Feasibility of Evaluating the CHIPRA Care Quality Measures in Electronic Health Record Data

• Published in: Pediatrics (Evanston) 2012-07, Vol.130 (1), p.139-149
• Main Authors: GOLD, Rachel, ANGIER, Heather, MANGIONE-SMITH, Rita, GALLIA, Charles, MCLNTIRE, Patti J, COWBURN, Stuart, TILLOTSON, Carrie, DEVOE, Jennifer E
• Format: Article
• Language: English
• Subjects: Adolescent; Biological and medical sciences; Body Mass Index; Child; Child, Preschool; Childrens health insurance programs; Chlamydia Infections - diagnosis; Community Health Centers - organization & administration; Community Health Centers - standards; Electronic Health Records; Feasibility Studies; Federal legislation; Female; General aspects; Humans; Insurance, Health - legislation & jurisprudence; Male; Medical sciences; Medically Uninsured; Miscellaneous; Oregon; Pediatrics; Pediatrics - legislation & jurisprudence; Pediatrics - standards; Pregnancy; Public health. Hygiene; Public health. Hygiene-occupational medicine; Quality Assurance, Health Care - legislation & jurisprudence; Quality Assurance, Health Care - methods; Quality Indicators, Health Care; Quality of care; Special; Young Adult
• ISSN: 0031-4005; 1098-4275
• DOI: 10.1542/peds.2011-3705

The Children's Health Insurance Program Reauthorization Act of 2009 (CHIPRA) includes provisions for identifying standardized pediatric care quality measures. These 24 "CHIPRA measures" were designed to be evaluated by using claims data from health insurance plan populations. Such data have limited ability to evaluate population health, especially among uninsured people. The rapid expansion of data from electronic health records (EHRs) may help address this limitation by augmenting claims data in care quality assessments. We outline how to operationalize many of the CHIPRA measures for application in EHR data through a case study of a network of >40 outpatient community health centers in 2009-2010 with a single EHR. We assess the differences seen when applying the original claims-based versus adapted EHR-based specifications, using 2 CHIPRA measures (Chlamydia screening among sexually active female patients; BMI percentile documentation) as examples. Sixteen of the original CHIPRA measures could feasibly be evaluated in this dataset. Three main adaptations were necessary (specifying a visit-based population denominator, calculating some pregnancy-related factors by using EHR data, substituting for medication dispense data). Although it is feasible to adapt many of the CHIPRA measures for use in outpatient EHR data, information is gained and lost depending on how numerators and denominators are specified. We suggest first steps toward application of the CHIPRA measures in uninsured populations, and in EHR data. The results highlight the importance of considering the limitations of the original CHIPRA measures in care quality evaluations.