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17025

The Rise of the Machines-the Electronic Medical Record Can Facilitate Disease Detection: Pediatric Morbid Obesity In the Crosshairs

Sunday, October 21, 2012
Room 270 (Morial Convention Center)
Caridad B. Martinez-Kinder, DO, Michael L. Forbes, MD, FAAP, Jennifer Dwyer, MD and Sherrie David, RN, Pediatrics, Akron Children's Hospital, Akron, OH

Purpose

Morbid obesity (MO) has been described as “the tobacco addiction of the 21st century.” Morbidly obese adults have elevated risks of preventable metabolic, cardiovascular, neurovascular and orthopedic complications. Morbidly obese adults almost always begin as morbidly obese adolescents. There is growing evidence, however, that pre-teen patients with morbid obesity represent a missed opportunity for pediatric providers to improve detection, diagnosis and management of this national health care crisis.  We hypothesized that a regional clinical database can enhance the detection rate of “occult” morbid obesity in a large, urban pediatric practice. The aims of this study were to a) to describe the prevalence of morbid obesity-for-age as defined by the CDC (MO-CDC) using a large clinical database and b) to describe the disease-specific documentation (DS-ICD9) rates by providers.

Methods

Data was compiled from the electronic medical records (EMR) of patients (2-20 years) who presented to the children’s hospital affiliated outpatient offices in northeastern Ohio during 2011. Using common fields (medical record number, name, gender, body mass index(BMI), race, encounter date, date of birth) and the MO-CDC BMI thresholds, we identified patients who met MO-CDC criteria during well child visits. Provider DS-ICD9 documentation rates were compared. Descriptive statistics were calculated.

Results

We identified 63,201 eligible patients with all necessary fields; 55.2% were male and 8,592 (13.6%) met criteria for MO-CDC. DS-ICD9 codes were documented in 4,405 (51.3%) of the MO-CDC cases. Among the documented, morbid obesity (ICD9, 278.01) was specifically entered in 232 (5.3%) of MO-CDC cases. Abnormal weight gain (783.1), overweight (278.02) and obesity-NOS (278.00) accounted for over 80% of the DS-ICD9. Multiple DS-ICD9 codes were used in 12% of patients.

Conclusion The use of a regional pediatric EMR facilitated the recognition of missed opportunities in the diagnosis and management of MO in children. While 13.6% met the MO-CDC BMI criterion, nearly half of those affected were undocumented. Additionally, the DS-ICD9 for morbid obesity, specifically, was not used in over 95% of affected cases when documented. There are limitations in this study. Undocumented diagnosis codes are a common problem with paper and EMR. It is possible that MO was recognized and managed by providers without documentation. We remain concerned, however, that the severe rates of under documentation (greater than 95%) may truly reflect undetected and unmanaged cases. This study may represent the failure of passive disease (MO) identification and management by providers. Further, we suggest active calculation and EMR alerts using the MO-CDC criterion at each visit. Finally, we suggest renaming the condition Clinical Obesity to emphasize the difference from obesity’s social and cosmetic consequences.