Literature DB >> 29668649

Examining Parental Medication Adherence as a Predictor of Child Medication Adherence in Pediatric Anxiety Disorders.

Greta A Bushnell1, M Alan Brookhart1, Bradley N Gaynes2, Scott N Compton3, Stacie B Dusetzina4, Til Stürmer1.   

Abstract

BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) are the recommended first-line pharmacotherapy for pediatric anxiety disorders but adherence remains difficult to predict.
OBJECTIVES: To estimate SSRI adherence in children with anxiety disorders and determine if prior parental medication adherence is predictive of child high SSRI adherence.
METHODS: We identified children (3-17 y) initiating SSRI treatment after an anxiety disorder diagnosis in a commercial claims database (2005-2014). We evaluated parent SSRI, statin, and antihypertensive adherence [6-mo proportion days covered (PDC), high adherence=PDC≥0.80] in the year before child SSRI initiation. We estimated risk differences (RD) of child high SSRI adherence (6-mo PDC) stratified by parent adherence and multivariable risk ratios using modified Poisson regression. We estimated change in c-statistic and risk reclassification when adding parent-level covariates with child-level covariates to predict child adherence.
RESULTS: In 70,979 children with an anxiety disorder (59%=female, 14=median age), the mean 6-month SSRI PDC was 0.72, with variation by anxiety disorder. Overall 64% of children had high adherence if their parent had high SSRI adherence versus 53% of children with parents with low SSRI adherence (RD, 12%; multivariable risk ratios, 1.17; 95% confidence interval, 1.14-1.20). Findings were similar for parent statin (RD=10%) and antihypertensive adherence (RD=8%) and when stratified by child age and parent sex. There was minor improvement in risk reclassification and the c-statistic after adding parent adherence and parent-level covariates.
CONCLUSIONS: Parental medication adherence could help providers identify children at risk of nonadherence to inform the treatment decision, reduce unnecessary medication switches, and lead to broader effective interventions.

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Year:  2018        PMID: 29668649      PMCID: PMC5945329          DOI: 10.1097/MLR.0000000000000911

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


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