well-established ambulatory treatment guidelines.
There are also several limitations to consider. First, because this was a claims-based analysis, possible misclassification of pre-diabetes and diabetes may have occurred. However, we conducted a sensitivity analysis that used a stricter definition of ≥2 ICD codes for our primary outcome of diabetes which did not impact our results. Second, some employer groups may have implemented complementary wellness initiatives which our claims-based analysis would not capture. However, we used propensity score matching at the employer level to find comparable control employer groups offering standard plans. Third, our analysis focused on commercially insured adults and may not be generalizable to uninsured or older patients. However, our focus on working-age adults is important because pre-diabetes affects more than one in three adults older than 20 years and the lifetime risk of incident diabetes is highest for younger individuals with pre-diabetes. Finally, our data were limited to 3 years of follow-up. However, our effect size of 8% absolute risk reduction over just 3 years seems clinically meaningful, particularly when considered across a population level.
In summary, the health and well-being of large segments of the US population and their associated healthcare costs are at stake if diabetes prevention is not prioritized. The sheer number of individuals affected with pre-diabetes necessitates the use of multifaceted approaches to curb this epidemic. Health insurance benefit designs that increase pre-diabetes awareness and enhance access to evidence-based care are associated with lower rates of incident diabetes and represent an important area of future study.