Lauren S Miller1, Meng Wu1, Anne M Schettine1, Lindsay W Cogan1,2. 1. New York State Department of Health, Office of Quality and Patient Safety, Albany, NY. 2. Department of Health Policy Management & Behavior, School of Public Health, University at Albany, Albany, NY.
Abstract
OBJECTIVE: The ability to identify children with special health care needs (CSHCN) is crucial to evaluate disparities in the quality of health care for children in Medicaid Managed Care. We developed and assessed the accuracy of a new method to classify CSHCN. DATA SOURCES: Secondary data analysis was conducted using NYS Medicaid administrative data and the Children with Chronic Conditions Screener (CCC Screener). STUDY DESIGN: This study included 5,907 NYS Medicaid beneficiaries (17 years old or younger) whose parents completed the CCC Screener in 2014. Medicaid administrative data were used to create a risk score to assess the risk of special needs, and a cut point was identified to differentiate between children with versus without special needs. Diagnostic accuracy of the method was assessed using sensitivity and specificity analyses. PRINCIPAL FINDINGS: Applying the CCC Screener as the "gold standard," the risk score correctly classified the majority of CSHCN as positive (sensitivity = 75 percent) and the majority of the children without special needs as negative (specificity = 79 percent). This method demonstrated decent diagnostic ability (AUC = 0.77). CONCLUSIONS: Our method can identify CSHCN in the NYS Medicaid Managed Care population and will help the State monitor the quality of care for this vulnerable population. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
OBJECTIVE: The ability to identify children with special health care needs (CSHCN) is crucial to evaluate disparities in the quality of health care for children in Medicaid Managed Care. We developed and assessed the accuracy of a new method to classify CSHCN. DATA SOURCES: Secondary data analysis was conducted using NYS Medicaid administrative data and the Children with Chronic Conditions Screener (CCC Screener). STUDY DESIGN: This study included 5,907 NYS Medicaid beneficiaries (17 years old or younger) whose parents completed the CCC Screener in 2014. Medicaid administrative data were used to create a risk score to assess the risk of special needs, and a cut point was identified to differentiate between children with versus without special needs. Diagnostic accuracy of the method was assessed using sensitivity and specificity analyses. PRINCIPAL FINDINGS: Applying the CCC Screener as the "gold standard," the risk score correctly classified the majority of CSHCN as positive (sensitivity = 75 percent) and the majority of the children without special needs as negative (specificity = 79 percent). This method demonstrated decent diagnostic ability (AUC = 0.77). CONCLUSIONS: Our method can identify CSHCN in the NYS Medicaid Managed Care population and will help the State monitor the quality of care for this vulnerable population. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
Entities:
Keywords:
Chronic disease; Medicaid; administrative data uses; child and adolescent health; disability; mental health
Authors: Christina D Bethell; Debra Read; John Neff; Stephen J Blumberg; Ruth E K Stein; Virginia Sharp; Paul W Newacheck Journal: Ambul Pediatr Date: 2002 Jan-Feb
Authors: P W Newacheck; B Strickland; J P Shonkoff; J M Perrin; M McPherson; M McManus; C Lauver; H Fox; P Arango Journal: Pediatrics Date: 1998-07 Impact factor: 7.124