Financial Incentives and Diabetes Disease Control in Employees: A Retrospective Cohort Analysis
Financial Incentives and Diabetes Disease Control in Employees: A Retrospective Cohort Analysis
Anita D. Misra-Hebert 2
Bo Hu 1
Glen Taksler 2
Robert Zimmerman 0
Michael B. Rothberg 2
0 Diabetes Center, Endocrinology and Metabolism Institute, Cleveland Clinic , Cleveland, OH , USA
1 Department of Quantitative Health Sciences, Cleveland Clinic , Cleveland, OH , USA
2 Center for Value-Based Care Research, Medicine Institute, Cleveland Clinic , Cleveland, OH , USA
BACKGROUND: Many employers offer worksite wellness programs, including financial incentives to achieve goals. Evidence supporting such programs is sparse. OBJECTIVE: To assess whether diabetes and cardiovascular risk factor control in employees improved with financial incentives for participation in disease management and for attaining goals. DESIGN: Retrospective cohort study using insurance claims linked with electronic medical record data from January 2008-December 2012. PARTICIPANTS: Employee patients with diabetes covered by the organization's self-funded insurance and propensity-matched non-employee patient comparison group with diabetes and commercial insurance. INTERVENTION: Financial incentives for employersponsored disease management program participation and achieving goals. MAIN MEASURES: Change in glycosylated hemoglobin (HbA1c), low-density lipoprotein (LDL), systolic blood pressure (SBP), and weight. RESULTS: A total of 1092 employees with diabetes were matched to non-employee patients. With increasing incentives, employee program participation increased (7 % in 2009 to 50 % in 2012, p < 0.001). Longitudinal mixed modeling demonstrated improved diabetes and cardiovascular risk factor control in employees vs. non-employees [HbA1c yearly change −0.05 employees vs. 0.00 non-employees, difference in change (DIC) p <0.001]. In their first participation year, employees had larger declines in HbA1c and weight vs. non-employees (0.33 vs. 0.14, DIC p = 0.04) and (2.3 kg vs. 0.1 kg, DIC p < 0.001), respectively. Analysis of employee cohorts corresponding with incentive offerings showed that fixed incentives (years 1 and 2) or incentives tied to goals (years 3 and 4) were not significantly associated with HbA1c reductions compared to non-employees. For each employee cohort offered incentives, SBP and LDL also did not significantly differ in employees compared with non-employees (DIC p > 0.05). CONCLUSIONS: Financial incentives were associated with employee participation in disease management and improved cardiovascular risk factors over 5 years.
diabetes; chronic disease; disease management; health promotion; J Gen Intern Med 31(8); 871-7 DOI; 10; 1007/s11606-016-3686-2 © Society of General Internal Medicine 2016
The prevalence of diabetes in the US continues to rise as obesity
prevalence increases.1 While factors affecting optimal self-care
behaviors such as stable psychosocial resources2 or having health
insurance3 contribute to glycemic control, diabetes control is also
affected by lifestyle choices.4 Three-quarters of the
disabilityadjusted life years attributable to diabetes are related to
bodymass index (BMI),5 a modifiable lifestyle risk factor. Medical
expenses for persons with diabetes are estimated to be 2.5 times
higher than for those without diabetes,6 with an estimated cost of
245 billion dollars in 2012 including direct medical costs and
Worksite wellness programs may improve diabetes control
through encouraging lifestyle changes and disease management.
Healthy changes in the work environment may impact
employees, whether or not they participate in disease management
programs.8 Financial incentives may promote health behavior
change.9 Incentives tied to wellness program participation have
been shown to affect health behaviors such as smoking10–12 and
reduce downstream health care costs.13 Incentives for achieving
specific health goals, such as a target glycosylated hemoglobin
(HbA1c) or blood pressure, remain uncommon14 and have not
been well studied.
One obstacle to understanding the effectiveness of financial
incentives in chronic disease management is the lack of
randomized trials. Observational studies comparing voluntary
participants in workplace wellness programs to non-participants are
subject to selection bias because highly motivated employees
may be more likely to participate and thus may differ from
non-participants. In contrast, a research design that considers
disease control among all employees exposed to incentives (not
just those who accept) compared with disease control among
similar non-employees obtaining regular care can control for this
type of bias.
The purpose of this study was to assess the impact of
financial incentives on control of diabetes and other
cardiovascular risk factors in employees. We hypothesized that
compared with non-employees obtaining regular care at the
same primary care practices, employees offered financial
incentives would show greater improvements in diabetes and
cardiovascular risk factor control. We also hypothesized that
employees who participated in disease management programs
would have greater improvements than those who did not.
The Cleveland Clinic employee health program (EHP) is a
selffunded insurance plan covering >38,000 employees. We
conducted a retrospective cohort study using EHP claims data linked
with electronic medical record (EMR) data from January 2008–
December 2012. The study was approved by the Institutional
Review Board at Cleveland Clinic. Participants included EHP
members with diabetes. The comparison group included patients
with diabetes with commercial health insurance cared for by the
same group of primary care physicians during the study period.
Our employee study cohort was created as outlined in Figure 1.
Applying the standard Healthcare Effectiveness Data and
Information Set (HEDIS) definition, we used claims data to identify
employees with diabetes. Employee claims were then linked to
the EMR. To confirm a diabetes diagnosis, we excluded any
employee without either (
) an HbA1c >6.5 % on the first value
in the dataset or (
) two International Classification of Diseases,
Ninth Revision (ICD 9) codes for diabetes and a diabetes
medication prescribed. To analyze the impact of the overall incentive
program, we performed a longitudinal analysis including all
employees who had HbA1C measures in at least 2, not
necessarily consecutive, years during the study period. To analyze the
effect of specific incentives, we created 2-year cohorts (2008–09,
2009–10, 2010–11, 2011–12). For each cohort, the first year
represented the baseline and the second year corresponded with
the introduction of a financial incentive; any employee who did
not have at least one HbA1c measurement in each of the 2 study
years was excluded from that cohort. The average HbA1c for
employees excluded at this step was 7.03 [standard deviation
(SD) 1.81] vs. 7.43 (SD 1.75) for included employees. We then
excluded employees who did not have a primary care physician
(PCP) in the EMR—indicating they did not obtain their routine
care in our health system. Based upon the PCP, a primary practice
site was assigned. Using EHP records, we designated each
employee as participating or not participating in disease
management programs in each year. For employee participants in disease
management, we created a pooled cohort from all four 2-year
cohorts to allow analysis of outcomes of employees in their first
year of program participation.
Exposures include the programs offered to all employees.
Beginning in July 2005, the Cleveland Clinic implemented a
series of wellness initiatives, initially focused on changing the
work environment to promote healthier lifestyles. Starting in
2008, the EHP offered free smoking cessation, weight
management, and fitness programs.
The EHP also administers disease management programs for
diabetes and other cardiovascular risk factors including obesity,
hypertension, and hyperlipidemia. In 2009, a fixed $100 financial
incentive was offered for participation in an employer-sponsored
disease management program; the incentive increased to $300 in
2010. In 2011, the incentive changed to a 30 % health insurance
premium discount ($600-$1200 depending on type of plan) tied
to both participation (15 % discount) and achievement of clinical
goals (additional 15 % discount). The same incentive continued
in 2012. Clinical goals included achievement of set HbA1c,
lowdensity lipoprotein (LDL) cholesterol, and blood pressure targets.
If requested, the HbA1c target could be individualized, but >90 %
of employees had a standardized goal of <7 %. Target for LDL
was <100 mg/dl and for systolic blood pressure (SBP) <130. The
weight target was individualized. Premium discounts were
applied in the year following participation or achievement of goals.
Our primary outcome measure was absolute change in
HbA1c. Secondary outcomes included change in LDL, SBP,
Each employee was matched to a non-employee in a 1-to-1
ratio based on propensity scores. The logistic models for
calculating propensity scores included HbA1c, age, gender,
race, BMI, insulin use and practice site at the matching
(baseline) year as covariates. Matching variables were chosen
based upon (
) diabetes control and disease burden (HbA1c,
insulin use), (
) demographic and clinical factors that may
affect diabetes control or prescribed targets (age,15,16 gender,17
race,18 BMI), and (
) care delivered by the same group of
Our data were analyzed in three ways: (
mixed modeling of outcomes for the 5 year cohort (2008–
12) of employees and matched non-employees, (
) analysis of
matched 2-year cohorts of employees (2008–09, 2009–10,
2010–11, 2011–12) and non-employees to assess the impact
of individual incentives, and (
) pooled analyses of outcomes
of all employee disease management program participants in
their first year of program participation compared to matched
First, to assess 5-year outcomes of employees compared to
non-employees, a longitudinal linear mixed model was created
using the data for all employees and non-employees in the
dataset. Second, to assess the impact of each separate incentive
offering, we analyzed the data in 2-year cohorts to correspond
with timing of incentives. Employees were divided into four
cohorts according to the years of their first HbA1c
measurement (i.e., 2008, 2009, 2010, and 2011). Within each cohort,
all employees who had a propensity score (no missing baseline
BMI) were matched. While an employee could be included in
more than one cohort, the employee was matched to a different
non-employee in each cohort. Propensity score
subclassifications and outcomes of matched employees and non-employee
comparison group by quartiles are shown in Appendix
Figs. S1–S4 and Tables S1–S4, respectively. We used the
Rpackage (Matching) to perform the propensity matching.19
Baseline characteristics of the matched employees and
comparison group were compared using the t-test and chi-squared
test for continuous and categorical characteristics,
respectively. For each cohort, we compared the outcome in the matching
year and the year after using the paired t-test for matched
employees and comparison group, respectively, and compared
the 1-year changes between the employees and comparison
group using the t-test.
Third, to analyze the effect of disease management program
participation, for employees who participated in diabetes and
weight management programs at any time between 2008–
2012 (in any of the cohorts), we used a pooled analysis to
compare the baseline(year prior to program participation)
HbA1c and weight for an employee to the outcomes for the
same group of employees in the first year of program
participation; we then assessed the outcome changes in the same
time period for the matched comparison group.
Statistical significance was considered at p-values less than
0.05. Results were not adjusted for multiple comparisons. All
analyses were conducted using SAS 9.3 (Cary, NC) and
Rstudio (Boston, MA).
There were 1092 employees matched to non-employees.
Characteristics of the study population appear in Table 1.
Comparison of matched vs. unmatched employees appears
in Appendix Table S5.
The proportion of all eligible employees enrolled in the
programs increased from 7 % (n = 52/793) in 2009 to 50 %
(n = 498/1004) in 2012 (p < 0.001) with employees entering
and leaving the program during this time (Appendix Fig. S5).
However, for employees with poorly controlled diabetes
(baseline HbA1c > 9), 9.8 % (n = 8/82) enrolled in 2009 and
increased to only 39.3 % (n = 48/122) in 2012. Thus, the
baseline mean HbA1c of participants joining the program fell
from 7.52 in 2009 to 7.35 in 2012.
Over 5 years, at the population level, employees had greater
reductions in HbA1c, SBP, LDL, and weight than did the
nonemployee comparison group (Table 2). Additional sensitivity
analyses modeling the longitudinal changes in outcomes based
upon when employees entered the cohorts appear in Appendix
Table S6. Employees had greater weight loss than the
comparison group whenever they entered but more significant
lowering of HbA1c than the comparison group only when
entering in 2008 and 2010.
At the population level, fixed, small financial incentives
(2008–09 and 2009–10 cohorts) and the first year in which
incentives were tied to treatment targets (2010–11 cohort)
were not associated with a significant decreases of HbA1c
among employees (Table 3). In the second year that incentives
were tied to treatment targets (2011–12 cohort), HbA1c
declined significantly among employees and the comparison
group, with no significant difference between the two groups.
Weight decreased in employees throughout the study period,
with significant changes compared to the non-employees only
in the initial cohort. Changes in mean LDL and SBP
throughout the study period were similar for the employees and
comparison group (difference in change p > 0.05 for all
cohorts). Sensitivity analyses applying linear mixed models
to the 2-year cohorts revealed similar results (Appendix
Subgroup analyses for patients with HbA1c >9 or BMI >27
(Appendix Table S8) showed a significant and similar
decreases in HbA1c in employees and the non-employee
comparison group. Weight also decreased similarly for both
groups except in the last cohort—the second year in which
incentives were tied to treatment targets—when employees’
weight decreased significantly more.
For employees participating in disease management
programs, a pooled analysis demonstrated that in their first year in
the program, their HbA1c declined by an average of 0.33
points (p < 0.001) and weight by 2.3 kg (p < 0.001) (Table 4),
greater than noted in the non-employee comparison group.
To further assess outcomes of program participants vs.
nonparticipants, we analyzed changes in HbA1c and weight for
Bever-participants^ in 2008–12 as compared to Balways
nonparticipants.^ Weight decreased significantly more in
employees who participated in disease management at any time
compared to non-participants (yearly change –1.07 kg vs. –
0.39 kg, p <0.001) but HbA1c did not (−0.06 % vs. −0.04 %, p
0.39, Appendix Table S9).
In this retrospective study of employees with diabetes in a
single institution, the implementation of financial incentives to
join disease management programs was associated with an
increase in program participation. As the initial goal of the
financial incentives was to encourage employees with diabetes
to join disease management, this program succeeded. Our
longitudinal modeling suggests that on a population level the
offering of incentives coupled with disease management
improved diabetes and cardiovascular risk factor control in
employees compared to matched non-employees. However,
our analysis of 2-year cohorts corresponding to the timing of
increasing incentives and incentives for attaining treatment
goals did not demonstrate a temporal association between
individual incentives and improvements in any study
outcomes for employees versus the comparison group. Even
employees with an HbA1c >9, who showed substantial
improvement in HbA1c in all cohorts, had changes similar to
those seen in non-employees (Appendix Table S8).
Our ability to demonstrate population benefits over the full
5 years, but inability to attribute those benefits to the
implementation of particular incentives, may be an artifact of the
study design. We found that among employees already in care,
i.e., those who had an HbA1c measure in consecutive years,
and included in the 2-year cohorts, the incentives did not
appear to have any impact when compared to
nonemployees also obtaining regular care. For those who may
have sought care and improved their measures within the same
year, their improvements would have been missed by the
cohort analysis, but measured in the longitudinal analysis.
The fact that employees participating in disease management
programs had improved HbA1C and weight compared to
nonemployees in the first year of joining supports this
Our observation that increasing incentives may have
resulted in more patients with better diabetic control joining
disease management programs, as evidenced by the lower
mean HbA1c in 2012 compared to 2009, and the finding that
disease management program participants had more weight
loss than non- participants (Table 4 and Table S9) highlight the
difficulty of conducting observational studies of incentives.
Without a comparison group, our findings could have been
misleading because of selection bias. On a population level,
substantial clinical improvements were noted in employees
corresponding with the introduction of financial incentives,
but almost identical changes were noted in the comparison
population. These improvements may be more related to being
in care than to incentives tied to specific outcomes once
patients are in care.
Employer-sponsored disease management programs are
common,14 have potential to improve diabetes control20 and
even prevent diabetes.21,22 A successfully designed worksite
health promotion model may offer a framework to be utilized
in other patient or community populations. Studies of financial
incentives have produced mixed results, particularly when
incentives target health behaviors.11Randomized trials suggest
that financial incentives are effective for improving tobacco
cessation rates,10,12 compliance with home monitoring for
diabetes,23 and reducing LDL.24 In contrast, incentives were
not effective in promoting health behaviors such as walking25
or weight loss.26 Our study adds to this body of knowledge by
reporting the impact of financial incentives tied to treatment
targets on measures of disease control.
One goal of financial incentives is to engage patients who
otherwise would not have sought care, and this may be the
most important effect of offering the incentives. Our
longitudinal model suggests an overall benefit of disease
management programs, and our pooled analysis of program
participants suggest benefit in the first year of joining. However,
even with potential rewards of >$1000 annually, no more than
50 % of patients agreed to participate. There is scant literature
on why patients decline disease management despite
incentives. One potential explanation for the lack of association we
observed between financial incentives and short-term diabetes
outcomes among patients already seeking care is that the
incentives were not optimally structured to motivate behavior
change.27 For example, the timing of the incentives— an
insurance premium discount applied in the year after achieving
treatment targets—may not be as effective as smaller, more
frequent payments closer to when goals are achieved.28
Covering copayment costs for medications7,29,30 for program
participation and not tied to reaching set treatment targets may
also be considered as an alternative to a premium discount.
However, even these types of incentives may yield only
modest improvements in medication adherence31 and presumably
smaller improvements in clinical outcomes. The use of
standardized treatment goals may also have discouraged
participation by those far from the goals. Recent recommendations
for diabetes care to be patient-centered,15 and evidence that
tailored behavioral interventions are effective for improving
control of diabetes and32 hypertension33 and for increasing
physical activity, support individualized treatment goals34
such as a mutually agreed upon HbA1c. In the EHP, weight
targets were individualized, which may have facilitated the
significant weight reduction we observed among employees
with a BMI >27 and contributed to the greater weight
reductions among employees over 5 years.
Creative incentive design could increase participation and
population level benefits. Redesign should include employees
with chronic disease as stakeholders to explore barriers to
program participation,35–37and to ensure the program and
incentive designs are both equitable38 and desirable. Shared
incentives for patients and physicians may also guide future
This is a single institution study; thus, our observed outcomes
may not be generalizable to other workplaces. Organizational
factors may have contributed to improved outcomes in
patients with diabetes.40 Providers—employees of the same
health system— may have been prompted to provide similar
care to their employee and non-employee patients as a result of
awareness of optimal disease management from the incentive
program. During this time period physicians also had ample
reminders of the importance of diabetes control, a publicly
reported quality measure.
We did not measure employee motivation to receive care for
diabetes before and after initiation of financial incentives. If
the incentive program increased motivation to improve health
during our study period, prompted by an invitation to an
employee to join disease management (whether or not they
joined), the long-term population health benefit may not have
been captured by our analysis of changes in 2-year cohorts and
may explain the results of our longitudinal modeling analyses.
In addition, the baseline diabetes control was good; thus,
introduction of financial incentives had little opportunity to
improve HbA1c. We also could not determine whether
patients in our comparison group participated in disease
management sponsored by their employer or insurer.
In this study, financial incentives offered to employees with
diabetes encouraged employees to enter disease management,
and program participation led to initial improvements in
diabetes control and weight. Over 5 years, the program appeared
to improve disease control. However improvements in
diabetic control, weight, LDL cholesterol, and systolic blood
pressure temporally related to individual incentive offerings were
similar to non-employees obtaining regular care in the same
primary care practices. Studies to identify successful elements
and a timeline to expected benefits of workplace financial
incentive programs are warranted.
Dr. Glen Taksler was funded by the Clinical and Translational Science
Collaborative of Cleveland (grant KL2TR000440) and the National
Center for Advancing Translational Sciences.
Author Contributions: Drs. Anita D. Misra-Hebert, Bo Hu, Glen
Taksler, and Michael B. Rothberg had access to all the data in the study and
take responsibility for the integrity of the data and the accuracy of the
Dr. Bo Hu, Department of Quantitative Health Sciences, Cleveland
Clinic, conducted and is responsible for the data analysis.
Drs. Anita D. Misra-Hebert, Bo Hu, Glen Taksler, and Michael B.
Rothberg made substantial contributions to the conception and design of the
project, interpretation of data for the work,and drafting and critically
revising the work for intellectual content, have approved the final
version, and agree to be accountable for all aspects of the work.
Dr. Robert Zimmerman made substantial contributions to the
interpretation of data for the work, drafting and critically revising the work for
intellectual content, has approved the final version, and agrees to be
accountable for all aspects of the work.
Compliance with Ethical Standards:
The authors report no financial disclosures.
These data were presented as an oral presentation at the Society of
General Internal Medicine national meeting in Toronto, Canada, on
April 24, 2015.
This publication was made possible in part by the Cleveland Clinic
Research Program Committee pilot funding grant program,
Conflict of Interest: The authors declare that they do not have a
conflict of interest.
1. Overweight and Obesity. http://www.cdc.gov/obesity/adult/index.html. Accessed January 26 , 2016 .
2. Peyrot M , McMurry JF , Kruger DF . A biopsychosocial model of glycemic control in diabetes: stress, coping and regimen adherence . J Health Soc Behav . 1999 ; 40 ( 2 ): 141 . doi: 10 .2307/2676370.
3. Benoit SR , Fleming R , Philis-Tsimikas A , Ji M. Predictors of glycemic control among patients with type 2 diabetes: a longitudinal study . BMC Public Health . 2005 ; 5 ( 1 ): 36 . doi: 10 .1186/ 1471 -2458-5-36.
4. Reduction in the Incidence of Type 2 Diabetes with Lifestyle Intervention or Metformin . N Engl J Med . 2002 ; 346 ( 6 ): 393 - 403 . doi: 10 .1056/ NEJMoa012512.
5. JAMA Network | JAMA | The State of US Health, 1990 - 2010 : Burden of Diseases, Injuries, and Risk Factors . http://jama.jamanetwork.com/article.aspx?articleID=1710486& utm_source=Silverchair%20Information%20Systems&utm_medium=email&utm_campaign= JAMA%3AOnlineFirst07%2F10%2F2013. Accessed January 26 , 2016
6. Zhuo X , Zhang P , Kahn HS , Bardenheier BH , Li R , Gregg EW . Change in Medical Spending Attributable to Diabetes: National Data From 1987 to 2011 . Diabetes Care. 2015 ;dc141687. doi: 10 .2337/dc14- 1687 .
7. American Diabetes Association. Economic costs of diabetes in the US in 2012 . Diabetes Care . 2013 ; 36 ( 4 ): 1033 - 1046 . doi: 10 .2337/dc12- 2625 .
8. Racette SB , Deusinger SS , Inman CL , et al. Worksite opportunities for wellness (WOW): effects on cardiovascular disease risk factors after 1 year . Prev Med . 2009 ; 49 ( 2-3 ): 108 - 114 . doi: 10 .1016/j.ypmed. 2009 . 06 .022.
9. Giles EL , Robalino S , McColl E , Sniehotta FF , Adams J. The effectiveness of financial incentives for health behaviour change: systematic review and meta-analysis . PLoS One . 2014 ; 9 ( 3 ), e90347 . doi: 10 .1371/journal. pone. 0090347 .
10. Volpp KG , Troxel AB , Pauly MV , et al. A randomized, controlled trial of financial incentives for smoking cessation . N Engl J Med . 2009 ; 360 ( 7 ): 699 - 709 . doi: 10 .1056/NEJMsa0806819.
11. Sutherland K , Christianson JB , Leatherman S. Impact of targeted financial incentives on personal health behavior a review of the literature . Med Care Res Rev . 2008 ; 65 ( 6 suppl) : 36S - 78S . doi: 10 .1177/ 1077558708324235.
12. Halpern SD , French B , Small DS , et al. Randomized trial of four financialincentive programs for smoking cessation . N Engl J Med . 2015 . doi: 10 . 1056/NEJMoa1414293.
13. Merrill RM , Hyatt B , Aldana SG , Kinnersley D. Lowering employee health care costs through the healthy lifestyle incentive program . J Public Health Manag Pract . 2011 ; 17 ( 3 ): 225 - 232 . doi: 10 .1097/PHH.0b013e3181f54128.
14. Mattke S , Liu H , Caloyeras JP , et al. Workplace Wellness Programs Study Final Report . 2013 . http://www.rand.org/pubs/research_reports/RR254. html. Accessed February 14 , 2015 .
15. American Diabetes Association. 1. Strategies for improving care . Diabetes Care . 2015 ; 38 ( Supplement 1 ): S5 - S7 . doi: 10 .2337/dc15- S004 .
16. McLaren LA , Quinn TJ , McKay GA . Diabetes control in older people . BMJ . 2013 ; 346 :f2625. doi: 10 .1136/bmj.f2625.
17. Siddiqui MA , Khan MF , Carline TE . Gender differences in living with diabetes mellitus . Mater Socio-Medica . 2013 ; 25 ( 2 ): 140 - 142 . doi: 10 .5455/ msm. 2013 . 25 . 140 - 142 .
18. Saydah S , Cowie C , Eberhardt MS , De Rekeneire N , Narayan KMV . Race and ethnic differences in glycemic control among adults with diagnosed diabetes in the United States . Ethn Dis . 2007 ; 17 ( 3 ): 529 - 535 .
19. Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching package for R | Sekhon | Journal of Statistical Software . http://www.jstatsoft.org/article/view/v042i07. Accessed November 15, 2015 .
20. Yoder VG , Dixon DL , Barnette DJ , Beardsley JR . Short-term outcomes of an employer-sponsored diabetes management program at an ambulatory care pharmacy clinic . Am J Health Syst Pharm . 2012 ; 69 ( 1 ): 69 - 73 . doi: 10 . 2146/ajhp110041.
21. Rolando L , Byrne DW , McGown PW , Goetzel RZ , Elasy TA , Yarbrough MI . Health risk factor modification predicts incidence of diabetes in an employee population: results of an 8-year longitudinal cohort study . J Occup Environ Med Am Coll Occup Environ Med . 2013 ; 55 ( 4 ): 410 - 415 . doi: 10 .1097/JOM.0b013e31827cbaec.
22. Aldana SG , Barlow M , Smith R , et al. The diabetes prevention program: a worksite experience . AAOHN J . 2005 ; 53 ( 11 ): 499 - 505 . quiz 506- 507 .
23. Sen AP , Sewell TB , Riley EB , et al. Financial incentives for home-based health monitoring: a randomized controlled trial . J Gen Intern Med . 2014 ; 29 ( 5 ): 770 - 777 . doi: 10 .1007/s11606-014-2778-0.
24. Bloch MJ , Armstrong DS , Dettling L , Hardy A , Caterino K , Barrie S. Partners in lowering cholesterol: comparison of a multidisciplinary educational program, monetary incentives, or usual care in the treatment of dyslipidemia identified among employees . J Occup Environ Med Am Coll Occup Environ Med . 2006 ; 48 ( 7 ): 675 - 681 . doi: 10 .1097/01.jom. 0000205997 .18143. 6c .
25. Kullgren JT , Harkins KA , Bellamy SL , et al. A mixed-methods randomized controlled trial of financial incentives and peer networks to promote walking among older adults . Health Educ Behav . 2014 ; 41 ( 1 Suppl) : 43S50S . doi: 10 .1177/1090198114540464.
26. Patel MS , Asch DA , Troxel AB , et al. Workplace wellness incentives for weight loss-A randomized, controlled trial . J Gen Intern Med . 2015 ; 30 ( 2 ): 45 - 551 . doi: 10 .1007/s11606-015-3271- 0 . Toronto, CANADA.
27. Loewenstein G , Asch DA , Volpp KG . Behavioral economics holds potential to deliver better results for patients, insurers, and employers . Health Aff . 2013 ; 32 ( 7 ): 1244 - 1250 . doi: 10 .1377/hlthaff. 2012 . 1163 .
28. Volpp KG , Asch DA , Galvin R , Loewenstein G. Redesigning employee health incentives-lessons from behavioral economics . N Engl J Med . 2011 ; 365 ( 5 ): 388 - 390 . doi: 10 .1056/NEJMp1105966.
29. Gibson TB , Wang S , Kelly E , et al. A value-based insurance design program at a large company boosted medication adherence for employees with chronic illnesses . Health Aff Proj Hope . 2011 ; 30 ( 1 ): 109 - 117 . doi: 10 . 1377/hlthaff. 2010 . 0510 .
30. Choudhry NK , Avorn J , Glynn RJ , et al. Full coverage for preventive medications after myocardial infarction . N Engl J Med . 2011 ; 365 ( 22 ): 2088 - 2097 . doi: 10 .1056/NEJMsa1107913.
31. Duru OK , Turk N , Ettner SL , et al. Adherence to metformin, statins, and ACE/ARBs within the diabetes health plan (DHP) . J Gen Intern Med . 2015 . doi: 10 .1007/s11606-015-3284-8.
32. Wolever RQ , Dreusicke M , Fikkan J , et al. Integrative health coaching for patients with type 2 diabetes a randomized clinical trial . Diabetes Educ . 2010 ; 36 ( 4 ): 629 - 639 . doi: 10 .1177/0145721710371523.
33. Friedberg JP , Rodriguez MA , Watsula ME , et al. Effectiveness of a tailored behavioral intervention to improve hypertension control primary outcomes of a randomized controlled trial . Hypertension . 2015 ; 65 ( 2 ): 440 - 446 . doi: 10 .1161/HYPERTENSIONAHA.114.03483.
34. Bock BC , Marcus BH , Pinto BM , Forsyth LH . Maintenance of physical activity following an individualized motivationally tailored intervention . Ann Behav Med Publ Soc Behav Med . 2001 ; 23 ( 2 ): 79 - 87 .
35. Kim AE , Towers A , Renaud J , et al. Application of the RE-AIM framework to evaluate the impact of a worksite-based financial incentive intervention for smoking cessation . J Occup Environ Med . 2012 ; 54 ( 5 ): 610 - 614 . doi: 10 . 1097/JOM.0b013e31824b2171.
36. Person AL , Colby SE , Bulova JA , Eubanks JW . Barriers to participation in a worksite wellness program . Nutr Res Pract . 2010 ; 4 ( 2 ): 149 - 154 . doi: 10 . 4162/nrp. 2010 . 4 .2.149.
37. Brna SA , Ruisinger JF , Howard PA , Barnes BJ , Hare SE . Study of nonparticipation in an employee diabetes program . J Am Pharm Assoc . 2012 ; 52 ( 5 ): e105 - e108 . doi: 10 .1331/JAPhA. 2012 . 10089 .
38. Horwitz JR , Kelly BD , DiNardo JE . Wellness incentives in the workplace: cost savings through cost shifting to unhealthy workers . Health Aff . 2013 ; 32 ( 3 ): 468 - 476 . doi: 10 .1377/hlthaff. 2012 . 0683 .
39. Asch DA , Troxel AB , Stewart WF , et al. Effect of financial incentives to physicians, patients, or both on lipid levels: a randomized clinical trial . JAMA . 2015 ; 314 ( 18 ): 1926 - 1935 . doi: 10 .1001/jama. 2015 . 14850 .
40. van Doorn- Klomberg AL , Braspenning JCC , Wolters RJ , Bouma M , de Grauw WJC , Wensing M. Organizational determinants of high-quality routine diabetes care . Scand J Prim Health Care . 2014 ; 32 ( 3 ): 124 - 131 . doi: 10 .3109/02813432. 2014 . 960252 .