Electronic Health Record Prompts for Childhood Obesity

(iPOP-UP Trial)

Recruiting at 2 trial locations

Overseen By Mahnoosh (Mona) Sharifi, MD, MPH

Age: Any Age

Sex: Any

Trial Phase: Academic

Sponsor: Yale University

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Approved in 1 Jurisdiction This treatment is already approved in other countries

Compensation: Varies

Number of Visits: Unknown

240772 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

The purpose of this study is to evaluate the dissemination and implementation of electronic health record-based clinical decision support tools for the management of pediatric overweight and obesity in primary care.

Do I have to stop taking my current medications for this trial?

The trial protocol does not specify whether you need to stop taking your current medications. It seems focused on implementing electronic health record tools rather than changing medication regimens.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What safety data exists for the EHR prompts for childhood obesity treatment?

The provided research does not directly address safety data for the EHR prompts for childhood obesity treatment. The studies focus on the effectiveness of electronic prompts in improving screening rates, implementing obesity prevention strategies, and standardizing weight management practices. However, they do not specifically mention safety data or adverse effects related to the use of these prompts. ^{1 2 3 4 5}

Is the use of electronic health record prompts for childhood obesity safe?

The studies reviewed focus on the effectiveness of electronic health record prompts in improving obesity screening and management, but they do not provide specific safety data. However, these prompts are generally considered safe as they are tools to aid healthcare providers in decision-making rather than direct medical treatments. ^{1 2 3 4 5}

Is the treatment iPOP-UP a promising treatment for childhood obesity?

Yes, iPOP-UP is a promising treatment for childhood obesity because it uses electronic health record prompts to improve screening rates for metabolic conditions, enhance documentation of obesity, and potentially inform better clinical care and prevention efforts. ^{1 4 6 7 8}

How is the iPOP-UP treatment for childhood obesity different from other treatments?

The iPOP-UP treatment is unique because it uses electronic health record (EHR) prompts to improve the screening and management of childhood obesity, which helps healthcare providers identify and address obesity more effectively during routine visits. ^{1 4 6 7 8}

What data supports the idea that Electronic Health Record Prompts for Childhood Obesity is an effective treatment?

The available research shows that using Electronic Health Record Prompts for Childhood Obesity can significantly improve the identification of children at risk for obesity and enhance education on obesity prevention. One study found a significant increase in the practice of identifying childhood obesity and documenting prevention education. This suggests that the treatment helps healthcare providers better recognize and address obesity in children, leading to healthier lifestyle changes. Compared to other methods, like smartphone apps, which focus on lifestyle changes, the prompts directly support healthcare providers in making informed decisions during patient visits. ^{2 9 10 11 12}

What data supports the effectiveness of the treatment iPOP-UP for childhood obesity?

Research shows that using electronic health record prompts and evidence-based guidelines in primary care can significantly improve the identification and education of childhood obesity. This approach helps healthcare providers better recognize and manage obesity, leading to healthier lifestyle changes in children. ^{2 9 10 11 12}

Who Is on the Research Team?

Mahnoosh (Mona) Sharifi, MD, MPH

Principal Investigator

Yale University

Are You a Good Fit for This Trial?

This trial is for primary care practices using a specific EHR system, their clinicians (including doctors, residents, fellows, PAs, and NPs), and patients aged 2-18 with overweight/obesity. It focuses on those seen for well or follow-up visits by prescribing clinicians.

Inclusion Criteria

Primary Care Practices: all primary care practices using the EHR system of one of the 3 health systems participating in the study that agree to participate in the iPOP-UP trial

I am a healthcare provider in pediatric primary care.

Exclusion Criteria

None - exclusion criteria are purposefully limited in this real-world implementation study

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention Implementation

Implementation of the iPOP-UP intervention to improve adherence to national guidelines for managing childhood obesity

18 months

Regular visits as per primary care schedule

Follow-up

Participants are monitored for changes in BMI and adherence to clinical guidelines

6 months

What Are the Treatments Tested in This Trial?

Interventions

• Improving Pediatric Obesity Practice Using Prompts (iPOP-UP)

Trial Overview The study tests the use of electronic prompts in patient records to help manage pediatric overweight and obesity in primary care settings. It aims to see how well these prompts work when used widely in real-world conditions.

How Is the Trial Designed?

Group I: Clinical Decision Support Tool Experimental Treatment 1 Intervention

Practices assigned to iPOP-UP intervention which involves EHR-based CDS tools refined through a formative evaluation and user-centered design.

Group II: Control Active Control 1 Intervention

Practices assigned to usual care that will not have access to the iPOP-UP CDS tool but will have access to many opportunities available to all pediatric clinicians nationally around the release of the new American Academy of Pediatrics guidelines for obesity management.

Improving Pediatric Obesity Practice Using Prompts (iPOP-UP) is already approved in United States for the following indications:

Approved in United States as iPOP-UP for:

• Pediatric overweight and obesity management

Who Is Running the Clinical Trial?

Yale University

Lead Sponsor

Trials

1,963

Recruited

3,046,000+

National Institute on Minority Health and Health Disparities (NIMHD)

Collaborator

Trials

473

Recruited

1,374,000+

Published Research Related to This Trial

Implementing evidence-based guidelines for childhood obesity identification and prevention in primary care significantly increased the identification of at-risk children, with a notable improvement in documentation (p < .0001).

The use of a tracking form during preventative care visits enhanced the delivery of obesity prevention education through motivational interviewing, leading to better engagement with families (p < .05).

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Implementation of childhood obesity identification and prevention strategies in primary care: A quality improvement project. Rankin, A., Blood-Siegfried, J., Vorderstrasse, A., et al.[2023]

A quality improvement project at a children's hospital successfully increased the prescription rate for weight management follow-up appointments from 32% to 58% among children with obesity or overweight, demonstrating effective implementation of provider education and system changes.

The initiative also resulted in a significant increase in attendance for weight management visits, with 40% of those prescribed follow-up attending, compared to only 13% before the project, indicating improved engagement in weight management care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Quality Improvement Initiative Addressing Provider Prescription of Weight Management Follow-up in Primary Care. Kharofa, RY., Siegel, RM., Morehous, JF.[2022]

A new app evaluation tool called Ped-WHAT was developed to assess smartphone applications for childhood obesity management based on evidence-based behavior modification strategies and American Academy of Pediatrics guidelines.

After training healthcare providers on how to use the Ped-WHAT tool, there were significant improvements in their knowledge and confidence in using these apps, highlighting the importance of provider education in effectively managing childhood obesity.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Obesity Applications in Smartphones: Development and Use of an Evaluation Tool. Al-Lami, N., Sear, K., Dai, W., et al.[2021]

Primary care physicians struggle to follow national guidelines for pediatric obesity screening and prevention, often due to unfamiliarity and barriers in their practice.

The study highlights the potential of electronic decision support tools to improve adherence to obesity-related recommendations, but emphasizes the need for thoughtful development and educational outreach to encourage their effective use.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Provider perspectives on electronic decision supports for obesity prevention. Dryden, EM., Hardin, J., McDonald, J., et al.[2012]

A quality improvement project in two children's hospitals led to a significant increase in the diagnosis of obesity among hospitalized children, reaching 70.2% for those with elevated BMI.

When obesity was documented, patients were 35 times more likely to receive at least one intervention during their hospital stay, highlighting the importance of proper diagnosis in facilitating effective management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Quality Improvement Project to Promote Identification and Treatment of Children With Obesity Admitted to Hospital. Myers, J., Werk, LN., Hossain, MJ., et al.[2021]

The implementation of an automated prompt in the electronic medical record significantly increased the screening rates for metabolic conditions in children with obesity, with lab test orders rising from 2% to 52% and completed screenings improving from 1% to 27%.

Health education referrals also saw a notable increase from 0.4% to 7%, indicating that the EMR intervention effectively enhanced both screening and referral processes, although there was no significant change in BMI percentile during the follow-up period.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

An electronic medical record (EMR) prompt improves screening rates for metabolic conditions among children with obesity. Lee, NE., Parker, MM., Concepcion, JQ.[2023]

The implementation of computer-assisted decision tools in pediatric weight management led to a significant increase in the measurement of height and weight in children and adolescents, rising from 66% to 94% over three years.

There was a dramatic improvement in the diagnosis of overweight and obesity among children, increasing from 12% to 61%, along with a rise in documented counseling for exercise and nutrition from 1% to 50%, demonstrating the effectiveness of the initiative.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Implementation of clinical practice guidelines for pediatric weight management. Coleman, KJ., Hsii, AC., Koebnick, C., et al.[2022]

A new algorithm was developed to accurately identify children aged 1-5.99 years with severe early onset obesity using both structured and unstructured data from electronic health records, achieving high precision with a rule-based approach (0.895 accuracy at one site).

This algorithm is crucial for targeting interventions in children at high risk for obesity-related health issues and aids in identifying genetic factors by excluding patients with other causes of obesity, enhancing future healthcare applications.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers. Lingren, T., Thaker, V., Brady, C., et al.[2020]

In a study of 12,093 medication dose alerts at Johns Hopkins Children's Medical and Surgical Center, only 6% of medication orders generated alerts, indicating a low compliance rate of 8.5% for dose range alerts and 5.5% for informational alerts.

The findings suggest that underdosing alerts are less valuable to providers compared to overdosing alerts, and the low compliance rates highlight the need to reassess clinical practices and alert thresholds in the medication ordering process.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluation of medication dose alerts in pediatric inpatients. Scharnweber, C., Lau, BD., Mollenkopf, N., et al.[2022]

A study of 49,694 pediatric patients revealed that conditions like asthma and allergic rhinitis are significantly associated with obesity incidence, particularly noted during healthcare visits leading up to the diagnosis of obesity.

The analysis identified 163 condition patterns related to obesity, suggesting that certain health issues prior to obesity diagnosis may serve as early indicators, warranting further investigation into their potential causal relationships.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Identification of temporal condition patterns associated with pediatric obesity incidence using sequence mining and big data. Campbell, EA., Qian, T., Miller, JM., et al.[2021]

Customizing electronic medical records (EMR) with evidence-based guidelines significantly improved the documentation of body mass index (BMI) and the diagnosis of overweight and obesity in children aged 7 to 18 years.

Despite the increase in diagnosis rates following EMR customization, the overall rates of obesity diagnosis still remain lower than the actual prevalence in the community, indicating a need for further improvement in screening practices.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Childhood obesity: Can electronic medical records customized with clinical practice guidelines improve screening and diagnosis? Saviñon, C., Taylor, JS., Canty-Mitchell, J., et al.[2018]

The use of a standardized electronic health record (EHR) template significantly improved the documentation of obesity in well-child care visits, increasing rates from 34% to 47%.

This improved documentation also led to enhanced counseling on nutrition and physical activity, with counseling rates rising from 44% to 66% for nutrition and from 9% to 23% for physical activity.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Impact of an Electronic Template on Documentation of Obesity in a Primary Care Clinic. Thaker, VV., Lee, F., Bottino, CJ., et al.[2018]

Citations

1. Netherlands pubmed.ncbi.nlm.nih.gov

Implementation of childhood obesity identification and prevention strategies in primary care: A quality improvement project. [2023]

2. United States pubmed.ncbi.nlm.nih.gov

A Quality Improvement Initiative Addressing Provider Prescription of Weight Management Follow-up in Primary Care. [2022]

3. United States pubmed.ncbi.nlm.nih.gov

Obesity Applications in Smartphones: Development and Use of an Evaluation Tool. [2021]

4. United States pubmed.ncbi.nlm.nih.gov

Provider perspectives on electronic decision supports for obesity prevention. [2012]

5. Netherlands pubmed.ncbi.nlm.nih.gov

Quality Improvement Project to Promote Identification and Treatment of Children With Obesity Admitted to Hospital. [2021]

6. United States pubmed.ncbi.nlm.nih.gov

An electronic medical record (EMR) prompt improves screening rates for metabolic conditions among children with obesity. [2023]

7. United States pubmed.ncbi.nlm.nih.gov

Implementation of clinical practice guidelines for pediatric weight management. [2022]

8. Germany pubmed.ncbi.nlm.nih.gov

Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers. [2020]

9. Ireland pubmed.ncbi.nlm.nih.gov

Evaluation of medication dose alerts in pediatric inpatients. [2022]

10. England pubmed.ncbi.nlm.nih.gov

Identification of temporal condition patterns associated with pediatric obesity incidence using sequence mining and big data. [2021]

11. United States pubmed.ncbi.nlm.nih.gov

Childhood obesity: Can electronic medical records customized with clinical practice guidelines improve screening and diagnosis? [2018]

12. United States pubmed.ncbi.nlm.nih.gov

Impact of an Electronic Template on Documentation of Obesity in a Primary Care Clinic. [2018]