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Do People with Obesity Lose Weight When Offered a Choice of Research-based Weight-Loss Treatment by Their Doctors? Daniel H Bessesen, MD, 3 Elizabeth Kealey, 1 David R Saxon, MD, 1 Erin C Leister, MS, 1 Elizabeth

Juarez-Colunga, PhD, 1 Adam G Tsai, MD, 2 Sean J Iwamoto, MD, 1 Rebecca B Speer, MA, 3 Hilde

Heyn3

1 University of Colorado Denver, Denver CO 2 Kaiser Permanente Medical Center, Denver CO

3 Denver Health and Hospital Authority, Denver CO

Original Project Title: A Toolbox Approach to Obesity Treatment in Primary Care PCORI ID: IH-12-11-4571 HSRProj ID: 20143059 ClinicalTrials.gov ID: NCT01922934

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To cite this document, please use: Bessesen D, Kealey E, Saxon D, et al. 2019. Do People with Obesity Lose Weight When Offered a Choice of Research-based Weight-Loss Treatment by Their Doctors? Washington, DC: Patient-Centered Outcomes Research Institute (PCORI). https://doi.org/10.25302/9.2019/IH.12114571

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Table of Contents

ABSTRACT ..........................................................................................................................................3 BACKGROUND ...................................................................................................................................5 METHODS ........................................................................................................................................ 12 RESULTS .......................................................................................................................................... 27

Baseline Characteristics of the Study Population ................................................................................... 27 Weight Loss............................................................................................................................................. 29 Secondary Outcomes .............................................................................................................................. 32 Provider Survey Results .......................................................................................................................... 37 Adverse Events ....................................................................................................................................... 38

DISCUSSION ..................................................................................................................................... 39 Decisional Context .................................................................................................................................. 39 Study Results in Context ......................................................................................................................... 39 Implementation of Study Results ........................................................................................................... 41 Generalizability ....................................................................................................................................... 42 Subpopulation Considerations ............................................................................................................... 43 Study Limitations .................................................................................................................................... 43 Future Research ...................................................................................................................................... 44

CONCLUSIONS ................................................................................................................................. 46 REFERENCES .................................................................................................................................... 47 APPENDICES .................................................................................................................................... 52

Appendix A: Description of Offered Weight Loss Tools ......................................................................... 52 Appendix B: Baseline Characteristics of Registry Cohort and Those Randomized to Intervention and Control Groups ....................................................................................................................................... 54 Appendix C: Subgroup Analysis Odds of Achieving 5% Body Weight Loss ............................................. 56 Appendix D: Subgroup Analysis Proportion with 5% Body Weight Loss by Intervention Group, Race/Ethnicity, and Baseline BMI ........................................................................................................... 57 Appendix E: Sensitivity Analyses for Primary Outcome of Percentage Achieving 5% or More Weight Loss ......................................................................................................................................................... 59 Appendix F: Choice of Tool at Visit 1 by Demographic Characteristics .................................................. 60 Appendix G: Adverse Events ................................................................................................................... 62 Appendix H: Demographic Characteristics by Clinic–Intervention Clinic (I)1 or Control Clinic(C)2 ......... 63 Appendix I: Characteristics of Intervention-Eligible Participants, Comparing Those Who Consented and Attended the 1st Visit vs. Those Who Declined or Did Not Respond ..................................................... 66

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ABSTRACT

Background: Evidence-based weight loss treatments are rarely offered in routine primary care practice owing in part to lack of reimbursement, lack of provider training and experience in discussing treatment options, and the difficulties inherent in discussing all available options. Little evidence exists about the effect of addressing these common barriers to optimal practice in real-world settings. Objectives: We sought to determine what fraction of randomly selected patients with obesity and weight-related comorbidities who were offered evidence-based medical weight management interventions achieved clinically meaningful weight loss (ie, ≥ 5% of initial weight) at 12 months. Additionally, we sought to measure the uptake and use of specific weight loss services when patients in a low-resource setting were given the opportunity to choose among a variety of options and obtain them at a relatively low out-of-pocket cost. Methods: We conducted a pragmatic randomized controlled weight loss trial in primary care clinics in an integrated health care organization that serves an ethnically diverse and medically underserved low-income urban population. The primary outcome we measured was whether patients lost 5% of their initial body weight at 12 months. Five different evidence-based weight loss treatment options were offered for a $5 or $10 monthly copay to 309 patients randomly selected from a registry of patients with obesity (BMI ≥ 30 and < 45 kg/m2) and at least one weight-related comorbidity. Participants were allowed to choose their initial intervention and to switch interventions at any point during the study, and they could add a second tool 6 months into the study. Patients in the registry who were not selected for the intervention and for whom 2 weights were available served as an observational comparator group. Study design was guided in part by patient stakeholder feedback before and during the trial. Results: In the intervention group, 119 people (38.5% of those contacted) sought and received treatment. The primary outcome of ≥ 5% weight loss was achieved in 34.5% of the intervention group compared with 15.7% of the usual care observational registry-based control group (n = 2930; p < 0.001). Mean percentage weight loss was –3.15% ± 6.41% in the intervention group and –0.30% ± 6.10% in the control group (p < 0.001). Of the subjects, 35.3% chose meal replacements, 27.7% weight loss medications, 21.8% recreation center passes, 6.7% Weight Watchers vouchers, and 5.0% group behavioral weight loss class, and 1.7% simply wanted monthly clinical visits. Those who attended more intervention visits, those who used phentermine/topiramate ER (extended release), and those who used a second tool during the last 6 months of the intervention were more likely to lose ≥ 5% of baseline weight than those who did not.

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Conclusions: More than one-third of randomly selected patients with obesity and a weight-related comorbidity sought medically supervised weight loss treatments when they were offered modest copays and support. At 1 year, these patients had lost and maintained the loss of ≥ 5% of their baseline weight (10 lbs for a 200 lb person). Limitations and subpopulation considerations: The study was not powered to determine the effects of each tool, and the results apply only to an ethnically diverse, medically underserved population that received care in a single integrated health system.

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BACKGROUND

Burden of obesity. Obesity is the leading public health challenge facing the United States in the

21st century.1,2 The overall prevalence of obesity in the nation in 2013-2014 was 37.7%. Among

men, the prevalence of a BMI > 30 kg/m2 was 35.0%; among women, it was 40.4%. The

prevalence of people with a BMI > 40 kg/m2 (class 3 obesity) was 7.7%. Among men and

women, 5.5% and 9.9%, respectively, had class 3 obesity.3 The prevalence of obesity among

children and adolescents aged 2-19 years in 2011-2014 was 17.0%, and extreme obesity was

5.8%.4

Obesity increases the risk of a range of health problems, and the contribution of obesity

to disability and to total mortality is substantial.5,6 Obesity has been projected to shorten life

expectancy in the United States. The clinical burden of obesity is equaled by the economic

burden: The medical costs of obesity-related health problems have been estimated to be

$209.7 billion annually, and the indirect costs of obesity—through missed work days, injuries,

and disability—are substantial.7 Ethnic minority groups and individuals of low socioeconomic

status have higher rates of obesity; as a result, obesity in these populations is an important

cause of health disparities.8

Treating obesity reduces comorbid disease and is widely advocated. The Diabetes Prevention

Program (DPP) demonstrated that a weight loss of 5% to 7% can prevent or delay development

of type 2 diabetes in at-risk individuals.9 Although the multicenter Look AHEAD (Action for

Health in Diabetes) study did not show reductions in cardiovascular disease morbidity and

mortality with weight loss, participants treated with an intensive lifestyle intervention did have

sustained improvements in cardiovascular risk factors and reductions in medication

requirements.10 A number of other studies also have shown that a weight loss of 5% to 10% can

provide meaningful health benefits.11

A broad consensus has emerged that evaluating and treating patients for obesity should

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be an integral part of usual clinical care. The American College of Physicians has concluded that

behavior modification, pharmacotherapy, and surgery are appropriate interventions for certain

obese patients.12 The American Heart Association, the American Gastroenterological

Association, the American Association of Clinical Endocrinologists, the US Preventive Services

Task Force, the Obesity Society, the American Diabetes Association, the Veterans

Administration and Department of Defense, the Endocrine Society, NIH, and many other

professional organizations have taken positions advocating more aggressive evaluation and

treatment of obesity.13-20

Clinically significant weight loss can be achieved using currently available tools and

strategies. Intensive lifestyle modification, conducted in a group setting and led by a qualified

expert, can produce weight losses of 8% to 10%.13 Commercial weight loss programs such as

Weight Watchers can produce a 3% to 5% weight loss at 1 to 2 years,21 and more structured

behavioral weight loss programs led by trained interventionists can produce a 5% to 8% weight

loss.22 Meal replacements produce an additional weight loss of 2.5 kg to 3 kg compared with

isocaloric diets of conventional foods and have led to an 8% weight loss at 4 years among

individuals who continued to use the strategy.23 Structured physical activity programs have

been shown to help many patients increase their levels of physical fitness, which in turn lowers

cardiovascular risk. Programs that increase physical activity typically produce a 1% to 3% weight

loss in randomized controlled trials (RCTs) and have been shown to be a critical component of

successful weight loss maintenance.24,25

Weight loss medications produce clinically significant weight loss and have been shown

to reduce risk factors for cardiovascular disease.18,26 Among the available medications,

phentermine currently accounts for the largest number of written prescriptions. Phentermine

produces a 3% to 5% placebo-subtracted weight loss.27,28 Phentermine/topiramate ER is the

most effective available combination weight loss medication, producing an 8% to 10% weight

loss in RCTs.29-31 In real-world clinical environments, unlike explanatory trials, patients and

providers have the option of choosing from a range of evidence-based treatment options.

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To date, no trials have offered randomly selected patients with obesity and a weight-

related comorbidity a range of treatment options to see how many would seek treatment,

which treatment they would choose, and whether they would adhere to the treatment and lose

weight.

Patients with obesity typically do not receive weight management services from their primary

care providers (PCPs). Despite broad recognition of obesity as a national epidemic, less than

half of patients with obesity report receiving weight loss counseling, even when obesity-related

comorbidities are present.32,33 As reported in the National Ambulatory Medical Care Survey,

between 1995-1996 and 2007-2008, rates of weight counseling in primary care actually

declined significantly despite increased rates of overweight and obesity in the United States,34

and most PCPs may provide no weight loss counseling during any visits.35 Several barriers to

providing weight loss counseling have been identified, including lack of training,36 lack of

reimbursement, perceived lack of time to counsel patients, provider bias toward patients with

obesity,37-39 and perceived futility (ie, how providers view their patients’ lack of ability to lose

weight).40 Despite these challenges, stakeholders are increasingly encouraging PCPs to take an

active role in obesity management. For example, the obesity counseling benefit for Medicare

beneficiaries stipulates that this activity must occur in the primary care setting,41 and recent

national weight management guidelines encourage PCPs to screen for obesity and refer

patients to appropriate intensive behavioral programs.13,15

To improve the quality of obesity care in the primary care setting, we conducted a

pragmatic trial using a toolbox approach to weight loss management in an integrated health

system. We based the study design on the idea that a flexible approach, tailored to the goals

and motivations of each patient, would be most likely to reach the greatest number of

individuals and to produce the greatest overall impact on weight. The toolbox approach

allowed patients to select from a variety of weight loss interventions that are not routinely

provided in the primary care setting: meal replacements, a commercial weight loss program,

intensive group lifestyle modification, recreation center vouchers, and pharmacotherapy. The

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objective of this study was to see whether offering a randomly selected group of patients with

obesity and a weight-related comorbidity a range of evidence-based weight loss options under

the supervision of their PCPs at relatively low out-of-pocket costs would result in significantly

more weight loss than usual care.

Engagement of patients, providers, and administrators in the design, execution, and

evaluation of the toolbox. Patient engagement occurred before the study began, with patient

focus groups in English and Spanish. Patient engagement continued throughout the study and

after its conclusion via quarterly patient advisory council (PAC) meetings in English and Spanish.

Provider engagement occurred before the initiation of the study: We held meetings with

providers at all clinics affiliated with Denver Health (DH) and took baseline surveys to assess

knowledge and attitudes about the care of obese patients. Provider engagement continued

throughout the study, with roughly quarterly meetings at intervention clinics for provider

education and feedback on the conduct of the study. Following the conclusion of the study, we

conducted a postintervention survey of all providers at all clinics. Administrator engagement

occurred through regular briefings with clinic and departmental administrative personnel and

through the attendance of departmental administrators at PAC meetings. Each of these

engagement activities is described in the report.

Preintervention patient stakeholder focus groups. Four focus groups were held between

October 2 and October 25, 2014, before the initiation of the study. We had asked PCPs to

nominate patients who met study eligibility criteria and who they felt would be interested in

the study and potentially helpful as we designed it; ultimately, we recruited 29 of these

nominated patients for the focus groups. Two groups were conducted in Spanish, and 2 were

conducted in English (n = 5-10 per group). Of the 29 patients who participated in the focus

groups, 27 went on to participate in the intervention (these individuals were not included in the

data analysis). An experienced facilitator trained in qualitative methods led the focus groups.

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Sessions lasted 90 minutes and were audio recorded and professionally transcribed; the

transcripts were augmented by notes taken during the sessions.

Patient engagement in these focus groups resulted in several major changes to the

study design. Patient stakeholders suggested that participants be allowed to continue to

receive weight loss support even if they did not want to select and pay for one of the weight

loss tools being offered (ie, they just wanted face-to-face visits for support and counseling). A

few study participants subsequently chose this option. The focus group members appreciated

the fact that patients would be allowed to change tools during the intervention if their original

choices proved unhelpful, but they suggested allowing participants to continue using a tool

regardless of adherence. They made important suggestions about the computer program used

to educate study participants about the interventions, including increasing the font size and

readability of the screens and offering multiple answer selection options rather than limiting

each question choice to a single selection.

Patient focus groups also provided useful insights into participants’ previous

experiences with specific weight loss interventions and provider interactions. Previous weight

loss experiences were reported to be overwhelmingly negative, and many focus group

members said they had experienced weight-related stigma in their interactions with health care

systems and providers. They mentioned social, emotional, and medical factors as barriers to

successful weight loss, and provided information on how they perceived the various tools in the

toolbox. Meal replacements were the most popular weight loss tool, and recreation center

passes were also perceived to be helpful. Participants saw value in group support but were not

enthusiastic about either the Weight Watchers or the comprehensive group behavioral weight

loss options. Participants perceived the weight loss medications to be risky and dangerous; a

number of participants cited their own previous bad outcomes or general awareness of

problems with fenfluramine/phentermine as reasons to avoid weight loss medications.

Participants also were reluctant to add another medication to what they perceived to be a high

number of medications in their personal regimens. These patient insights were conveyed to

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study staff to let them know ahead of time what kinds of preconceived ideas subjects might

have about weight loss treatments and thus to improve their interactions with participants.

Patient advisory council meetings. Individuals who participated in the 4 preintervention focus groups

were invited to join PACs and to engage with the toolbox intervention for 12 months in the same

manner as the patients randomly selected for the trial. The purpose of enrolling PAC members in the

trial was to provide ongoing feedback on the conduct of the trial, although we did not include their

outcome measures in the final study analyses. Eight PAC meetings were held during the trial (4 in English

and 4 in Spanish); the meetings consisted of 4 to 8 people per session. Because PAC members had

participated in preintervention focus groups before other subjects enrolled in the study, they were able

to provide important feedback, which we incorporated into the study as it progressed. For example, PAC

members suggested improvements in the educational handouts that provided basic information on

behavioral approaches to weight loss, including diet and physical activity. They also recommended that

participants be allowed to select a second weight loss tool at the 6-month point in the study; 29.4% of

study participants ultimately chose this second tool option. PAC members made several other important

suggestions that were outside the purview of the study but related to obesity care at Denver Health,

including the need for mental health and group support to help with weight loss and the need for a long-

term weight loss maintenance program.

Primary care provider stakeholder meetings. From December 2013 through July 2014, before the study

actually began, the toolbox team conducted monthly meetings at each of the 4 intervention clinics (PCP-

I) and the 4 control clinics (PCP-C). PCPs at the clinics completed preintervention surveys at these

meetings. During the postintervention period, between September 2016 and December 2016, providers

were notified that the trial had concluded and were asked to complete postintervention surveys. In an

effort to survey all PCPs at clinic sites, study staff contacted those who were not present at meetings at

which the surveys were distributed. We asked PCPs to fill out the surveys anonymously, under the

assumption that PCPs would respond more honestly to questions about weight loss interventions if they

were not concerned that their answers would be judged by study staff. To ensure anonymity, we

collected demographic data separately from all PCPs who completed surveys.

On a 0-to-10 Likert scale (0 being least comfortable and 10 being most comfortable), PCPs rated

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their comfort discussing each weight loss tool with their patients: lifestyle modification programs,

portion-controlled foods, exercise, phentermine, and phentermine/topiramate ER. This list of obesity

interventions in the survey was similar to those offered in the toolbox trial. PCPs also rated the

effectiveness of these tools for weight loss on a 0-to-10 Likert scale (0 being least effective and 10 being

most effective). We measured PCPs’ views on the importance of obesity as a problem and their comfort

level with general weight loss counseling using similar 0-to-10 Likert scales.

Administrative stakeholders. The administrative director of the Denver Health Department of Medicine

attended PAC meetings, where she heard firsthand DH patients’ concerns about the care they received

from primary care clinics regarding their weight issues, as well as their enthusiasm for the toolbox

approach used in the study.

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METHODS

Study Design

A Toolbox Approach to the Treatment of Obesity in Primary Care was a 12-month single-

institution registry-based pragmatic RCT testing the effectiveness of offering a variety of low-

copay medical weight loss interventions compared with usual clinical care for patients with

obesity and at least one weight-related comorbidity. Denver Health PCPs helped the study team

create a registry of obese patients with at least one weight-related comorbidity. From that

registry, a group of patients who received their primary care from 1 of the 4 intervention clinics

was randomly selected to participate in the study. PCPs could exclude potential subjects whom

they believed were not appropriate for the trial. For a $5 or $10 copayment, each participant

was offered a toolbox of weight loss treatment options: meal replacements, a commercial

weight loss program, intensive group lifestyle modification, recreation center passes, and

pharmacotherapy with either phentermine alone or phentermine/topiramate ER. (The

manufacturer provided phentermine/topiramate ER. Subjects who used phentermine took 1

month out of 4 off of therapy.) Participants were allowed to choose their preferred tool, and

they could switch to a different one at any point during the trial. The study team also selected

an observational, registry-based control group. IRBs at both DH and the University of Colorado

approved the protocol and amendments. All participants were informed that they were

participating in a study and provided consent after they completed the educational computer

program. (We used deidentified patient-level data on control subjects for this analysis, so these

subjects were not consented.) Feedback from patient stakeholders influenced elements of the

trial design.

Power/Sample Size Calculation

In the funded application, we estimated that the registry of obese patients would number

about 8000, 10% of whom would likely be excluded because of exclusion criteria (8000 x 0.90 =

7150). We also allowed for participant dropout for those who would be randomized to the

intervention group (rate = 14%). The original power analysis yielded a sample size of 300

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patients after dropout (350 x [1-0.14] = 300) in the intervention and 6800 in the control group.

This would allow us to detect a difference of 5% with 80% power (15% achieving the desired

weight loss in intervention vs 10% in control groups) and 6% with 90% power (16% vs 10%) at

0.05 significance. However, the actual sample size in the study was lower and the estimates of

the proportion of patients who lost weight was higher. At the request of the first reviewers of

the final research report in the spring of 2017, we conducted a post hoc power calculation

considering several scenarios. On the basis of a sample size of 119 and 2640 in the intervention

and control groups, with 80% power (alpha = 0.05), the study could detect a difference in the

primary outcome on the order of 7% to 10% in the intervention versus the comparator group,

depending on whether the percentage of patients who achieved > 5% weight loss was between

5% and 15% in the control group. With 90% power (alpha = 0.05), the study could detect a

difference of 8% to 12%.

Forming the Study Cohort

We used the DH computerized data warehouse to create an obesity cohort registry in the

spring of 2014. Inclusion criteria included patients aged 18-80 with a BMI (body mass index) ≥/=

30 kg/m2 and < 45 kg/m2 with at least 1 weight-related comorbidity as defined by ICD-9

(International Classification of Diseases, Ninth Revision) diagnostic codes (including diabetes,

prediabetes, osteoarthritis, back pain, hypertension, hyperlipidemia, metabolic syndrome,

coronary artery disease, atherosclerosis, cerebrovascular disease, sleep disorder, and

congestive heart failure) who had received primary care at DH at least twice within the previous

12 months and once within the previous 6 months. We used these factors to select subjects

who were most likely to realize health benefits from weight loss and to be engaged in care.

This registry contained information on 4730 patients from 9 primary care clinics

affiliated with DH. We selected 4 of these clinics to be the ones at which the intervention would

be implemented; we selected them because they had space for study staff to conduct the

intervention. We compared the patients at these clinics with those at the control clinics. To

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attain a sample size of 350 patients who would be offered the intervention, we selected an

additional 80 patients (total 430) to account for potential exclusions. Of the 2684 patients at

the 4 intervention clinics, 428 were randomly selected for the intervention group (2 patients

were excluded because they were focus group participants). Patients in the registry who were

not selected for the intervention served as the observational control group. This included all

patients at clinics that were not chosen as intervention clinics (N = 2046) and patients at

intervention clinics who had not been randomly selected to participate in the study (N = 2256).

We used this group as a comparator to describe weight loss during usual care at DH.

Of the 428 patients in the intervention group, potential participants were excluded if

they had a history of a heart attack or stroke within the past 6 months; were pregnant; or had

contraindications to weight loss, such as active cancer treatment, severe collagen vascular

disease, end-stage liver disease, or end-stage renal disease requiring dialysis. Before attempted

recruitment, the study team gave PCPs a list of their patients who had been selected to receive

the intervention; in line with normal clinical decision making, the PCPs were allowed to exclude

patients whom they did not consider to be good candidates for participation in a clinical weight

loss program. Recruitment occurred between September 2014 and July 2015. Subjects were

invited to receive help with their weight. The study team made 2 recruitment phone calls to

each eligible participant and sent letters about the study to those who could not be reached by

phone. The details of subject recruitment and retention are shown in Figure 1.

The team offered potential participants a $20 gift card as an incentive for attending an

initial 1-hour visit with study staff (visit 0). At that visit, a computer program designed

specifically for the trial was used to explain the weight loss treatment options that would be

available during the study. Participants were told they would receive introductory weight loss

tools including a pedometer, a diet/exercise log, and a calorie-counting book, and would be

expected to keep a diet and exercise log.

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Figure 1. Screening, randomization, and assessment of study participants.

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At the end of visit 0, if the person chose to participate in the study, he or she chose a

single weight loss treatment option. The study team gave the participant a computer printout

with detailed information about the chosen treatment and mailed a copy to his or her PCP. At a

return visit 1 to 2 weeks later (visit 1), diet and exercise logs were collected and reviewed and

participants finalized their weight loss tool selections and paid the first month’s copay: $5 for a

recreation center voucher, Weight Watchers vouchers, or phentermine, or $10 for the group

behavioral weight loss program, meal replacements, or phentermine/topiramate ER. We

determined copay amounts on the basis of relative market costs, with input from the

preintervention focus groups: $5 copays were assigned to the less expensive tools and $10

copays to the more expensive tools. Because some individuals did not return for visit 1 and

therefore never received intervention-supported treatment, we considered those who paid a

copay at visit 1 and began using a weight loss tool to be the group that actually received the

designed intervention and are thus the subjects included in the analysis.

After visit 1, participants were asked to attend monthly visits with study staff in their

home primary care clinic. During those visits, participants were weighed, discussed their weight

loss efforts and use of the tools during the previous month, and paid the monthly copay.

Participants had the opportunity to continue using their current tool or to switch to a different

one. Interim visits occurred on an as-needed basis if a participant wanted to switch tools, had a

blood pressure reading at the monthly visit that was too high to receive the medication, or had

forgotten the copay at the original visit.

Study Setting

Obesity disproportionally affects Hispanic and non-Hispanic black populations.3 In addition, lack

of insurance coverage for readily available weight loss interventions leads to high out-of-pocket

costs, which might be prohibitive for patients of low socioeconomic status. We conducted this

study at Denver Health, a comprehensive integrated health care organization that serves an

ethnically diverse and medically underserved low-income urban population. As of 2014, DH

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served a population consisting of roughly two-thirds racial/ethnic minorities: 43% Hispanic, 14%

African American, and 6% Asian American, Native American, or multiracial. Most of these

patients have government insurance or are uninsured. We conducted the toolbox intervention

in 4 primary care clinics (intervention clinics); 5 other primary care clinics served as control

clinics to test the possibility that the treatment of control patients in the intervention clinics

might have been affected by the intervention. DH is run by an authority and uses EPIC as the

electronic health record (EHR). There are 80 PCPs at the 9 outpatient clinics.

Interventions

Toolbox of weight loss options. We offered the participants a variety of medical weight loss

options that have shown efficacy in clinical trials but are seldom offered during routine clinical

care, including a partial meal replacement program, vouchers for a commercial weight loss

program (Weight Watchers), recreation center membership (good at any of the 27 recreation

centers operated by the City and County of Denver), phentermine, phentermine/topiramate ER,

and a group behavioral weight loss program (see Appendix A). PCPS screened and supervised

use of medications. If a subject demonstrated a rise in pulse (>10 bpm) or blood pressure

(outside the reference range) or did not lose 5% of baseline weight after 3 months, the

medication was stopped and he or she was offered other tools. After 6 months of participation

in the study, participants could opt to pay a second copay and add either recreation center

vouchers or a weight loss maintenance program based on the DPP. All subjects in the

intervention group received weight management educational handouts at monthly visits. Study

staff developed these handouts, which emphasized nutrition, physical activity, environment,

and behavior change strategies for weight management; they were similar to the publicly

available DPP curriculum.

Usual care in control group. Patients in the registry who were not randomly selected to receive

the intervention served as observational controls. We accessed the DH computerized data

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warehouse to obtain longitudinal weight data on all control patients from their primary care

and specialty visits in the year following the creation of the registry (June 2, 2014). We

performed a manual review on the medical records of 120 control group patients to estimate

the rates at which this group had been offered medical weight loss treatment interventions by

their PCPs during the course of the study.

Physician education. We delivered 8 education sessions to participating PCPs, 2 at each

intervention clinic site. One session, delivered before the initiation of the study, covered the

details of the study design and conduct and provided information about the evidence-based

weight loss treatments included in the toolbox, as well as the selection of patients for

treatment and how to communicate with patients regarding weight management. A second

session was conducted at each intervention clinic roughly 6 months into the study to reinforce

the previously presented information on counseling and treatment options for patients with

obesity and to allow for a dialogue on practical issues in the conduct of the study.

Follow-up. We conducted individual follow-up visits at the intervention clinics. The visits were

approximately half-hour one-on-one sessions between the participant and a member of the

study staff. Bilingual study staff members provided care for subjects who spoke only Spanish. In

line with the pragmatic nature of the trial, study participants who missed scheduled visits were

not removed from the study but were instead offered the opportunity to return for care at any

point during their 12-month study enrollment. In other words, follow-up care closely modeled

what takes place during routine clinical care, in which patients commonly miss visits and return

when they can or when they choose to seek care. Subjects who missed visits were called

several times and sent a letter encouraging them to return to the intervention; if they did not

respond, we informed their PCPs that they had not returned. Results considering missing data

are presented under Analytical and Statistical Approaches.

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Study Outcomes

The primary outcome was the percentage of participants who achieved 5% weight loss at 12

months in the intervention group compared with the observational, registry-based cohort of

patients who received usual clinical care. We chose this degree of weight loss because

moderate weight loss of 5% to 10% is an achievable benchmark and is associated with clinically

meaningful improvements in obesity-related conditions such as type 2 diabetes, hypertension,

dyslipidemia, cardiovascular disease, sleep apnea, and osteoarthritis.13

Secondary outcomes included participant preferences for and use of weight loss tools

and visit attendance. Weight was measured in light clothing using clinic scales at each visit.

Blood pressure and pulse were measured at every visit; waist circumference was measured

quarterly. Laboratory data were not systematically collected as part of the study protocol but

were collected on a schedule determined by each patient’s PCP as deemed necessary for usual

clinical care.

Data Collection and Sources

Weight data were collected on intervention subjects at each monthly visit. Study staff assessed

overall adherence to intervention tools as attendance at monthly visits. We also obtained data

directly from community recreation centers regarding the number of visits subjects made to

these facilities each month. Weight data for subjects in the control group came from the EHR. It

is standard practice in DH primary care clinics to weigh patients at every visit and record this

weight in the EHR. We selected a window of +/– 6 months from the date subjects were

randomly assigned to intervention or control groups, because subjects in the comparator arm

were receiving usual care and did not have any scheduled study visits. We considered and

tested a narrower window of +/– 3 months; however, because patients did not come in at

predetermined times, this window yielded weight data on only 75% of the control subjects. By

increasing the window of observation, we were able to get weight data on 90% of the

comparator subjects. Two members of the study team (one physician and one nonphysician)

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examined the medical records of all subjects in the control group who had a weight gain or loss

of > 15% of baseline weight to determine whether an error had been made in recording the

weight value or a medical condition was responsible for the change.

Analytical and Statistical Approaches

The baseline characteristics available on both groups included demographics, body size

measurements, and comorbidities. We compared these characteristics between the

intervention group and the registry-based observational control group (see Appendix B). Among

those who were randomly selected for the intervention group invitation, we compared

characteristics between those who consented to enrollment and those who declined. After we

arrived at our final sample for analysis (excluding those who were ineligible, did not agree to

participate, or did not have visits in the appropriate time frame), we described and compared

baseline characteristics of those enrolled in the intervention group and those in the control

group. We present the number of study/clinic visits attended by both groups and their total

follow-up time. In the intervention group, we show the proportion of participants who chose

each tool in the toolbox at the first visit and how many tools they were exposed to during the

study.

Before final data analysis, we performed a data audit to assess quality on all control

group subjects who lost or gained more than 15% of their baseline body weight (n = 94); 17

subjects had invalid weights. In 7 cases, these were data entry problems that could be

corrected, but in 10 cases we could not determine what the proper weight should be, so we

used another weight within the window for analysis.

While we examined mean weight loss between subjects in the intervention and control

groups (described in the Results section), the primary outcome defined in our original proposal

was the proportion of participants who lost at least 5% of their body weight at the end of the

12-month study period between the treatment group and the control group, using a chi-square

test. In our primary analyses, we used the intent-to-treat (ITT) approach, in which we

22

considered participants in the intervention arm who came to the first study visit as the group

we intended to treat. Additionally, we compared the weight loss between groups using a per

protocol approach, in which we considered participants who attended at least 4 study visits to

be those who received study treatment.

In a sensitivity analysis, we calculated the proportion of all participants who consented

to the intervention who achieved 5% weight loss, regardless of whether they attended the first

study visit to receive their weight loss tool, and compared this proportion with the proportion

in the control group. Because participants who consented but did not attend the first study visit

had no study weights on file, we used weights from regular clinic visits to measure weight loss.

As an exploratory analysis, we also examined the nadir weight between groups during the

follow-up period, comparing the proportion of participants who had achieved at least 5%

weight loss at their nadir weight.

We performed 3 separate sensitivity analyses to examine the potential effect of missing

data. First, we assumed that patients with missing baseline or follow-up data were not

successful at losing 5% of initial body weight. Second, we used the last observation carried

forward method for participants with no weight measurement at 12 months to calculate the

proportion who achieved 5% weight loss. (This approach systematically biases the results

toward overestimating benefits and underestimating harms, and is generally shunned as an

imputation method; however, we were asked to perform this analysis by reviewers of this final

report.) After using these 2 methods to calculate the proportion who achieved 5% weight loss,

we repeated our primary analysis comparison by comparing this proportion between the

intervention and control groups. Finally, to relax missing assumptions to missing at random and

to estimate weight change trajectory by group, we used all available weight measurements

during the study period and fit a longitudinal linear mixed model on the weight change from

baseline (kg) using random slopes and unstructured covariance and allowing for an interaction

between treatment group and time and for change in weight trajectory at 6 months.

To address potential confounding of factors, we conducted additional adjusted analyses

by fitting a generalized linear mixed effects model on the binary outcome of achieving 5%

23

weight loss. This model included a fixed effect for treatment group and a random effect for

clinic, to account for any correlation among participants within the same clinic. We considered

age, sex, race/ethnicity, baseline BMI category, and insurance for inclusion in our adjusted

model, and retained covariates with P value < 0.10.

Finally, for intervention participants, we performed a post hoc analysis to determine

whether there was a dose-response relationship between visit attendance and weight loss by

calculating the proportion of participants who achieved ≥ 5% weight loss by the number of

visits they attended. Because we allowed for multiple tool exposures, we were unable to

compare the effectiveness of individual tools. However, we calculated the proportion of

participants who lost ≥ 5% of their initial weight as a function of whether they had ever used a

specific tool during the study period.

We stored intervention group data using Research Electronic Data Capture (REDCap)

software. We stored control group data in the Denver Health Medical Center’s data warehouse.

We performed analyses using SAS version 9.4 ([computer program] Cary, NC: SAS Inc; 2019).

Conduct of the Study

During the course of the study, a number of challenges and issues arose that necessitated

changes to the protocol from that initially approved by our IRB. These changes were discussed

and reviewed by PCORI throughout the study duration. In addition, input from our PAC yielded

ideas that we thought would improve the design and conduct of the study, and we

incorporated these into the protocol. These changes included power calculations, laboratory

data limitations, requests from our PAC, writing of study prescriptions, and additional lost-to-

follow-up procedures.

The sample size of the registry of obese patients was 4730 patients once we restricted

the registry to those with obesity who also had 2 visits to their PCP in the preceding 12 months,

24

with 1 in the past 6 months and at least 1 weight-related comorbidity (see “Forming the Study

Cohort”).

We applied these restrictions to identify patients who were engaged with care (had a

PCP and were being seen in a clinic) and were most likely to benefit from weight loss (had a

weight-related comorbidity). These characteristics and their justifications were proposed,

reviewed, and funded by PCORI. To reach the target of 350 patients proposed in the initial

application, the intervention was to be offered to 430 (350 + 80) patients, to account for

potential provider exclusion of some patients. Two of the 430 were already participating in

focus groups, making them ineligible for the study; thus, we identified 428 patients to contact.

Of these patients, 53 met the exclusion criteria. We attempted to contact 375 eligible patients,

but could not reach 66 of them. The intervention was ultimately offered to 309 individuals. The

post hoc power analysis based on these altered numbers revealed that, despite these changes,

our study was still highly powered to detect a difference in the primary outcome measure

between the intervention and control groups (see Methods section). The table in Appendix H

lists the characteristics of patients seen at different clinics. During the conduct of the study a

new clinic opened that drew patients from 2 of the control clinics and added new patients to

those cared for by DH. That is why 9 clinics are listed on this table; however, the content of the

registry was not altered by this change. Finally, we looked for differences between the patients

who participated in visit 1 and those who were eligible but did not respond to the invitation.

These results are shown in Appendix I. The only significant difference we found was that those

who consented had a higher BMI than those who did not respond.

In the initial study plan, a proposed secondary outcome was changes in serum lipid

levels and HbA1C (hemoglobin A1C) levels with weight loss. However, it became apparent early

on in the trial that this outcome would not be captured using our trial design, which allowed for

laboratory data collection during the course of routine clinical care. We chose this data

collection method to make the trial more pragmatic, but the collection of this information

during routine clinical care (ie, as ordered by regular providers) was variable and resulted in

25

insufficient data to make any conclusions about the effects of the intervention on these

laboratory markers of cardiovascular risk.

Other changes made to the protocol were based on feedback from our PAC. These

included allowing individuals to withdraw from the study and return later; adding a second tool

halfway through the program (either the recreation center pass or a monthly didactic weight

maintenance support group); and adding educational handouts on general behavioral

approaches to weight loss, including diet and physical activity, for all participants rather than

just those who chose the meal replacement tool. The PAC suggested a number of minor

changes as well, such as the way that study questionnaires were distributed and collected and

how meal replacement plans could be implemented in a way that would fit with subjects’ usual

diets. We provided a “no tool” option, not originally conceptualized, that allowed patients to

stay in the study and meet with staff members even if none of the tools worked for them; these

patients were included in the analysis as having been exposed to the intervention. Finally, we

developed a lost-to-follow-up procedure that included reaching out to providers after patients

had missed a visit and had not responded to 2 calls and a letter. This is more effort than is

typically made in usual practice. We took these steps to maximize our data collection;

furthermore, this level of care could be implemented in a care program focused on weight loss.

We decided to offer monthly weight maintenance didactic/support group meetings as a

stand-in tool for patients who were too busy or not interested in the other tools we offered.

Unfortunately, because only a few Spanish-speaking patients selected the original group

behavioral weight loss tool, we had to close that option; however, we had enough interest in

the Spanish weight maintenance monthly support group to offer that option as a second tool.

We originally thought that PCPs would write the monthly prescriptions for weight loss

medications; however, to ensure that this task was completed in a timely manner without

burdening the PCPs, the study primary investigator wrote these prescriptions on their behalf.

Finally, we decided to provide a 2-month supply of the selected tool to each participant at the

conclusion of the 1-year intervention to help them transition back to usual care and to

26

incentivize previously withdrawn or lost-to-follow-up patients to return for a final visit so we

could measure their weight and get their feedback on an end-of-study questionnaire.

We do not know whether these design choices had a meaningful impact on the study’s

internal or external validity. To have similar effects, a program would likely need to replicate

these aspects. The changes to the protocol were made and approved during the conduct of the

study, and we are not aware of any study protocol violations.

27

RESULTS

Baseline Characteristics of the Study Population

The obesity registry we created for the study consisted of 4730 individuals (68.7% women, 63%

Hispanic or Latino) with a mean age of 52.0 ± 13.8 years and a mean BMI of 35.0 ± 3.9. Of the

428 patients randomly selected from the registry for the intervention arm, 375 (87.6%) were

deemed eligible to participate (Figure 1). Of the eligible patients, we were able to contact 309,

and 140 (45.3% of those contacted) chose to attend an incentivized visit to learn about the

weight loss services being offered through the trial. A total of 119 patients (38.5% of those

contacted) paid an initial copay to begin using an intervention tool. We used this group as the

intervention group for purposes of this analysis, as those who never used a tool would not be

expected to benefit from the intervention. These participants included 83 women (69.7%) and

36 men, 65 (54.6%) participants who self-identified as Hispanic or Latino, and 35 (29.4%) who

spoke Spanish as their primary language. The mean age of the participants (± SD) was 51.0 ±

11.8 years, mean weight was 100.8 ± 19.8 kg, and mean BMI was 36.0 ± 4.2 (Table 1).

The registry-based control group consisted of 4214 patients after exclusion of those in

the focus group arm, those ≥ 80 years old (n = 81), and those who were deceased (n = 7). Those

in the control group who were eligible comparators had to have had a PCP visit (ie, measured

weight) within the same approximate follow-up time window during which the intervention

group began the intervention (± 3 months). On the basis of these criteria, 2930 patients (69.5%

of eligible controls in the registry) had sufficient data available to serve as comparators for the

primary analysis. See Table 1 for baseline demographic information for the eligible controls and

the subjects engaged with the intervention.

Final weights measured within ± 6 months of the 12-month follow-up target date were

available for 90.1% (n = 2640) of the control group who had been seen in a primary care clinic

during the study period and 95.0% (n = 113) of the intervention group. The final weight

28

measurements in the intervention group consisted of 86 captured from those who attended

the final study visit; we selected the rest from their next-nearest study visit within 6 months, or

their nearest weight measurement from a regular DH clinic visit within 6 months of the target

date of their final visit.

Table 1. Baseline Characteristics of Eligible Control Group Versus Engaged Intervention Group

Characteristic

Eligible Controls

(n = 2930)

Engaged in

Intervention

(n = 119)

Sex—number of patients (%)

Female 2064 (70.4) 83 (69.7)

Male 866 (29.6) 36 (30.3)

Race/ethnicity—number of patients (%)

White/Caucasian 2335 (79.7) 98 (82.4)

Black/African American 545 (18.6) 20 (16.8)

Asian 8 (0.3) 0 (0)

Native Indian/Alaskan 0 (0) 1 (0.8)

Other 24 (0.8) 0 (0)

Unknown 18 (0.6) 0 (0)

Hispanic or Latino 1859 (63.4) 65 (54.6)

Primary language

English 2033 (69.4) 84 (70.6)

Spanish 897 (30.6) 35 (29.4)

Age—years 50.9 +/– 13.1 51.0 +/– 11.8

Weight—kg 94.4 +/– 16.1 100.8 +/– 19.8

BMI—kg/m2 35.2 +/– 3.9 36.0 +/– 4.2

BMI category

30-34.9 1612 (55.0) 62 (52.1)

35-39.9 901 (30.8) 32 (26.9)

40-45 417 (14.2) 25 (21.0)

Medical conditions—number of patients (%)

29

Characteristic

Eligible Controls

(n = 2930)

Engaged in

Intervention

(n = 119)

Diabetes, hypertension, or dyslipidemia 2376 (81.1) 99 (83.2)

Diabetes 1350 (46.1) 58 (48.7)

Hypertension 2063 (70.4) 78 (65.5)

Dyslipidemia 1596 (54.5) 63 (52.9)

Insurance

Medicaid 1201 (41.0) 36 (30.3)

Medicare 812 (27.7) 33 (27.7)

CICP/DFAP 761 (26.0) 38 (31.9)

Commercial 90 (3.1) 9 (7.6)

Self-pay/other 66 (2.3) 3 (2.5)

Abbreviations: CICP, Colorado Indigent Care Program; DFAP, Denver Health Financial Assistance Program.

Weight Loss

Intention-to-treat population. We were able to access final weight measurements for N = 113

of the intervention group and n = 2640 of the control group, which enabled us to calculate

whether they had achieved 5% weight loss. At least 5% weight loss was achieved by 39 of 113

(34.5%) of those who initiated treatment (ie, 10% of the randomly selected group) compared

with 415 of 2640 (15.7%) of the control group (P < 0.001). The mean (± SD) weight loss was –3.2

± 6.7 kg and –0.4 ± 5.8 kg in the intervention and control groups, respectively (Table 2). Mean

percentage weight loss was –3.15% ± 6.41% in the intervention group and –0.30% ± 6.10% in

the control group.

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Table 2. Percentage With 5% Body Weight Loss, Mean Weight Loss, and Mean Percentage Weight Loss Over 12 Months

Variable Intervention Group

Control Group P Valuea

Intention-to-Treat Population N = 113 N = 2640

Participants achieving 5% weight loss—

number (%) 39 (34.5) 415 (15.7) P < 0.001

Mean weight change—kg (SD) –3.2 (6.7) –0.4 (5.8) p < 0.001

Mean weight change—% (SD) –3.2 (6.4) –0.3 (6.1) p < 0.001

Per Protocol Population N = 89 N = 2640

Participants achieving 5% weight loss—

number (%) 36 (40.4) 415 (15.7) p < 0.001

Mean weight change—kg (SD) –3.8 (6.7) –0.4 (5.8) p < 0.001

Mean weight change—% (SD) –3.9 (6.4) –0.3 (6.1) p < 0.001

a Chi-square test for categorical variables; t test for continuous variables.

Per protocol and sensitivity analyses. The per protocol analysis (all subjects who attended at

least visit 1) produced similar results, showing that a higher percentage of participants in the

intervention group achieved ≥ 5% weight loss than those in the control group (40.4% vs 15.7%).

Sensitivity analyses to assess the effects of missing data on the percentage of individuals

obtaining 5% weight loss showed similar results. Figure 2 shows the difference in mean weight

change (kg) in the intervention versus control groups.

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Figure 2. Weight change by time and treatment group.

32

In sensitivity analyses including the 21 people who consented to the study but did not attend

visit 1, baseline and final weights from the medical record registry data were available for only

13 participants, bringing the total number of intervention participants analyzed to N = 126. We

observed similar results in the primary ITT analysis, with 40 of 126 (31.8%) participants in the

intervention group achieving the desired weight loss compared with 15.7% in the control group

(P < 0.001).

After adjusting for sex, race/ethnicity, and baseline BMI category in our generalized

linear mixed model, we still observed a significant relationship between treatment group and

weight loss, with participants in the intervention group having 2.66 higher odds of achieving ≥

5% weight loss than those in the control group (95% CI, 1.77-3.99; p < 0.001). Additionally, we

observed that white non-Hispanic participants (OR [odds ratio], 1.96; 95% CI, 1.51-2.53) and

black/other non-Hispanic participants (OR, 1.49; 95% CI, 1.15-1.93) had higher odds of

achieving ≥ 5% weight loss than Hispanic participants (overall P value < 0.001). Participants in a

higher baseline BMI category were more likely to achieve 5% weight loss (BMI 35-<45 vs 30-

<35) (OR, 1.20; 95% CI, 0.97-1.47; P value 0.09), and male participants were less likely than

female participants to lose weight (OR, 0.81; 95%CI, 0.64-1.02; P value 0.08), although these

relationships were not statistically significant (see Appendix C). Participant age and insurance

payer were not associated with the weight loss outcome. We did not observe a significant

correlation among participants at the same clinic.

Secondary Outcomes

Weight loss intervention adoption and use. Of the eligible randomly contacted patients, 119 of

309 (38.5%) selected a weight loss tool and returned 1 to 2 weeks later for their first study visit,

at which they paid a $5 or $10 copay to receive the tool. Initially, the participants chose the

following tools: 42 (35.3%) meal replacements; 34 (27.7%) weight loss medications (1

phentermine, 33 phentermine/topiramate ER); 26 (21.8%) recreation center passes; 8 (6.7%)

Weight Watchers vouchers; 6 (5.0%) group behavioral weight loss class (Colorado Weigh); and 2

(1.7%) none of the tools (ie, clinical visits only). Over the course of the study, participants used

the following numbers of tools: 51 (42.9%) used 1 tool; 52 (43.7%) used 2 tools; 14 (11.8%)

33

used 3 tools; and 1 (0.8%) used 4 tools. The option to add a second tool at 6 months was

chosen by 35 119 (29.4%) of participants. Phentermine/topiramate ER use accounted for an

increasing percentage of the tools selected as the study progressed, whereas selection of the

meal replacement and recreation center options appeared to decline over time (Figure 3 and

Table 3). Appendix F shows how baseline demographic variables related to the initial choice of

tools.

Figure 3. Tools selected at each visit.

34

To better understand how the use of weight loss services in the intervention group differed

from the weight loss care provided during usual primary care visits at DH, we performed chart

reviews on 120 randomly selected patients from the eligible registry-based control group. We

reviewed these patients’ primary care visit notes over a 12-month period, starting with the

weight measurement closest in time to the creation of the patient registry. We found that

obesity was defined as a problem for only 52 of 120 (43.3%) patients, and 55 of 120 (45.8%)

charts included evidence that a discussion about weight took place between patient and

provider. Weight loss services similar to those in our study had been provided to 11.7% of

eligible control patients and to 45% of those in the intervention (these patients received

information on evidence-based weight loss tools). Specifically, charts suggested that 3 of 120

(2.5%) received a weight loss medication, 4 of 120 (3.3%) received information about

commercial weight loss programs, 2 of 120 (1.7%) discussed gym membership, 0 of 120 (0%)

received information about meal replacements, and 5 of 120 (4.2%) were referred to a weight

management specialist or a structured program. Diet and exercise handout materials were the

most commonly identified intervention provided in the clinics—58 of 120 (48.3%) charts noted

that these materials had been disseminated.

35

Table 3. Tools Selected at Each Visit in the Intervention Group (%)a

a Percentage values represent those who attended that visit, not those who initiated treatment.

Visit attendance. We had final weight date on 113 participants, which meant we could include

them in the primary ITT analysis: 82 of 113 (72.6%) attended more than 4 of a possible 12

weight management visits, and 54 of 113 (47.8%) attended more than 8 visits during their 12-

month enrollment in the trial. There appeared to be a correlation between number of visits

attended and likelihood of losing 5% or more of initial body weight. Specifically, 5% weight loss

was achieved in 6.9% of those who attended 1 to 4 visits, 15.2% who attended 5 to 8 visits,

24.6% who attended 9 to 11 visits, and 53.3% who attended 12 visits (Figure 4). Of the 119

participants who attended the first visit, 23 made use of the interim visits, with 21 participants

attending 1 interim visit and 2 participants attending 3 interim visits. Because the study design

included 12 scheduled visits, only the non-study visits would be comparable between the

control and intervention groups. On the basis of a negative binomial regression model, there is

36

no difference in the mean number of visits during the 12-month follow-up; specifically, the

mean number of visits in the control group is 4.32 (95% CI, 4.2-4.43) versus 4.44 (95% CI, 3.89-

5.06) in the intervention group.

Figure 4. Proportion of intervention group who achieved > 5% weight loss by number of visits attended.

Relationship of tool selection to achieving clinically meaningful weight loss. Although the

study was not powered to observe differences in weight loss outcomes between the individual

components of the toolbox intervention, post hoc analyses suggest that use of certain elements

of the toolbox was associated with a greater likelihood of achieving clinically meaningful weight

loss at 12 months. Specifically, 22 of 35 (62.9%) patients who added a second tool and 25 of 45

37

(55.6%) patients who used phentermine/topiramate ER or phentermine alone at any point

during the study lost 5% or more of their initial body weight. This finding compares with lower

rates of weight loss achievement when other tools were used: 15 of 55 (27.3%) with meal

replacement and 21 of 55 (38.2%) with recreation center passes (Table 4).

Table 4. Relationship of Specific Tool Exposure to Weight Loss in the Intervention Group

Lost 5% of Initial

Weight?

Measure Response Statistics No

(N = 74) Yes

(N = 39) Overall

(N = 113) P Valuea

Ever selected meal replacements No N (%)b 34 (58.6%) 24 (41.4%) 58 (51.3%) 0.11

Yes 40 (72.7%) 15 (27.3%) 55 (48.7%)

Ever selected recreation center No N (%) 40 (69.0%) 18 (31.0%) 58 (51.3%) 0.42

Yes 34 (61.8%) 21 (38.2%) 55 (48.7%)

Ever selected Qsymia/phentermine No N (%) 54 (79.4%) 14 (20.6%) 68 (60.2%) <0.001

Yes 20 (44.4%) 25 (55.6%) 45 (39.8%)

Added second tool No N (%) 61 (78.2%) 17 (21.8%) 78 (69.0%) <0.001

Yes 13 (37.1%) 22 (62.9%) 35 (31.0%)

Exposure to medication or meal

replacements

Neither N (%) 25 (83.3%) 5 (16.7%) 30 (26.5%) <0.001

Medications 9 (32.1%) 19 (67.9%) 28 (24.8%)

Meal replacements 29 (76.3%) 9 (23.7%) 38 (33.6%)

Both 11 (64.7%) 6 (35.3%) 17 (15.0%)

a Chi-square test. b Percentages (%) are row percentages.

Provider Survey Results

Eighty PCPs (71% female, 71% physicians) completed the preintervention survey (pre), and 82

PCPs (66% female, 70% physicians) completed the postintervention survey (post). Before the

38

trial, PCPs were most comfortable discussing exercise (median 8, interquartile range [IQR] 7-9),

and this did not change after the trial (P = 0.71). PCPs were least comfortable discussing

phentermine/topiramate ER (4, 2-6) but had a significantly increased comfort level after the

trial (pre 3, 1.5-6; post 5, 3-7; P < 0.001). PCP-I drove this increased comfort level (P < 0.001)

rather than PCP-C (P = 0.17). PCP-I also became more comfortable discussing phentermine (pre

7, 4-8; post 8, 7-9; P = 0.026). After the trial, PCPs collectively gave higher effectiveness ratings

to phentermine/topiramate ER (pre 5, 3-6; post 7, 5-8; P < 0.001). PCP-I eventually rated

exercise less effective (pre 7, 4-8.5; post 5, 3-7; P = 0.035) and phentermine more effective (pre

5, 5-7; post 7, 6-8; P < 0.001).

Adverse Events

We collected data on adverse events in the intervention group in a manner consistent with how

care is delivered in real-world clinical environments rather than in a systematic way, as done in

more explanatory trials. Of the 140 patients who attended an initial incentivized visit, none

experienced serious adverse events related to the intervention during the course of the trial.

One patient died and one had a stroke during the trial, but both events were determined by the

data safety monitoring committee to be unrelated to the intervention. Minor adverse events

were reported in 10 of 140 (7.14%) study participants, most related to the use of

phentermine/topiramate ER: eye pain (1 event), gastroesophageal reflux disease (1), fainting

(1), chest pain (1), depression (1), and anxiety (1) (see Appendix G).

39

DISCUSSION

Decisional Context

Health care organizations and payers are struggling to deal with America’s obesity epidemic.

RCTs have shown that several different interventions might produce 5% to 10% weight loss, a

degree of weight reduction associated with significant improvements in several obesity-related

conditions. However, currently little weight management care is provided in routine clinical

environments. Despite widespread recognition that obesity-related morbidity is a major driver

of health care costs, few health care delivery systems are attempting to tackle obesity in a

comprehensive and systematic way by providing evidence-based medical treatment options.

Administrators’ decisions about the provision of weight management services are hindered by a

lack of real-world evidence about patient use of services and outcomes when these services are

provided. Administrators will likely need detailed cost–benefit data before they will make an

investment in a program like this, but we did not perform this type of analysis because it is not

allowed using PCORI funding.

Study Results in Context

The principal finding of this study was that 34.5% of a randomly selected group of

socioeconomically disadvantaged patients with obesity who were offered a variety of low-cost

medical weight loss interventions achieved clinically meaningful weight loss (≥5% of initial body

weight) at 12 months. This was a highly significant difference compared with usual care

comparators: Only 15.7% of patients in a registry lost this amount of weight. In fact, weight loss

in the control group might very well be an overestimate, as many of these patients likely lost

weight unintentionally (ie, owing to illness). A previous randomized trial conducted in primary

care by Wadden et al (POWER-UP) found that a combination of quarterly PCP visits, brief

monthly lifestyle coaching, and meal replacements or weight loss medication resulted in 34.9%

of patients losing 5% of body weight or more over 24 months,42 compared with 26% of patients

who received only brief lifestyle counseling and 21.5% who received usual care. In comparison

with our study, POWER-UP had more stringent inclusion and exclusion criteria; the usual care

40

control group received more weight management support than would typically be provided (to

keep subjects in the study); and weight loss treatment enhancements were free to study

participants. Our study provides evidence of how many randomly selected patients who are

obese and have a weight-related comorbidity would seek and pursue weight loss treatments if

they were required to attend monthly follow-up sessions and pay monthly copays of $5 or $10.

Secondary outcomes in our trial focused on the use of the weight loss services offered.

This is an area of great interest to administrative stakeholders but it has not been explored in

clinical weight loss trials. Overall, the study showed that interest in receiving services to lose

weight within the primary care setting was moderate among a group of randomly selected

patients with obesity: 45.3% of contacted patients attended an initial incentivized visit to learn

more about the evidence-based treatment options, and 38.5% of contacted patients engaged

with the intervention by selecting an option and paying a copay for a weight loss intervention.

This level of treatment is significantly higher than that in the usual care comparator group, in

which only 11.7% of patients received any information about even one evidence-based

treatment option. Patient engagement, as measured by visit attendance, was strong: Nearly

half of the patients included in the final analysis attended 8 or more visits over the 12-month

study period. The number of visits per year needed to optimize the percentage of patients who

achieve clinically meaningful weight loss is not known, but our study suggests that when

patients are allowed to choose from a variety of low-cost treatment options, a large percentage

will meet this benchmark despite less than perfect attendance at monthly visits.

Little is known about patient preferences for specific weight loss interventions when a

variety of options are offered simultaneously as first-line therapy. We found that more than

80% of patients who were offered the toolbox intervention initially chose 1 of 3 medical weight

loss options: meal replacements, anti-obesity pharmacotherapy, or recreation center passes.

Few patients initially chose the behavioral weight loss options, perhaps because they

had engaged in these types of programs before (behavioral programs are the most commonly

offered weight loss interventions). Almost a third of patients chose to pay a second copay so

41

they could use 2 interventions; of those, almost two-thirds lost more than 5% of initial body

weight.

Implementation of Study Results

This study demonstrated that when evidence-based weight loss tools are offered to an

unselected group of obese patients with a weight-related comorbidity, patients are likely to use

them. Patients favored certain tools: meal replacements, anti-obesity pharmacotherapy

(specifically phentermine/topiramate ER, which has greater weight loss efficacy than

phentermine alone), and recreation center passes. This suggests that a similar program could

eliminate the interventions that fewer of our patients chose yet still achieve high rates of

clinically significant weight loss. Group behavioral interventions have a strong evidence base,

but they are expensive to implement and seem to be selected infrequently when other options

are available. Use of anti-obesity pharmacotherapy and the addition of a second tool after a

period of sustained engagement seemed to be associated with the highest rates of weight loss

success; therefore, these options should be strongly considered in designing future toolbox-like

interventions. Barriers to wider adoption of anti-obesity pharmacotherapies include cost, lack

of insurance coverage, patient and provider concerns about the safety of these agents, and lack

of provider knowledge about the medications. Thus, despite their popularity in this study, it

might be especially challenging to implement medication-based clinical weight loss

interventions without novel care delivery systems and changes to reimbursement. In this study,

PCP participation varied: Some providers actively supported their patients’ weight loss efforts,

while others played a more passive role. It was clear that PCPs were very busy and appreciated

the support of study staff and that it would be difficult for them to take on the duties that study

staff assumed without changes to their other responsibilities. This important finding suggests

that relying exclusively on PCPs to implement these strategies will probably not work.

The consensus among the PAC participants at the conclusion of the study was that the

toolbox project was a valuable and important weight loss initiative that offered a good variety

of options for assistance, education, and support to patients seeking to lose weight.

Participants were excited, optimistic, and hopeful that the DH administration would

42

incorporate many parts of the toolbox strategy into the organization’s ongoing approach to

helping patients manage their weight. The participants offered their assistance in making this

case to the administration of the hospital. Ultimately, patient advocacy could be important in

the dissemination of a program like this one.

Administrators and providers in community health have formed a task force to examine

the overall approach to the clinical problem of obesity at DH, and one of the nonintervention

clinics has implemented a new intervention. In March 2017, a new CEO was appointed to lead

DH. The toolbox team presented the findings of this study to management in spring 2018. It is

likely that cost–benefit data will be needed to convince administrators to invest in a program

like this one, but this type of analysis is not permitted with the funding we received from

PCORI.

Generalizability

This study took place in Denver’s primary safety net health care system, in which most patients

are of low socioeconomic status. Despite being at a financial disadvantage, patients were

willing to pay monthly copays that were similar in price to what they might pay for insurance-

covered medications for medical weight loss interventions. One might therefore presume that a

similar program implemented in a more affluent population might result in even higher rates of

utilization of weight loss services than those in this study. Most of the participants were women

(this has been seen in many weight loss studies) and ethnic minorities. As a result, these

findings apply only to these groups.

Although generally pragmatic in nature, this study did use several clinical resources that

are not typically available in primary care settings. Study visits were conducted by study staff

rather than by staff already available at the intervention clinics. However, the study was

conceived with the notion that, in a real-world setting, patient navigators could assume this

role. Counseling and prescribing were conducted by study staff rather than PCPs. This is not

standard for weight loss treatments, but it is similar to diabetes care in some primary care

clinics, where pharmacists manage medications under the supervision of PCPs and diabetes

43

educators provide education and behavioral support. Implementation science research would

be required to ensure that the tested intervention could be translated into diverse clinical

settings with varying degrees of resource availability.

Subpopulation Considerations

This intervention was not powered to evaluate the effectiveness of individual tools and

strategies in the weight management toolbox, but we found some evidence suggesting that

study participants preferred and had greater weight loss with certain tools. It is possible that

unique subgroups of patients do better with specific weight loss tools or combinations of tools,

but a much larger trial would be needed to identify these predictors.

A small group of our patients lost > 10% of body weight and can thus be considered

successful outliers. These individuals tended to use weight loss medications, attend follow-up

visits regularly, and adopt a second tool during the second 6 months of the study. This trial was

small and of limited duration, but heterogeneity of treatment response existed, and it would be

beneficial to explore this in greater depth in larger trials.

Study Limitations

The study was not strictly an RCT. Subject selection was random, but the intervention was

implemented at only 4 of 8 available sites. The intervention sites were not selected at random,

which might have introduced bias. However, data regarding patient characteristics at

intervention and control clinics suggest that this was not a major problem. Because some sites

included both intervention and control participants, some contamination could have occurred

through providers offering more weight loss counseling than usual care. However, a manual

chart review allowed us to estimate that the rate at which participants in the control group had

been offered medical weight loss treatment was low (11.7%, compared with 45% in the

intervention group); thus, we believe that contamination was minimal.

The window for collecting weight data in the comparator group was longer than that for

the intervention group and longer than that used in a typical RCT. This study was of short

44

duration, so the potential for long-term weight loss maintenance or additional weight loss after

12 months in the setting of this intervention is not known.

We learned that conducting a trial in a very pragmatic manner (in which usual care is

relied on to acquire laboratory data) involves significant limitations. Although much is known

about the benefits of weight loss for cardiometabolic risk factors, we thought we would be able

to observe improvements in commonly collected clinical measures such as HbA1C and lipid

levels. Unfortunately, the variable manner in which clinical data were collected during routine

care resulted in a high level of missing data, which prevented us from evaluating changes in

these variables over time.

Similarly, inconsistent collection of medication information and limited medication

reconciliation systems in routine clinical practice prevented us from evaluating changes in

medication use by individual participants over the course of the study.

Denver Health is a unique health care organization that serves an ethnically diverse and

generally socioeconomically disadvantaged population. In addition, most of the subjects in the

study were women. Therefore, it is difficult to predict how our intervention might translate into

other clinical settings in other health care organizations. In this design (in which patients select

from among various strategies) we could not determine whether the strategy caused specific

effects or whether those effects were due to unmeasured differences among the patients who

selected different options. For example, perhaps those who selected meal replacements have

greater food insecurity or those who selected gym memberships have more transportation

options (and other resources). The effects might be because of a wide range of subject

variables rather than just the program or the tool selected.

Future Research

We believe that future research into a number of areas related to our study’s findings would be

useful to the field of clinical obesity management. As mentioned in the study limitations

section, a larger trial of longer duration in more diverse clinical environments (cluster

randomized design) would provide more comprehensive information about this strategy to

45

inform decision making by health care system administrators. Such a study, if carefully

designed, could provide information about the effect of medical weight loss on comorbid

conditions and cardiovascular risk factors, and could enable researchers to determine the

effectiveness of individual components of the toolbox intervention. It could also provide more

information about predictors of success for certain patient subpopulations with specific tools or

combinations of tools. Such knowledge would enable clinicians to better tailor weight loss

interventions to individual patients.

Data gathered about the use of anti-obesity medications in this study were particularly

interesting, as little is known about the use and effectiveness of FDA-approved anti-obesity

medications in real-world settings. Our trial showed that the fraction of patients using

phentermine/topiramate ER increased over the course of the study and that a larger

percentage of patients who ever used this medication achieved 5% or more of weight loss in

comparison with the other available interventions. This result is not surprising given available

RCT data that phentermine/topiramate ER is predicted to produce more weight loss than the

other medical interventions included in this study. However, the finding that patients chose

medications at a high level initially and throughout the trial highlights a significant gap in

obesity management care between the treatment patients desire and choose and what they

are actually offered in the real world: Only about 1% of patients with obesity are treated with

medications in practice,43 but about 40% of our study participants chose to use

phentermine/topiramate ER at some point during the study.

Implementation science research will ultimately be required to help integrate this trial

or similar clinical weight loss interventions into different clinical settings. We foresee that the

toolbox intervention could easily be tailored to individual practice settings, depending on local

differences in resource availability; subsidization opportunities; and the values of patients,

providers, and administrators.

46

CONCLUSIONS

Offering a toolbox of low-cost, broadly available weight loss interventions to a randomly

selected group of patients with obesity and at least one weight-related comorbidity resulted in

more than twice as many people achieving 5% or more weight loss at 12 months compared

with patients who received usual care. Patients were interested in this intervention (as

evidenced by moderate levels of engagement) and they showed a preference for certain

treatment modalities.

As with all pragmatic trials, a balance must be struck between external and internal

validity. In this study, external validity was optimized by having few exclusion criteria, providing

the intervention in a diverse population with many comorbid conditions, and allowing patients

to choose among several possible interventions. Internal validity was maintained by precise

measurement of the primary outcome (weight) in the intervention group. However, we did not

attempt to rigorously measure all possible confounding variables that could affect weight,

because the care provided was meant to mimic usual care settings. Furthermore (although this

is unlikely to have occurred at a high rate), it is possible that internal validity was compromised

to some extent if patients in the control group heard about the weight loss intervention and

decided to increase their own weight loss efforts or if providers in the intervention clinics

changed their usual practice in response to their experience with the intervention.

From the perspective of health care organization administration, this study provides

practical evidence about how a population with a high degree of obesity-related comorbidities

uses a diverse offering of medical weight management services and how using those services

affects that population’s ability to achieve clinically meaningful weight loss. For providers who

are skeptical about the potential success of providing weight management services, this study’s

results show that many patients are interested in receiving weight management services in the

primary care setting and that making weight loss interventions more readily available can result

in clinically significant weight loss that is sustained for a year in a third of these patients.

47

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52

APPENDICES

Appendix A: Description of Offered Weight Loss Tools

Weight Loss Tool Description of Intervention

Anticipated Percentage Weight Loss from Baseline1

Cost to Patient Per Month

Partial Meal Replacements

30 portion-controlled entrees and 60 low-calorie shakes provided per month. Individuals are encouraged to supplement meal replacements with 2 servings of fruit and at least 3 servings of vegetables daily. (Weight Management Services HMR Boston MA.)

5-8% $10

Recreation Center passes A monthly pass allowing for up to 30 visits per month. These facilities have equipment for cardiovascular training, weight training, a pool, and formal exercise instruction (eg, aerobics, yoga). During the time of the study recreation centers were available throughout the Denver metropolitan area and pass membership allowed for visits at any location.

Variable $5

Phentermine FDA-approved weight loss medication. The initial dose was 15mg daily, with a blood pressure follow up visit in 4 weeks. The dose was escalated to 30mg per day after 4 weeks and depended on patient preference, a loss of at last 2% of initial weight, and no significant increase in blood pressure or pulse. Standard contraindications and precautions were followed in prescribing the drug.

3-5% $5

53

Phentermine/topiramate ER (Qsymia)

FDA-approved weight loss medication. Dose titration and discontinuation were followed per prescribing guidelines. A dose of phentermine 3.75 mg/topiramate 23 mg extended-release once daily for 14 days and then an increase to 7.5 mg/46 mg once daily. If at 12 weeks of treatment the patient had not lost at least 3% of baseline body weight the medication was either discontinued or the dose was escalated to 11.25 mg/69 mg daily for 14 days and then 15 mg/92 mg once daily. After 12 weeks, if at least 5% of baseline body weight had not been lost the medication was discontinued.

8-10% $10

Weight Watchers vouchers

Largest commercial behavioral weight loss program in the U.S. Monthly pass to 4 meetings per month.

5-6% $5

Group Behavioral Weight Loss Program (“Colorado Weigh program based on the Diabetes Prevention Program or DPP)

A three-phase group behavioral weight loss program. Phase 1 is aimed at producing weight loss (1-2 pounds/week). Phase 2 helps patients transition between weight loss and weight loss maintenance. Phase 3 is focused on weight loss maintenance. Participants meet weekly for 12 weeks, then biweekly for 12 weeks, and then once monthly up to one year.

8-10% $10 for first 3 months, then $5 per month

1 During the initial study visit, patients were provided with information about the best estimate of the weight loss that might be expected should they adhere to each listed intervention. This information was also provided each time the participant chose to switch tools during the course of the study.

54

Appendix B: Baseline Characteristics of Registry Cohort and Those

Randomized to Intervention and Control Groups

Characteristic

Total Registry (n=4730)

Intervention (n=428) Control (n=4302)

Sex -- number of patients (%) Female 3248 (68.7) 268 (62.6) 2980 (69.3) Male 1482 (31.3) 160 (37.4) 1322 (30.7) Race or ethnic group- number of patients (%) White/Caucasian 3785 (80.0) 351 (82.0) 3434 (79.8) Black/African American 861 (18.2) 72 (16.8) 789 (18.3) Asian 12 (0.3) 0 (0) 12 (0.3) Native Indian/Alaskan 1 (0.0) 1 (0.2) 0 (0) Other 36 (0.8) 0 (0) 36 (0.8) Unknown 35 (0.7) 4 (0.9) 31 (0.7) Hispanic or Latino 2982 (63.0) 257 (60.0) 2725 (63.3) Primary Language English 3247 (68.6) 313 (73.1) 2934 (68.2) Spanish 1483 (31.4) 115 (26.9) 1368 (31.8)

Age -- years 51.0 +/- 13.8 52.7 +/- 13.1 50.8 +/- 13.8

Body Mass Index (BMI) 35.0 +/- 3.9 35.1 +/- 3.9 35.0 +/- 3.9 BMI category 30-34.9 2713 (57.4) 247 (57.7) 2466 (57.3) 35-39.9 1366 (28.9) 125 (29.2) 1241 (28.8) 40-45 651 (13.8) 56 (13.1) 595 (13.8) Medical conditions -- number of patients (%)

55

Diabetes, hypertension, or dyslipidemia 3802 (80.4) 349 (81.5) 3453 (80.3) Diabetes 2093 (44.2) 190 (44.4) 1903 (44.2) Hypertension 3247 (68.6) 299 (69.9) 2948 (68.5) Dyslipidemia 2503 (52.9) 233 (54.4) 2270 (52.8) Insurance Medicaid 1237 (40.6) 36 (30.3) 1201 (41.0) Medicare 845 (27.7) 33 (27.7) 812 (27.7) CICP2/DFAP3 799 (26.2) 38 (31.9) 761 (26.0) Commercial 99 (3.2) 9 (7.6) 90 (3.1) Self pay/other 69 (2.3) 3 (2.5) 66 (2.3)

2 Colorado Indigent Care Program (CICP) 3 Denver Health Financial Assistance Program (DFAP)

56

Appendix C: Subgroup Analysis Odds of Achieving 5% Body Weight Loss

Effect Comparison Adjusted1 Odds Ratio (95% CI)

P-value

Intervention Group

Intervention vs. Control 2.66 (1.77, 3.99) <0.001

Race/Ethnicity Black/Other Non-Hispanic vs. Hispanic

1.49 (1.15, 1.93) <0.001

White Non-Hispanic vs. Hispanic

1.96 (1.51, 2.53)

Sex Male vs. Female 0.81 (0.64, 1.02) 0.08 Baseline BMI 35<45 vs 30 <35 1.20 (0.97, 1.47) 0.09

1Estimated via generalized linear mixed model with random effect for clinic.

57

Appendix D: Subgroup Analysis Proportion with 5% Body Weight Loss

by Intervention Group, Race/Ethnicity, and Baseline BMI

ITT: Lost >5% of initial body weight Total

No Yes

N (Row %) N (Row %) N (%)

Race/Ethnicity Study Group

14 (70.0%) 6 (30.0%) 20 (0.7%) Black/Other

Non-Hispanic

Tool

Control 415 (81.2%) 96 (18.8%) 511 (18.6%)

Total 429 (80.8%) 102 (19.2%) 531 (19.3%)

White

Non-Hispanic

Study Group

19 (59.4%) 13 (40.6%) 32 (1.2%) Tool

Control 339 (77.2%) 100 (22.8%) 439 (15.9%)

Total 358 (76.0%) 113 (24.0%) 471 (17.1%)

Hispanic Study Group

41 (67.2%) 20 (32.8%) 61 (2.2%) Tool

Control 1471 (87.0%) 219 (13.0%) 1690 (61.4%)

Total 1512 (86.4%) 239 (13.6%) 1751 (63.6%)

Baseline BMI Study Group

30-<35 Tool 42 (71.2%) 17 (28.8%) 59 (2.1%)

Control 1236 (85.5%) 210 (14.5%) 1446 (52.5%)

Total 1278 (84.9%) 227 (15.1%) 1505 (54.7%)

58

ITT: Lost >5% of initial body weight Total

No Yes

N (Row %) N (Row %) N (%)

35-<45 Study Group

Tool 32 (59.3%) 22 (40.7%) 54 (2.0%)

Control 989 (82.8%) 205 (17.2%) 1194 (43.4%)

Total 1021 (81.8%) 227 (18.2%) 1248 (45.3%)

59

Appendix E: Sensitivity Analyses for Primary Outcome of Percentage

Achieving 5% or More Weight Loss

Analysis Performed -- no.

(%)

Intervention Group

(n=119)

Control Group

(n=2930)

Total

(n=3049) p-value1

1) Assumed missing weights

meant <5% weight loss

achieved 39 (32.8) 415 (14.2) 454 (14.9) <0.001

2) Used last observation

carried forward 39 (32.8) 435 (14.8) 474 (15.5) <0.001

3) Used nadir weight 54 (45.4) 643 (21.9) 697 (22.9) <0.001

1Chi-square test

60

Appendix F: Choice of Tool at Visit 1 by Demographic Characteristics

Meal

Replacements

Recreation

Center

Voucher Qsymia Phentermine

Colorado

Weigh

Weight

Watchers

DPP1

Maintenance

Support

Group None

N=number (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%)

Total 42 (100.0%) 26 (100.0%) 33 (100.0%) 1 (100.0%) 6 (100.0%) 8 (100.0%) 1 (100.0%) 2 (100.0%)

Race/Ethnicity

3 (7.1%) 10 (38.5%) 4 (12.1%) 0 (0%)

Black

Non-Hispanic 1 (16.7%) 1 (12.5%) 0 (0%) 1 (50.0%)

White

Non-Hispanic 9 (21.4%) 3 (11.5%) 10 (30.3%) 0 (0%) 5 (83.3%) 5 (62.5%) 0 (0%) 1 (50.0%)

Other

Non-Hispanic 0 (0%) 0 (0%) 1 (3.0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%)

Hispanic 30 (71.4%) 13 (50.0%) 18 (54.5%) 1 (100.0%) 0 (0%) 2 (25.0%) 1 (100.0%) 0 (0%)

Gender

16 (38.1%) 11 (42.3%) 5 (15.2%) 1 (100.0%)

Male 0 (0%) 2 (25.0%) 0 (0%) 1 (50.0%)

Female 26 (61.9%) 15 (57.7%) 28 (84.8%) 0 (0%) 6 (100.0%) 6 (75.0%) 1 (100.0%) 1 (50.0%)

Baseline Body

Mass Index

(BMI)

21 (50.0%) 19 (73.1%) 14 (42.4%) 0 (0%)

30-<35 3 (50.0%) 4 (50.0%) 1 (100.0%) 0 (0%)

35-<40 10 (23.8%) 6 (23.1%) 11 (33.3%) 1 (100.0%) 1 (16.7%) 2 (25.0%) 0 (0%) 1 (50.0%)

40-<45 11 (26.2%) 1 (3.8%) 8 (24.2%) 0 (0%) 2 (33.3%) 2 (25.0%) 0 (0%) 1 (50.0%)

Insurance

12 (28.6%) 8 (30.8%) 14 (42.4%) 0 (0%)

Medicaid 0 (0%) 2 (25.0%) 0 (0%) 0 (0%)

61

Meal

Replacements

Recreation

Center

Voucher Qsymia Phentermine

Colorado

Weigh

Weight

Watchers

DPP1

Maintenance

Support

Group None

N=number (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%)

Medicare 11 (26.2%) 4 (15.4%) 8 (24.2%) 0 (0%) 5 (83.3%) 2 (25.0%) 1 (100.0%) 2 (100.0%)

CICP2/DFAP3 16 (38.1%) 11 (42.3%) 7 (21.2%) 1 (100.0%) 0 (0%) 3 (37.5%) 0 (0%) 0 (0%)

Commercial

(including

Denver

Health) 3 (7.1%) 1 (3.8%) 3 (9.1%) 0 (0%) 1 (16.7%) 1 (12.5%) 0 (0%) 0 (0%)

Self pay/Other 0 (0%) 2 (7.7%) 1 (3.0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%)

1Diabetes Prevention Program (DPP) 2Colorado Indigent Care Program (CICP) 3Denver Health Financial Assistance Program (DFAP)

62

Appendix G: Adverse Events

Adverse Event Total Events

Eye pain1 1/140 (0.71%)

Gastroesophageal

reflux disease1 1/140 (0.71%)

Fainting1 1/140 (0.71%)

Chest pain1 1/140 (0.71%)

Depression1 1/140 (0.71%)

Anxiety/chest pain1 1/140 (0.71%)

Stroke2 1/140 (0.71%)

Alcohol withdrawal2 2/140 (1.43%)

Death2 1/140 (0.71%) 1In patients using phentermine-topiramate ER

2Unrelated to study enrollment and interventions

63

Appendix H: Demographic Characteristics by Clinic–Intervention Clinic (I)1 or Control Clinic(C)2

Clinic 1I1 Clinic 2C 2 Clinic 3C Clinic 4C Clinic 5C Clinic 6I Clinic 7I Clinic 8I Clinic 9C

N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%)

Total 762 (100.0%) 623 (100.0%) 263 (100.0%) 331 (100.0%) 437 (100.0%) 811 (100.0%) 107 (100.0%) 1004 (100.0%) 392 (100.0%)

Gender

271 (35.6%) 196 (31.5%) 72 (27.4%) 94 (28.4%) 144 (33.0%) 275 (33.9%) 40 (37.4%) 282 (28.1%) 108 (27.6%) Male

Female 491 (64.4%) 427 (68.5%) 191 (72.6%) 237 (71.6%) 293 (67.0%) 536 (66.1%) 67 (62.6%) 722 (71.9%) 284 (72.4%)

Baseline BMI

428 (56.2%) 334 (53.6%) 158 (60.1%) 216 (65.3%) 245 (56.1%) 470 (58.0%) 60 (56.1%) 593 (59.1%) 209 (53.3%) 30-<35

35-<40 223 (29.3%) 209 (33.5%) 74 (28.1%) 81 (24.5%) 115 (26.3%) 236 (29.1%) 31 (29.0%) 275 (27.4%) 122 (31.1%)

40-<45 111 (14.6%) 80 (12.8%) 31 (11.8%) 34 (10.3%) 77 (17.6%) 105 (12.9%) 16 (15.0%) 136 (13.5%) 61 (15.6%)

Race

0 (0%) 1 (0.2%) 2 (0.8%) 0 (0%) 0 (0%) 5 (0.6%) 1 (0.9%) 2 (0.2%) 1 (0.3%) Asian

Black/African American 290 (38.1%) 16 (2.6%) 111 (42.2%) 79 (23.9%) 200 (45.8%) 95 (11.7%) 19 (17.8%) 42 (4.2%) 9 (2.3%)

Native Indian/Alaskan 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 1 (0.1%) 0 (0%) 0 (0%) 0 (0%)

White/Caucasian 458 (60.1%) 598 (96.0%) 148 (56.3%) 251 (75.8%) 234 (53.5%) 690 (85.1%) 85 (79.4%) 948 (94.4%) 373 (95.2%)

Other 5 (0.7%) 6 (1.0%) 1 (0.4%) 1 (0.3%) 1 (0.2%) 9 (1.1%) 2 (1.9%) 7 (0.7%) 4 (1.0%)

64

Clinic 1I1 Clinic 2C 2 Clinic 3C Clinic 4C Clinic 5C Clinic 6I Clinic 7I Clinic 8I Clinic 9C

N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%)

Unknown 9 (1.2%) 2 (0.3%) 1 (0.4%) 0 (0%) 2 (0.5%) 11 (1.4%) 0 (0%) 5 (0.5%) 5 (1.3%)

Ethnicity

1 (0.1%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) Missing

Non- Hispanic or Latino 416 (54.6%) 106 (17.0%) 187 (71.1%) 109 (32.9%) 258 (59.0%) 339 (41.8%) 62 (57.9%) 207 (20.6%) 63 (16.1%)

Hispanic or Latino 345 (45.3%) 517 (83.0%) 76 (28.9%) 222 (67.1%) 179 (41.0%) 472 (58.2%) 45 (42.1%) 797 (79.4%) 329 (83.9%)

Race/Ethnicity

288 (37.8%) 16 (2.6%) 110 (41.8%) 79 (23.9%) 195 (44.6%) 95 (11.7%) 19 (17.8%) 40 (4.0%) 9 (2.3%)

Black

Non-Hispanic

White

Non-Hispanic 120 (15.7%) 83 (13.3%) 74 (28.1%) 29 (8.8%) 63 (14.4%) 230 (28.4%) 40 (37.4%) 157 (15.6%) 50 (12.8%)

Other

Non-Hispanic 9 (1.2%) 7 (1.1%) 3 (1.1%) 1 (0.3%) 0 (0%) 14 (1.7%) 3 (2.8%) 10 (1.0%) 4 (1.0%)

Hispanic 345 (45.3%) 517 (83.0%) 76 (28.9%) 222 (67.1%) 179 (41.0%) 472 (58.2%) 45 (42.1%) 797 (79.4%) 329 (83.9%)

Primary Language

596 (78.2%) 409 (65.7%) 213 (81.0%) 152 (45.9%) 308 (70.5%) 592 (73.0%) 107 (100.0%) 616 (61.4%) 254 (64.8%) English

65

Clinic 1I1 Clinic 2C 2 Clinic 3C Clinic 4C Clinic 5C Clinic 6I Clinic 7I Clinic 8I Clinic 9C

N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%) N (%)

Spanish 166 (21.8%) 214 (34.3%) 50 (19.0%) 179 (54.1%) 129 (29.5%) 219 (27.0%) 0 (0%) 388 (38.6%) 138 (35.2%)

Insurance

Medicaid 312 (40.9%) 276 (44.3%) 118 (44.9%) 136 (41.1%) 155 (35.5%) 308 (38.0%) 15 (14.0%) 389 (38.7%) 168 (42.9%)

Medicare 216 (28.3%) 182 (29.2%) 61 (23.2%) 47 (14.2%) 96 (22.0%) 235 (29.0%) 26 (24.3%) 288 (28.7%) 77 (19.6%)

CICP 3 // DFAP 4 198 (26.0%) 133 (21.3%) 70 (26.6%) 131 (39.6%) 158 (36.2%) 227 (28.0%) 8 (7.5%) 291 (29.0%) 130 (33.2%)

Commercial (including Denver Health) 16 (2.1%) 14 (2.2%) 9 (3.4%) 9 (2.7%) 10 (2.3%) 25 (3.1%) 53 (49.5%) 17 (1.7%) 4 (1.0%)

Self pay/Other 20 (2.6%) 18 (2.9%) 5 (1.9%) 8 (2.4%) 18 (4.1%) 16 (1.9%) 5 (4.7%) 19 (1.9%) 13 (3.3%)

1 Intervention Clinic (I) 2 Control Clinic (C) 3 Colorado Indigent Care Program (CICP) 4 Denver Health Financial Assistance Program (DFAP)

66

Appendix I: Characteristics of Intervention-Eligible Participants, Comparing Those Who Consented

and Attended the 1st Visit vs. Those Who Declined or Did Not Respond

Intervention Eligible

Measure Response Statistics

Attended 1st visit

(N=119)

Declined/No response (N=256)

Overall (N=375)

Age, years Mean (SD) 51.0 (11.8) 52.5 (13.0) 52.1 (12.6)

Baseline Body Mass Index (BMI)

Mean (SD) 36.01 ( 4.3) 34.7 ( 3.6) 35.1 ( 3.9)

30-<35 N (%) 62 (52.1%) 152 (59.4%) 214 (57.1%)

35-<40 32 (26.9%) 79 (30.9%) 111 (29.6%)

40-<45 25 (21.0%) 25 (9.8%) 50 (13.3%)

Gender Male N (%) 36 (30.3%) 101 (39.5%) 137 (36.5%)

Female 83 (69.7%) 155 (60.5%) 238 (63.5%)

Race/Ethnicity Black NH N (%) 20 (16.8%) 41 (16.0%) 61 (16.3%)

White NH 33 (27.7%) 48 (18.8%) 81 (21.6%)

Other NH 1 (0.8%) 1 (0.4%) 2 (0.5%)

Hispanic 65 (54.6%) 166 (64.8%) 231 (61.6%)

Primary Language English N (%) 84 (70.6%) 185 (72.3%) 269 (71.7%)

Spanish 35 (29.4%) 71 (27.7%) 106 (28.3%)

67

Intervention Eligible

Measure Response Statistics

Attended 1st visit

(N=119)

Declined/No response (N=256)

Overall (N=375)

Diabetes/Hyperlipidemia/Hypertension

No N (%) 20 (16.8%) 52 (20.3%) 72 (19.2%)

Yes 99 (83.2%) 204 (79.7%) 303 (80.8%)

Diabetes No N (%) 61 (51.3%) 145 (56.6%) 206 (54.9%)

Yes 58 (48.7%) 111 (43.4%) 169 (45.1%)

Hyperlipidemia No N (%) 56 (47.1%) 118 (46.1%) 174 (46.4%)

Yes 63 (52.9%) 138 (53.9%) 201 (53.6%)

Hypertension No N (%) 41 (34.5%) 79 (30.9%) 120 (32.0%)

Yes 78 (65.5%) 177 (69.1%) 255 (68.0%)

Insurance Medicaid N (%) 36 (30.3%) 103 (40.4%) 139 (37.2%)

Medicare 33 (27.7%) 74 (29.0%) 107 (28.6%)

CICP 2/DFAP3 38 (31.9%) 65 (25.5%) 103 (27.5%)

Commercial (including Denver Health)

9 (7.6%) 9 (3.5%) 18 (4.8%)

Self pay/Other 3 (2.5%) 4 (1.6%) 7 (1.9%)

2 Colorado Indigent Care Program (CICP) 3 Denver Health Financial Assistance Program (DFAP)

68

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Disclaimer: The [views, statements, opinions] presented in this report are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute® (PCORI®), its Board of Governors or Methodology Committee.

Acknowledgement:

Research reported in this report was [partially] funded through a Patient-Centered Outcomes Research Institute® (PCORI®) Award (#IH-12-11-4571) Further information available at: https://www.pcori.org/research-results/2013/do-people-obesity-lose-weight-when-offered-choice-research-based-weight-loss