Alyson B. Goodman

Background: Many studies rely on the International Classification of Diseases, 9th or 10th Revision, Clinical Modification codes to define obesity in electronic health records data. While prior studies found misclassification and low sensitivity of codes for pediatric obesity, it remains unclear whether this misclassification is random and what are the implications of combining different code types to define obesity. Methods: We assessed prevalence, sensitivity, and specificity of obesity codes among 7.4 million children aged 2–19 years over 2014–2021. Among those with obesity in 2021, we estimated the probability of receiving any code or a specific code type by patient characteristics. Results: Obesity code utilization increased in prevalence from 3.9% in 2014 to 9.8% in 2021; prevalence of obesity based on BMI increased from 17.4% to 20.5%. Code sensitivity increased from 19.8% to 40.8%. Among children with obesity in 2021, those with severe obesity (reference: no severe obesity) and chronic disease (reference: no chronic disease) were more likely to get a code, and the highest likelihood was associated with obesity diagnosis codes (vs. status codes). Conclusions: Despite increases, obesity code utilization remained low. Obesity code misclassification is not random and certain child characteristics (e.g., severe obesity or chronic disease) are associated with a higher probability of getting a code. There are also significant differences by code type; thus, caution should be taken before combining obesity codes as a proxy for obesity status, especially in longitudinal analyses. More universal documentation of obesity may improve the quality of care and the use of these data for evaluation and research purposes.

Equitable access to affordable, effective, and safe obesity prevention and treatment remains a problem for many children and families in the U.S. In 2023, the American Academy of Pediatrics (AAP) published its first Clinical Practice Guideline (CPG) for pediatric obesity evaluation and treatment, aiding the field’s awareness of effective approaches. CDC has supported the adapting and packaging of existing, effective Family Healthy Weight Programs that deliver CPG-recommended intensive behavioral treatment for kids. Currently, at least six family-centered programs are recognized by CDC and can be implemented in clinical and community settings to support child health. CDC and other national partners are coordinating the movement of these research-tested FHWPs into public health practice. This work includes implementing FHWPs in over 60 US communities and supporting national-level infrastructure improvements. CDC is committed to engaging with stakeholders to help scale proven strategies that ensure all children receive the care they need to thrive.

Background: Prior studies have documented differences in the age, racial, and ethnic characteristics among patients with SARS-CoV-2 infection. However, little is known about how these characteristics changed over time during the pandemic and whether racial, ethnic, and age disparities evident early in the pandemic were persistent over time. This study reports on trends in SARS-CoV-2 infections among U.S. adults from March 1, 2020 to January, 31 2022, using data from electronic health records. Methods and Findings: We captured repeated cross-sectional information from 43 large healthcare systems in 52 U.S. States and territories, participating in PCORnet ^® , the National Patient-Centered Clinical Research Network. Using distributed queries executed at each participating institution, we acquired information for all patients ≥ 20 years of age who were tested for SARS-CoV-2 (both positive and negative results), including care setting, age, sex, race, and ethnicity by month as well as comorbidities (assessed with diagnostic codes). During this time period, 1,325,563 patients had positive (13% inpatient) and 6,705,868 patients had negative (25% inpatient) viral tests for SARS-CoV-2. Disparities in testing positive were present across racial and ethnic groups, especially in the inpatient setting. Compared to White patients, Black or African American and other race patients had relative risks for testing positive of 1.5 or greater in the inpatient setting for 12 of the 23-month study period. Compared to non-Hispanic patients, Hispanic patients had relative risks for testing positive in the inpatient setting of 1.5 or greater for 16 of 23. Ethnic and racial differences were present in emergency department and ambulatory settings but were less common across time than in inpatient settings. Trends in infections by age group demonstrated higher test positivity for older patients in the inpatient setting only for most months, except for June and July of 2020, April to August 2021, and January 2022. Comorbidities were common, with much higher rates among those hospitalized; hypertension (38% of patients SARS-CoV-2 positive vs. 29% for those negative) and type 2 diabetes mellitus (22% vs. 13%) were the most common. Conclusion and Relevance: Racial and ethnic disparities changed over time among persons infected with SARS-CoV-2. These trends highlight potential underlying mechanisms, such as poor access to care and differential vaccination rates, that may have contributed to greater disparities, especially early in the pandemic. Monitoring data on characteristics of patients testing positive in real time could allow public health officials and policymakers to tailor interventions to ensure that patients and communities most in need are receiving adequate testing, mitigation strategies, and treatment.

Context: We describe a participatory framework that enhanced and implemented innovative changes to an existing distributed health data network (DHDN) infrastructure to support linkage across sectors and systems. Our processes and lessons learned provide a potential framework for other multidisciplinary infrastructure development projects that engage in a participatory decision-making process. Program: The Childhood Obesity Data Initiative (CODI) provides a potential framework for local and national stakeholders with public health, clinical, health services research, community intervention, and information technology expertise to collaboratively develop a DHDN infrastructure that enhances data capacity for patient-centered outcomes research and public health surveillance. CODI utilizes a participatory approach to guide decision making among clinical and community partners. Implementation: CODI's multidisciplinary group of public health and clinical scientists and information technology experts collectively defined key components of CODI's infrastructure and selected and enhanced existing tools and data models. We conducted a pilot implementation with 3 health care systems and 2 community partners in the greater Denver Metro Area during 2018-2020. Evaluation: We developed an evaluation plan based primarily on the Good Evaluation Practice in Health Informatics guideline. An independent third party implemented the evaluation plan for the CODI development phase by conducting interviews to identify lessons learned from the participatory decision-making processes. Discussion: We demonstrate the feasibility of rapid innovation based upon an iterative and collaborative process and existing infrastructure. Collaborative engagement of stakeholders early and iteratively was critical to ensure a common understanding of the research and project objectives, current state of technological capacity, intended use, and the desired future state of CODI architecture. Integration of community partners' data with clinical data may require the use of a trusted third party's infrastructure. Lessons learned from our process may help others develop or improve similar DHDNs.

Context: Integrating longitudinal data from community-based organizations (eg, physical activity programs) with electronic health record information can improve capacity for childhood obesity research. Objective: A governance framework that protects individual privacy, accommodates organizational data stewardship requirements, and complies with laws and regulations was developed and implemented to support the harmonization of data from disparate clinical and community information systems. Participants and Setting: Through the Childhood Obesity Data Initiative (CODI), 5 Colorado-based organizations collaborated to expand an existing distributed health data network (DHDN) to include community-generated data and assemble longitudinal patient records for research. Design: A governance work group expanded an existing DHDN governance infrastructure with CODI-specific data use and exchange policies and procedures that were codified in a governance plan and a delegated-authority, multiparty, reciprocal agreement. Results: A CODI governance work group met from January 2019 to March 2020 to conceive an approach, develop documentation, and coordinate activities. Governance requirements were synthesized from the CODI use case, and a customized governance approach was constructed to address governance gaps in record linkage, a procedure to request data, and harmonizing community and clinical data. A Master Sharing and Use Agreement (MSUA) and Memorandum of Understanding were drafted and executed to support creation of linked longitudinal records of clinical- and community-derived childhood obesity data. Furthermore, a multiparty infrastructure protocol was approved by the local institutional review board (IRB) to expedite future CODI research by simplifying IRB research applications. Conclusion: CODI implemented a clinical-community governance strategy that built trust between organizations and allowed efficient data exchange within a DHDN. A thorough discovery process allowed CODI stakeholders to assess governance capacity and reveal regulatory and organizational obstacles so that the governance infrastructure could effectively leverage existing knowledge and address challenges. The MSUA and complementary governance documents can inform similar efforts.

Harrison MR, et al. Clin Nutr Res. 2019 Oct;8(4):255-264. https://doi.org/10.7762/cnr.2019.8.4.255