Increasing Diagnosis and Treatment of Overweight and Obese Pediatric Patients

Impact of electronic medical record utilization on obesity screening and intervention for obese patients with endometrial cancer

OBJECTIVE

To identify the prevalence of obesity documented within the electronic medical record problem list.

METHODS

We conducted a retrospective cohort study of adult patients with obesity and endometrial cancer receiving care from January 2018 to March 2021 at a single institution. Obesity intervention was defined as receipt of at least one of the following: referral to weight loss clinic, referral to a nutritionist, completion of obesity intervention tab, or documentation of weight loss counseling. Our secondary objectives were to (1) identify the prevalence of completed obesity interventions, (2) identify the number of patients who have achieved weight loss since their initial visit, and (3) identify covariates associated with presence of obesity on problem list, completion of obesity interventions, and weight loss.

RESULTS

We identified 372 patients who met inclusion criteria. Of eligible patients, 202 (54%) had obesity documented on their problem list and 171 (46%) completed at least one obesity intervention. Within our cohort, 195 (52%) patients achieved weight loss from diagnosis or initial clinical encounter at our institution to most recent clinical encounter with median weight loss of 3.9 kg (IQR 1.5-8.0). In the multivariable logistic regressions, patients with obesity on the problem list were approximately twice as likely to have completion of obesity intervention (OR 1.91, 95% CI 1.09, 3.35, p=0.024). Although presence of obesity on the problem list was not associated with weight loss, completion of health maintenance obesity intervention tab in the electronic medical record (Epic) was associated with weight loss (OR 2.77, 95% CI 1.11, 6.89, p=0.03).

CONCLUSIONS

Only half of obese endometrial cancer patients had documentation of obesity within the electronic medical record problem list. The electronic medical record could be leveraged to achieve compliance with weight loss interventions. Further investigation on how the electronic medical record can be optimized to help patients achieve weight loss is needed.

Clinician Needs for Electronic Health Record Pediatric and Adolescent Weight Management Tools: A Mixed-Methods Study

BACKGROUND

 Clinicians play an important role in addressing pediatric and adolescent obesity, but their effectiveness is restricted by time constraints, competing clinical demands, and the lack of effective electronic health record (EHR) tools. EHR tools are rarely developed with provider input.

OBJECTIVES

 We conducted a mixed method study of clinicians who provide weight management care to children and adolescents to determine current barriers for effective care and explore the role of EHR weight management tools to overcome these barriers.

METHODS

 In this mixed-methods study, we conducted three 1-hour long virtual focus groups at one medium-sized academic health center in Missouri and analyzed the focus group scripts using thematic analysis. We sequentially conducted a descriptive statistical analysis of a survey emailed to pediatric and family medicine primary care clinicians (n = 52) at two private and two academic health centers in Missouri.

RESULTS

 Surveyed clinicians reported that they effectively provided health behavior lifestyle counseling at well-child visits (mean of 60 on a scale of 1-100) and child obesity visits (63); however, most felt the current health care system (27) and EHR tools (41) do not adequately support pediatric weight management. Major themes from the clinician focus groups were that EHR weight management tools should display data in a way that (1) improves clinical efficiency, (2) supports patient-centered communication, (3) improves patient continuity between visits, and (4) reduces documentation burdens. An additional theme was (5) clinicians trust patient data entered in real time over patient recalled data.

CONCLUSION

 Study participants report that the health care system status quo and currently available EHR tools do not sufficiently support clinicians working to manage pediatric or adolescent obesity and provide health behavior counseling. Clinician input in the development and testing of EHR weight management tools provides opportunities to address barriers, inform content, and improve efficiencies of EHR use.

Sensitivity of Clinical Pediatric Obesity Diagnosis Documented in Electronic Health Records

Objective. This study tested the sensitivity of obesity diagnosis in electronic health records (EHRs) using body mass index (BMI) classification and identified variables associated with obesity diagnosis. Methods. Eligible children aged 2 to 18 years had a calculable BMI in 2017 and had at least 1 visit in 2016 and 2017. Sensitivity of clinical obesity diagnosis compared with children's BMI percentile was calculated. Logistic regression was performed to determine variables associated with obesity diagnosis. Results. Analyses included 31 059 children with BMI at or above 95th percentile. Sensitivity of clinical obesity diagnosis was 35.81%. Clinical obesity diagnosis was more likely if the child had a well visit, had Medicaid insurance, was female, Hispanic or Black, had a chronic disease diagnosis, and saw a provider in a practice in an urban area or with academic affiliation. Conclusion. Sensitivity of clinical obesity diagnosis in EHR is low. Clinical obesity diagnosis is associated with nonmodifiable child-specific factors but also modifiable practice-specific factors.

Identification of temporal condition patterns associated with pediatric obesity incidence using sequence mining and big data

Background

Electronic health records (EHRs) are potentially important components in addressing pediatric obesity in clinical settings and at the population level. This work aims to identify temporal condition patterns surrounding obesity incidence in a large pediatric population that may inform clinical care and childhood obesity policy and prevention efforts.

Methods

EHR data from healthcare visits with an initial record of obesity incidence (index visit) from 2009 through 2016 at the Children’s Hospital of Philadelphia, and visits immediately before (pre-index) and after (post-index), were compared with a matched control population of patients with a healthy weight to characterize the prevalence of common diagnoses and condition trajectories. The study population consisted of 49,694 patients with pediatric obesity and their corresponding matched controls. The SPADE algorithm was used to identify common temporal condition patterns in the case population. McNemar’s test was used to assess the statistical significance of pattern prevalence differences between the case and control populations.

Results

SPADE identified 163 condition patterns that were present in at least 1% of cases; 80 were significantly more common among cases and 45 were significantly more common among controls (p < 0.05). Asthma and allergic rhinitis were strongly associated with childhood obesity incidence, particularly during the pre-index and index visits. Seven conditions were commonly diagnosed for cases exclusively during pre-index visits, including ear, nose, and throat disorders and gastroenteritis.

Conclusions

The novel application of SPADE on a large retrospective dataset revealed temporally dependent condition associations with obesity incidence. Allergic rhinitis and asthma had a particularly high prevalence during pre-index visits. These conditions, along with those exclusively observed during pre-index visits, may represent signals of future obesity. While causation cannot be inferred from these associations, the temporal condition patterns identified here represent hypotheses that can be investigated to determine causal relationships in future obesity research.

Characteristics of Correctly Identified Pediatric Obesity and Overweight Status and Management in an Academic General Pediatric Clinic

This study identified and characterized the rates of documentation and guideline-based management of overweight and obese children within an academic pediatric clinic through a retrospective electronic medical record review of 7422 well-child visits in 2016. Diagnosis and treatment were analyzed by patient's weight diagnosis, sex, age, and provider training level. The percentages of correctly identified severely obese (90.2%), obese (77.0%), and overweight (42.0%) children were much higher than in previous retrospective chart reviews; however, less than 30% of children were referred for more intensive weight management to a dietitian or pediatric obesity weight management program. Increased provider training level was associated with a lower adherence to pediatric obesity guidelines. Strategic modifications to electronic medical records that automatically offer body mass index-associated weight diagnoses with a link to treatment pathways and resources are needed to facilitate improved compliance with current pediatric obesity guidelines in the primary care setting.