"The Problem's Bigger than We Are": Understanding How Local Factors Influence Child Welfare Responses to Substance Use in Pregnancy, A Qualitative Study.

State eligibility for certain federal child welfare funding requires a gubernatorial assurance that infants affected by substances receive plans of safe care (POSC). We conducted 18 interviews with state and county child welfare staff to understand how POSC has been implemented and found variability in practice driven by vague policy, challenges of cross-system collaboration, and a lack of knowledge about substance use disorder. Policy improvements should align requirements with POSC practice and create shared accountability with key partners.

Hospital Quality Indicators for Opioid-Exposed Infants: Results From an Expert Consensus Panel.

OBJECTIVE: To elicit expert consensus on quality indicators for the hospital-based care of opioid-exposed infants. METHODS: We used the ExpertLens online platform to conduct a 3-round modified Delphi panel. Expert panelists included health care providers, parents in recovery, quality experts, and public health experts. We identified 49 candidate quality indicators from a literature review and environmental scan. A total of 32 experts rated the importance and feasibility of the indicators using a 9-point Likert scale (Round 1), reviewed and discussed the initial ratings (round 2), and revised their original ratings (Round 3). Numeric scores corresponded with descriptive ratings of "low" (1-3), "uncertain" (4-6), or "high" (7-9). We measured consensus using the RAND/UCLA Appropriateness Method. RESULTS: Candidate quality indicators assessed structures, processes, and outcomes in multiple domains of clinical care. After the final round, 36 indicators were rated "high" on importance and feasibility. Experts had strong consensus on the importance of quality indicators to assess universal screening of pregnant people for substance use disorder, hospital staff training, standardized assessment for neonatal opioid withdrawal syndrome, nonpharmacologic interventions, and transitions of care. For indicators focused on processes and outcomes, experts saw feasibility as dependent on the information routinely documented in electronic medical records or billing records. To present a more complete picture of hospital quality, experts suggested development of composite measures that summarize quality across multiple indicators. CONCLUSIONS: A panel of experts reached consensus on a range of quality indicators for hospital-based care of opioid-exposed infants, with potential for use in national benchmarking, intervention studies, or hospital performance measurement.

Performance of Phenotype Algorithms for the Identification of Opioid-Exposed Infants.

OBJECTIVE: Observational studies examining outcomes among opioid-exposed infants are limited by phenotype algorithms that may under identify opioid-exposed infants without neonatal opioid withdrawal syndrome (NOWS). We developed and validated the performance of different phenotype algorithms to identify opioid-exposed infants using electronic health record data. METHODS: We developed phenotype algorithms for the identification of opioid-exposed infants among a population of birthing person-infant dyads from an academic health care system (2010-2022). We derived phenotype algorithms from combinations of 6 unique indicators of in utero opioid exposure, including those from the infant record (NOWS or opioid-exposure diagnosis, positive toxicology) and birthing person record (opioid use disorder diagnosis, opioid drug exposure record, opioid listed on medication reconciliation, positive toxicology). We determined the positive predictive value (PPV) and 95% confidence interval for each phenotype algorithm using medical record review as the gold standard. RESULTS: Among 41 047 dyads meeting exclusion criteria, we identified 1558 infants (3.80%) with evidence of at least 1 indicator for opioid exposure and 32 (0.08%) meeting all 6 indicators of the phenotype algorithm. Among the sample of dyads randomly selected for review (n = 600), the PPV for the phenotype requiring only a single indicator was 95.4% (confidence interval: 93.3-96.8) with varying PPVs for the other phenotype algorithms derived from a combination of infant and birthing person indicators (PPV range: 95.4-100.0). CONCLUSIONS: Opioid-exposed infants can be accurately identified using electronic health record data. Our publicly available phenotype algorithms can be used to conduct research examining outcomes among opioid-exposed infants with and without NOWS.

Neonatal Opioid Withdrawal Syndrome Is Associated With Infant Foster Care Entry At The County Level.

Although the number of infants diagnosed with neonatal opioid withdrawal syndrome (NOWS) and the number of infants entering foster care have increased substantially in the US since 2009, analyses exploring their relationship are lacking. Using data from 580 US counties in eight US states from the period 2009-17, we examined the association of county rates of NOWS and county-level characteristics with infant foster care entries. In adjusted analyses, every one diagnosis of NOWS per ten births was associated with a 41 percent higher rate of infant foster care entry, and rural county residence was associated with a 19 percent higher rate of infant foster entry. A higher employment rate was associated with lower rates of infant foster care entry both overall and in urban counties when we stratified by rurality. These findings suggest that policy makers could use information about county characteristics to better target funding to support opioid-affected families at risk for foster care involvement.