Abstract
Background:
Primary care practices can help patients address obesity through weight loss, however, there are many barriers to doing so. This study examined weight management services provided and factors associated with higher reported provision of services.
Methods:
A survey was given to practice members in 18 primary care practices in a Colorado-based health system. The survey assessed weight management services to determine the amount and type of weight loss assistance provided and other factors that may be important. We used descriptive statistics to summarize responses and linear regression with generalized estimating equations to assess the association between the practice and practice member characteristics and the amount of weight management services provided.
Results:
The overall response rate was 65% (257/397). On average, clinicians reported performing 70% of the services, and when grouped into minimal, basic, and extensive, the clinicians on average performed 87%, 78%, and 69% of them respectively. In a multivariable model adjusted for demographics, factors associated with performing more services included perception of overall better practice culture (more team-ness, less chaos, better change culture) (p=0.004) and perception of weight management implementation climate (support for, recognition and expectation to support weight loss) (p=0.07). Not associated in bivariate analyses were practice-level measures and clinician-specific scores for work satisfaction, and satisfaction with and assessment of appropriateness for practice provision of weight loss services.
Conclusions:
Practice-associated factors such as culture and implementation climate may be worth examining to understand how to implement weight management in primary care.
Introduction
Obesity is a critical public health issue contributing to the leading causes of death in the US.1 Primary care serves as a common setting for addressing prevention and treatment of disorders caused by obesity, such as diabetes and hypertension, and many patients note weight management as a top priority.2–6 There are many evidence-based treatments available for patients with obesity, including medications, diet and nutrition counseling, behavior change support, and surgery; however, these treatments are often not implemented in primary care.7–10 Although clinicians note the high importance of treating patients’ obesity as a standard of care,11 barriers include insufficient clinician training/familiarity with obesity treatment, challenges with access for/prioritization of obesity treatment, lack of workable structures, workflows and resources, and low/no reimbursement for direct provision of obesity care without other comorbidities.12–15 Patients also face many barriers including stigma, lack of motivation, ability to successfully lose weight, and cost and lack of access to services.16–19 However, recent research reveals that practices can, in fact, deliver obesity care if the barriers are identified and addressed.12, 20 With structures and supports in place, patients are achieving weight loss outcomes that have potential to slow the public health trends toward increasing obesity and the resulting comorbid conditions.21–26
Understanding more about what motivates primary care practice members toward providing obesity care and what steps could be taken to overcome perceived barriers is needed. This study reports on a survey completed by practice members at 18 diverse primary care practices in Colorado regarding their perceptions of the importance of obesity care in their practice, what services are currently provided, satisfaction with the care provided, challenges with providing obesity care, and interests in overcoming these challenges. These data add to the growing knowledge base about overcoming implementation challenges to address this public health problem.
Methods
PATHWEIGH Study
The data for this report were gathered as part of a National Institutes of Health (NIH)-funded clinical trial on implementation of PATHWEIGH. PATHWEIGH strives to be a comprehensive approach including electronic medical record tool sets, weight management training for clinicians and specialist consultation support. This study uses a type 1 hybrid effectiveness-implementation stepped-wedge cluster randomized design to compare patient-specific and implementation outcomes of a weight management intervention to standard of care in 57 primary care clinics in Colorado.27 This paper reports on an analysis of the baseline surveys given to practice members at the primary care practices prior to the start of the intervention for the first cohort of 20 clinics. Two surveys were used: (i) a practice survey completed for each practice, and (ii) a practice member survey that was administered to clinicians (i.e., physicians and advanced practice providers including physician assistants and nurse practitioners), other providers, and staff within each practice.
Survey Instruments
The practice survey (Supplement A) was developed to identify practice-level characteristics and behaviors. The purpose of the survey was to provide basic information on the characteristics of the practice including the patient population, location and type, quality improvement efforts and current weight management services. It assessed the capacity of the clinic for implementation of a weight loss intervention by identifying the number of staff and clinicians, the current treatment and billing practices regarding weight management, and whether the practice was actively engaged in quality improvement practices. No standardized scales were used in this survey.
The practice member survey (Supplement B) was developed to assess individual practice members’ backgrounds and demographics, current perceptions of weight management importance and climate for implementation, current weight management activities provided for patients, and clinicians’ background and experience with providing weight management and interest in learning more about providing weight management. Several scales were utilized to assess overall practice culture at the individual and practice level as well as burnout and work satisfaction of practice members. These scales were not related to weight management in the practice but intended to assess the overall milieu of the practice.
The Practice Culture Assessment Scale included 22 Likert scale items (1=Strongly disagree to 5=Strongly agree) that were used to compute scores for the subscales of Change Culture, Work Culture, and Chaos.28–32 Subscale scores ranged from 0 to 100 and higher scores represented more of the concept. An Overall Culture score was also computed by averaging the scores of the three subscales (reverse coding the Chaos subscale), where a higher score indicated stronger practice culture. Change Culture items focus on how the practice approaches collaborative quality improvement, problem resolution, and change management. Work Culture items assess how practice members work together for a pleasant and productive practice environment and high quality care, and Chaos items assess instability, disruption, and disorganization in the practice.33 Practice culture is often found to be related to the ability of the practice to implement new initiatives and may be useful in understanding implementation of weight management efforts.34, 35
Burnout and work satisfaction was assessed by asking practice members three questions about: their level of burnout (1=No burnout to 5=Complete burnout),36, 37 if they felt personally rewarded by their work (1=Not rewarded to 5=Fully rewarded), and if they were satisfied in their current practice (1=No satisfaction to 5=Complete satisfaction).38 These attributes of employees can have an impact on their interest and ability to take on new initiatives such as a weight management intervention.39–41 An overall Work Satisfaction score was computed by averaging the scores across the domains (reverse coding burnout), where a higher score indicated that the respondent had greater satisfaction from their work.
Additional measures were used to determine current practices and readiness for weight management as an intervention, specifically. To assess current practices in the provision of weight management, clinicians were presented with 19 weight management services or tasks and were asked to indicate the frequency with which they provided the services (not at all, sometimes, very often), which were then dichotomized (not at all vs. at least sometimes) for analysis. Based on divisions within how weight management is likely to be categorized in primary care practice, three groupings were created a priori based on what level of support for weight management they provided. Group 1 was minimal and included essentially identification of weight as an issue and brief one-time advising to patients. Group 2 was basic weight management treatment that was short-term and limited in options. Group 3 was comprehensive support characterized by more utilization, more in-depth treatment options, and ongoing care over time including repeated visits and tracking. Questions related to direct provision of weight management services were only asked for respondents who had indicated that they were medical providers.
An Implementation Climate Scale for interventions was utilized to address the ability of a practice to effectively implement a weight management intervention in the primary care practice setting.42 It included six questions within three constructs (Expected, Supported, Rewarded) with Likert scale responses from 1=Not at all to 5=To a great extent. An average score was computed for each individual, and then averaged within a practice to present a practice-level climate score ranging from 1 to 5. Higher values indicate a better organizational climate for weight management, with a range from 1 to 5. Intraclass correlation coefficient (ICC) was estimated, where values closer to 1 indicate that climate perception are more strongly shared among practice members.
Data Collection
The practice survey was completed by a single practice administrator at each of the 20 clinics. The practice member survey was administered to all clinicians and staff at each of the practices. The surveys were implemented in REDCap and were pretested with non-study practice clinicians and research team members to ensure that the survey questions were concordant with the study team’s research questions. A personalized link was distributed by email to all practice members at the 20 practices. To increase response to the survey, respondents were compensated with a $10 gift card and two reminders were sent 3 weeks apart. Practices also received other compensation for this and other data collection efforts.
Data Analysis
Descriptive statistics (means, medians, frequencies, percentages) were used to summarize responses. Spearman correlations were used to study relationships between the scale scores. We used linear regression to assess the association between the clinician characteristics and the amount of weight management provided. To account for potential correlation between survey respondents within the same practice, we used a generalized estimating equation approach with an independence covariance structure. Respondent demographics (age, gender, years of experience) and variables that had p<0.1 in univariable analyses were included in a multivariable model. All analyses were performed using R version 4.0.4.
Results
Although all practices completed some surveys, two practices were omitted from the analysis because they declined to participate in the study. Among the remaining 18 clinics, the overall response rate was 64% (=254/399), with an average response rate within practice of 68% among all practice members and 66% among clinicians, specifically. Of the respondents, 70 (28%) were clinicians, 8 (3%) were other providers (e.g., behavioral health, pharmacy), 120 (47%) were clinical support staff, and 54 (21%) were administrative staff. Compared to the other practice member roles, clinicians had the highest proportion of males (47%), those aged over 45 (58%), and those with a part-time position (37%) (Table 1). Clinicians also had the highest median years of experience (20; IQR: 10–25). A large proportion of respondents (85%) indicated that they had personally wanted to or had tried to lose weight.
Table 1.
Respondent characteristics, Overall and by Role
| Characteristic | N | Overall, N = 254 | Clinician, N = 70 | Other Medical Provider, N = 8 | Staff/Other, N = 176 |
|---|---|---|---|---|---|
|
| |||||
| Gender | 254 | ||||
| Female | 212 (84%) | 37 (53%) | 8 (100%) | 167 (96%) | |
| Male | 40 (16%) | 33 (47%) | 0 (0%) | 7 (4%) | |
| Age | 253 | ||||
| Under 30 | 50 (20%) | 0 (0%) | 2 (25%) | 48 (27%) | |
| 30–45 | 110 (43%) | 29 (41%) | 4 (50%) | 77 (44%) | |
| 46–60 | 81 (32%) | 38 (54%) | 1 (12%) | 42 (24%) | |
| Over 60 | 12 (5%) | 3 (4%) | 1 (12%) | 8 (5%) | |
| Years of Experience | 253 | 11 (5, 20) | 20 (10, 25) | 6 (4, 8) | 10 (4, 19) |
| FTE | 250 | ||||
| Full-time (90% or higher) | 211 (84%) | 43 (63%) | 6 (75%) | 162 (93%) | |
| Part-time (less than 90% total) | 39 (16%) | 25 (37%) | 2 (25%) | 12 (7%) | |
| Experience with personal weight loss | 253 | 214 (85%) | 54 (77%) | 6 (75%) | 154 (88%) |
n (%); Median (IQR); Clinicians include physicians and advanced practice providers including physician assistants and nurse practitioners
Current status of providing weight management
From the practice survey, out of the 18 clinics, only six (33%) indicated that their clinicians provided visits specifically for weight management, using brief advice and/or counselling to patients during these visits. Only four (22%) additionally had follow-up visits. In contrast, 15 (83%) practices indicated that their clinicians or other providers provide brief advice on weight loss during office visits for other conditions or specified purposes. A higher proportion of practices indicated that they made referrals for bariatric surgery (67%), referrals to weight loss programs (50%), prescribed weight loss medication (44%), and provided patient education material on weight loss (39%). No practices indicated that they provided medical supervision for meal replacement programs, information about insurance coverage of obesity treatments, or group weight loss programs on-site. For nine practices (50%), the practice administrator was not aware of how weight loss services or visits were billed/paid for in their practice, and most (83%) did not know if their practice had experienced any difficulties with billing for obesity services from any payer.
From the practice member survey, clinicians were surveyed about their use of 19 listed services for weight management. Of the 19 listed services for weight management (Figure 1), on average clinicians indicated that they performed 73% (IQR: 63%−83%) of the services. Of the services in Group 1 (minimal), 2 (basic), 3 (superior), on average clinicians performed 87%, 68%, and 69% of the services, respectively, with 97% of providers indicating that they provide at least one service in each group. There were 36 (55%) providers that provided all services in Group 1, three (5% of total) that provided all services in Groups 1 and 2, and the same three that provided all 19 of the services. None of the clinicians indicated that they had obesity treatment certification, 40 (58%) had never received additional continuing medical education (CME) on how to provide obesity treatment or weight loss, and 25% said that they had received this CME but that it was not within the last 3 years.
Figure 1.
Percentage of clinician respondents that indicated that they provided each of the weight management services. Groups indicate the level of weight loss services conducted (1: minimal, 2: basic, 3: superior)
Perceptions about providing weight management
Clinicians and other medical providers were asked about their satisfaction with their practice’s ability to help patients with weight management, for which 38% indicated that they were somewhat satisfied, 29% said they were not satisfied, and 21% responded that it depended on the patient. They had an average score of 4.3 (IQR: 4–5) on a Likert scale question (1=Totally disagree to 5=Totally agree) asking about agreement with the statement that weight loss for patients with overweight or obesity is something that a primary care practice should provide as part of comprehensive primary care. When provided with a list of concerns about making weight management a priority (Table 2), the most reported concern by clinicians was that they didn’t have time in their schedule (70%). For clinical support staff, their reasons were that they didn’t have weight management workflows set up in their practice (46%), which was also indicated as a concern by administrative staff (31%).
Table 2.
Top concerns for providing weight management, by Role
| Characteristic | Clinician, N = 70 | Other Medical Provider, N = 8 | Staff/Other, N = 176 |
|---|---|---|---|
| I/our providers don’t have time in their schedule | 49 (70%) | 4 (50%) | 48 (27%) |
| We don’t have weight management workflows set up in our practice | 38 (54%) | 2 (25%) | 73 (41%) |
| I/our providers don’t know how | 30 (43%) | 0 (0%) | 15 (9%) |
| I/our providers don’t feel like patients will be able to successfully change and lose weight | 27 (39%) | 1 (12%) | 19 (11%) |
| We don’t have time to set up a new program | 21 (30%) | 1 (12%) | 17 (10%) |
| We won’t get paid/will lose money | 14 (20%) | 0 (0%) | 7 (4%) |
| Our patients will not want their providers to bring up weight loss with them | 10 (14%) | 2 (25%) | 33 (19%) |
| I/our providers are not interested in providing weight management | 6 (9%) | 0 (0%) | 10 (6%) |
| None of the above are concerns | 5 (7%) | 2 (25%) | 59 (34%) |
| Other | 4 (6%) | 0 (0%) | 9 (5%) |
Climate for implementing weight management
In the practice survey, all of the 18 practices indicated that they had quality improvement activities happening in their practice. Most practices (67%) indicated that they had a practice leader who drives forward quality improvement. Many (61%) also had a process for identifying quality improvement goals and tracking progress towards goals. More than half (56%) of the practices indicated that they had at least some or great success when quality improvement efforts were attempted in their practice, and 33% indicated that it varied by the specific effort.
In the practice member surveys, respondents completed a scale assessing climate for implementing weight management in their practice. The median Implementation Climate Scale for weight management across the sites was 2.4 (IQR: 2.2–2.7; range: 1.9–3.1), which indicates a moderate climate for performing weight loss management. We assessed the reliability of this practice-level construct in our sample and found that within a practice there was variability in the responses of practice members (ICC=0.34). There was moderate positive correlation (rho=0.27) between the individual and their practice-level measures of implementation climate. There was moderate negative correlation (rho=−0.10) between implementation climate at the practice and the number of quality improvement initiatives occurring in the practice, indicating that practices with more QI activities happening had a lower implementation climate for weight management.
For the practice culture (not specific to weight management), the respondents overall had high Change Culture (median: 75; IQR: 65–82.5), moderate Work Culture (median: 59.4; IQR: 50–68.8), and low Chaos (median: 31.3; IQR: 18.8–50). The Chaos subscale had the greatest variability across the different practices, with median Chaos score within practices ranging from 18.8–56.3. The overall Practice Culture was moderate (median: 66.7; IQR: 55.6–76.3).
For the three domains assessing burnout and work satisfaction, 40% of respondents indicated experiencing at least some burnout, the majority of respondents (83%) agreed/strongly agreed that they felt that their work was personally rewarding, and most respondents (77%) agreed/strongly agreed that they were satisfied in their current practices. Clinicians experienced a greater sense of burnout (59% indicated at least some burnout), felt less rewarded (71% agreed/strongly agreed), and were less satisfied (64% agreed/strongly agreed) than the other roles. There was strong positive correlation (rho=0.55) between individual-level perception of overall Practice Culture and their Work satisfaction score.
Learning about weight management
The vast majority of clinicians (96%) indicated that they would be interested in learning more about at least one of the presented weight management topics. The highest ranked topics were recommendations about diet and eating plans and organizing workflows to accommodate weight management. Of the suggested ways to learn about weight management, 69% indicated that they would like to learn using a single two-hour e-learning module and get CME credit, 53% wanted someone to come to the practice to provide information, 41% wanted resources in a program like UpToDate (a subscription-based online clinical reference), and 33% wanted to be able to call another clinician experienced in weight management to ask questions.
Factors associated with the provision of weight management
Using regression analyses with a GEE framework to account for clustering, we studied what clinician and practice factors contribute to how much weight management is provided. We define this outcome as the total number of weight management services selected from the list of 19 services and a free-text field for “Other” (range: 0–20). In bivariable analyses (Table 3), being female, individual-level perception of practice culture and individual-level perception of implementation climate were associated (p<0.05) with providing more services. In a multivariable model adjusted for respondent age, gender, and years of experience (Table 3), the mean number of services provided by clinicians was greater for women (p<0.001), those aged 45 years or younger (p=0.07), and those with a better perception of their practice’s change culture (p=0.004) and better implementation culture (p=0.07).
Table 3.
GEE results for association of clinician and practice factors with amount of weight care management provided (n=63).
| Unadjusted | Adjusted2 | |||||
|---|---|---|---|---|---|---|
| Characteristic | Estimate1 | SE | P-value | Estimate1 | SE | P-value |
| Clinician-level | ||||||
| Male (Ref: Female) | −1.79 | 0.55 | 0.001 | −2.04 | 0.49 | <0.001 |
| Age >45 (Ref: ≤45) | −0.17 | 0.70 | 0.80 | −1.42 | 0.78 | 0.07 |
| Years of experience 6–15ys (Ref: ≤5ys) | −0.50 | 0.89 | 0.57 | −0.43 | 0.99 | 0.66 |
| ≥15ys (Ref: ≤5ys) | −0.04 | 1.20 | 0.97 | 0.72 | 1.17 | 0.53 |
| Practice culture | 0.06 | 0.02 | <0.001 | 0.05 | 0.02 | 0.004 |
| Implementation climate | 1.33 | 0.60 | 0.03 | 1.11 | 0.61 | 0.07 |
| Work satisfaction | 0.41 | 0.41 | 0.31 | − | − | − |
| Satisfaction with practice provision of weight management (scale from 1 to 5) | −0.17 | 0.19 | 0.36 | − | − | − |
| Appropriateness for practice provision of weight management (scale from 1 to 5) | −0.11 | 0.59 | 0.85 | − | − | − |
| Practice-level | ||||||
| # Quality improvement activities conducted | −0.17 | 0.14 | 0.23 | − | − | − |
| Practice Culture | 0.04 | 0.06 | 0.49 | − | − | − |
| Implementation Climate | −0.97 | 1.45 | 0.50 | − | − | − |
| Joy and Burnout | 0.27 | 1.38 | 0.85 | − | − | − |
Coefficient estimates correspond to a unit increase in the mean number of services provided for a one unit/level increased in the predictor;
The multivariable model is adjusted for respondent demographics and variables that had p<0.1 in the univariable analyses; SE=robust standard error.
Discussion
In this study of weight management efforts, we found clinicians reported providing many services already such as identifying weight as a health issue, providing education on weight and its effects on health, referring to other services for weight loss and providing education and support for weight loss efforts. However, few clinicians reported providing ongoing care for weight management such as using ongoing tracking and other clinical management. This sample of clinicians and other practice members did not report a high level of satisfaction with the assistance they are currently providing in this area although there was a high level of interest in learning more and support for providing weight management as a standard of care.
These results also make clear the importance of contextual factors in association with services provided by clinicians for weight management. Practice culture and gender were significant factors related to the total number of weight management services. Higher implementation climate for weight management and younger age (<=45 years old) were marginally associated (p=0.07) with providing additional weight management services. This indicates that practices could improve in the culture for implementation of weight management by receiving more recognition and support (elements of implementation climate) for providing weight management services. Support could be in the form of removal of common barriers noted such as not having enough time or not having workflows set up for weight management. Creating a supportive culture for weight management could also look like offering recognition and encouragement of clinicians learning the most effective approaches for treatment of obesity or offering visits prioritized on weight. Additionally, having dedicated staff who champion the use of services that promote weight management could also contribute to improving the practice environment with support for weight management.43 Supportive culture as an element of implementation is a consistent with the abundant literature on other practice improvements in primary care such as medical home transformation.34, 44, 45
These results are consistent with others previous research on the existence of barriers to implementation of weight management services but extend understanding to why these barriers exist. The practice survey found that, even though all of these practices had support for quality improvement, this support varied. Lack of support for quality improvement could thwart efforts for any type of quality improvement effort.46 However, we also found that practices with a larger number of ongoing quality improvement projects were more likely to have a less positive implementation climate for weight management and less weight management services provided by its clinicians. This suggests that in these practices their priorities were already aligned elsewhere and/or that they lack capacity to take on new initiatives. This is consistent with previous research that priority and capacity are both important factors to implementation47. Realigning priorities at the practice level could overcome this challenge by becoming informed on the benefits that weight loss could have for many patient metrics such as HEDIS.
One area our results differed from others was the financial impact of weight management services. Lack of reimbursement is a common barrier, however, this was not stated as such in our study. “We won’t get paid/will lose money” was selected as a barrier by only 20% of clinicians, 0% of other providers and 4% of staff. We wonder if in these health system practices, practice team members are insulated from the financial aspects of billing and coding by having system level support for this area rather than being more directly involved themselves. In terms of weight management services in our list, “Complete coding or billing to provide weight prioritized visits” was only answered by 27.3% of clinicians. Perhaps many clinicians provide one-time advice and assistance and simply use billing under other conditions using standard evaluation and management (E&M) codes. This could have important implications for implementation aspects of getting more adoption of these services in primary care.
Limitations include that these data represent the responses of practice members in one health system in one state. Although the practices were geographically dispersed and represent different patients populations, they may not represent all primary care practices nationally. The results may have been different if the full sample had completed the survey; results may be biased toward those more interested or available to comment on the topic of weight management.. These data were collected during the COVID-19 pandemic (March-June 2021), which may have influenced response rates and results given other priorities at the time and the need to administer the surveys all online.
Conclusion
Providing more assistance with weight loss is needed in primary care to address the rising rates of overweight and obesity in the U.S. The study illustrates factors that may make implementation of weight management a challenge and point to solutions for addressing this issue. Further research should investigate if interventions addressing the challenges directly is successful in greater attention on weight management and thus results for patients’ health status in terms of prevention of obesity-related comorbidities.
Supplementary Material
Funding:
National Institutes of Diabetes, Digestive and Kidney Diseases (NIDDK; grant # 1R18DK127003
Footnotes
Conflicting and Competing Interests: none
Contributor Information
Krithika Suresh, Colorado School of Public Health Department of Biostatistics & Informatics.
Emileigh Willems, Colorado School of Public Health Department of Biostatistics & Informatics.
Johnny Williams, II, University of Colorado Department of Family Medicine.
R. Mark Gritz, University of Colorado Department Medicine – Division of Health Care Policy Research; University of Colorado Adult & Child Center for Outcomes Research & Delivery Science (ACCORDS).
L. Miriam Dickinson, University of Colorado Department of Family Medicine.
Leigh Perreault, University of Colorado Department Medicine – Endocrinology/Metabolism/Diabetes.
Jodi Summers Holtrop, University of Colorado Department of Family Medicine; University of Colorado Adult & Child Center for Outcomes Research & Delivery Science (ACCORDS).
References
- 1.Centers for Disease Control and Prevention. Leading Causes of Death. Accessed January 31, 2022. https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm
- 2.Semlitsch T, Stigler FL, Jeitler K, Horvath K, Siebenhofer A. Management of overweight and obesity in primary care-A systematic overview of international evidence-based guidelines. Obes Rev. Sep 2019;20(9):1218–1230. doi: 10.1111/obr.12889 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Tronieri JS, Wadden TA, Chao AM, Tsai AG. Primary Care Interventions for Obesity: Review of the Evidence. Curr Obes Rep. Jun 2019;8(2):128–136. doi: 10.1007/s13679-019-00341-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Hessler DM, Fisher L, Bowyer V, et al. Self-management support for chronic disease in primary care: frequency of patient self-management problems and patient reported priorities, and alignment with ultimate behavior goal selection. BMC Fam Pract. Aug 29 2019;20(1):120. doi: 10.1186/s12875-019-1012-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Ahern AL, Boyland EJ, Jebb SA, Cohn SR. Participants’ explanatory model of being overweight and their experiences of 2 weight loss interventions. Ann Fam Med. May-Jun 2013;11(3):251–7. doi: 10.1370/afm.1446 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Abshire DA, Gibbs S, McManus C, Caldwell T, Cox A. Interest, Resources, and Preferences for Weight Loss Programs among Primary Care Patients with Obesity. Patient Educ Couns. Sep 2020;103(9):1846–1849. doi: 10.1016/j.pec.2020.04.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Dietz WH, Baur LA, Hall K, et al. Management of obesity: improvement of health-care training and systems for prevention and care. Lancet. Jun 20 2015;385(9986):2521–33. doi: 10.1016/s0140-6736(14)61748-7 [DOI] [PubMed] [Google Scholar]
- 8.Bleich SN, Pickett-Blakely O, Cooper LA. Physician practice patterns of obesity diagnosis and weight-related counseling. Patient Educ Couns. Jan 2011;82(1):123–9. doi: 10.1016/j.pec.2010.02.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Stanford FC, Johnson ED, Claridy MD, Earle RL, Kaplan LM. The Role of Obesity Training in Medical School and Residency on Bariatric Surgery Knowledge in Primary Care Physicians. International journal of family medicine. 2015;2015:841249. doi: 10.1155/2015/841249 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Yates EA, Macpherson AK, Kuk JL. Secular trends in the diagnosis and treatment of obesity among US adults in the primary care setting. Obesity (Silver Spring). Sep 2012;20(9):1909–14. doi: 10.1038/oby.2011.271 [DOI] [PubMed] [Google Scholar]
- 11.Luo Z, Gritz M, Connelly L, et al. A Survey of Primary Care Practices on Their Use of the Intensive Behavioral Therapy for Obese Medicare Patients. J Gen Intern Med. Sep 2021;36(9):2700–2708. doi: 10.1007/s11606-021-06596-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Nederveld A, Phimphasone-Brady P, Connelly L, Fitzpatrick L, Holtrop JS. The Joys and Challenges of Delivering Obesity Care: a Qualitative Study of US Primary Care Practices. J Gen Intern Med. Sep 2021;36(9):2709–2716. doi: 10.1007/s11606-020-06548-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Huang J, Yu H, Marin E, Brock S, Carden D, Davis T. Physicians’ weight loss counseling in two public hospital primary care clinics. Acad Med. 2004 Feb 2004;79(2):156–61. [DOI] [PubMed] [Google Scholar]
- 14.Simon R, Lahiri SW. Provider Practice Habits and Barriers to Care in Obesity Management in a Large Multicenter Health System. Endocr Pract. Apr 2018;24(4):321–328. doi: 10.4158/EP-2017-0221 [DOI] [PubMed] [Google Scholar]
- 15.Walker RE, Kusch J, Fink JT, et al. Facilitating Factors and Barriers to Weight Management in Women: Physician Perspectives. J Patient Cent Res Rev. Winter 2018;5(1):18–27. doi: 10.17294/2330-0698.1495 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Woodruff RC, Schauer GL, Addison AR, Gehlot A, Kegler MC. Barriers to weight loss among community health center patients: qualitative insights from primary care providers. BMC Obes. 2016;3:43. doi: 10.1186/s40608-016-0123-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Özer ZY, Özcan S, Seydaoğlu G, Kurdak H. Barriers to losing weight for women attending group visits in primary care: A qualitative exploration using in-depth interviews. Eur J Gen Pract. Dec 2021;27(1):331–338. doi: 10.1080/13814788.2021.1998446 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Delahanty LM, Trief PM, Cibula DA, Weinstock RS. Barriers to Weight Loss and Physical Activity, and Coach Approaches to Addressing Barriers, in a Real-World Adaptation of the DPP Lifestyle Intervention: A Process Analysis. Diabetes Educ. Dec 2019;45(6):596–606. doi: 10.1177/0145721719883615 [DOI] [PubMed] [Google Scholar]
- 19.Kurz D, Befort C. Travel burden in a rural primary care behavioral weight loss randomized trial: Impact on visit attendance and weight loss. J Rural Health. Feb 21 2022;doi: 10.1111/jrh.12652 [DOI] [PubMed] [Google Scholar]
- 20.Holtrop JS, Connelly L, Gomes R. Models for delivering weight management in primary care: results from the Making Obesity Services and Treatments work (MOST) Study. Under Review. 2022; [Google Scholar]
- 21.Lv N, Azar KMJ, Rosas LG, Wulfovich S, Xiao L, Ma J. Behavioral lifestyle interventions for moderate and severe obesity: A systematic review. Prev Med. Jul 2017;100:180–193. doi: 10.1016/j.ypmed.2017.04.022 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Look Ahead Research Group, Wadden TA, West DS, et al. The Look AHEAD study: a description of the lifestyle intervention and the evidence supporting it. Obesity (Silver Spring). May 2006;14(5):737–52. doi: 10.1038/oby.2006.84 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Katzmarzyk PT, Apolzan JW, Gajewski B, et al. Weight loss in primary care: A pooled analysis of two pragmatic cluster-randomized trials. Obesity (Silver Spring). Dec 2021;29(12):2044–2054. doi: 10.1002/oby.23292 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Befort CA, VanWormer JJ, Desouza C, et al. Effect of Behavioral Therapy With In-Clinic or Telephone Group Visits vs In-Clinic Individual Visits on Weight Loss Among Patients With Obesity in Rural Clinical Practice: A Randomized Clinical Trial. JAMA. Jan 26 2021;325(4):363–372. doi: 10.1001/jama.2020.25855 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Katzmarzyk PT, Martin CK, Newton RL Jr., et al. Weight Loss in Underserved Patients - A Cluster-Randomized Trial. N Engl J Med. Sep 3 2020;383(10):909–918. doi: 10.1056/NEJMoa2007448 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Perreault L, Hockett CW, Holmstrom H, Tolle L, Kramer ES, Holtrop JS. PATHWEIGH Tool for Chronic Weight Management Built into EPIC Electronic Medical Record: Methods, Pilot Results and Future Directions. Obes Sci Pract. 2020;4(1):42–48. [Google Scholar]
- 27.Suresh K, Holtrop JS, Dickinson LM, et al. PATHWEIGH, pragmatic weight management in adult patients in primary care in Colorado, USA: study protocol for a stepped wedge cluster randomized trial. Trials. Jan 10 2022;23(1):26. doi: 10.1186/s13063-021-05954-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Dickinson WP, Dickinson LM, Nutting PA, et al. Practice facilitation to improve diabetes care in primary care: a report from the EPIC randomized clinical trial. Ann Fam Med. January-February, 2014 2014;12(1):8–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Dickinson WP, Dickinson LM, Jortberg BT, et al. A Cluster Randomized Trial Comparing Strategies for Translating Self-Management Support into Primary Care Practices. Journal of the American Board of Family Medicine : JABFM. May-Jun 2019;32(3):341–352. doi: 10.3122/jabfm.2019.03.180254 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Fernald D, Hall T, Montgomery L, et al. Colorado Residency PCMH Project: Results From a 6-Year Transformation Effort. Fam Med. Jul 2019;51(7):578–586. doi: 10.22454/FamMed.2019.928558 [DOI] [PubMed] [Google Scholar]
- 31.Dickinson WP, Dickinson LM, Jortberg BT, Hessler DM, Fernald DH, Fisher L. A protocol for a cluster randomized trial comparing strategies for translating self-management support into primary care practices. BMC Fam Pract. Jul 24 2018;19(1):126. doi: 10.1186/s12875-018-0810-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Dickinson WP, Nease DE, Rhyne RL, et al. Practice Transformation Support and Patient Engagement to Improve Cardiovascular Care: From EvidenceNOW Southwest (ENSW). J Am Board Fam Med. 2020;33(5):675–686. doi: 10.3122/jabfm.2020.05.190395 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Dickinson LM, Dickinson WP, Nutting PA, et al. Practice context affects efforts to improve diabetes care for primary care patients: a pragmatic cluster randomized trial. J Gen Intern Med. Apr 2015;30(4):476–82. doi: 10.1007/s11606-014-3131-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Cohen D, McDaniel RR Jr., Crabtree BF, et al. A practice change model for quality improvement in primary care practice. J HealthcManag. 2004;49(3):155–168. NOT IN FILE. [PubMed] [Google Scholar]
- 35.Damschroder LJ, Lowery JC. Evaluation of a large-scale weight management program using the consolidated framework for implementation research (CFIR). Implement Sci. May 10 2013;8:51. doi: 10.1186/1748-5908-8-51 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Dolan ED, Mohr D, Lempa M, et al. Using a single item to measure burnout in primary care staff: a psychometric evaluation. J Gen Intern Med. May 2015;30(5):582–7. doi: 10.1007/s11606-014-3112-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Trockel M, Bohman B, Lesure E, et al. A Brief Instrument to Assess Both Burnout and Professional Fulfillment in Physicians: Reliability and Validity, Including Correlation with Self-Reported Medical Errors, in a Sample of Resident and Practicing Physicians. Acad Psychiatry. Feb 2018;42(1):11–24. doi: 10.1007/s40596-017-0849-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Fields DL. Job Satisfaction. Taking the measure of work : a guide to validated scales for organizational research and diagnosis. Information Age Publishing; 2013:1–42. [Google Scholar]
- 39.Messias E, Flynn V, Gathright M, Thrush C, Atkinson T, Thapa P. Loss of Meaning at Work Associated with Burnout Risk in Academic Medicine. Southern medical journal. Mar 2021;114(3):139–143. doi: 10.14423/smj.0000000000001220 [DOI] [PubMed] [Google Scholar]
- 40.Loerbroks A, Glaser J, Vu-Eickmann P, Angerer P. Physician burnout, work engagement and the quality of patient care. Occup Med (Lond). Jul 1 2017;67(5):356–362. doi: 10.1093/occmed/kqx051 [DOI] [PubMed] [Google Scholar]
- 41.Hung DY, Harrison MI, Liang SY, Truong QA. Contextual Conditions and Performance Improvement in Primary Care. Qual Manag Health Care. Apr/Jun 2019;28(2):70–77. doi: 10.1097/qmh.0000000000000198 [DOI] [PubMed] [Google Scholar]
- 42.Jacobs SR, Weiner BJ, Bunger AC. Context matters: measuring implementation climate among individuals and groups. Implement Sci. Apr 17 2014;9:46. doi: 10.1186/1748-5908-9-46 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Bunce AE, Gruss I, Davis JV, et al. Lessons learned about the effective operationalization of champions as an implementation strategy: results from a qualitative process evaluation of a pragmatic trial. Implement Sci. Oct 1 2020;15(1):87. doi: 10.1186/s13012-020-01048-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Tomoaia-Cotisel A, Scammon DL, Waitzman NJ, et al. Context matters: the experience of 14 research teams in systematically reporting contextual factors important for practice change. Ann Fam Med. May-Jun 2013;11 Suppl 1:S115–23. doi: 10.1370/afm.1549 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Solberg LI, Stuck LH, Crain AL, et al. Organizational factors and change strategies associated with medical home transformation. Am J Med Qual. Jul-Aug 2015;30(4):337–44. doi: 10.1177/1062860614532307 [DOI] [PubMed] [Google Scholar]
- 46.Balasubramanian BA, Marino M, Cohen DJ, et al. Use of Quality Improvement Strategies Among Small to Medium-Size US Primary Care Practices. Ann Fam Med. Apr 2018;16(Suppl 1):S35–s43. doi: 10.1370/afm.2172 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Solberg LI. Improving medical practice: a conceptual framework. Ann Fam Med. May-Jun 2007;5(3):251–6. doi:5/3/251 [pii] 10.1370/afm.666 [DOI] [PMC free article] [PubMed] [Google Scholar]
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