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Objective: To measure the effectiveness of a
wellness program in a small company using four well-being indicators
designed to measure dimensions of physical health, emotional health,
healthy behavior, and basic access to health-related conditions and
services.
Methods: Indicator scores were obtained and compared between Lincoln
Industries employees and workers in the neighboring Lincoln/Omaha
community during 2009.
Results: Nearly all Lincoln Industries employees participated in the
wellness program. Physical health, mental health, and healthy behavior
were significantly greater for Lincoln Industries employees.
Self-perceived access to basic needs was not significantly greater among
Lincoln Industries employees.
Conclusion: Well-being index scores provide evidence for the
effectiveness of the wellness program in this small company setting with
respect to better dimensions of physical health, emotional health, and
healthy behavior than geographically similar work
This research project is complete,
peer-reviewed and published in the April, 2011 issue of the JOURNAL of
OCCUPATIONAL and ENVIRONMENTAL MEDICINE,
volume 53 issue 4
(Merrill, Ray M. PhD, MPH; Aldana, Steven G. PhD; Pope, James E. MD;
Anderson, David R. PhD, LP; Coberley, Carter R. PhD; Vyhlidal, Tonya P.
MEd; Howe, Greg MS; Whitmer, R. William MBA)
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Objective: This study evaluates the level of
participation and effectiveness of a worksite wellness program in a
small business setting.
Methods: Three years of wellness participation and risk data from
Lincoln Industries was analyzed.
Results: All Lincoln Industry employees participated in at least some
level of wellness programming. Significant improvements in body fat,
blood pressure, and flexibility were observed across time. The largest
improvements in risk were seen among older employees and those with the
highest baseline values.
Conclusions: This small business was able to improve the health of
the entire workforce population by integrating wellness deeply into
their culture and operations. Replication of this program in other small
business settings could have a large impact on public health since 60
million adults in the United States work in small business.
This research project is complete,
peer-reviewed and published in the Feb, 2011 issue of the JOURNAL of
OCCUPATIONAL and ENVIRONMENTAL MEDICINE, volume 53, Issue 2 (Ray, M.
Merrill PhD, MPH; Steven, G. Aldana PhD; Tonya, P. Vyhlidal MEd; Howe,
Greg MS; David, R. Anderson PhD, LP; R., William Whitmer MBA)
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A PROSPECTIVE AND RANDOMIZED RESEARCH PROEJCT TO COMPARE THE EFFECTIVENESS OF
THE ORNISH PROGRAM WITH TRADITIONAL CARDIAC REHABILITATION IN REDUCING CAROTID
ARTERY MEDIA AND INTIMA THICKNESS AND A VARIETY OF THE OTHER HEALTH PARAMETERS.
A prospective, controlled and randomized evaluation of heart disease patients
who agree to be randomized into either the Ornish or traditional cardiac
rehabilitation programs. In addition to all the outcomes evaluated in the above
research project, these study subjects also have carotid artery
ultrafast-sonography to determine media and intima thickness (a direct measure
of vascular disease.) This test will provide hard copy pictures of
atherosclerotic (plaque) build up in the carotid artery. There is good evidence
that the amount of plaque in the carotid artery corresponds to the plaque in
coronary (heart) arteries. In addition, there will be blood analysis for
homosystene (HCY), C-reactive protein, ferritin, and fibrinogen. The hypothesis
states that those who are randomized and remain in the Ornish program will have
less thickening or actual reduction in carotid artery thickness (reversal of
cardiovascular disease) over time compared to the traditional rehabilitation
group.
This study was funded by the Midwest Center for
Health and Healing, in Rockford IL. (Aldana, S, Whitmer, R., Greenlaw, R., et al).
BEHAVIOR MODIFICATION. Vol. 30, No 4, July 2006; 506-525)
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Cardiovascular Risk Reductions
Associated With Aggressive
Lifestyle Modification and Cardiac Rehabilitation
Patients who have been
treated for coronary heart disease can enroll in traditional cardiac
rehabilitation, the Ornish program, or no rehabilitation. No study has compared
the impact of each on cardiovascular disease (CVD) risk factors.
This study compares CVD risk changes in post coronary bypass graft or
percutaneous coronary intervention procedure patients who participated in the
Ornish Heart Disease Reversing Program, a traditional cardiac rehabilitation
program, and a control group that received no formal cardiac risk-reduction
program. This was a longitudinal, observational study of 84 patients receiving
CVD standard of care who elected to participate in one of the three study
groups. Assessments of CVD risk factors and anginal severity were obtained at
baseline, 3 months and 6 months.
Those patients participating in the Ornish program had significantly greater
reductions in original frequency, body weight, body mass index, systolic blood
pressure, total cholesterol, low-density lipoprotein cholesterol, glucose,
dietary fat and increases in complex carbohydrates than were experienced in the
traditional or control groups.
(Aldana S., Whitmer R., Greenlaw R., et.al) Heart & Lung (32) (6),
Nov/Dec 2003; 374-381.)
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In 2003, the cost per employee, for family health care coverage, when
averaged across all plan designs was $9,068. Of this amount, the employer paid
$6,656. If increases average a conservative 10% per year over the next several
years, then in 2008, the cost per employee will be $14,601, with the employer
paying $10,659 per employee. This assumes the current percent contribution
between employer and employee remains constant. For most employers, this is a
crisis situation, with little relief in site.
This invited editorial provides a detailed over-view of employer reactions to
routine double digit annual increases in health care costs based on numerous
published employer surveys. Commentary explores why there is little hope for
moderation in health care costs: the baby boomers, the graying of America,
escalating hospital charges and the obesity epidemic. The editorial documents
that 50% - 70% of all diseases and medical problems are caused by life style
choice: smoking, obesity, excess stress, lack of fitness, poor nutrition, lack
of compliance in managing diabetes, hypertension, etc. The dichotomy of the
health care cost crisis is that of the $1.8 trillion annual budget, less than 6%
is devoted to prevention of all kinds, including attempts to influence lifestyle
choices.
The editorial concludes, “A Wake-Up Call for Corporate America is that an
employee health care cost crisis is here. If the employer assumes the
responsibility to pay for the diagnosis and treatment of employee/dependent
illness, then serious consideration must be given to the reallocation of
existing investment in human capital funds. This redirection of funding should
be toward health enhancement programs and services that optimize
employee/dependent health, which can reduce health care use, moderate cost
increases, reduce illness absence and improve work performance”.
(Whitmer R.,
Pelletier K., Anderson D., et.al) Journal of Occupational and
Environmental Medicine (45) (9), Sept. 2003; 916-925.)
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The Gender-Specific Effects
of Modifiable Health Risk
Factors on Coronary Heart Disease and Related Expenditures
This research project uses the HERO database. Of the 46,026 employees in the
database 2,459 were diagnosed as having CAD through CPT and ICD-9-CM codes. This
represents the study group.
A variety of risk factors, many of which are controllable through lifestyle
changes, contribute to the probability of CAD and health care costs. The risks
include: stress, smoking, obesity, hypertension, diabetes, lack of regular
exercise, high cholesterol and family history.
While there is minimal data available on the comparative economical impact of
risk factors on health care cost, there is even less when investigating this
question based on gender. Because of this, the following questions are
addressed:
- Based on gender, what are the absolute and relative costs
associated with each risk factor when treating patients with CAD? What are
the differences across risk factors? Are there differences in costs when
comparing males and females? If so, what are the differences?
- Based on gender, what is the occurrence of CAD and hospitalization
due to CAD? Are there differences when comparing males and females? If so,
what are the differences?
- Based on odds ratios, which risk factors are most prevalent among a
group of employees with CAD? What is the rank order?
Among this large, multi-employer group of workers who completed a health risk
appraisal (HRA), the difference between the occurrence of CAD between males
(6.3%) and females (5.7%) was only 0.6%. Among males, smoking was the number one
predictor of heart disease, while with women, profound obesity and uncontrolled
stress were the prime predictors. There was no level of consistency between men
and women relative to the association between health risks and costs. For
example, men reporting to be depressed most of the time had total health care
costs 91% more than men who reported not being depressed. Among women, those
reporting to be depressed most of the time had health care costs only 5% more
than those reporting not being depressed.
Behavioral change intervention application has usually been the same for men
and women. If the intent is to provide interventions based on the potential for
maximum reduction in medical costs, occurrence of CAD and hospitalization due to
CAD, this study suggests different intervention goals between males and females
may be appropriate.
This study was funded through grant number NAG-6218 from the National
Aeronautics and Space Administration (NASA).
(Wasserman, J, Whitmer, R, Bazzarre, T, et. al., Jour Occup Env Med, (42)(11),
November 2000; 973-985).
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This study uses the HERO database. Union Pacific
Railroad (UPRR), like many others, has an aging workforce. Prudent financial
planning mandates that future medical expenses be understood.
UPRR has a long history of providing and promoting aggressive health
promotion programs. For this reason, they have a rich database of employee
health risks and demographics. The objective was to adjust the HERO database to
accurately reflect the demographic characteristics of the UPRR employee
population. Multivariate statistical techniques were used to create models
predicting health risk prevalence and expenditures based on information
contained in the HERO database plus demographic characteristics, risk values and
cost data provided by the UPRR database. Risk factors examined are: 1) alcohol
consumption, 2) blood glucose, 3) blood pressure, 4) cholesterol, 5) nutrition,
6) fitness, 7) mental health, 8) tobacco use, 9) stress and 10) weight.
Demographics included are: 1) age, 2) gender, 3) ethnicity and 4) job
classification. These models will be used to estimate future health risks and
expenditures.
In summary, the study indicates:
This study paper describes the development of an economic forecasting
model to predict medical care expenditures assuming four different scenarios
of population risk. The variables used to predict medical care expenditures
are employee demographics and health risk profiles. Intermediate outcomes
include health risk measures related to exercise patterns, body weight,
eating habits, smoking, alcohol consumption, total cholesterol, blood
glucose, blood pressure, stress and depression. Major outcome measures
included projected total annual payments by UPRR for medical care services,
for the decade following 1998. The UPRR work force is projected to grow by
500 employees per year over the ten-year study period. The average age is
expected to increase form 44 to 48. The study reports that without further
health promotion intervention, seven of the 11 risk factors assessed would
likely worsen among UPRR’s work force. Medical care cost increases are
projected to range from $22.2 million to $99.6 million in constant 1998
dollars over the next decade, depending on the effectiveness of risk factor
modification programs. If UPRR is successful in reducing modifiable health
risks 1% per year over a ten year period, the aggregate reduction in health
care costs are projected to be 77.4 million With an expected health
promotion budget averaging $1.9 million annually over ten years, health
risks must decline at least 0.09% per year for the program to pay for
itself.
This study was funded by and unrestricted grant from the Union Pacific
Railroad.
(Leutzinger, J, Ozminkowski, R, Dunn, R, et. al. Am J Health Promot, (15)(1),
Sept/Oct 2000; 35-44.
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This study uses the HERO database in which 46,026 employees
met all inclusion criteria for the analysis. The purpose was to assess the
relationship between modifiable health risks and total health care expenditures
for a large group of employees. This study is different than Research Project
Two which examined individual health care expenditures as the outcome. Here the
outcome is the total cost impact of a given health risk.
Risk data were collected through voluntary participation in health risk
assessments (HRA) and workplace biometric screening. These data were linked to
health care plan enrollment and employee health care expenditures from employer’s
fee-for-service health care plans over a six year period.
Several research questions were addressed:
- What is the association between each of the eleven modifiable
health risks and health care expenditures?
- What percent of total health care expenditures are associated with
each of the eleven modifiable risks?
It was found that employees with modifiable health risks were responsible for
25% total expenditures. Those employees who reported being under constant stress
with no methods for coping were responsible for 7.9% of total health care costs.
Being a former smoker was associated with 5.6% total medical expenditures
followed by obesity at 4.1%. The association between risks and expenditures was
estimated using a two-part regression model, controlling for demographics and
other confounders. Risk prevalence data were used to estimated group-level
impact of risks on expenditures.
This study was co-funded through an unrestricted grant from HERO and The
StayWell Company.
(Anderson, D, Whitmer, R, Goetzel, R, et. al., Am J Health Promot, (15)(1),
Sept/Oct 2000; 45-52).
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A medical economics study using the HERO database, that addresses
two questions:
- Do those at high risk have greater health care costs than those at
lower risk? If so, what is the amount over time? What is the most
expensive, what is number two, number three, and so on?
- Do those with specific risk factor combinations have greater
medical expenditures than those without these risks? If so, what is the
amount over time?
This study was funded
by a consortium of 22 HERO sustaining partners. Research design involves a
retrospective, two-stage, multi-variate analysis, including logistic and linear
regression models. This permits the examination of specific risk factors as
independent variables, thus eliminating the impact of other risks. In addition
to adjusting for specific risk factors, other confounding factors adjusted for
were: gender, age, educational level, race, type of job, employer and number of
months employees were followed after the first HRA was completed. Ten risk
factors were evaluated, six self-reported and four biometric. The self-reported
were: physical activity, alcohol consumption, nutrition, tobacco use, stress and
depression. The biometric measurements were: cholesterol, blood pressure, blood
glucose and weight.
Using the HERO database, research inclusion criteria were: active employees
age 18 to 64 at the time of the first HRA and those who could be followed for at
least six months after the completion of the first HRA. Based on this, there
were 46,026 study subjects, all of whom completed a common HRA and were enrolled
in fee-for-service health care plans. They were followed for up to three years
after the completion of the first HRA.
It was found that those with self-reported, persistent depression (n=997,
2.2% of the study sample) had adjusted annual health care expenditures 70%
greater than those who reported not being depressed. Number two was uncontrolled
stress (n=8,641, 18%). These individuals had annual adjusted medical costs 46%
greater than those who were not stressed. The third most costly risk was high
blood glucose (n=2,271, 5%), with adjusted medical expenses 35% greater than
those with normal blood glucose. The other most costly risks in descending
adjusted order were: obesity (+21%), tobacco use (former +20%, current +15%),
high blood pressure (+12%), and poor exercise habits (+10%). There was a
dichotomy between the adjusted and unadjusted data relative to high cholesterol
levels (n=8,641, 18%). Based on unadjusted data, health care costs were 17%
greater than those with normal cholesterol levels, however, when adjusted,
health care costs were 0.8% lower. Those at high risk for health problems due to
excessive alcohol consumption (n=1,723, 4%) had adjusted health care
expenditures 3% lower than those at lower risk. This is not unexpected, as those
with drinking problems often avoid the health care system. In the case of
nutrition, those who reported poor nutritional habits (n=9,278, 20%) had
adjusted health care expenditures 9% lower than those who reported good
nutritional habits. This finding was perplexing, because it is in contrary to
the body of published nutrition research. It may be explained by the fact that
the impact of all other risks usually associated with poor nutrition (obesity,
hypertension, high cholesterol, high blood glucose) have been eliminated through
the adjustment process.
The finding that psychosocial risks were the most costly was unexpected and
medically newsworthy. This study suggests that sufficient attention should be
directed toward worksite depression and stress screening along with the
opportunity for adequate diagnosis and treatment.
This research project is complete, peer-reviewed and published in the October
1998 issue of the JOURNAL of OCCUPATIONAL and ENVIRONMENTAL MEDICINE (Goetzel,
Anderson, Whitmer, et.al., JOEM, (40) (10). October 1998; 1-12).
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HERO has facilitated the creation of a large,
retrospective, multi-employer health promotion research database. This was
accomplished by collaboration among HERO, the StayWell Company, the MEDSTAT
Group, and six large employers: Chevron Corporation, Health Trust, Inc.,
Hoffmann La Roche, Marriott Corporation and the states of Michigan and
Tennessee. All employers are clients of The StayWell Company and The MEDSTAT
Group. A top priority in the creation of the HERO database was the ability to
examine the impact of risk factors, risk factor combinations and risk factor
change on individual medical expenditures.
The HERO health promotion research database includes 47,500 employees, all of
whom completed a common health risk appraisal (HRA), the StayWell Health Path®,
and were enrolled in a fee-for-service, self-insured health care plan for the
study period of 1990 to 1996. Approximately 12,000 of the employees completed
two or more HRAs during this time. The HERO database was created by connecting
the HRA data set with the medical claims data set along with the eligibility
data set. Including the eligibility data permitted the inclusion of study
subjects that had no medical claims. The confidentiality of individuals was
maintained by scrambling personal identifiers across all data sources. The
merging of these data sets yielded 113,963 person years experience. The previous
largest research database of this kind is the Control Data - Milliman Robertson
database which includes about 13,000 study subjects and provides approximately
40,000 person years experience.
Creation of the HERO database could have a major impact on the future of
health promotion and disease management research. It is amenable to the design
of numerous longitudinal research studies that examine the association or impact
of single risk factors, risk factor combinations, risk factor change, selected
chronic diseases and demographics on: medical costs, diagnosis, treatments,
procedures, outcomes, hospitalization or any other parameter usually recorded in
a typical fee-for-service medical claims database.
A consortium of 20 HERO sustaining partners funded the creation of the
database. HERO is willing to facilitate research, using the database, for
outside clients.
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