Preoperative Depression Status and 5 Year Metabolic and Bariatric Surgery Outcomes in the PCORnet Bariatric Study Cohort.

OBJECTIVE: To examine whether depression status before metabolic and bariatric surgery (MBS) influenced 5-year weight loss, diabetes, and safety/utilization outcomes in the PCORnet Bariatric Study. SUMMARY OF BACKGROUND DATA: Research on the impact of depression on MBS outcomes is inconsistent with few large, long-term studies. METHODS: Data were extracted from 23 health systems on 36,871 patients who underwent sleeve gastrectomy (SG; n=16,158) or gastric bypass (RYGB; n=20,713) from 2005-2015. Patients with and without a depression diagnosis in the year before MBS were evaluated for % total weight loss (%TWL), diabetes outcomes, and postsurgical safety/utilization (reoperations, revisions, endoscopy, hospitalizations, mortality) at 1, 3, and 5 years after MBS. RESULTS: 27.1% of SG and 33.0% of RYGB patients had preoperative depression, and they had more medical and psychiatric comorbidities than those without depression. At 5 years of follow-up, those with depression, versus those without depression, had slightly less %TWL after RYGB, but not after SG (between group difference = 0.42%TWL, P = 0.04). However, patients with depression had slightly larger HbA1c improvements after RYGB but not after SG (between group difference = - 0.19, P = 0.04). Baseline depression did not moderate diabetes remission or relapse, reoperations, revision, or mortality across operations; however, baseline depression did moderate the risk of endoscopy and repeat hospitalization across RYGB versus SG. CONCLUSIONS: Patients with depression undergoing RYGB and SG had similar weight loss, diabetes, and safety/utilization outcomes to those without depression. The effects of depression were clinically small compared to the choice of operation.

External validity in distributed data networks.

PURPOSE: While much has been written about how distributed networks address internal validity, external validity is rarely discussed. We aimed to define key terms related to external validity, discuss how they relate to distributed networks, and identify how three networks (the US Food and Drug Administration's Sentinel System, the Canadian Network for Observational Drug Effect Studies [CNODES], and the National Patient Centered Clinical Research Network [PCORnet]) deal with external validity. METHODS: We define external validity, target populations, target validity, generalizability, and transportability and describe how each relates to distributed networks. We then describe Sentinel, CNODES, and PCORnet and how each approaches these concepts, including a sample case study. RESULTS: Each network approaches external validity differently. As its target population is US citizens and it includes only US data, Sentinel primarily worries about lack of external validity by not including some segments of the population. The fact that CNODES includes Canadian, United States, and United Kingdom data forces them to seriously consider whether the United States and United Kingdom data will be transportable to Canadian citizens when they meta-analyze database-specific estimates. PCORnet, with its focus on study-specific cohorts and pragmatic trials, conducts more case-by-case explorations of external validity for each new analytic data set it generates. CONCLUSIONS: There is no one-size-fits-all approach to external validity within distributed networks. With these networks and comparisons between their findings becoming a key part of pharmacoepidemiology, there is a need to adapt tools for improving external validity to the distributed network setting.

Electronic Health Record-Based Recruitment and Retention and Mobile Health App Usage: Multisite Cohort Study.

BACKGROUND: To address the obesity epidemic, there is a need for novel paradigms, including those that address the timing of eating and sleep in relation to circadian rhythms. Electronic health records (EHRs) are an efficient way to identify potentially eligible participants for health research studies. Mobile health (mHealth) apps offer available and convenient data collection of health behaviors, such as timing of eating and sleep. OBJECTIVE: The aim of this descriptive analysis was to report on recruitment, retention, and app use from a 6-month cohort study using a mobile app called Daily24. METHODS: Using an EHR query, adult patients from three health care systems in the PaTH clinical research network were identified as potentially eligible, invited electronically to participate, and instructed to download and use the Daily24 mobile app, which focuses on eating and sleep timing. Online surveys were completed at baseline and 4 months. We described app use and identified predictors of app use, defined as 1 or more days of use, versus nonuse and usage categories (ie, immediate, consistent, and sustained) using multivariate regression analyses. RESULTS: Of 70,661 patients who were sent research invitations, 1021 (1.44%) completed electronic consent forms and online baseline surveys; 4 withdrew, leaving a total of 1017 participants in the analytic sample. A total of 53.79% (n=547) of the participants were app users and, of those, 75.3% (n=412), 50.1% (n=274), and 25.4% (n=139) were immediate, consistent, and sustained users, respectively. Median app use was 28 (IQR 7-75) days over 6 months. Younger age, White race, higher educational level, higher income, having no children younger than 18 years, and having used 1 to 5 health apps significantly predicted app use (vs nonuse) in adjusted models. Older age and lower BMI predicted early, consistent, and sustained use. About half (532/1017, 52.31%) of the participants completed the 4-month online surveys. A total of 33.5% (183/547), 29.3% (157/536), and 27.1% (143/527) of app users were still using the app for at least 2 days per month during months 4, 5, and 6 of the study, respectively. CONCLUSIONS: EHR recruitment offers an efficient (ie, high reach, low touch, and minimal participant burden) approach to recruiting participants from health care settings into mHealth research. Efforts to recruit and retain less engaged subgroups are needed to collect more generalizable data. Additionally, future app iterations should include more evidence-based features to increase participant use.

Patient Recruitment Into a Multicenter Clinical Cohort Linking Electronic Health Records From 5 Health Systems: Cross-sectional Analysis.

BACKGROUND: There is growing interest in identifying and recruiting research participants from health systems using electronic health records (EHRs). However, few studies have described the practical aspects of the recruitment process or compared electronic recruitment methods to in-person recruitment, particularly across health systems. OBJECTIVE: The objective of this study was to describe the steps and efficiency of the recruitment process and participant characteristics by recruitment strategy. METHODS: EHR-based eligibility criteria included being an adult patient engaged in outpatient primary or bariatric surgery care at one of 5 health systems in the PaTH Clinical Research Network and having ≥2 weight measurements and 1 height measurement recorded in their EHR within the last 5 years. Recruitment strategies varied by site and included one or more of the following methods: (1) in-person recruitment by study staff from clinical sites, (2) US postal mail recruitment letters, (3) secure email, and (4) direct EHR recruitment through secure patient web portals. We used descriptive statistics to evaluate participant characteristics and proportion of patients recruited (ie, efficiency) by modality. RESULTS: The total number of eligible patients from the 5 health systems was 5,051,187. Of these, 40,048 (0.8%) were invited to enter an EHR-based cohort study and 1085 were enrolled. Recruitment efficiency was highest for in-person recruitment (33.5%), followed by electronic messaging (2.9%), including email (2.9%) and EHR patient portal messages (2.9%). Overall, 779 (65.7%) patients were enrolled through electronic messaging, which also showed greater rates of recruitment of Black patients compared with the other strategies. CONCLUSIONS: We recruited a total of 1085 patients from primary care and bariatric surgery settings using 4 recruitment strategies. The recruitment efficiency was 2.9% for email and EHR patient portals, with the majority of participants recruited electronically. This study can inform the design of future research studies using EHR-based recruitment.

Lifestyle Habits Associated with Weight Regain After Intentional Loss in Primary Care Patients Participating in a Randomized Trial.

BACKGROUND: Though long-term weight loss maintenance is the treatment goal for obesity, weight regain is typical and few studies have evaluated lifestyle habits associated with weight regain. OBJECTIVE: To identify dietary and physical activity habits associated with 6- and 24-month weight regain among participants in a weight loss maintenance clinical trial. DESIGN: Secondary analysis of randomized clinical trial data. PARTICIPANTS: Adult primary care patients with recent, intentional weight loss of at least 5%. MAIN MEASURES: Lifestyle habits included consumption of low-fat foods, fish, desserts, sugary beverages, fruits, and vegetables and eating at restaurants from the Connor Diet Habit Survey; moderate-vigorous physical activity by self-report; steps recorded by a pedometer; and sedentary behavior by self-report. The outcome variable was weight change at 6 and 24 months. Linear regression models estimated adjusted associations between changes in weight and changes in dietary and physical activity habits. KEY RESULTS: Overall, participants (mean (SD): 53.4 (12.2) years old; 26% male; 88% white) maintained weight loss at 6 months (n = 178, mean (SD): - 0.02 (5.70)% change) but began to regain weight by 24 months (n = 157, mean (SD): 4.22 (9.15)% increase). When considered all together, more eating at restaurants, reduced fish consumption, and less physical activity were most consistently associated with weight regain in fully adjusted models at both 6 and 24 months of follow-up. In addition, more sedentary behavior was associated with weight regain at 6 months while reduced consumption of low-fat foods, and more desserts and sugary beverages were associated with weight regain at 24 months. CONCLUSIONS: Consuming less fish, fewer steps per day, and more frequent restaurant eating were most consistently associated with weight regain in primary care patients. Primary care providers may consider addressing specific lifestyle behaviors when counseling patients after successful weight loss. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01946191.

Effect of Electronic Health Record-Based Coaching on Weight Maintenance: A Randomized Trial.

Background: Weight regain after intentional loss is common. Most evidence-based weight management programs focus on short-term loss rather than long-term maintenance. Objective: To evaluate the benefit of coaching in an electronic health record (EHR)-based weight maintenance intervention. Design: Randomized controlled trial. (ClinicalTrials.gov: NCT01946191). Setting: Practices affiliated with an academic medical center. Participants: Adult outpatients with body mass index (BMI) of 25 kg/m2 or higher, intentional weight loss of at least 5% in the previous 2 years, and no bariatric procedures in the previous 5 years. Intervention: Participants were randomly assigned to EHR tools (tracking group) versus EHR tools plus coaching (coaching group). The EHR tools included weight, diet, and physical activity tracking flow sheets; standardized surveys; and reminders. The coaching group received 24 months of personalized coaching through the EHR patient portal, with 24 scheduled contacts. Measurements: The primary outcome was weight change at 24 months. Secondary outcomes included 5% weight loss maintenance and changes in BMI, waist circumference, number of steps per day, health-related quality of life, physical function, blood pressure, and satisfaction. Results: Among 194 randomly assigned participants (mean age, 53.4 years [SD, 12.2]; 143 [74%] women; 171 [88%] white), 157 (81%) completed the trial. Mean baseline weight and BMI were 85.8 kg (SD, 19.1) and 30.4 kg/m2 (SD, 5.9). At 24 months, mean weight regain (± SE) was 2.1 ± 0.62 kg and 4.9 ± 0.63 kg in the coaching and tracking groups, respectively. The between-group difference in weight change at 24 months was significant (-2.86 kg [95% CI, -4.60 to -1.11 kg]) in the linear mixed model. At 24 months, 65% of participants in the coaching group and 50% in the tracking group maintained weight loss of at least 5%. Limitation: Single-site trial, which limits generalizability. Conclusion: Among adults with intentional weight loss of at least 5%, use of EHR tools plus coaching resulted in less weight regain than EHR tools alone. Primary Funding Source: Agency for Healthcare Research and Quality and National Institutes of Health.

Understanding Primary Care Patients' Self-weighing Habits: Cohort Analysis from the PaTH Clinical Data Research Network.

BACKGROUND: Greater than 60% of adults have overweight or obesity. Self-weighing is an effective weight loss and weight maintenance tool. However, little is known about self-weighing habits among the primary care patient population. Our objective was to examine the frequency of patient-reported self-weighing, and to evaluate the associations of self-weighing with demographic characteristics and self-monitoring behaviors. METHODS: We conducted an analysis of survey data collected as part of the PaTH Clinical Data Research Network, which recruited a cohort of 1,021 primary care patients at 4 academic medical centers. Patients of all body mass index (BMI) categories were included. RESULTS: Response rate of 6-month survey was 727 (71%). The mean age was 56 years, and most were female (68%), White (78%), college graduates (66%), and employed/retired (85%). The mean BMI was 30.2 kg/m2, 80% of participants had a BMI â‰§ 25 kg/m2. Of patients with BMI â‰§ 25 kg/m2, 35% of participants self-weighed weekly and 23% daily. Participants who reported self-weighing at least weekly were more likely to be older (59 vs 54 years, p < 0.01), married (p = 0.01), college graduates (p = 0.03), White (p < 0.01), and employed vs disabled/unemployed (p < 0.01). Patients who self-weighed daily had a lower BMI (29 kg/m2 vs 31 kg/m2, p = 0.04). Patients who tracked exercise or food intake were more likely to self-weigh daily (p < 0.01), as were patients wanting to lose or maintain weight (p < 0.01). CONCLUSIONS: Despite its potential for primary and secondary obesity prevention, only 35% of primary care patients with overweight or obesity engage in self-weighing weekly and less than a quarter (23%) self-weigh daily. Socioeconomic status appears to be a factor influencing regular self-weighing in this population, potentially contributing to greater health disparities in obesity rates. Patients who self-weighed daily had a lower BMI, suggesting that it may play a role in primary prevention of obesity. More work is needed to explore self-weighing among patients.

Comparative Effectiveness and Safety of Bariatric Procedures for Weight Loss: A PCORnet Cohort Study.

Background: There has been a dramatic shift in use of bariatric procedures, but little is known about their long-term comparative effectiveness. Objective: To compare weight loss and safety among bariatric procedures. Design: Retrospective observational cohort study, January 2005 to September 2015. (ClinicalTrials.gov: NCT02741674). Setting: 41 health systems in the National Patient-Centered Clinical Research Network. Participants: 65 093 patients aged 20 to 79 years with body mass index (BMI) of 35 kg/m2 or greater who had bariatric procedures. Intervention: 32 208 Roux-en-Y gastric bypass (RYGB), 29 693 sleeve gastrectomy (SG), and 3192 adjustable gastric banding (AGB) procedures. Measurements: Estimated percent total weight loss (TWL) at 1, 3, and 5 years; 30-day rates of major adverse events. Results: Total numbers of eligible patients with weight measures at 1, 3, and 5 years were 44 978 (84%), 20 783 (68%), and 7159 (69%), respectively. Thirty-day rates of major adverse events were 5.0% for RYGB, 2.6% for SG, and 2.9% for AGB. One-year mean TWLs were 31.2% (95% CI, 31.1% to 31.3%) for RYGB, 25.2% (CI, 25.1% to 25.4%) for SG, and 13.7% (CI, 13.3% to 14.0%) for AGB. At 1 year, RYGB patients lost 5.9 (CI, 5.8 to 6.1) percentage points more weight than SG patients and 17.7 (CI, 17.3 to 18.1) percentage points more than AGB patients, and SG patients lost 12.0 (CI, 11.6 to 12.5) percentage points more than AGB patients. Five-year mean TWLs were 25.5% (CI, 25.1% to 25.9%) for RYGB, 18.8% (CI, 18.0% to 19.6%) for SG, and 11.7% (CI, 10.2% to 13.1%) for AGB. Patients with diabetes, those with BMI less than 50 kg/m2, those aged 65 years or older, African American patients, and Hispanic patients lost less weight than patients without those characteristics. Limitation: Potential unobserved confounding due to nonrandomized design; electronic health record databases had missing outcome data. Conclusion: Adults lost more weight with RYGB than with SG or AGB at 1, 3, and 5 years; however, RYGB had the highest 30-day rate of major adverse events. Small subgroup differences in weight loss outcomes were observed. Primary Funding Source: Patient-Centered Outcomes Research Institute.

Cost effectiveness of an internet-delivered lifestyle intervention in primary care patients with high cardiovascular risk.

OBJECTIVE: To assess the cost-effectiveness of an online adaptation of the diabetes prevention program (ODPP) lifestyle intervention. METHODS: ODPP was a before-after evaluation of a weight loss intervention comprising 16 weekly and 8 monthly lessons, incorporating behavioral tools and regular, brief, web-based individualized counseling in an overweight/obese cohort (mean age 52, 76% female, 92% white, 28% with diabetes). A Markov model was developed to estimate ODPP cost effectiveness compared with usual care (UC) to reduce metabolic risk over 10years. Intervention costs and weight change outcomes were obtained from the study; other model parameters were based on published reports. In the model, diabetes risk was a function of weight change with and without the intervention. RESULTS: Compared to UC, the ODPP in our cohort cost $14,351 and $29,331 per quality-adjusted life-year (QALY) gained from the health care system and societal perspectives, respectively. In a hypothetical cohort without diabetes, the ODPP cost $7777 and $18,263 per QALY gained, respectively. Results were robust in sensitivity analyses, but enrolling cohorts with lower annual risk of developing diabetes (≤1.8%), enrolling fewer participants (≤15), or increasing the hourly cost (≥$91.20) or annual per-participant time (≥1.45h) required for technical support could increase ODPP cost to >$20,000 per QALY gained. In probabilistic sensitivity analyses, ODPP was cost-effective in 20-58% of model iterations using an acceptability threshold of $20,000, 73-92% at $50,000, and 95-99% at $100,000 per QALY gained. CONCLUSIONS: The ODPP may offer an economical approach to combating overweight and obesity.

Gestational weight gain, early pregnancy maternal adiposity distribution, and maternal hyperglycemia.

To estimate the effects of gestational weight gain (GWG), central adiposity and subcutaneous fat on maternal post-load glucose concentration, pregnant women [n = 413, 62% black, 57% with pregravid body mass index (BMI) ≥25] enrolled in a cohort study at ≤13 weeks gestation. GWG was abstracted from medical records. In a sub-sample of women (n = 214), waist circumference (WC), and biceps and triceps skinfold thicknesses were measured at enrollment. At 24-28 weeks gestation, post-load glucose concentration was measured using a 50-g 1-h oral glucose tolerance test. After adjustment for pre-pregnancy BMI, age, parity, race/ethnicity, smoking, marital status, annual family income, education, family history of diabetes, and gestational age of GDM screening, each 0.3-kg/week increase in weight in the first trimester was associated with a 2.2 (95% CI 0.1, 4.3)-mg/dl increase in glucose concentration. Each 8.6-mm increase in biceps skinfold thickness and each 11.7-mm increase in triceps skinfold thickness was associated with 4.3 (95% CI 0.2, 8.5)-mg/dl increase in maternal glucose, independent of BMI and other confounders. Neither GWG in the second trimester nor WC at ≤13 weeks was significantly associated with glucose concentration after confounder adjustment. Independent of pre-pregnancy BMI, high early pregnancy GWG and maternal subcutaneous body fat may be positively associated with maternal glucose concentrations at 24-28 weeks.

Impact of electronic health record-coaching features in weight change: A secondary analysis from the MAINTAIN-pc randomized trial.

OBJECTIVE: This study aimed to evaluate whether coaching features were successfully transmitted via electronic health record (EHR) communication and to evaluate their relationship with weight change in a previously tested EHR-based coaching intervention. METHODS: A secondary analysis from the Maintaining Activity and Nutrition through Technology-Assisted Innovation in Primary Care (MAINTAIN-pc) study randomized clinical trial was conducted in nine primary care practices and one specialty practice (endocrinology) affiliated with the University of Pittsburgh Medical Center. Eligibility included age 18 to 75 years, intentional 5% weight loss in the previous 2 years, access to an internet-connected computer, and receipt of care from a University of Pittsburgh Medical Center primary care provider. Survey data were collected during the randomized clinical trial. RESULTS: Participants content with intervention delivery via the EHR and those who felt a strong connection to their coach had significantly less weight regain (p = 0.013 and p < 0.01, respectively). Participants who had needs unmet by the intervention (e.g., "in-person" support in a group setting or individual settings) regained more weight (p < 0.01). CONCLUSIONS: The data suggest heterogeneity in the patient population regarding preference for in-person versus EHR-based coaching formats. Such heterogeneity might result in the differential success of EHR-based interventions.

Associations between sleep health and obesity and weight change in adults: The Daily24 Multisite Cohort Study.

OBJECTIVES: To examine cross-sectional and longitudinal associations of individual sleep domains and multidimensional sleep health with current overweight or obesity and 5-year weight change in adults. METHODS: We estimated sleep regularity, quality, timing, onset latency, sleep interruptions, duration, and napping using validated questionnaires. We calculated multidimensional sleep health using a composite score (total number of "good" sleep health indicators) and sleep phenotypes derived from latent class analysis. Logistic regression was used to examine associations between sleep and overweight or obesity. Multinomial regression was used to examine associations between sleep and weight change (gain, loss, or maintenance) over a median of 1.66 years. RESULTS: The sample included 1016 participants with a median age of 52 (IQR = 37-65), who primarily identified as female (78%), White (79%), and college-educated (74%). We identified 3 phenotypes: good, moderate, and poor sleep. More regularity of sleep, sleep quality, and shorter sleep onset latency were associated with 37%, 38%, and 45% lower odds of overweight or obesity, respectively. The addition of each good sleep health dimension was associated with 16% lower adjusted odds of having overweight or obesity. The adjusted odds of overweight or obesity were similar between sleep phenotypes. Sleep, individual or multidimensional sleep health, was not associated with weight change. CONCLUSIONS: Multidimensional sleep health showed cross-sectional, but not longitudinal, associations with overweight or obesity. Future research should advance our understanding of how to assess multidimensional sleep health to understand the relationship between all aspects of sleep health and weight over time.

Association of Eating and Sleeping Intervals With Weight Change Over Time: The Daily24 Cohort.

Background We aim to evaluate the association between meal intervals and weight trajectory among adults from a clinical cohort. Methods and Results This is a multisite prospective cohort study of adults recruited from 3 health systems. Over the 6-month study period, 547 participants downloaded and used a mobile application to record the timing of meals and sleep for at least 1 day. We obtained information on weight and comorbidities at each outpatient visit from electronic health records for up to 10 years before until 10 months after baseline. We used mixed linear regression to model weight trajectories. Mean age was 51.1 (SD 15.0) years, and body mass index was 30.8 (SD 7.8) kg/m2; 77.9% were women, and 77.5% reported White race. Mean interval from first to last meal was 11.5 (2.3) hours and was not associated with weight change. The number of meals per day was positively associated with weight change. The average difference in annual weight change (95% CI) associated with an increase of 1 daily meal was 0.28 kg (0.02-0.53). Conclusions Number of daily meals was positively associated with weight change over 6 years. Our findings did not support the use of time-restricted eating as a strategy for long-term weight loss in a general medical population.

Lifestyle strategies after intentional weight loss: results from the MAINTAIN-pc randomized trial.

Introduction/Purpose: Weight maintenance following intentional weight loss is challenging and often unsuccessful. Physical activity and self-monitoring are strategies associated with successful weight loss maintenance. However, less is known about the type and number of lifestyle strategies used following intentional weight loss. The purpose of this study was to determine the types and amounts of strategies associated with successful long-term weight loss maintenance. Methods: Data from the 24-month Maintaining Activity and Nutrition Through Technology-Assisted Innovation in Primary Care (MAINTAIN-pc) trial were analyzed. MAINTAIN-pc recruited adults (n=194; 53.4±12.2 years of age, body mass index (BMI): 30.4±5.9 kg/m2, 74% female) with recent intentional weight loss of ≥5%, randomized to tracking tools plus coaching (i.e., coaching group) or tracking tools without coaching (i.e., tracking-only group). At baseline, 6, 12, and 24 months, participants reported lifestyle strategies used in the past 6 months, including self-monitoring, group support, behavioral skills, and professional support. General linear models evaluated changes in the number of strategies over time between groups and the consistency of strategies used over the 24-month intervention. Results: At baseline, 100% used behavioral skills, 73% used group support, 69% used self-monitoring, and 68% used professional support in the past 6 months; at 24 months, these rates were 98%, 60%, 75%, and 61%, respectively. While the number of participants utilizing individual strategies did not change significantly over time, the overall number of strategies participants reported decreased. More strategies were used at baseline and 6 months compared to 12- and 24-month follow-ups. The coaching group used more strategies at months 6 and 12 than the tracking-only group. Consistent use of professional support strategies over the 24-month study period was associated with less weight regain. Conclusion: Weight loss maintenance interventions that incorporate continued follow-up and support from healthcare professionals are likely to prevent weight regain after intentional weight loss.

Stakeholder engagement infrastructure to support multicenter research networks: Advances from the clinical research networks participating in PCORnet.

Background: The evidence based on the inclusion of patients and other stakeholders as partners in the clinical research process has grown substantially. However, little has been reported on how stakeholders are engaged in the governance of large-scale clinical research networks and the infrastructure used by research networks to support engagement in network-affiliated activities. Objectives: The objective was to document engagement activities and practices emerging from Clinical Research Networks (CRNs) participating in PCORnet, the National Patient-Centered Clinical Research Network, specifically regarding governance and engagement infrastructure. Methods: We conducted an environmental scan of PCORnet CRN engagement structures, assets, and services, focusing on network oversight structures for policy development and strategic decision-making. The scan included assets and services for supporting patient/stakeholder engagement. Data were collected by searching web-based literature and tool repositories, review of CRN Engagement Plans, analysis of previously collected key informant interviews, and CRN-based iterative review of structured worksheets. Results: We identified 87 discrete engagement structures, assets, and services across nine CRNs. All CRNs engage patients/stakeholders in their governance, maintain workgroups and/or staff dedicated to overseeing engagement strategies, and offer one or more services to non-CRN researchers to enhance conducting engaged clinical research. Conclusions: This work provides an important resource for the research community to explore engagement across peers, reflect on progress, consider opportunities to leverage existing infrastructure, and identify new collaborators. It also serves to highlight PCORnet as a resource for non-CRN researchers seeking to efficiently conduct engaged clinical research and a venue for advancing the science of engagement.

Seasonal variation in blood pressure control across US health systems.

OBJECTIVE: We aimed to characterize seasonal variation in US population-based blood pressure (BP) control and BP-related metrics and evaluate the association between outdoor temperature and BP control variation. METHODS: We queried electronic health records (EHRs) from 26 health systems, representing 21 states, to summarize BP metrics by quarters of 12-month periods from January 2017 to March 2020. Patients with at least one ambulatory visit during the measurement period and a hypertension diagnosis during the first 6 months or prior to the measurement period were included. Changes in BP control, BP improvement, medication intensification, average SBP reduction after medication intensification across quarters and association with outdoor temperature were analyzed using weighted generalized linear models with repeated measures. RESULTS: Among 1 818 041 people with hypertension, the majority were more than 65 years of age (52.2%), female (52.1%), white non-Hispanic (69.8%) and had stage 1/2 hypertension (64.8%). Overall, BP control and process metrics were highest in quarters 2 and 3, and lowest in quarters 1 and 4. Quarter 2 had the highest percentage of improved BP (31.95 ±â€Š0.90%) and average SBP reduction after medication intensification (16 ±â€Š0.23 mmHg). Quarter 3 had the highest percentage of BP controlled (62.25 ±â€Š2.55%) and lowest with medication intensification (9.73 ±â€Š0.60%). Results were largely consistent in adjusted models. Average temperature was associated with BP control metrics in unadjusted models, but associations were attenuated following adjustment. CONCLUSION: In this large, national, EHR-based study, BP control and BP-related process metrics improved during spring/summer months, but outdoor temperature was not associated with performance following adjustment for potential confounders.

Primary care providers' perspectives on online weight-loss programs: a big wish list.

BACKGROUND: Integrating online weight-loss programs into the primary care setting could yield substantial public health benefit. Little is known about primary care providers' perspectives on online weight-loss programs. OBJECTIVE: To assess primary care providers' perspectives on online weight-loss programs. METHODS: We conducted focus group discussions with providers in family medicine, internal medicine, and combined internal medicine/pediatrics in Texas and Pennsylvania, USA. Open-ended questions addressed their experience with and attitudes toward online weight-loss programs; useful characteristics of existing online weight-loss programs; barriers to referring patients to online weight-loss programs; and preferred characteristics of an ideal online weight-loss program. Transcripts were analyzed with the grounded theory approach to identify major themes. RESULTS: A total of 44 primary care providers participated in 9 focus groups. The mean age was 45 (SD 9) years. Providers had limited experience with structured online weight-loss programs and were uncertain about their safety and efficacy. They thought motivated, younger patients would be more likely than others to respond to an online weight-loss program. According to primary care providers, an ideal online weight-loss program would provide-at no cost to the patient-a structured curriculum addressing motivation, psychological issues, and problem solving; tools for tracking diet, exercise, and weight loss; and peer support monitored by experts. Primary care providers were interested in receiving reports about patients from the online weight-loss programs, but were concerned about the time required to review and act on the reports. CONCLUSIONS: Primary care providers have high expectations for how online weight-loss programs should deliver services to patients and fit into the clinical workflow. Efforts to integrate online weight-loss programs into the primary care setting should address efficacy and safety of online weight-loss programs in clinic-based populations; acceptable methods of sending reports to primary care providers about their patients' progress; and elimination or reduction of costs to patients.

Night eating, weight, and health behaviors in adults participating in the Daily24 study.

BACKGROUND: Night eating syndrome (NES) is associated with adverse health outcomes. This study evaluated the relationship between night eating severity, weight, and health behaviors. METHODS: Participants (N = 1017; 77.6% female, mean Body Mass Index (BMI) = 30.5, SD = 7.8 kg/m2, age = 51.1, SD = 15.0 years) were recruited from three health systems. Participants completed the Night Eating Questionnaire (NEQ) and questionnaires assessing sleep, chronotype, physical activity, diet, weight, and napping. RESULTS: In the overall sample, higher NEQ scores were associated with higher BMI (p < .001) and consumption of sugar-sweetened beverages (p < .001), as well as lower fruit/vegetable consumption (p = .001). Higher NEQ scores were associated with increased odds of having overweight/obesity (p < .001), eating fast food (p < .001), moderate-vigorous physical activity (p = .005), and smoking (p = .004). Participants who exceeded the screening threshold for NES (n = 48, 4.7%) reported elevated BMI (p = .014), an increased likelihood of overweight/obesity (p = .004), greater sugar-sweetened beverages consumption (p < .001), napping less than twice per week (p = .029), shorter sleep duration (p = .012), and a later chronotype (M = 4:55, SD = 2:45). CONCLUSION: Night eating severity was associated with obesity and intake of fast food and sugar-sweetened beverages. Interventions to address night eating and associated behaviors may enhance the efficacy of weight management interventions and promote engagement in positive health behaviors.

Comparative Safety and Effectiveness of Roux-en-Y Gastric Bypass and Sleeve Gastrectomy for Weight Loss and Type 2 Diabetes Across Race and Ethnicity in the PCORnet Bariatric Study Cohort.

Importance: Bariatric surgery is the most effective treatment for severe obesity; yet it is unclear whether the long-term safety and comparative effectiveness of these operations differ across racial and ethnic groups. Objective: To compare outcomes of Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) across racial and ethnic groups in the National Patient-Centered Clinical Research Network (PCORnet) Bariatric Study. Design, Setting, and Participants: This was a retrospective, observational, comparative effectiveness cohort study that comprised 25 health care systems in the PCORnet Bariatric Study. Patients were adults and adolescents aged 12 to 79 years who underwent a primary (first nonrevisional) RYGB or SG operation between January 1, 2005, and September 30, 2015, at participating health systems. Patient race and ethnicity included Black, Hispanic, White, other, and unrecorded. Data were analyzed from July 1, 2021, to January 17, 2022. Exposure: RYGB or SG. Outcomes: Percentage total weight loss (%TWL); type 2 diabetes remission, relapse, and change in hemoglobin A1c (HbA1c) level; and postsurgical safety and utilization outcomes (operations, interventions, revisions/conversions, endoscopy, hospitalizations, mortality, 30-day major adverse events) at 1, 3, and 5 years after surgery. Results: A total of 36 871 patients (mean [SE] age, 45.0 [11.7] years; 29 746 female patients [81%]) were included in the weight analysis. Patients identified with the following race and ethnic categories: 6891 Black (19%), 8756 Hispanic (24%), 19 645 White (53%), 826 other (2%), and 783 unrecorded (2%). Weight loss and mean reductions in HbA1c level were larger for RYGB than SG in all years for Black, Hispanic, and White patients (difference in 5-year weight loss: Black, -7.6%; 95% CI, -8.0 to -7.1; P < .001; Hispanic, -6.2%; 95% CI, -6.6 to -5.9; P < .001; White, -5.9%; 95% CI, -6.3 to -5.7; P < .001; difference in change in year 5 HbA1c level: Black, -0.29; 95% CI, -0.51 to -0.08; P = .009; Hispanic, -0.45; 95% CI, -0.61 to -0.29; P < .001; and White, -0.25; 95% CI, -0.40 to -0.11; P = .001.) The magnitude of these differences was small among racial and ethnic groups (1%-3% of %TWL). Black and Hispanic patients had higher risk of hospitalization when they had RYGB compared with SG (hazard ratio [HR], 1.45; 95% CI, 1.17-1.79; P = .001 and 1.48; 95% CI, 1.22-1.79; P < .001, respectively). Hispanic patients had greater risk of all-cause mortality (HR, 2.41; 95% CI, 1.24-4.70; P = .01) and higher odds of a 30-day major adverse event (odds ratio, 1.92; 95% CI, 1.38-2.68; P < .001) for RYGB compared with SG. There was no interaction between race and ethnicity and operation type for diabetes remission and relapse. Conclusions and Relevance: Variability of the comparative effectiveness of operations for %TWL and HbA1c level across race and ethnicity was clinically small; however, differences in safety and utilization outcomes were clinically and statistically significant for Black and Hispanic patients who had RYGB compared with SG. These findings can inform shared decision-making regarding bariatric operation choice for different racial and ethnic groups of patients.

Interventions and Operations after Bariatric Surgery in a Health Plan Research Network Cohort from the PCORnet, the National Patient-Centered Clinical Research Network.

PURPOSE: Obesity is a highly prevalent condition with severe clinical burden. Bariatric procedures are an important and expanding treatment option. This study compared short-(30-day composite adverse events) and long-term (intervention/operation, endoscopy, hospitalization, and mortality up to 5 years) safety outcomes associated with three bariatric surgical procedures. MATERIALS AND METHODS: This observational cohort study replicated an electronic health record study comparing short- and long-term problems associated with three bariatric surgical procedures between January 1, 2006, and September 30, 2015, within a Health Plan Research Network. RESULTS: Of 95,251 adults, 34,240 (36%) underwent adjustable gastric banding (AGB), 36,206 (38%) Roux-en-Y gastric bypass (RYGB), and 24,805 (26%) sleeve gastrectomy (SG). Median (interquartile range) years of follow-up was 3.3 (1.4-5.0) (AGB), 2.5 (1.0-4.6) (RYGB), and 1.1 (0.5-2.1) (SG). Overall mean (SD) age was 44.2 (11.4) years. The cohort was predominantly female (76%). Thirty-day composite adverse events occurred more frequently following RYGB (3.8%) than AGB (3.1%) and SG (2.8%). Operation/intervention was less likely in SG than in RYGB (adjusted hazard ratio (AHR), 0.87; 95%CI, 0.80-0.96; P=0.003), and more likely in AGB than in RYGB (AHR, 2.10; 95%CI, 2.00-2.21; P<0.001). Hospitalization was less likely after ABG and SG than after RYGB: AGB vs. RYGB, AHR=0.73; 95%CI, 0.71-0.76; P<0.001; SG vs. RYGB, AHR=0.79; 95%CI, 0.76-0.83; P<0.001. Mortality was most likely for RYGB (SG vs. RYGB: AHR, 0.76; 95%CI, 0.64-0.92; P=0.004; AGB vs. RYGB: AHR, 0.49; 95%CI, 0.43-0.56; P=0.001). CONCLUSIONS: Interventions, operations, and hospitalizations were more often associated with AGB and RYGB than SG while RYGB had the lowest risk for revision.