Refining Measurement of Substance Use Disorders Among Women of Child-Bearing Age Using Hospital Records: The Development of the Explicit-Mention Substance Abuse Need for Treatment in Women (EMSANT-W) Algorithm.

Substance use disorder (SUD) in women of reproductive age is associated with adverse health consequences for both women and their offspring. US states need a feasible population-based, case-identification tool to generate better approximations of SUD prevalence, treatment use, and treatment outcomes among women. This article presents the development of the Explicit Mention Substance Abuse Need for Treatment in Women (EMSANT-W), a gender-tailored tool based upon existing International Classification of Diseases, 9th Edition, Clinical Modification diagnostic code-based groupers that can be applied to hospital administrative data. Gender-tailoring entailed the addition of codes related to infants, pregnancy, and prescription drug abuse, as well as the creation of inclusion/exclusion rules based on other conditions present in the diagnostic record. Among 1,728,027 women and associated infants who accessed hospital care from January 1, 2002 to December 31, 2008 in Massachusetts, EMSANT-W identified 103,059 women with probable SUD. EMSANT-W identified 4,116 women who were not identified by the widely used Clinical Classifications Software for Mental Health and Substance Abuse (CCS-MHSA) and did not capture 853 women identified by CCS-MHSA. Content and approach innovations in EMSANT-W address potential limitations of the Clinical Classifications Software, and create a methodologically sound, gender-tailored and feasible population-based tool for identifying women of reproductive age in need of further evaluation for SUD treatment. Rapid changes in health care service infrastructure, delivery systems and policies require tools such as the EMSANT-W that provide more precise identification methods for sub-populations and can serve as the foundation for analyses of treatment use and outcomes.

Development of the drug-exposed infant identification algorithm (DEIIA) and its application to measuring part C early intervention referral and eligibility in Massachusetts, 1998-2005.

The objectives of this study were to develop an algorithm using government-collected administrative data to identify prenatally drug-exposed infants (DEI) and determine the percent who were referred to and eligible for Part C Early Intervention (EI) in Massachusetts. Data from the population-based Pregnancy to Early Life Longitudinal (PELL) Data System were used to develop the Drug-Exposed Infant Identification Algorithm (DEIIA). The DEIIA uses positive toxicology screens on the birth certificate and International Classification of Diseases, 9th Edition, Clinical Modification diagnostic codes in hospital records of the mother (prenatal and birth) and infant (birth and postnatal) to identify infants affected by substance abuse/dependence, withdrawal, and/or prenatal exposure to non-medical use of controlled substances. PELL-EI data linkages were used to determine the percent referred, evaluated, and eligible. The DEIIA identified 7,348 drug-exposed infants born in Massachusetts from 1998 to 2005 to resident mothers (1.2 % of all births). Most DEI (82.6 %) were identified from maternal/infant birth hospital records. Sixty-one percent of all DEI were referred to EI; 87.2 % of those referred were evaluated, and 89.4 % of those evaluated were found eligible. EI data contained information on drug exposure for 59.9 % of referred DEI. Only 2.8 % of MA resident births who were referred to EI but not identified by the DEIIA had drug indicators in EI data. DEI referrals to EI are federally mandated, but many are not referred. The DEIIA uses data available in most states and could be used as a public health screening tool to improve access to developmental services for DEI.

Racial/ethnic differences in hospital use and cost among a statewide population of children with Down syndrome.

Children with Down syndrome (DS) use hospital services more often than children without DS, but data on racial/ethnic variations are limited. This study generated population-based estimates of hospital use and cost to 3 years of age by race/ethnicity among children with DS in Massachusetts using birth certificates linked to birth defects registry and hospital discharge data from 1999 to 2004. Hospital use (≥ 1 post-birth hospitalization and median days hospitalized birth and post-birth) and reasons for hospitalization were compared across maternal race/ethnicity using relative risk (RR) and Wilcoxon rank sums tests, as appropriate. Costs were calculated in 2011 United States dollars. Greater hospital use was observed among children with DS with Hispanic vs. Non-Hispanic White (NHW) mothers (post-birth hospitalization: RR 1.4; median days hospitalized: 20.0 vs. 11.0, respectively). Children with DS and congenital heart defects of Non-Hispanic Black (NHB) mothers had significantly greater median days hospitalized than their NHW counterparts (24.0 vs. 16.0, respectively). Respiratory diagnoses were listed more often among children with Hispanic vs. NHW mothers (50.0% vs. 29.1%, respectively), and NHBs had more cardiac diagnoses (34.1% vs. 21.5%, respectively). The mean total hospital cost was nine times higher among children with DS ($40,075) than among children without DS ($4053), and total costs attributable to DS were almost $18 million. Median costs were $22,781 for Hispanics, $18,495 for NHBs, and $13,947 for NHWs. Public health interventions should address the higher rates of hospital use and hospitalizations for respiratory and cardiac diseases among racial/ethnic minority children with DS in Massachusetts.