Assessing the Burden of Neonatal Abstinence Syndrome: Validation of ICD-9-CM Data, Florida, 2010-2011

Trends in maternal opioid use: Statewide differences by sociodemographic characteristics in Florida from 2000 to 2019

BACKGROUND

Maternal opioid use (MOU) remains a public health concern. Studies have demonstrated significant increases in MOU, but estimates using ICD-10-CM or stratified by sociodemographic variables are limited.

OBJECTIVES

Using a statewide, population-based dataset of Florida resident deliveries from 2000 to 2019, we examined the trend of MOU by age, race/ethnicity, education level, and insurance.

METHODS

Florida administrative data was used to conduct a retrospective cohort study. MOU was identified using opioid-related hospital discharge diagnoses documented prenatally or at delivery. Maternal sociodemographic variables were obtained from Florida vital statistics. Joinpoint regression was used to identify statistically significant changes in the trends overall and stratified by sociodemographic variables. Results are presented as annual percentage changes (APC) and 95% confidence intervals.

RESULTS

Our sample included over 3.6 million Florida resident mothers; of which, MOU was identified in 1% (n = 22,828) of the sample. From 2000 to 2019, MOU increased over ten-fold from 8.7 to 94.7 per 10,000 live birth deliveries. MOU increased significantly from 2000 to 2011 (APC: 32.8; 95% CI: 29.4, 36.2), remained stable from 2011 to 2016, and decreased significantly from 2016 to 2019 (APC: 3.9; 95% CI: -6.6, -1.0). However, from 2016 to 2019, MOU increased among non-Hispanic Black mothers (APC: 9.2; 95% CI: 7.5, 11.0), and those ages 30-34 (APC: 2.9; 95% CI: 1.2, 4.6) and 35-39 (APC: 6.4; 95% CI: 4.3, 8.4).

CONCLUSIONS

Accurate prevalence estimates of MOU by sociodemographic factors are necessary to fully understand prevalence trends, describe the burden among sub-populations, and develop targeted interventions.

Accuracy of diagnostic codes for prenatal opioid exposure and neonatal opioid withdrawal syndrome

OBJECTIVE

Determine the accuracy of diagnostic codes in identifying Prenatal Opioid Exposure (POE) and Neonatal Opioid Withdrawal Syndrome (NOWS).

STUDY DESIGN

A cross-sectional study of 374,222 mother-infant dyads with delivery from 01/01/2010 to 12/31/2019. We ascertained maternal diagnostic codes for opioid use during pregnancy and infant diagnostic codes for drug exposure and withdrawal. We assessed sensitivity and positive predictive value (PPV) for POE and NOWS, defined using laboratory, pharmacy, and clinical data.

RESULTS

Maternal codes had low sensitivity (36.4%) and PPV (34.7%) for POE. Infant codes for drug exposure were neither sensitive for POE (14%) nor NOWS (31.6%) and had low PPV. Codes for newborn withdrawal had low sensitivity (31.6%) for detecting NOWS, but high PPV (85%). Sensitivity improved (95.1%) for NOWS requiring pharmacologic treatment.

CONCLUSIONS

Diagnostic codes identify POE and NOWS poorly. Improved case identification would include pharmacy and laboratory results, and clearly defined criteria for evidence of withdrawal.

Trajectories of Prescription Opioid Utilization During Pregnancy Among Prepregnancy Chronic Users and Risk of Neonatal Opioid Withdrawal Syndrome

Little is known about the impact of dose, duration, and timing of prenatal prescription opioid exposure on the risk of neonatal opioid withdrawal syndrome (NOWS). Using a cohort of 18,869 prepregnancy chronic opioid users nested within the 2000-2014 Medicaid Analytic eXtract, we assessed average opioid dosage within biweekly gestational age intervals, created group-based trajectory models, and evaluated the association between trajectory groups and NOWS risk. Women were grouped into 6 distinct opioid use trajectories which, based on observed patterns, were categorized as 1) continuous very low-dose use, 2) continuous low-dose use, 3) initial moderate-dose use with a gradual decrease to very low-dose/no use, 4) initial high-dose use with a gradual decrease to very low-dose use, 5) continuous moderate-dose use, and 6) continuous high-dose use. Absolute risk of NOWS per 1,000 infants was 7.7 for group 1 (reference group), 28.8 for group 2 (relative risk (RR) = 3.7, 95% confidence interval (CI): 2.8, 5.0), 16.5 for group 3 (RR = 2.1, 95% CI: 1.5, 3.1), 64.9 for group 4 (RR = 8.4, 95% CI: 5.6, 12.6), 77.3 for group 5 (RR = 10.0, 95% CI: 7.5, 13.5), and 172.4 for group 6 (RR = 22.4, 95% CI: 16.1, 31.2). Trajectory models-which capture information on dose, duration, and timing of exposure-are useful for gaining insight into clinically relevant groupings to evaluate the risk of prenatal opioid exposure.

Predictive value of indicators for identifying child maltreatment and intimate partner violence in coded electronic health records: a systematic review and meta-analysis

OBJECTIVE

Electronic health records (EHRs) are routinely used to identify family violence, yet reliable evidence of their validity remains limited. We conducted a systematic review and meta-analysis to evaluate the positive predictive values (PPVs) of coded indicators in EHRs for identifying intimate partner violence (IPV) and child maltreatment (CM), including prenatal neglect.

METHODS

We searched 18 electronic databases between January 1980 and May 2020 for studies comparing any coded indicator of IPV or CM including prenatal neglect defined as neonatal abstinence syndrome (NAS) or fetal alcohol syndrome (FAS), against an independent reference standard. We pooled PPVs for each indicator using random effects meta-analyses.

RESULTS

We included 88 studies (3 875 183 individuals) involving 15 indicators for identifying CM in the prenatal period and childhood (0-18 years) and five indicators for IPV among women of reproductive age (12-50 years). Based on the International Classification of Disease system, the pooled PPV was over 80% for NAS (16 studies) but lower for FAS (<40%; seven studies). For young children, primary diagnoses of CM, specific injury presentations (eg, rib fractures and retinal haemorrhages) and assaults showed a high PPV for CM (pooled PPVs: 55.9%-87.8%). Indicators of IPV in women had a high PPV, with primary diagnoses correctly identifying IPV in >85% of cases.

CONCLUSIONS

Coded indicators in EHRs have a high likelihood of correctly classifying types of CM and IPV across the life course, providing a useful tool for assessment, support and monitoring of high-risk groups in health services and research.