Using time-to-event analysis to identify preconception and prenatal predictors of child protective services contact

Austin, Anna E.; Parrish, Jared W.; Shanahan, Meghan

doi:10.1016/j.chiabu.2018.05.025

Cited by 15 publications

(18 citation statements)

References 42 publications

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“…Delays of surgical cleft lip repair within this patient population may be attributed to prioritizing the establishment of overall patient safety prior to surgery. Given that low socioeconomic status and unstable social history are associated with child maltreatment and Child Protective Service involvement, surgical delay in this patient population may also reflect the substantial financial and social resources necessary for patients to comply with such intensive care regimens (Parrish et al, 2011; Putnam-Hornstein et al, 2013; Austin et al, 2018). Indeed, financial and social barriers have been shown to predict increased rates of missed appointments among patients with CL/P (Lynn et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Sociodemographic Predictors of Patient Age at Time of Cleft Lip and Palate Repair

Lynn

Ranganathan

Bageris

et al. 2020

The Cleft Palate Craniofacial Journal

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Objective: To identify the impact of sociodemographic and health variables on the age at which patients undergo cleft lip repair, cleft palate repair, and primary speech evaluation. Design: A retrospective, noninterventional quality assessment, and quality improvement study was designed. Setting: This institutional study was performed at Michigan Medicine in Ann Arbor, MI. Patients: All patients born between 2011 and 2014 who received surgical cleft repair, excluded those who were adopted (n = 165). Main Outcome Measure: The age at which patients undergo cleft lip repair, cleft palate repair, and primary speech evaluation. Results: Cleft lip repair was performed significantly later for patients identifying as Asian (18 weeks, P = .01), patients with Child Protective Services contact (19 weeks, P = .01), patients with a significant comorbidity (14 weeks, P = .02), and patients who underwent preliminary lip adhesion surgery (19 weeks, P < .01). Cleft palate repair was performed significantly later for patients identifying racially as Asian (19 weeks, P = .03) and other (22 weeks, P = .03). Preliminary speech and language evaluation were performed significantly later for patients identifying as black (55 weeks, P = .03) and patients diagnosed with an isolated cleft lip (71 weeks, P < .01). Conclusions: Timing of cleft lip, cleft palate repair, and primary speech and language evaluation are subject to variation which may be predicted by clinically accessible factors. By identifying race, Child Protective Services contact, and care variables as significant predictors of increased patient age at time of intervention, multidisciplinary cleft care teams can proactively allocate patient support resources.

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Section: Discussionmentioning

confidence: 99%

Sociodemographic Predictors of Patient Age at Time of Cleft Lip and Palate Repair

Lynn

Ranganathan

Bageris

et al. 2020

The Cleft Palate Craniofacial Journal

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“…Logistic regression methods were used for analysing risk factors and associated outcomes, attrition analysis and sensitivity analysis. Advanced analytical methods included generalised linear models (GLM) [108], multinomial logistic regression using Vermunt's three step Latent Class Analysis approach and Growth Mixture Modelling [92], and survival analysis using Kaplan-Meier, Cox (proportional hazards) regression and Nelson-Aalen Estimation methods [55,99]. A few studies used a combination of methods, where in most cases logistic regression was included as one of the main methods [45,47,55,82].…”

Section: Methodsmentioning

confidence: 99%

“…The simplest method reported was listwise deletion [4,21,59,97,98] and including missing data as a separate category for each covariate in regression analysis (Missing Indicator Method) [47,81,[93][94][95][96]. Sophisticated methods included multiple imputation using Markov chain iterative regression methods (MCMC) [94], multiple imputation using chained equations (MICE) [45], and multiple imputation using the fully conditional specification (FCS) method [99] (S3 Table ).…”

Section: Biases Reportedmentioning

confidence: 99%

“…Other authors also reported restricting the analysis to groups of people with certain characteristics [45] or adding [94] or removing [81] one or more covariates to the analysis in order to reduce bias. Addition of covariates at subsequent waves resulted in either strengthening, weakening or no change to the effect sizes in some studies [99]. The main sensitivity analysis methods presented in the eight studies were logistic regression [21,45,58,59,81,98,102] and multiple regression analysis [52] controlling for known confounders and effect modifiers (S3 Table ).…”

Section: Plos Onementioning

confidence: 99%

“…Overall, the quality of all studies was strong (Qualsyst median score = 93%), but most of the studies rated poorly on the reporting of data linkage methods (GUILD and RECORD median score = 23%). Only three of the 30 studies [55,92,99] described the data linkage procedures in sufficient detail. This is of concern, as a small amount of data linkage errors may lead to significant bias and inconsistencies in estimating parameters of a statistical model.…”

Section: Quality Of Reporting On Data Linkage Proceduresmentioning

confidence: 99%

See 2 more Smart Citations

Research using population-based administration data integrated with longitudinal data in child protection settings: A systematic review

et al. 2021

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Introduction Over the past decade there has been a marked growth in the use of linked population administrative data for child protection research. This is the first systematic review of studies to report on research design and statistical methods used where population-based administrative data is integrated with longitudinal data in child protection settings. Methods The systematic review was conducted according to Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. The electronic databases Medline (Ovid), PsycINFO, Embase, ERIC, and CINAHL were systematically searched in November 2019 to identify all the relevant studies. The protocol for this review was registered and published with Open Science Framework (Registration DOI: 10.17605/OSF.IO/96PX8) Results The review identified 30 studies reporting on child maltreatment, mental health, drug and alcohol abuse and education. The quality of almost all studies was strong, however the studies rated poorly on the reporting of data linkage methods. The statistical analysis methods described failed to take into account mediating factors which may have an indirect effect on the outcomes of interest and there was lack of utilisation of multi-level analysis. Conclusion We recommend reporting of data linkage processes through following recommended and standardised data linkage processes, which can be achieved through greater co-ordination among data providers and researchers.

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Breastfeeding Duration and Reported Child Maltreatment in a Population-based Alaskan Birth Cohort

et al. 2021

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Using time-to-event analysis to identify preconception and prenatal predictors of child protective services contact

Cited by 15 publications

References 42 publications

Sociodemographic Predictors of Patient Age at Time of Cleft Lip and Palate Repair

Sociodemographic Predictors of Patient Age at Time of Cleft Lip and Palate Repair

Research using population-based administration data integrated with longitudinal data in child protection settings: A systematic review

Breastfeeding Duration and Reported Child Maltreatment in a Population-based Alaskan Birth Cohort

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