The majority of weight management research is based on data from randomized controlled studies conducted in clinical settings. As these findings are translated into community-based settings, additional research is needed to understand patterns of lifestyle change and dropout. The purpose of this study was to examine reasons for and consequences associated with dropout  from an insurance-funded weight management program. Using a mixed methods approach with objectively measured changes in body weight and attendance along with quantitative and qualitative survey data, patterns of intention and behavior change were explored. The results from a sample of 400 respondents support the idea that there are both positive and negative consequences of program participation. Overall, 1 in 5 respondents lost a clinically significant amount of weight during the program (>5% of baseline body weight) and 1 in 3 experienced a positive consequence, while only 6% expressed a negative outcome of participation. Additionally, nearly 90% of all of the consequences that emerged from the data were positive. Attitude change was a major theme, including positive health intentions, perceived success, learning skills, and new appreciation of exercise.  Much of the extant research on weight loss and weight management in adults has focused on the factors associated with adherence during, or after, programs which are typically staged in academic or clinical settings, using randomized controlled designs , 2. DespOther studies have shown that program participants who disengage may still join other behaviors or programs. For instance, Ecclestone et al.  tracked Research examining other health behaviors, such as smoking cessation, has shown that it can take a sequence of repeated, unsuccessful attempts before long-term healthy behaviors are maintained . For exaAs weight management programs increasingly become translated into community settings, a certain degree of dropout can be expected as participants manage multiple time commitments and as program staff members manage multiple job responsibilities. Translation into community settings will bring along with it a greater need for accountability and compliance. Private fitness centers, health departments, and public and private insurers will want to know if these programs are sustainable or profitable. For example, programs established by health insurance agencies tend to have compliance guidelines to which participants must adhere to remain eligible to receive subsidized services. Fitness centers and community clinics benefit from these subsidized programs because they earn money by providing professional services to the policy holder. The main reason for stringent compliance guidelines is that providing such programs can be costly, particularly for insurance-funded programs, which aim to address various health risks that impact chronic disease and curb insurance expenses associated with chronic disease . Thus, aThus, the purpose of this study was to examine reasons for and consequences associated with dropout  from a state-wide, insurance-funded weight management program. The research questions included the following: (1) What are the reasons people drop out from an insurance-funded weight management program? (2) What are the positive and negative consequences associated with dropout? and (3) What are the differences in consequences and future health behavior intentions for those who drop out early, middle, or late into the program?West Virginia is a small, Appalachian state ranked among the least healthy states in the US based on adult prevalence of obesity (33% versus 27.5% US Median), diabetes (12% versus 8.7% US Median), and heart disease (6% versus 4% US Median), all of which rank in the top 10 in the United States . The est2 or higher or an eligible waist circumference . The program, which requires a $20 monthly copay, includes access to a fitness facility in the local community and services provided by a personal trainer, dietitian, and exercise physiologist. Previous single-site and large-scale evaluations of this program's effectiveness have shown low reach, moderate to high effectiveness in short-term and long-term weight loss, and strong potential for sustainability [The program is a two-year benefit offered by PEIA for people with a BMI of 25 kg/mnability , 13–15.The requirements for ongoing participation (for up to two years) are maintaining at least eight monthly visits to the fitness facility, attending appointments with professionals, and showing improvements in weight or other measured health parameters. Participants are allotted specific minutes of professional services each month in the program. For example, in the first six months, participants receive 120 minutes of personal training per month, three 30–60-minute consultations with a dietician, and two 60-minute fitness assessments by an exercise physiologist. However, there is no standard model of service delivery as each professional is allowed the freedom to deliver fitness and dietary services within their own scope of practice. Facility staff are responsible for entering objective data on participant attendance and body measurements  on a monthly basis into a secure, web-based platform used for evaluation and billing.Participant compliance with program requirements is reviewed on a bimonthly basis. Those participants that do not meet the eight visits per month minimum attendance criteria for two or more consecutive months are removed from the program. Therefore, participants may be administratively removed for noncompliance with these requirements or other issues may arise that cause the termination of their program . In addition, participants may voluntarily choose to drop out from the program for personal reasons. When they are removed or choose to drop out from the program, they receive a letter informing them of their change in status. One month later, they receive an invitation to complete a program evaluation survey.n = 973) received the program evaluation survey containing questions related to their participation in the program. The survey was sent first via email through a unique link to the participants who provided their email addresses at the start of the program. The electronic version of the survey was sent twice via Survey Monkey with a one-week interval between the first attempt and the reminder. If they did not respond to the email survey, a hard copy of the survey was mailed, which is the first step for participants without an email address. After a week without response from the paper-based survey, a reminder post card was sent to the participant. Using this Dillman [The study used a mixed methods design including quantitative data on objective outcomes  as well as self-reported reasons and consequences in both quantitative and qualitative forms collected from the program evaluation survey. All program participants over the age of 18 who exited the program during 2014  to 4 (completely satisfied). The final question analyzed in this study inquired about the participants' intentions of carrying out the following health-related behaviors in the future, in a categorical format : (a) continue as a private fitness member at the facility; (b) exercise for 30 minutes per day, five days per week; (c) exercise for 60 minutes per day, five days per week; (d) seek out a registered dietician; (e) enroll in a group exercise program; or (f) enroll in a group nutrition program.After inquiring about their future intentions, two demographic questions  preceded a final question where they could express other thoughts about the program. Because of the wording of this last question, many of its responses were related to satisfaction or dissatisfaction with the program . In addition to satisfaction/dissatisfaction, participants also tended to express the positive and negative consequences related to their participation in the program and thus these data were included in the subsequent qualitative analysis.First, a frequency analysis of the participants' characteristics was carried out. Then, a frequency analysis of their overall intentions for future health-related behaviors was performed. Finally, the two open-ended questions were analyzed through content analysis  to addreFor the final research question, respondents were classified into three groups depending on the timing of their program exit: (1) “early” drops (participation of 6 months or less); (2) “mid” drops (between 7 and 12 months of participation); and (3) “late” drops (between 13 and 24 months of participation). Two-way chi-square analysis was used to explore the future intention data as well as the patterns of consequences experienced across the three groups. These bivariate analyses were used to determine if there was any relationship between the length of time in the program prior to exit and their coded consequences and stated intentions. Effect size estimates for all analyses are reported as the contingency coefficient, and values >.3 can be considered moderate.The respondents were aged between 24 and 70 years, with a mean age of 48.6 years (SD = 11.1). The mean length of participation in the program was 9.8 months (SD = 5.6), with 33.7% exiting the program within the first six months, 35.7% exiting between 7 and 12 months, and 30.6% completing 13–24 months. Among the male participants, mean weight at the beginning of the program was 262.2 lbs (SD = 57.3), while women had a mean weight of 210 lbs (SD = 49.6). Men's mean waist circumference at the beginning of the program was 46.9 inches (SD = 6.9) and women's was 42.4 inches (SD = 9.8). On a 6-point Likert scale, with one meaning “not at all satisfied” and six meaning “completely satisfied,” participants had a mean satisfaction of 4.4 (SD = 1.5). At the time of survey completion, the average percent body weight loss for the respondents was 2.27% (SD = 4.9). Additionally, upon program exit, 21% of respondents lost at least 5% of their baseline body weight during the course of the program, while 26.7% had gained weight.t-tests was conducted to compare the groups on characteristics at baseline. These analyses were conducted separately for men and women. Analyses indicated that mean BMI, waist circumference, body fat percentage, and length of participation in the program of participants who dropped out from the program and responded the survey were not significantly different from the participants who dropped out and did not respond the survey (p > .05). However, the nonrespondents' age  was significantly lower than the respondents' , t(971) = 5.33, p < .001. Despite this small difference in age, survey respondents and nonrespondents appear to report similar profiles related to their weight and program participation, thus reducing the concern for selection bias in the subsample of respondents.To check for demographic differences between the survey respondents and nonrespondents, a series of independent samples Among the 400 survey respondents, 375 participants responded to the question about their reasons to drop out from the program, while 272 responded to the final open-ended question. Reasons for dropout were allowed to emerge from either of these two questions. In total, reasons to drop out from the program were coded 420 times, with some participants indicating more than one reason and some leaving the question blank. Seven major themes regarding the participants' reasons to drop out from the program emerged from the survey responses: competing priority (36.9%), medical (22.8%), negative experience (13.1%), programmatic issues (12.4%), administrative drop (7.4%), insurance coverage change (6.4%), and completed attempt (1.0%). The competing priority theme was the largest emergent theme with 155 occurrences (36.9%) and included the subthemes of time (18.3%), caregiving (5.7%), distance (5.2%), lack of motivation (4.1%), personal reasons (2.1%), and grief (1.4%). Time was a frequently coded subtheme, including statements of limited or lack of time to comply with the program requirements . Caregiving meant having to take care of older family members  or children . Distance included the gym being far from home or work and moving to another place. Lack of motivation included need for external motivation, not being able to meet requirements, and just not wanting to participate anymore . Personal reasons contained personal or family reasons that were not specified . Finally, grief regarded difficulties in adherence due to grieving the death of a close person .The medical reasons theme included other Physical Limitation (20.9%), injury at facility (1.7%), and weight loss surgery (0.2%). Other physical limitation was the most frequently coded subtheme and included a variety of health issues other than injury at facility and weight loss surgery . Getting injured at the facility was reported by seven respondents, which prevented further exercise participation . Weight Loss Surgery  was indicated by one participant.The theme negative experience (13.1%) included the subthemes of dissatisfaction (7.4%), negative feedback (2.4%), price (2.1%), and lack of support (1.2%). Dissatisfaction included disappointment with results, training, and services in general . Negative feedback included negative feedback from measurements (1.0%) and pain (1.4%). The first could be exemplified as “the negative feedback made me feel like a failure instead of acknowledging my improvement, so I quit going,” while the second involved any kind of pain related to the participation of the program . Price comprised unwillingness or impossibility of paying for direct or indirect costs of the program . Finally, lack of support included family and social support. Lack of family support (1.0%) was coded when family members were unsupportive of the participant's compliance with the program , while lack of social support (0.2%) contained only one respondent who wished to have a buddy exerciser: “I needed to have someone to work out with!”.Programmatic issues was divided into the subthemes facility problem (11.7%) and gym culture (0.7%). The subtheme facility problem was further divided into professionals (6.2%), facility closure (4.5%), and facility hours (1.0%). The professionals subtheme regarded problems with the staff delivering the services offered by the program, such as trainer's or dietitian's ineffectiveness, limited availability, and lack of support . Facility closure represented when the gym closed or stopped offering the program and this situation triggered the participants' dropout . Finally, facility hours included dissatisfaction with the facility hours . Gym culture included expressions of uncomfortable feelings due to the gym environment .The themes completed attempt, insurance coverage, and administrative drop  were less meaningful since they involved administrative issues. Insurance coverage contained participants who left for another job or retired, thus losing the insurance benefits, and administrative drop encompassed respondents who were removed by the program administration due to noncompliance. Completed attempt included people who believed that they had already completed the program and ceased going to the facility.Among the 400 survey respondents, 272 responded to the final open-ended question about their experiences in the program. Two major themes emerged from these 272 responses: positive and negative consequences from participation in the program. Positive consequences were coded 150 times (88.2%) and negative consequences 20 times (11.8%). Positive consequences included three subthemes: psychological (52.7%), behavioral (22.0%), and physical (25.3%). These subthemes were further divided into smaller categories, as shown on Three themes emerged in the positive psychological consequences. The first was attitude change (41.3%), which included the codes positive intentions (32%), perception of success (6.7%), and appreciate exercise (2.7%). The most common subtheme within the attitude change was positive intentions, which comprised intentions such as continuing to exercise, joining another weight management or exercise program, and seeking nutrition guidance . The second most common was perception of success, including subjective comments regarding achieving success . The last subtheme within the attitude change was appreciate exercise, which included liking exercise and realizing positives of exercising .Another subtheme included in the positive psychological consequences was learning (8%), which contained several learning experiences, such as learning about exercise, eating, self-motivation, and weight loss . Finally, the last subtheme within the positive psychological consequences theme was feelings (3.3%), which contained general positive feelings such as being proud .The second major theme within the positive consequences was behavioral (22%), which comprised maintenance (14.7%) and changes (7.3%). Behavioral maintenance included continuing to exercise and eating healthy . Behavioral changes referred to changes in exercise and eating habits without referring to the maintenance of these changes .The final major subtheme within the positive consequences was physical (25.3%), which included the subthemes weight loss (15.3%), health improvement (5.3%), and fitness improvement (4.7%). Weight loss subtheme was subcoded into lost weight (13.3%) and continue to lose weight (2%), which differed regarding when the weight loss happened (during the program or after dropping out of it). An example of lost weight is “I lost 45 pounds in the program” and one of continue to lose weight is “since leaving the program I have lost about 15 pounds.” Health improvement regarded improvements in health-related markers , stress, energy, and pain . Fitness improvement was related to enhancement in physical capability such as strength, flexibility, stamina, and resistance .n = 20), the psychological consequences was the most frequent coded subtheme and was further subcategorized into attitudes (40%), feelings (35%), and lack of learning (5%). Attitudes included dissatisfaction with weight loss (15%) and lower motivation for being dropped (25%). The first comprised expressions that weight loss was not enough to satisfy the participant . The latter regarded the participant's decrease in motivation as a consequence of being removed from the program . Still within the negative psychological consequences, the code feelings included negative feelings such as guilt, disappointment, and shame . Finally, the last negative psychological consequence was lack of learning and it was coded once: “I didn't really learn anything new or take away anything useful.” The physical negative consequences were comprised of only one subtheme: weight gain (20%). It included statements of weight gain during the program or after leaving it .Among the negative consequences (n = 400) intentions for future health-related behaviors, 64% intended to exercise 30 minutes per day, five days per week, 16% intended to exercise 60 minutes per day, five days per week, 11% intended to join a group exercise program, and 21% intended to continue as a private member of the fitness facility that they were attending during the program. Additionally, 7% intended to seek the help of a registered dietitian to make nutrition changes and 13% intended to enroll in a group nutrition program. When comparing these intentions among respondents who dropped out of the program early (6 months or less of participation), in the middle (between 7 and 12 months), or later (between months 13 and 24), two trends in the data were found. Chi-square analysis showed that respondents who stayed for seven or more months in the program were more likely to intend to continue exercising five days a week for at least 30 minutes (68.6% combined for the mid and later groups) compared to early dropouts (55%); however this effect was not significant, χ2 = 7.09, p = .131, cc = 0.14. This trend was not found for intentions to exercise five days a week for 60 minutes, which overall remained low in the overall sample (16.1%). However, early dropouts (8.2%) were significantly more likely to intend to seek a dietitian help to make weight changes than middle dropouts (5.8%), χ2 = 12.97, p = .011, cc = 0.18. The pattern of intentions to seek out group exercise classes or group nutrition services did not differ in a meaningful way across the three groups. In general, exercise intentions were substantially higher than dietary intentions.Regarding the respondents'  = 1.59, p = .451, cc = 0.07. Overall, one-third of those who answered this open-ended question reported a positive consequence of program participation.The final set of chi-square analyses targeted the relationship between stage of dropout  and consequences expressed. First, two analyses were conducted to see if the percentage of respondents reporting positive or negative consequences differed across the three groups. Subsequent analyses explored the various subthemes of positive and negative consequences across the groups. Positive consequences experienced in the program did show an increasing trend across the three groups, from 30.4% to 31.3% to 38.8%, but this relationship was not significant χ2 = 5.30, p = .071, cc = 0.14.The largest differences in reported positives themes were from the psychological category. Those participants who dropped out after 12 months (32.5%) were nearly twice as likely to report a positive psychological outcome compared to those who dropped out early (17.4%); however, this small effect failed to reach significance, χ2 = 9.723, p = .008, cc = 0.19. This pattern held true for all of the subthemes of negative consequences, with the exception of “dissatisfaction with weight loss.”A different trend was revealed for the negative consequences, with those who dropped out in the middle group reporting a negative outcome 3–5 times as often (12.5%) as the early (2.2%) or late (3.8%) dropouts, The results of this mixed methods study support the idea that there are both positive and negative consequences experienced in a sample of weight management program dropouts. Overall, 1 in 5 respondents lost a clinically significant amount of weight during the program (>5% of baseline body weight), regardless of the time of program exit, and 1 in 3 experienced a positive consequence, while only 6% expressed a negative outcome of participation. Additionally, nearly 90% of all of the consequences that emerged from the data were positive. Thus, some of the dropouts appear to have experienced substantial success in terms of outcomes or lessons learned through participation, and five times as many respondents reported a positive consequence compared to those who reported a negative consequence of participation. In particular, the psychological consequences seem meaningful. Attitude change and skill acquisition were major themes, including positive health intentions, perceived success, learning skills, and new appreciation of exercise. These findings support previous theories of health behavior change including the theory of planned behavior's connection between intentions, self-efficacy, and past behavior  as well Approximately two-thirds of the respondents indicated they intend to continue exercising five days a week for 30 minutes, an amount of physical activity that would meet guidelines for general health . Some reNot all participants reported positive outcomes, however, and approximately 1 in 4 of the dropouts gained weight during the program. It is important to note that most of the negative consequences reported were also psychological in nature (including lower motivation and dissatisfaction with weight loss), and there were no strong themes for things such as “injury” or “worsened disability.” Integrating the objective and subjective data on consequences allows an observation that approximately 20%  to 33% (percent of respondents who self-reported a positive consequence) of dropouts of this community-based weight management program experienced a meaningful positive consequence resulting from program participation. Future research may consider capturing some of these possible benefits along with reporting the outcomes of those who complete intervention programs.The average respondent dropped out approximately 10 months into this two-year-long program, and negative consequences were reported at a higher rate among middle dropouts compared to early or late dropouts. This particular phase of the program (between 7 and 12 months of participation) appears to be the highest risk of dropout and may warrant additional attention. Competing priorities  was the most widely cited reason for program exit (noted by 37% of respondents), suggesting that the working adults in the program often struggle to manage the multiple commitments of work, family, and health. This evidence supports the idea that some people need more support than others based of the timing of their attempt and the strength of their motivation at program entry. These data also support the finding from Grave et al.  that somIn this particular program, there is also a significant change to the services provided to participants during this time frame. In particular, their access to personal training drops from 120 minutes per month to 60 minutes per month, and they are not scheduled for another fitness or dietary reassessment until month 13. This reduction in professional services and the lack of accountability that comes along with those reductions may cause some participants to lose motivation and commitment. It is also possible that adhering to the facility-based program that requires at least eight in-person visits per month is not sustainable for everyone over two years. Anecdotally, many participants report traveling substantial distances to reach the facility, particularly in rural parts of the state. Adding further support in the form of behavioral services may be needed considering that many program enrollees enter with various comorbidities or physical limitations. This issue highlights a key difference in populations who are enrolled in community-based programs compared to clinical trials; prior to group assignment, many participants with comorbidities are often excluded from trials. Adding behavioral services (in various forms and at various stages of the program) could help participants learn new skills and stay engaged long enough to maintain the multiple health behaviors they have initiated .The final discussion point worth noting relates to the differences observed when working with high risk adults and translating programs into communities. Though this program is a fitness facility based program, the weight management program participants are often dissimilar from typical gym members. They are typically obese, possess low fitness at baseline, and present with additional health risk factors including hypertension, hyperlipidemia, and/or diabetes. As insurance companies try to build connections with the fitness industry, it is imperative that fitness staff are trained to safely and accurately assess, prescribe modified exercise to, and train high risk clients. A mismatch between the needs of these participants and the staff training may be contributing to weak outcomes, injuries, and program noncompliance. These issues were noted by some participants who dropped out, thus highlighting the difficulty of ensuring high “treatment fidelity” in a large, community-based program.The results of this study should be interpreted given the following limitations. Despite the analyses indicating the responders are not that different from the nonresponders, there is still the potential for self-selection bias in the data. With a 40% response rate, it is possible that survey responders were more likely to report positive consequences than those who chose not to respond. Next, in our analyses of those who were dropped from the program, we did not differentiate between those who left the program voluntarily and those who were dropped due to noncompliance. However, this difference between groups is not as large as it seems. All participants self-enroll in the program and decide on their own to attend the facility or to stop coming. Thus, both groups are “voluntary” drops. Some participants are conscientious enough to call program staff, and the others simply stop going to the facility and then are dropped within 2-3 months for noncompliance. Finally, the study is limited because there is no follow-up data indicating if the positive intentions expressed at program exit led to future observable behaviors. Future studies will explore these patterns over time and should address the relative importance of the psychosocial and environmental factors and barriers that emerged among participants .There is strength in the study's design and data given the unique mix of quantitative, objectively observed changes in body weight and attendance along with the qualitative reasons, and consequences expressed by several hundred respondents. The loss of internal validity when programs are disseminated into multiple community settings is unavoidable. However, we cannot expect to treat or reverse the obesity epidemic in the US with the limited reach of randomized controlled trials in clinical settings. We must embrace the messiness of community-based programs, especially those funded by insurance agencies, because they are sustainable and possess strong external validity. Findings of the current study can be used to inform and improve future community-based research and multisite intervention programs with similar rural populations in the United States that experience the greatest health disparities in chronic disease.


Many studies have focused on the need of health systems to educated physicians in the clinical prevention, research methodology, epidemiology and health care management and emphasize the important role of this training in the public health promotion. On this basis, Shiraz University of Medical Sciences (SUMS) has established MD/MPH dual degree program since the year 2012. In the current study, Delphi technique was used. Both qualitative and quantitative methods were applied in the Delphi process. The Delphi team members including experts with extensive experience in teaching, research and administration in the field of educational management and health/medical education reached consensus in almost 86% of the questionnaire items through three Delphi rounds. MD/MPH program for SUMS was designed based on the items agreed and thematic analysis used in these rounds. The goals, values, mission and program requirements including the period, the entrance condition, and the number of units, and certification were determined. Accordingly, the courses of the program are presented in parallel with the MD education period. MPH courses consist of 35 units including 16 obligatory and 15 voluntary ones. Designing MD/MPH program in SUMS based on the existent models in the universities in different countries, compatible with educational program of this university and needs of national health system in Iran, can be a beneficial measure towards promoting the students’ knowledge and theoretical/practical skills in both individual and social level. Performing some additional research to assess the MD/MPH program and some cohort studies to evaluate the effect of this program on the students’ future professional life is recommended. According to the views of many experts, students' education in most of the medical schools is focusing on the individual treatment and diagnosis based on the biomedical model; thus, the absence or lack of education emphasizing the population-based model and prevention is considerable. Remarkably, the estimations show that less than 1% of physicians passing adequate training in the health sciences and having inadequate knowledge not only imposes extra costs on the health system, but also has a detrimental effect on the quality of research and clinical practice .Accordingly, many studies indicate the need of health systems to well-educated physicians in the clinical prevention, research methodology, epidemiology and health care management and emphasize the important role of this training in the public health promotion -10. MostIn Iran, Tehran University of Medical Sciences (TUMS) established the MPH dual degree program for the first time in the year 2007-8 by admitting 42 exceptionally talented students. The main goal of this program is training students in analytical and managerial skills needed for development of expert managers in clinical and public health fields and its emphasis is on the functional solution of health system issues. The most important primary motivations of students who entered this program in different countries were learning research methodology scientifically and systematically, improving academic resume for post-graduate education and achieving academic or managerial position . GeneralOn this basis, Shiraz University of Medical Sciences (SUMS) established MD/MPH dual degree program in the year 2012. This article describes the design phases of this period as well as its details. In the current study, Delphi technique was used. Both qualitative and quantitative methods were applied in the Delphi process. Delphi is a structured process that uses a series of questionnaires or ‘rounds’ to gather information until consensus in the panels is reached . This teFirst roundThe first questionnaire consisted of 26 questions obtained from literature reviews and expert members’ opinions of the committee responsible for designing and implementing the program. To allow expression of a wide range of views, the questionnaire comprised open-ended questions . PrintedSimultaneously, the Latin databases including Medline, Cochrane, Google Scholar, Scirus, Embase, and Web of Science were searched and related studies, rules and guidelines on the topic of instructional system design, MD/MPH program and dimensions of educational programs applied in different universities throughout the world were gathered. After the primary search, a number of secondary searches were also conducted based upon “related links” as well as additional works by the authors identified in the primary search to gather excessive data. Thereafter, generated ideas and suggestions from round 1 and gathered data from literature review were combined and similar ideas were clustered into emerging themes. Three of the authors as the Delphi coordinators did this separately at first and then jointly to discuss different interpretations. The items were used as input for round 2. Second roundIn the second round, the participants were presented with the previous round items and themes. The participants were asked to score each item using five-point Likert scale . Space was provided for optional comments at the end of each theme and at the end of instrument. Based on the literature, we defined consensus as at least 80% of the participants in the Delphi team ticking the same answer category (e.g. 5 ‘extremely important’) and no more than 15% an answer category two or three categories away (e.g. 2 ‘slightly important’ or 1 ‘not important’) . Items oThird roundIn the third questionnaire, the other items on which the consensus was not achieved in the previous round were included, together with feedback on the responses of the panel and the participant’s own responses. The participants were asked to reconsider their previously given responses in light of the opinion of other panel members. Space was again made available at the end of each theme as well as at the end of the instrument for optional comments. The scoring process was the same as the previous round. At the end of the round, consensus was reached in almost 86% of the questionnaire items. Therefore, the Delphi team members reached consensus and Delphi rounds were stopped.Afterwards, MD/MPH program for SUMS was designed based on the agreed items and thematic analysis used in the Delphi rounds. This program model was recommended to the competent authorities in the university and was assessed. Finally, the suggested program was approved by the university authorities and got started.Goals of the programThe general goal of the MD/MPH program is promoting the students' analytical skills and preparing them to participate in a wide range of positions in the health and clinical care. The specific goals of the program are as follows:- The development of the students' managerial skills to cope with future health managerial duties- The development of the students' analytical skills to enable them to practically resolve the problems of the health system- The development of the students' community-based skillss' research skills- The development of the students' creativity and innovation- The improvement of the studentValues of the programValues of the MD/MPH program at SUMS are as follows:The maintenance and promotion of the communities' health, based on the human rightsJustice in health Community based health Enabling people to manage their health careAccountability, responsibility and approaching health as a human right by health care providersThe mission of the programThe students should attain the following abilities after passing MD/MPH Program:Identifying the health issues at national and international level accuratelyDetermining the scope and size of the health issuesDetermining the reasons and factors influencing healthDesigning appropriate strategies for prevention and intervention Determining the most effective method of intervention based on the political, economic and social situationDeveloping the new methods of health care management and its evaluationThe period of the programMedical education in Iran lasts 7 years and consists of 3 stages including basic sciences, physiopathology, and clerkship. The students enter the MPH program at the beginning of the physiopathology stage. The courses of the program are presented in parallel with the MD education period. Conditions for entrance to the programTop medical students whose grade point average of their previous semesters is A (17/20 or higher) are eligible to enter the MD/MPH program. After the students register in the program voluntarily, the written and oral exams will be held. The students meeting the passing score will be eligible to enter the MD/MPH program.The number of the coursesMPH courses consist of 35 units. 16 obligatory units are offered during the first stage and 15 voluntary units are offered during the second stage of the program. The voluntary units are selected based on the students’ interests. Thesis as a 4 unit course should be passed at the end of the program. Its topic is chosen based on the health system/university research priorities and students’ interest .The MPH courses are compatible with medical courses. The number of units per MPH semester is 4-6. The courses are held in the afternoons and weekends.Students in this program visit the research centers and health care providing centers based on the courses taken . Furthermore, holding scientific meetings by experts in health sciences is another type of activity in MD/MPH program.CertificationMPH degree is granted to the graduates of the MD/MPH program in addition to MD certificate. Graduates of this program can participate in the postgraduate studies in different Ph.D and medical specialties. MPH degree will be awarded to those who have successfully passed their medical courses. Health systems in the world are faced with various and changing issues. For example, communicable diseases were very important in the past; however, chronic and non-communicable diseases through epidemiological transition have become more serious in the recent decades. Presently, the significant influence of environmental factors, air pollution, occupational risk factors and social determinants of health on communities’ health has been identified. The MD/MPH program provides the graduates with enough knowledge to face with diverse and changing health-related issues and enable them to deal with these situations in the future , 25-26.Based on this, the MD/MPH program is implemented in different universities in the world. Each of these programs has had different experiences and findings that indicate their effectiveness. For example, a study on the MD/MPH program at Tufts University showed that the implementation of MD/MPH program can better meet the changing needs of clinicians and their patients while also promoting the health of the public . EstabliIn our study, MD/MPH program was designed through Delphi technique which is one of the most effective methods to reflect the individuals’ diverse ideas and opinions. In fact, designing/implementing committee of the program tried to localize the MD/MPH program model applied in other universities and increase the potential benefits of the program using Delphi method. For instance, the beginning time and the period of the program were localized according to the current medical education condition in SUMS. To illustrate, MD/MPH is a full-time program in some of the world universities and medical students have to quit their medical education for a period of time to pass MPH. However, this study showed that passing MPH program and medical education at the same time is more effective and practical in SUMS, a notion which was frequently mentioned by the Delphi team members. Moreover, entering the MPH program at the beginning of the physiopathology stage is the most suitable entry time for medical students regarding their knowledge gained through the passed medical courses at that point of time and also their medical studies in the future. This study had some limitations. Firstly, Delphi team members consisted of only experts of the field and not students. To confront this restriction, some research was conducted on MD/MPH students immediately after initiation of the program and some revisions were held based on the results. For example, the former voluntary courses in the program were then added by defining scientific writing (2 units) and academic writing (2 units) courses after doing some need assessment studies on MD/MPH students. Moreover, the Delphi team members were so busy and gathering research data through Delphi rounds was a time consuming process.Consequently, MD/MPH program is implemented in SUMS presently and more than 100 medical students through three application periods have entered the program and are passing their courses continually. In general, designing MD/MPH program in SUMS based on the existent models, compatible with educational program of this university and needs of national health system in Iran can be a beneficial measure towards promoting the students’ knowledge and theoretical/practical skills in both individual and social level.At last, performing further research to assess the MD/MPH program and some cohort studies to evaluate the effect of this program on the students’ future professional life is recommended.


Physical activity is known to prevent falls; however, use of widely available exercise programs for older adults, including EnhanceFitness and Silver Sneakers, has not been examined in relation to effects on falls among program participants. We aimed to determine whether participation in EnhanceFitness or Silver Sneakers is associated with a reduced risk of falls resulting in medical care.International Classification of Diseases, 9th Revision, Clinical Modification, Sixth Edition and E-codes.A retrospective cohort study examined a demographically representative sample from a Washington State integrated health system. Health plan members aged 65 or older, including 2,095 EnhanceFitness users, 13,576 Silver Sneakers users, and 55,127 nonusers from 2005 through 2011, were classified as consistent users ; intermittent users , or nonusers of EnhanceFitness or Silver Sneakers. The main outcome was measured as time-to-first-fall requiring inpatient or out-of-hospital medical treatment based on the In fully adjusted Cox proportional hazards models, consistent  and intermittent  EnhanceFitness participation were both associated with a reduced risk of falls resulting in medical care. Intermittent Silver Sneakers participation showed a reduced risk .Participation in widely available community-based exercise programs geared toward older adults  reduced the risk of medical falls. Structured programs that include balance and strength exercise, as EnhanceFitness does, may be effective in reducing fall risk. Falls affect 30% to 40% of community-living adults over age 65 every year. Half of falls result in some type of injury, and falls may contribute to declining function, loss of independence, illness, and death . Fall-reFall prevention research has found that regular physical activity incorporating strength and balance exercise can reduce falls, fall-related injuries, and falls resulting in medical care –7. CommuOur objective was to examine the relationship between participation in EF or SS and risk for a fall requiring medical treatment , in a sample of GHC Medicare plan enrollees. On the basis of existing evidence that physical activity plays an important role in fall prevention, we hypothesized that consistent users of either program would have lower risks of a medical fall compared with nonusers.A retrospective cohort study was conducted among a demographically representative sample of the Seattle-area population of older adults. The exposure of interest was defined as participation in either the EF or SS program and the outcome was the first occurrence of a medical fall during the study period (2005–2011). Participants were members older than age 65 of GHC, which serves patients throughout the states of Washington and Northern Idaho. Participants were selected by using the following eligibility criteria: Integrated Group Practice members , continuous enrollment for at least 1 year, aged 65 to 98, and eligible for the Medicare EF and SS programs for some portion of 2005 through 2011. Individuals were excluded if they met any of the following specific criteria: residing in long-term care or nursing home setting, receiving hospice care , wheelchair-bound (V46 or V53.8), aged 99 or older, or having a diagnosis of a serious mental health or substance use disorder . All demographic, health, and medical record data were extracted from GHC electronic health records and merged with participation data supplied by the EF and SS programs. GHC has complete records of health care use and costs, and these data have been validated and are frequently used for research . This reEF, a nationally disseminated, evidence-based exercise program  for oldeParticipation in either program was defined as documentation of attendance at either the EF or SS programs at least twice in a given year. Because specific attendance counts were not available in the data set, participation in the EF and SS programs was stratified into 3 levels in an effort to approximate regular exposure to the programs. These strata were 1) consistent users, who participated every year they were enrolled in GHC during the study period (2005–2011); 2) intermittent users, who participated at least 1 but not all years they were enrolled; and 3) nonusers, who never participated in either program while enrolled. Mean duration of enrollment in GHC for this sample was 4.7  years.Falls requiring medical treatment were identified through the use of both inpatient and outpatient recording of ICD-9-CM codes  and E-codes  indicating medical treatment of an injury related to having had a fall . The pre2, calculated from most recent height and weight for each year; continuous), smoking status (yes/no), and Charlson Comorbidity Index score : age (continuous), sex , race/ethnicity , body mass index ; diagnosis of dementia , walking disorder , osteoarthritis , osteoporosis , musculoskeletal conditions , and visual impairment . All comorbidity diagnosis variables were time-varying and constructed to reference a diagnosis for the given condition in the year before the year of interest.Initially, Kaplan–Meier survival curves were fit to the data to depict the time-to-medical-fall for each group. Time-to-event analyses were then conducted using days from entry into the study to the date of a fall, loss to follow-up, or the end of the study period . Individuals were censored if loss to follow-up occurred because of death or withdrawal from the GHC system. Specific dates for these events were unavailable and therefore defined as June 30 of the last year an individual appeared in the data set if that year was before 2011. A series of Cox Proportional Hazard models compared time-to-fall of nonusers to that of consistent and intermittent users of each program. Several models were constructed: a crude model (no adjustment for confounders), a demographic model , and a full model . In fully adjusted models, individuals with missing values for a covariate were dropped from the analysis. All analyses were conducted using Stata 13 .Compared with nonusers, consistent and intermittent users of either program were more likely to be female, less likely to smoke, and had lower Charlson comorbidity scores  and 2. HIn hierarchically adjusted Cox regression models , a decreTo our knowledge, this is the first study to directly investigate the impact on the risk of medical falls of 2 exercise programs not specific to fall prevention. Consistent use of EF, our proxy for regular participation in the program over several years, was associated with the greatest reduction in risk of a medical fall, lowering risk by 20% to 30%. However, even intermittent use of the EF program also decreased the risk of medical falls. Although this finding corroborates previous evidence suggesting that strength and balance exercises, major components of the EF program, are essential to reducing fall and fall injury risk in older adults ,21,22, fThe results were less clear for the impact of the SS program. Unadjusted findings were suggestive of moderate risk reduction, but full adjustment yielded significant reduction only for intermittent users. This risk reduction was smaller than those seen for EF but was in the range of a 10% to 15% reduction in medical falls. However, the finding of significant impacts only for intermittent users runs counter to established findings in the literature, which suggest that consistent physical activity yields the strongest health impacts . This reDespite these limitations in the SS analysis, the magnitude of the association observed for SS participants was smaller than that seen with EF, a more structured program that includes balance and strength exercises that research suggests are critical to reducing fall risk . BecauseEF has routinely scheduled classes multiple times per week and a strong social environment, promoting regular attendance at the EF program over many years. Users of the more free-form and independently driven SS program may be more likely to vary in the amount of use. On the basis of data supplied by each program, aggregate use statistics for this sample in 2011 support this differential attendance pattern. This finding suggests not only that EF users tend to use the program more frequently but also that the use pattern in the sample is more normally distributed (meaning that SS may have few very frequent users skewing the mean use statistic). This differential usage pattern may make the consistent and intermittent categories created for our analyses more problematic for SS, as the consistent category would be less likely to strongly parallel regular use. In short, although these results suggest that the EF program is more successful in reducing the risk of medical falls for this population, the nature of SS as an independently driven program with more sporadic attendance patterns lends itself more to misclassification under the participation definitions used in these analyses and makes conclusions about the program’s association with fall-related outcomes less robust.This study has several limitations. First, it focuses only on falls resulting in medical care, as these appear in the inpatient or outpatient medical record, making it possible to measure without the use of self-report. This outcome definition excludes fall cases for which people do not seek medical attention and any injury truly due to a fall but not reported (and thus not coded) as such in the medical record. Despite this limitation, falls resulting in medical care are of high priority for risk reduction efforts given their adverse personal and societal effects ,27.Although missing data were not an issue for the outcome of interest, some data were missing for certain covariates, primarily race and BMI. Though these missing data resulted in small reductions in sample size for full adjustment models, they are not believed to have limited power. Participation in EF and SS is voluntary and, therefore, inherently self-selected. People who choose to participate in these programs may be systematically different from those who do not in ways that may affect their fall risk. Therefore, the potential for residual confounding remains. No information about engagement in physical activity outside either program was available for users or nonusers. The inability to adjust for baseline physical activity level in either group is a limitation; however, only 6% to 25% of older adults are estimated to regularly engage in the balance training and muscle-strengthening exercises requisite to fall risk reduction ,29, suggDespite these limitations, this study has several strengths. First, all outcomes and comorbidities were based on ICD-9-CM codes in the medical record rather than self-report. This procedure greatly reduces the potential for misclassification of comorbidity and outcome status, lending itself to a higher degree of accuracy in risk estimates. Furthermore, the use of this administrative data allowed for adjustment of many fall-related comorbidities that can be difficult to capture, including a history of gait and balance problems. Additionally, these analyses were based on a large, demographically representative sample, increasing power to detect associations and maximizing the generalizability of findings.The results of this analysis provide evidence that participation in EF is associated with a reduced risk of medical falls. Furthermore, as hypothesized, this relationship shows a consistent pattern in which the strongest protective association was for consistent users of the program. Participation in SS may provide a moderate degree of fall protection, although findings were inconclusive. Overall, results suggest that evidence-based physical activity programs, particularly EF, should be more widely disseminated into communities not only for their general effects on fitness but also for their likely benefits on prevention of fall-related health care use, an important personal and societal outcome.


The American College of Surgeons’ National Surgical Quality Improvement Program (NSQIP) is the first nationally validated, risk-adjusted, outcomes-based program to measure and compare the quality of surgical care across North America. Participation in this program may provide an opportunity to reduce the incidence of adverse events related to surgery.A systematic review of the literature was performed. MedLine, EMBASE and PubMed were searched for studies relevant to NSQIP. Patient characteristics, intervention, and primary outcome measures were abstracted. The intervention was participation in NSQIP and monitoring of Individual Site Summary Reports with or without implementation of a quality improvement program. The outcomes of interest were change in peri-operative adverse events and mortality represented by pooled risk ratios (pRR) and 95% confidence intervals (CI).Eleven articles reporting on 35 health care institutions were included. Nine (82%) of the eleven studies implemented a quality improvement program. Minimal improvements in superficial , deep  and organ space  infections were observed at centers that did not institute a quality improvement program. However, centers that reported formal interventions for the prevention and treatment of infections observed substantial improvements . Studies evaluating other adverse events noted decreased incidence following NSQIP participation and implementation of a formal quality improvement program.These data suggest that NSQIP is effective in reducing surgical morbidity. Improvement in surgical quality appears to be more marked at centers that implemented a formal quality improvement program directed at the reduction of specific morbidities. The Veterans Affairs Surgical Quality Improvement Program (VASQIP), was a program developed in the 1990s to evaluate risk-adjusted surgical quality . As of 2For each patient captured in NSQIP, up to 135 variables are collected and entered into the database, including demographic data, baseline comorbidities, operative information, and 30-day post-operative adverse events and mortality. While there is some variability in case sampling, most hospitals with greater than 1,680 surgical cases per year enter the first 40 eligible cases in each eight-day period. In contrast, hospitals with less than 1,680 cases per year usually submit data from all surgical cases[The information provided to NSQIP is used to identify differences in the incidence of peri-operative adverse events across specialties and between similar-procedure-volume institutions. Institutions are informed of their performance through Individual Site Summary Reports (ISSR) that are generated semi-annually by NSQIP. NSQIP reports include: total cases, number of adverse events, deaths, expected event rate based on pre-operative risk, logistic model observed/expected ratios with 95% confidence intervals , outlier status, and hospital decile rank. Relative deficiencies may be targeted by hospitals for quality improvement and the impact of quality improvement initiatives may be tracked over time using NSQIP reports. Institutions may or may not implement formal quality improvement programs to address sub-standard outcomes[We performed a systematic review and meta-analysis to determine whether participation in NSQIP is associated with a reduction in peri-operative adverse events. We also examined whether simple monitoring of outcomes is sufficient to induce improvements in hospital-specific surgical outcomes, or whether quality improvement initiatives are necessary. We hypothesized that a directed quality improvement program would result in greater adverse event reductions.th 2013 using the search terms NSQIP and National Surgical Quality Improvement Program. All duplicate studies were removed and two reviewers independently screened article titles and abstracts. The reviewers reconciled any disagreements on which full text articles would be obtained for further screening.A comprehensive search of Medline, Embase, and Pub Med was performed . Two medTo be eligible for this review, articles had to report data collected from NSQIP-participating hospitals, and had to present evidence of monitoring of the Individual Site Summary Report or the implementation of a quality improvement program. Included studies compared surgical data before and after commencement of either 1) monitoring the Individual Site Summary Reports (ISSRs) only, or 2) the implementation of a formal quality improvement program in addition to ISSRs. Studies which implemented a formal quality improvement program first identified potential areas for improvement using data provided by their Individual Site Summary Reports. Our primary objective was to determine the degree of surgical quality, defined as the incidence of 30-day morbidities and mortality associated with surgical procedures. We defined formal quality improvement programs as the implementation of protocols or practice guidelines within the hospital with the specific aim of reducing surgical morbidity and/or mortality.The following categories of articles were excluded from this review:(1) Articles not available in English;(2) Studies that did not compare surgical quality data before and after either the monitoring of the NSIQP Individual Site Summary Reports or the implementation of a quality improvement program;(3) Case studies/case series;(4) Conference abstracts;(5) Commentaries, editorials and review articles;(6) Systematic reviews; and (7) Studies which included results from VASQIP patients. Although systematic reviews were not eligible, they were used to identify additional relevant articles.For each article, two reviewers abstracted data using a standardized electronic form. Any disagreements were reconciled by consensus, and if needed, a third party. For studies that reported surgical outcome data over multiple years before and after joining NSQIP, we considered the first year of data presented as pre-quality improvement and the most recent year of data as post-quality improvement implementation. When the number of adverse events was reported as a proportion of the total number of patients, the number of events was calculated by multiplying the total number of patients in the study by the proportion of patients with the adverse event. Publication date, country of study origin, duration of follow-up, and study population size were also collected. Patient characteristics and the type of formal quality improvement program utilized were recorded when available. Outcome data collected included any individually reported adverse event, overall 30-day morbidity, and mortality before and after implementation of the quality improvement initiatives.There are no validated methods for assessing the quality of observational studies included in a systematic review. We therefore conducted an assessment of study quality based on STROBE guidelines for reporting of observational studies.Overall pooled estimates of the risk ratios (pRR) with 95% confidence interval (CI) for each outcome  were calculated using random effects models. In addition, studies were stratified by use of a specific quality intervention or not. No statistical testing was performed to determine the association between quality intervention and adverse events. Funnel plots were generated to assess potential publication bias. All analysis was done using the Comprehensive Meta Analysis Software, version 2.2.064.Of the 1024 titles and abstracts identified by the electronic search, 940 were excluded for being irrelevant or for not meeting our inclusion criteria . A totalIncluded articles were published between January 2010 and January 2013 from hospitals in the United States. Surgical quality data were collected between 2005 and 2011, with specific years varying between studies. Colorectal procedures were the most commonly analyzed surgeries (n = 4), followed by vascular (n = 2), non-specific general surgery (n = 1), otolaryngology (n = 1), non-cardiac (n = 1), intra-abdominal (n = 1) and hepatopancreatobiliary (n = 1) .Nine 82%) of the 11 studies implemented a quality improvement program. Of these, one study used Surgical Care Improvement Project (SCIP) guidelines, while o2% of theThe quality of included studies was evaluated based on an adaptation of STROBE guidelines. All included studies reported on study design, study setting, variables analyzed, statistical methods, outcome data, and summary/interpretation of key findings. Overall, each included study contained at least 60% of the recommended STROBE checklist items .Only one study presented data on 30-day post-operative mortality. In thisTwo studies presented data on 30-day post-operative morbidity (defined as any complication within 30 days of surgery),11. In oNine studies presented data on the incidence of superficial surgical site infections (SSIs), 7 presented deep SSI information, and 6 presented organ/abdominal space infection information Figs –4. ModesTwo studies reported on deep venous thrombosis complications, one which implemented a quality improvement program, and one did not. The study which did not implement a quality improvement programobserved The American College of Surgeons’ National Surgical Quality Improvement Program provides comprehensive and accurate performance feedback to hospitals. However, upon conducting a systematic review of the literature published from NSQIP-participating hospitals, our analysis suggests that implementing a formal quality improvement program may be more effective than merely monitoring surgical outcomes using NSQIP Individual Site Summary Reports. Indeed, in NSQIP hospitals that implemented a quality improvement program, there was a reduction in the incidence of almost all post-operative complications.This review captured studies implementing a broad range of quality programs. All of the seven studies that reported such initiatives for a common post-operative complication of wound infection reported a successful reduction in surgical site infections, 14–19. There are several potential limitations to this comprehensive review. As with all systematic reviews, we are limited by the quality of the published studies and authors may have preferentially reported programs that have shown an improvement, resulting in a publication bias Figs –7. It isMost hospitals within the United States are accredited by the Joint Commission, which requires an intrinsic quality improvement process. This means that the majority of the hospitals in our study had an ongoing improvement program in place prior to joining NSQIP. However, the intrinsic program required by the Joint Commission targets overall patient care improvement within a hospital. There is no identification of potential areas for improvement or areas of weakness at each specific hospital. Quality improvement programs directed at reducing the incidence of specific morbidities or reducing morbidities associated with a specific procedure are likely results of the NSQIP ISSR’s. Lastly, the phenomenon of regression to the mean may explain some of the improvements observed in hospitals that reported on outcomes that had historically performed worse in than similar-volume institutions. However, this effect on NSQIP institutions appears to be minimal, as NSQIP-related improvements were found to be independent from this effect.To our knowledge, this is the first systematic review to attempt to evaluate the effectiveness of the National Surgical Quality Improvement Program in improving post-operative morbidity and mortality. No analysis was performed on mortality rates, as there was insufficient data. Our analysis of morbidity rates suggest that implementation of a formal quality improvement program based on NSQIP feedback was more effective compared to passive monitoring of surgical outcomes generated by NSQIP’s Individual Site Summary reports. These findings have noteworthy implications for hospitals that participate in NSQIP but have not yet adopted quality improvement programs to address deficiencies. Establishing and implementing outcome-directed quality improvement programs may be of significant benefit to NSQIP-participating hospitals that aim to improve surgical quality by reducing the incidence of specific post-surgical complications, however it is not known if this translates to overall surgical quality improvement.S1 PRISMA Checklist(DOCX)Click here for additional data file.S1 File(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Those who pay for health care are increasingly looking for strategies to influence individuals to take a more active role in managing their health. Incenting health plan members and/or employees to participate in wellness programs is a widely used approach.In this study, we examine financial incentives to health plan members to participate in an online self-management/wellness program—US $20 for completing the patient activation measure (PAM) and an additional US $40 for completing 8 learning modules. We examined whether the characteristics of plan members differed by the degree to which they responded to the incentives. Further, we examined whether participation in the wellness program was associated with improvements in PAM scores and changes in health care utilization.This retrospective study compared demographic characteristics and change in PAM scores and health utilization for 144,625 health plan members in 2011. Four groups were compared: (1) those who were offered the incentives but chose not to participate , (2) those who received the initial incentive (PAM only) but did not complete 8 topics (n=7099), (3) those who received both incentives (completing 8 topics but no more) (n=2693), and (4) those who received both incentives and continued using the online program beyond what was required by the incentives (n=6249).P<.001).In multivariate regression models, those who used the online program (8 topics or beyond) increased their PAM score by approximately 1 point more than those who only took the PAM and did not use the wellness program (P<.03). In addition, emergency department visits were lower for all groups who responded to any level of the incentive as compared to those who did not (P<.01). No differences were found in other types of utilization.The vast majority of health plan members did not participate in the program . Of those who participated, only 7099 of 16,041 (44.25%) completed the PAM for the first incentive, 2693 (16.79%) completed 8 topics for the second incentive, and 6249 (38.96%) received both incentives and continued using the program beyond the incentive requirements. Nonparticipants were more likely to be men and to have lower health risk scores on average than the other three groups of participants (The incentive was not sufficient to spark most health plan members to use the wellness program. However, the fact that many program participants went beyond the incentive in their use of the online wellness program suggests that the users of the online program found value in using it, and it was their own internal motivation that stimulated this additional use. Providing an incentive for program participation may be an effective pathway for working with less activated patients, particularly if the program is tailored to the needs of the less activated. Patients are key in determining their health care outcomes. They are the ones that carry out the day-to-day care management tasks and decide whether or not to make the necessary lifestyle adjustments to improve their health. Without patients’ participation, even with best practices on the part of health care providers, it is very difficult to achieve optimal health outcomes . To contIncenting health plan members and/or employees to take Health Risk Appraisals (HRAs) is a widely used approach. The HRAs typically include questions about health behaviors and provide the individual feedback with a list of behavioral changes they could make to improve their health. A 2013 study estimated that 55% of large employers offered an HRA to employees and 54% of those provided an incentive to complete it [Studies indicate that incentives are most effective at achieving behavior change that requires a single activity, such as receiving a vaccination or a screening, as compared to actions that require ongoing engagement ,7. ThereHowever, there are fewer concerns about the use of incentives to complete an HRA. There is evidence that incentives do yield greater participation in HRAs ,10. The Might an incentive to participate in a wellness/self-management program undercut internal motivation? One way to examine this question is to assess the impact of an incentive on program participation and on changes in patient activation. Patient activation is defined as having the knowledge, skill, and confidence to manage one’s own health and health care. Individuals who are more activated, are typically more motivated to effectively manage their health. While there are alternative ways to define activation or engagement, there is only one validated measure, the 13-item Patient Activation Measure (PAM). Multiple studies show that people who score higher on PAM are more motivated to improve their health. The PAM score is predictive of most health behaviors, many clinical indicators, and the use of costly health care services ,13. If PMost of the research on the efficacy of health program participation is based on programs offered at the worksite or programs offered in the community. Because wellness and self-management support programs are now also being offered as online programs, they are no longer limited to these venues. Studies indicate that there is some positive impact of self-directed online self-management programs. For example, Solomon and colleagues, evaluating the impact of an online program among chronic disease patients, found that the program increased patient activation an average of 4 points  more than did the control group . SimilarIn this study, we examine the impact of providing financial incentives to commercially insured health plan members to participate in an online self-directed self-management/wellness program. We assess the impact of a US $20 financial incentive to take a PAM assessment and a second US $40 incentive to complete 8 user-selected learning modules or topics in the online program and to set 8 behavioral goals.Our specific research questions were: (1) What are the characteristics of those who respond to the two levels of financial incentives and those who do not respond at all to the incentive?; (2) What are the characteristics of those who participate beyond the financial incentive in using the wellness/ self-management program? How much further beyond the incentive does their participation go?; and (3) What is the impact of participating in the online program on patient activation and health care utilization?In 2011, commercially insured members of a large health plan were offered a US $20 incentive to go online to take the PAM questions. They were given a further US $40 incentive to complete 8 topics and set behavioral goals in the online self-directed wellness/self-management program. The participant could choose the topic areas and behavioral goals they wanted to focus on. Thus there are four groups in the study: (1) nonparticipants in the online program, (2) those who only completed the PAM and received the first incentive, (3) those who completed the PAM and 8 topics and received the first and second incentive, and (4) those who received both incentives and continued using the online program beyond the required number of topics.Participants were incented to go to an online program that assessed their level of patient activation and to participate in a self-directed online wellness/self-management program. All the topics and suggested goals that users are able to select from in the online program are tailored to the users’ level of activation. The program tailors to the 4 levels of activation, from low (level 1) to high (level 4). Users can choose what they want to focus on, from disease specific self-management to wellness activities. The lowest activation level topics start at a very foundational level. The program breaks information down into small bits and suggests action steps or goals that less activated individuals are likely to succeed at, but may not be clinically meaningful at this point . The approach is based on the theories of behavioral activation that show motivation will follow action . The strThis retrospective study compared demographic characteristics and change in PAM and health utilization for four groups of health plan members in 2011: (1) those who were offered the incentives but chose not to participate in the online wellness program, (2) those who received the initial incentive (PAM only) but did not complete 8 topics and goals, (3) those who received both incentives , and (4) those who received both incentives and continued using the online wellness program beyond what was required by the incentives. The study protocol (designated as 12012011.001), was approved by the internal review boards (IRB) of the University of Oregon and George Washington University.The total population eligible for participation was 144,675 health plan members who were adults and had consistent coverage over the study period. Given that 128,634 people declined to respond to the incentive (88.91% of the eligible population did not use the online wellness program), we selected a random sample of 500 of these nonparticipating plan members to represent the nonparticipant group. The other 3 groups included all of those who chose to respond to the incentives and individually decided what level of incentive they would pursue . ObservaThe study population excluded those plan members who were recruited for a special program that involved telephonic coaching because of serious health issues. We excluded this group whether they participated in the telephonic coaching or not. These excluded patients were sicker with more chronic conditions and higher levels of hospitalization and emergency department use than the larger population of plan members.The independent variable in this study was the extent to which the eligible health plan member used the online wellness program .Dependent variables included the PAM and health care utilization measures. The PAM consists of 13 items that form an interval level, unidimensional, Guttman-like scale. The measure has been shown to have strong psychometric properties. The PAM items are statements on confidence, beliefs, knowledge, and skills about managing one’s health, which respondents can answer with degrees of agreement or disagreement . The measure is scored on a theoretical 0-100 scale with most patients falling in the 35-95 point range. Four levels of activation have been previously identified, reflecting a developmental progression from passive receipt of care toward greater activation ,18.Utilization data were derived from claims data. Primary care, specialty care, emergency department (ED) use, and hospital stays were the utilization variables assessed. For primary and specialty care visits, we examined the actual number of visits in the pre and post period. For the ED and hospitalizations, we examined whether or not there were any visits.In our analyses we also examined and controlled for demographic and health variables. Average income for the member’s zip code is used as a proxy for member’s income in the analysis. The Adjusted Clinical Groups (ACG) score is a measure of illness severity and is included in the analysis to control for health status differences in the study groups.We first examined the demographic and health characteristics of the four groups, using baseline data from the last 6 months of 2010, using chi-square and analysis of variance (ANOVA) tests. Additionally, we used descriptive statistics to examine how much use of the online wellness program each of the four groups engaged in.Then, we examined bivariate relationship between the changes from pre- to post- in the outcome measures (PAM scores and utilization) using follow-up data collected from the first 6 months of 2012. Finally, we developed multivariate analyses to examine the relationships between group participation level and the post-period outcomes, controlling for the pre-period outcome value, demographic characteristics, and ACG risk score. The sample size for Patient activation in the follow-up is reduced to 46% of the original sample size because not all members completed the pam again in 2012. All analyses weight the observations by the inverse probability of selection and adjust the standard errors accordingly.The people who participated in the four different levels of the online wellness program had different demographic characteristics . The groThere were also differences in the groups in terms of their health status. Those who responded to the incentive or went beyond the incentive had slightly higher ACG risk scores than those not responding to the incentive. However, those not responding to any of the incentives were more likely to have diabetes and hypertension than those who responded to the incentive or went beyond the incentive.It is interesting to note that those members who went beyond the incentive in their use of the online program, had usage considerably beyond the requirements of the incentive, viewing on average over 20 topics ; 69.88% We also looked at baseline PAM level as a predictor of how members responded to the incentive. There were no significant differences in the groups in primary care, specialty care, or hospital visits in either the baseline or post period. However, there were differences in the groups in the post period for ED visits, with highest rates for nonparticipants. It is notable that ED visits increased for all groups from the baseline to the post period, but the change was not significantly different among the groups.Only about 11% of those offered an incentive to participate in an online wellness program participated in it. Those who participated in any level of the incentive were more likely to be female, slightly older, and less likely to have diabetes, hypertension, and depression than those who did not respond. We did not have PAM data on the group who did not respond to the incentive; however, among those who did respond, those with slightly higher scores at baseline were more likely to go beyond the incentive in using the online program. That is to say, the incentive seemed to be most effective in stimulating participation among those who were slightly more activated and in better health. This is consistent with a prior study indicating that it is the more activated who are more likely to participate in offered health programs . It is aContrary to concerns raised by some investigators, the findings do not indicate that the incentive to participate in the online program undermined or supplanted internal motivations to manage one’s own health . For thoThe findings break new ground in this research arena, in that most evaluations of wellness programs and incentives do not measure the impact of the program on the individual’s knowledge, skill, and confidence in managing their health (activation). By including activation in the analysis, the findings help to elucidate who these programs are reaching  and who they are helping.At the same time, the findings are limited by the fact that we did not have PAM data on those who chose not to participate in the incentive program, nor on participants who did not complete a PAM in 2012 as well as 2011. They are also limited by the design of the study. Because participants were not randomly assigned to the four study groups, we cannot rule out that the findings are the result of some other, unmeasured, factor. Finally, because the study was conducted within one health plan in one geographic region and only included insured adults, the generalizability of the findings are limited.The findings indicate that participantion in the program resulted in a small decline in the PAM scores of those who, at baseline, were in the highest level of activation. It may be that the intervention was not as useful or appropriate for these participants. However, the fact that program participation appeared to stimulate increased activation in those who were the least activated at baseline is a promising finding. These findings are consistent with the findings from other intervention studies that show that the least activated gain the most from an intervention ,15,20. RWhile the incentive was most effective in recruiting higher activated members, less activated members also responded to the incentive. Providing an incentive for program participation may be an effective pathway for working with less activated patients, particularly if the program is tailored to the needs of the less activated. However, it is important to note that the vast majority of health plan members did not respond to the incentive at all.With increased costs and an aging population base, strategies to effectively manage population health is a global concern. This study adds to our understanding of who is likely to respond to incentives and how participation in the programs may influence behaviors and health care utilization.