OBJECTIVES:
The goal of this study was to develop an algorithm based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), codes for classifying children with chronic disease (CD) according to level of medical complexity and to assess the algorithm’s sensitivity and specificity.
METHODS:
A retrospective observational study was conducted among 700 children insured by Washington State Medicaid with ≥1 Seattle Children’s Hospital emergency department and/or inpatient encounter in 2010. The gold standard population included 350 children with complex chronic disease (C-CD), 100 with noncomplex chronic disease (NC-CD), and 250 without CD. An existing ICD-9-CM–based algorithm called the Chronic Disability Payment System was modified to develop a new algorithm called the Pediatric Medical Complexity Algorithm (PMCA). The sensitivity and specificity of PMCA were assessed.
RESULTS:
Using hospital discharge data, PMCA’s sensitivity for correctly classifying children was 84% for C-CD, 41% for NC-CD, and 96% for those without CD. Using Medicaid claims data, PMCA’s sensitivity was 89% for C-CD, 45% for NC-CD, and 80% for those without CD. Specificity was 90% to 92% in hospital discharge data and 85% to 91% in Medicaid claims data for all 3 groups.
CONCLUSIONS:
PMCA identified children with C-CD (who have accessed tertiary hospital care) with good sensitivity and good to excellent specificity when applied to hospital discharge or Medicaid claims data. PMCA may be useful for targeting resources such as care coordination to children with C-CD.
Methods
Study PopulationWashington and Colorado residents who gave birth to live singleton infants and were enrolled in the Medicaid-AFDC program at the time of delivery composed the study populations. We chose women in the Medicaid-AFDC program because the eligibility requirements for this program
A B S T R A C T BACKGROUND AND OBJECTIVES:The Pediatric Medical Complexity Algorithm (PMCA) was developed to stratify children by level of medical complexity. We sought to refine PMCA and evaluate its performance based on the duration of eligibility and completeness of Medicaid data.
Few studies have examined health care access for the growing population of pregnant women who cycle in and out of urban jails. The present study compared use of Medicaid-funded perinatal services for births to women who were in jail during pregnancy and births to women who had been in jail, but not while pregnant. Jail contact during pregnancy increased the likelihood women would receive prenatal care (odds ratio [OR] = 5.95; 95% confidence interval [CI] 2.18-16.23) and maternity support services (OR = 1.80; 95% CI 1.12-2.88), but was associated with fewer total prenatal and support visits. Jail contact during a previous pregnancy was associated with fewer prenatal care visits, more support service visits, and longer time receiving case management. Jail settings can become a place of coordination between public health and criminal justice professionals to ensure that pregnant women receive essential services following release. Service coordination may increase women's engagement in health services during future pregnancies, with or without subsequent incarceration.
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