Details

Autor(en) / Beteiligte

• Bailey, L Charles
• Milov, David E
• Kelleher, Kelly
• Kahn, Michael G
• Del Beccaro, Mark
• Yu, Feliciano
• Richards, Thomas
• Forrest, Christopher B
• Bullen, Chris

Titel

Multi-Institutional Sharing of Electronic Health Record Data to Assess Childhood Obesity

Ist Teil von

• PloS one, 2013-06, Vol.8 (6), p.e66192-e66192

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2013

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• To evaluate the validity of multi-institutional electronic health record (EHR) data sharing for surveillance and study of childhood obesity. We conducted a non-concurrent cohort study of 528,340 children with outpatient visits to six pediatric academic medical centers during 2007-08, with sufficient data in the EHR for body mass index (BMI) assessment. EHR data were compared with data from the 2007-08 National Health and Nutrition Examination Survey (NHANES). Among children 2-17 years, BMI was evaluable for 1,398,655 visits (56%). The EHR dataset contained over 6,000 BMI measurements per month of age up to 16 years, yielding precise estimates of BMI. In the EHR dataset, 18% of children were obese versus 18% in NHANES, while 35% were obese or overweight versus 34% in NHANES. BMI for an individual was highly reliable over time (intraclass correlation coefficient 0.90 for obese children and 0.97 for all children). Only 14% of visits with measured obesity (BMI ≥95%) had a diagnosis of obesity recorded, and only 20% of children with measured obesity had the diagnosis documented during the study period. Obese children had higher primary care (4.8 versus 4.0 visits, p<0.001) and specialty care (3.7 versus 2.7 visits, p<0.001) utilization than non-obese counterparts, and higher prevalence of diverse co-morbidities. The cohort size in the EHR dataset permitted detection of associations with rare diagnoses. Data sharing did not require investment of extensive institutional resources, yet yielded high data quality. Multi-institutional EHR data sharing is a promising, feasible, and valid approach for population health surveillance. It provides a valuable complement to more resource-intensive national surveys, particularly for iterative surveillance and quality improvement. Low rates of obesity diagnosis present a significant obstacle to surveillance and quality improvement for care of children with obesity.