Design and implementation of electronic health record-based tools to support a weight management program in primary care.

Objectives: This paper reports on a mixed methods formative evaluation to support the design and implementation of information technology (IT) tools for a primary care weight management intervention delivered through the patient portal using primary care staff as coaches. Methods: We performed a qualitative needs assessment, designed the IT tools to support the weight management program, and developed implementation tracking metrics. Implementation tracking metrics were designed to use real world electronic health record (EHR) data. Results: The needs assessment revealed IT requirements as well as barriers and facilitators to implementation of EHR-based weight management interventions in primary care. We developed implementation metrics for the IT tools. These metrics were used in weekly project team calls to make sure that project resources were allocated to areas of need. Conclusion: This study identifies the important role of IT in supporting weight management through patient identification, weight and activity tracking in the patient portal, and the use of the EHR as a population management tool. An intensive multi-level implementation approach is required for successful primary care-based weight management interventions including well-designed IT tools, comprehensive involvement of clinic leadership, and implementation tracking metrics to guide the process of workflow integration. This study helps to bridge the gap between informatics and implementation by using socio-technical formative evaluation methods early in order to support the implementation of IT tools. Trial registration: clinicaltrials.gov, NCT04420936. Registered June 9, 2020.

Implementing weight maintenance with existing staff and electronic health record tools in a primary care setting: Baseline results from the MAINTAIN PRIME trial.

BACKGROUND: There is need for interventions that can assist with long-term maintenance of healthy body weight and be sustainably integrated into existing primary care teams. The goal of MAINTAIN PRIME (Promoting Real (World) IMplEmentation) is to evaluate whether a successful electronic health record (EHR)-based weight maintenance intervention can be adapted to a new clinical setting with primary care staff serving as coaches. METHODS: EHR tools include tracking tools, standardized surveys, and standardized "SmartPhrases" for coaching. Inclusion criteria were age 18-75 years, voluntary 5% weight loss in the past 2 years with prior BMI ≥ 25 kg/m2, and no bariatric procedures in past 2 years. Participants were randomized 1:1 to tailored online coaching with EHR tracking tools (coaching) or EHR tracking tools alone (tracking). RESULTS: We screened 405 individuals between September 2021 and April 2023; 269 participants enrolled (134 coaching; 135 tracking). The most common reason for not enrolling was ineligibility (55%). At baseline, participants were 50.3 (SD 15.02) years old, 66.4% female, and 84% White; 83.7% reported moderate physical activity. Average weight and BMI at baseline were 205.0 (SD 48.9) lbs. and 33.2 (6.8) kg/m2, respectively. Participants lost an average of 10.7% (SD 5.2) of their body weight before enrolling. We recruited 39 primary care coaches over the same period. Conclusion The study successfully identified and recruited primary care patients with recent intentional weight loss for participation in a weight maintenance program that uses EHR-based tools. We also successfully recruited and trained primary care staff as coaches.

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.

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.

The Effect of Tailored, Daily, Smartphone Feedback to Lifestyle Self-Monitoring on Weight Loss at 12 Months: the SMARTER Randomized Clinical Trial.

BACKGROUND: Self-monitoring (SM) is the centerpiece of behavioral weight loss treatment, but the efficacy of smartphone-delivered SM feedback (FB) has not been tested in large, long-term, randomized trials. OBJECTIVE: The aim of this study was to establish the efficacy of providing remote FB to diet, physical activity (PA), and weight SM on improving weight loss outcomes when comparing the SM plus FB (SM+FB) condition to the SM-only condition in a 12-month randomized controlled trial. The study was a single-site, population-based trial that took place in southwestern Pennsylvania, USA, conducted between 2018 and 2021. Participants were smartphone users age ≥18 years, able to engage in moderate PA, with a mean BMI between 27 and 43 kg/m2. METHODS: All participants received a 90-minute, one-to-one, in-person behavioral weight loss counseling session addressing behavioral strategies, establishing participants' dietary and PA goals, and instructing on use of the PA tracker (Fitbit Charge 2), smart scale, and diet SM app. Only SM+FB participants had access to an investigator-developed smartphone app that read SM data, in which an algorithm selected tailored messages sent to the smartphone up to 3 times daily. The SM-only participants did not receive any tailored FB based on SM data. The primary outcome was percent weight change from baseline to 12 months. Secondary outcomes included engagement with digital tools (eg, monthly percentage of FB messages opened and monthly percentage of days adherent to the calorie goal). RESULTS: Participants (N=502) were on average 45.0 (SD 14.4) years old with a mean BMI of 33.7 (SD 4.0) kg/m2. The sample was 79.5% female (n=399/502) and 82.5% White (n=414/502). At 12 months, retention was 78.5% (n=394/502) and similar by group (SM+FB: 202/251, 80.5%; SM: 192/251, 76.5%; P=.28). There was significant percent weight loss from baseline in both groups (SM+FB: -2.12%, 95% CI -3.04% to -1.21%, P<.001; SM: -2.39%, 95% CI -3.32% to -1.47%; P<.001), but no difference between the groups (-0.27%; 95% CI -1.57% to 1.03%; t =-0.41; P=.68). Similarly, 26.3% (66/251) of the SM+FB group and 29.1% (73/251) of the SM group achieved ≥5% weight loss (chi-square value=0.49; P=.49). A 1% increase in FB messages opened was associated with a 0.10 greater percent weight loss at 12 months (b=-0.10; 95% CI -0.13 to -0.07; t =-5.90; P<.001). A 1% increase in FB messages opened was associated with 0.12 greater percentage of days adherent to the calorie goal per month (b=0.12; 95% CI 0.07-0.17; F=22.19; P<.001). CONCLUSIONS: There were no significant between-group differences in weight loss; however, the findings suggested that the use of commercially available digital SM tools with or without FB resulted in a clinically significant weight loss in over 25% of participants. Future studies need to test additional strategies that will promote greater engagement with digital tools. TRIAL REGISTRATION: Clinicaltrials.gov NCT03367936; https://clinicaltrials.gov/ct2/show/NCT03367936.

Effect of tailored, daily feedback with lifestyle self-monitoring on weight loss: The SMARTER randomized clinical trial.

OBJECTIVE: This study aimed to test the efficacy of self-monitoring and feedback (SM+FB) versus SM without FB (SM) in a behavioral weight-loss intervention at 6 months. METHODS: This was a randomized clinical trial. Eligibility criteria included the following: ≥18 years of age, BMI ≥ 27 and ≤43, smartphone user, and ability to engage in moderate physical activity. All participants received a 90-minute 1:1 counseling session, a Fitbit Charge 2, and a digital scale for SM. SM+FB participants were provided access to a customized smartphone application that provided three daily FB messages. The primary outcome was percentage of weight change from 0 to 6 months. RESULTS: The sample (N = 502) was 45 (SD 14.4) years old, BMI was 33.7 (SD 4.00) kg/m2 , 79.5% of participants were female (n = 399), and 84.3% were White (n = 423). At 6 months, there was 85.86% retention and a significant percentage of weight change in both groups (SM+FB: -3.16%, 95% CI: -3.85% to -2.47%, p < 0.0001; SM: -3.20%, 95% CI: -3.86% to -2.54%, p < 0.0001) but no significant between-group mean difference (-0.04%, 95% CI: -0.99% to 0.91%, p = 0.940). A ≥5% weight loss was achieved by 31.9% of the SM+FB group and 28.3% of the SM group. CONCLUSIONS: There was no significant between-group difference in weight loss at 6 months.

Modified early warning score-based clinical decision support: cost impact and clinical outcomes in sepsis.

OBJECTIVE: The objective of this study was to assess the clinical and financial impact of a quality improvement project that utilized a modified Early Warning Score (mEWS)-based clinical decision support intervention targeting early recognition of sepsis decompensation. MATERIALS AND METHODS: We conducted a retrospective, interrupted time series study on all adult patients who received a diagnosis of sepsis and were exposed to an acute care floor with the intervention. Primary outcomes (total direct cost, length of stay [LOS], and mortality) were aggregated for each study month for the post-intervention period (March 1, 2016-February 28, 2017, n = 2118 visits) and compared to the pre-intervention period (November 1, 2014-October 31, 2015, n = 1546 visits). RESULTS: The intervention was associated with a decrease in median total direct cost and hospital LOS by 23% (P = .047) and .63 days (P = .059), respectively. There was no significant change in mortality. DISCUSSION: The implementation of an mEWS-based clinical decision support system in eight acute care floors at an academic medical center was associated with reduced total direct cost and LOS for patients hospitalized with sepsis. This was seen without an associated increase in intensive care unit utilization or broad-spectrum antibiotic use. CONCLUSION: An automated sepsis decompensation detection system has the potential to improve clinical and financial outcomes such as LOS and total direct cost. Further evaluation is needed to validate generalizability and to understand the relative importance of individual elements of the intervention.

The SMARTER Trial: Design of a trial testing tailored mHealth feedback to impact self-monitoring of diet, physical activity, and weight.

BACKGROUND: Self-monitoring food intake and physical activity (PA) is positively related to weight loss and the addition of feedback (FB) messages has been shown to reinforce behavior change. Moreover, the more immediate the delivery of reinforcing FB messages, the more likely they will promote the desired behaviors. PURPOSE: Describe design and rationale of SMARTER, a National Institute of Heart, Lung, and Blood (NHLBI)-sponsored randomized, controlled trial, which compares the differential efficacy of two weight loss treatments among 530 adults, ages 18 and older. METHODS: Single-site, 2-group design trial with subjects randomized 1:1 to either: 1) self-monitoring (SM), where participants self-monitor diet, PA, and weight using a commercial smartphone application (app); or 2) SM + FB, where participants self-monitor and receive real-time, tailored feedback (FB) as pop-up messages up to 3 times/day for 12 months. Daily FB messages address diet and PA behaviors and a weekly FB message addresses self-weighing. We hypothesize that subjects assigned to SM + FB will show greater weight loss at 6 and 12 months and greater sustained engagement in the program than the SM group, measured by adherence to the study's lifestyle and SM protocol. We will explore temporal relationships of the frequency, timing, and type of FB delivered and subsequent lifestyle behaviors through examination of serially collected real-time SM (diet, PA, weight) data over 12 months. CONCLUSIONS: If efficacious, this fully scalable intervention could be efficiently translated and disseminated to reach large numbers of individuals through commercial apps at lower cost than existing in-person weight loss programs.

Obesity, islet cell autoimmunity, and cardiovascular risk factors in youth at onset of type 1 autoimmune diabetes.

CONTEXT: The current increase in childhood type 1 diabetes (T1D) and obesity has led to two conflicting hypotheses and conflicting reports regarding the effects of overweight on initiation and spreading of islet cell autoimmunity vs earlier clinical manifestation of preexisting autoimmune ß-cell damage driven by excess weight. OBJECTIVE: The objective of the study was to address the question of whether the degree of ß-cell autoimmunity and age are related to overweight at diabetes onset in a large cohort of T1D youth. DESIGN: This was a prospective cross-sectional study of youth with autoimmune T1D consecutively recruited at diabetes onset. SETTING: The study was conducted at a regional academic pediatric diabetes center. PATIENTS: Two hundred sixty-three consecutive children younger than 19 years at onset of T1D participated in the study. MAIN OUTCOME MEASURES: Relationships between body mass index and central obesity (waist circumference and waist to height ratio) and antigen spreading (islet cell autoantibody number), age, and cardiovascular (CVD) risk factors examined at onset and/or 3 months after the diagnosis were measured. RESULTS: There were no significant associations between number of autoantibodies with measures of adiposity. Age relationships revealed that a greater proportion of those with central obesity (21%) were in the youngest age group (0-4 y) compared with those without central obesity (6%) (P = .001). PATIENTS with central obesity had increased CVD risk factors and higher onset C-peptide levels (P < .05). CONCLUSIONS: No evidence was found to support the concept that obesity accelerates progression of autoantibody spreading once autoimmunity, marked by standard islet cell autoantibody assays, is present. Central obesity was present in almost one-third of the subjects and was associated with early CVD risk markers already at onset.

Carbohydrate malabsorption may increase daily energy requirements in infants.

OBJECTIVE: Carbohydrate malabsorption in infants has been found to increase nutrient losses. However, the effect of this alteration on daily metabolic rate is unknown. We assessed daily metabolic rates in infants with asymptomatic carbohydrate malabsorption (ACM) after a single fruit juice load. METHODS: Sixteen healthy infants with ACM (63.3 +/- 5.6 cm, 7.5 +/- 1.0 kg, 5.6 +/- 0.8 mo, peak breath hydrogen [BH2] = 39.1 +/- 22.4 ppm) and 16 without ACM (64.3 +/- 3.9 cm, 7.8 +/- 1.0 kg, 5.0 +/- 0.8 mo, BH2 = 9.4 +/- 4.7 ppm), after a single fruit juice load, had 24-h energy expenditure (24-h EE; kcal x kg(-1) x d(-1)), resting (RMR; kcal x kg(-1) x d(-1)) and sleeping (SMR; kcal x kg(-1) x d(-1)) metabolic rates extrapolated from 3.5-h assessments in the Enhanced Metabolic Testing Activity Chamber. Furthermore, RMR was calculated with the World Health Organization (WHO), Schofield weight-based and weight- and height-based equations. Carbohydrate absorption was determined by BH2. Differences (P < 0.05) were determined by t test. RESULTS: All infants with ACM had greater (P < 0.05) extrapolated 24-h EE (91.2 +/- 24.8 versus 78.0 +/- 6.8) and RMR (71.8 +/- 15.2 versus 59.5 +/- 5.9). This represented an increase of 15-18.5%, respectively, in energy expenditures. Carbohydrate malabsorption was a significant determinant of EE, RMR, and SMR. However, the WHO (53.8 +/- 1.0 versus 54.1 +/- 0.9) and both Schofield equations (54.7 +/- 0.9 versus 54.9 +/- 1.0 and 50.6 +/- 7.5 versus 47.3 +/- 6.7) failed to detect any differences in RMR. There was a 20 percentile reduction in growth performance in infants with carbohydrate malabsorption. CONCLUSIONS: Infants with ACM following fruit juice ingestion may have increased daily energy expenditure leading to increased metabolic requirements.

Daily metabolic rate in healthy infants.

BACKGROUND: Previous estimates of daily metabolic rate in infants were based on short-term unstandardized measurements of energy expenditure (EE). OBJECTIVE: Determine 24-hour metabolic profiles in infants. METHODS: Energy expenditure (kcal/min by indirect calorimetry) and physical activity (oscillations in weight/min/kg body weight) were measured in 10 healthy infants (5.0+/-0.8 months, 68+/-3 cm, 7.3+/-0.8 kg) for 24 hours in the Enhanced Metabolic Testing Activity Chamber while allowing parental interaction. Energy intake, 24-hour EE, resting metabolic rate (RMR), and sleeping metabolic rate (SMR) (kcal/kg/day) were determined. In addition, extrapolated 24-hour EE, RMR, and SMR from the first 4 and 6 hours of data were compared with 24-hour measurements. RESULTS: Twenty-four-hour energy intake, EE, RMR, and SMR (mean+/-SD) were 78.2+/-17.6, 74.7+/-3.8, 65.1+/-3.5, and 60.3+/-3.9, respectively. EE and physical activity showed a decrease at 11:30 pm and a return to daytime levels by 5:30 am, suggesting a metabolic circadian rhythm. Extrapolated 24-hour EE, RMR, and SMR from the first 4 hours (72.2+/-6.6, 65.9+/-8.7, and 64.9+/-6.4) and 6 hours (74.8+/-6.7, 65.8+/-6.6, and 64.8+/-5.6) were similar to 24-hour measurements. CONCLUSIONS: An apparent circadian rhythm in metabolic rate and physical activity was detected by 24-hour measurements. Furthermore, shorter-term measurements of the variables were comparable with 24-hour values.

Association between infantile colic and carbohydrate malabsorption from fruit juices in infancy.

OBJECTIVE: To determine whether infantile colic (IC) is associated with malabsorption of carbohydrates present in fruit juices. METHODS: In this double-blind study, parents of 30 healthy infants (5.1 +/- 0.7 months, 7.4 +/- 1.0 kg, 64 +/- 4 cm) were administered a questionnaire to quantitatively assess IC. Thereafter, they were divided into 2 groups, 16 infants with and 14 without IC. Within each treatment group infants were fed 120 mL (16.3 +/- 2.0 mL/kg) of either white grape (sorbitol-free; 1:1 fructose-to-glucose ratio) or apple (sorbitol 0.5 g/dL; 2.6:1 fructose-to-glucose ratio) juice. Physical activity (PA), energy expenditure (EE), crying, and sleeping times were measured for 0.5 and 3.0 hours before and after juice feeding, respectively, using the Enhanced Metabolic Testing Activity Chamber. Carbohydrate malabsorption was determined by breath hydrogen (BH(2)) gas analysis after juice feedings. Statistical differences between groups were determined by 2-way analysis of variance with the Tukey procedure. RESULTS: Infants with IC fed apple juice exhibited carbohydrate malabsorption as shown by increased BH(2) excretion, whereas those without IC absorbed carbohydrates normally when fed this juice. Infants fed apple juice with carbohydrate malabsorption cried more and consequently slept less during the last 1.5 hours of the study. This was associated with increased PA and EE as compared with infants without IC fed apple juice. In contrast, infants fed white grape juice, regardless of IC, showed no increase in BH(2) excretion, PA, and EE. Furthermore, crying and sleeping times were unchanged in infants fed white grape juice regardless of the presence or absence of IC. CONCLUSIONS: IC was associated with carbohydrate malabsorption from fruit juices containing sorbitol and a high fructose-to-glucose ratio.

New equations for calculating the components of energy expenditure in infants.

OBJECTIVES: To derive new equations for 24-hour energy expenditure (24-h EE; kcal/d) and resting (RMR; kcal/d) and sleeping metabolic rates (SMR; kcal/d) in young infants by using the Enhanced Metabolic Testing Activity Chamber (EMTAC). METHODS: Data from 50 (25 male/25 female) healthy normally growing infants (4.9 +/- 1.6 months, 7.1 +/- 1.4 kg, 65 +/- 5 cm) who had 24-h EE, RMR, and SMR extrapolated from 4- to 6-hour metabolic measurements in the EMTAC were used to derive new equations for 24-h EE, RMR, and SMR. Equations were derived by means of multiple regression analysis (SPSS 8.0), with weight alone or with length and weight entered as independent variables. Similar data from 10 additional test infants (4 male/6 female, 5.1 +/- 0.6 months, 7.5 +/- 1.0 kg, 65 +/- 5 cm) were used to cross-validate the new equations. RESULTS: Twenty-four-hour EE, RMR, and SMR were 79.6 +/- 19.2, 66.8 +/- 15.1, and 62.3 +/- 10.3 kcal/kg per day, respectively. No differences existed in RMR (kcal/kg per day) from the 10 test infants between the weight (68.6 +/- 1.9) and height-weight based equations (68.4 +/- 6.1) or that measured by the EMTAC (67.6 +/- 10.2). Weight was the major predictor of 24-h EE, RMR, and SMR. The WHO, Schofield-weight and weight-height equations underestimated (P <.05) by 19%, whereas the new equations were within 4% of RMR obtained from the EMTAC. CONCLUSIONS: The new equations for assessing energy requirements in healthy infants are more accurate than those previously published that underestimated 24-h EE by 15 kcal/kg per day.