Parental Factors Affecting Pediatric Medication Management in Underserved Communities

Rungvivatjarus, Tiranun; Huang, Maria Z.; Winckler, Britanny; Chen, Scarlett; Fisher, Erin; Rhee, Kyung E.

doi:10.1016/j.acap.2022.09.001

Cited by 4 publications

(3 citation statements)

References 31 publications

(31 reference statements)

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“…These findings can be used to guide future interventions and may aid in the optimization of medication administration for pediatric patients. 24 Educational campaigns for responsible self-medication should be strengthened by encouraging community pharmacies to take the initiative to actively guide and educate patients about the proper use of over-the-counter medications. 25 Continuous efforts should be made to create age-appropriate formulations that offer both dosing flexibility and palatable taste.…”

Section: Discussionmentioning

confidence: 99%

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A cross-sectional survey among parents to report challenges and barriers in the administration of medicines to children in United Arab Emirates

et al. 2023

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Background: Lack of knowledge among parents can result in inappropriate administration practices. After analyzing different studies among children, there was no data on challenges and barriers in the administration of medicines among children in this region because of the diverse environmental issues and challenges in the UAE. The objective of this study was to determine the reported administration practices of parents and challenges and barriers in the administration of medicines among children in UAE. Methods: A questionnaire-based survey was conducted. A convenience sampling technique was used to collect the data. An online Raosoft® sample size calculator was applied (n = 248). The inclusion criteria were parents who had a child under 10 years of age and gave consent to participate in this study. Children with vision problems, cognitive/physical disabilities, and caregivers other than parents were excluded from this study. Results: The study reported response rate of 73.2%. The mean ± S.D age of the parents in years was 35.5 ± 7.8, and the mean ± S.D of children aged years was 2.60 ± 1.54. 26.2% of parents reported treatment failure due to oral medicine administration. A total of 22.2% of parents reported that they gave medicines in doses higher than prescribed by the doctor to treat their children more quickly. Similarly, a total of 64.5% of the parents reported self-medication without consultation from a healthcare provider. Conclusions: The study concluded that there were inappropriate medicine administration practices among parents. Parents reported administration of higher doses to treat their children quickly.

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Section: Discussionmentioning

confidence: 99%

“…These findings can be used to guide future interventions and may aid in the optimization of medication administration for pediatric patients. 24 …”

Section: Discussionmentioning

confidence: 99%

A cross-sectional survey among parents to report challenges and barriers in the administration of medicines to children in United Arab Emirates

et al. 2023

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“…Health literacy affects a person’s capability to interpret and execute health information [ 43 , 44 ]. Patients with poorer health literacy frequently misunderstood drug information, including over-the-counter drugs [ 45 , 46 ], which could lead to unintended yet preventable adverse drug events especially in underserved communities [ 47 , 48 ]. These support the need to examine sociodemographic factors for evaluation of ADE risk at the time of prescribing, as well as interventions to improve patient understanding of their medications.…”

Section: Discussionmentioning

confidence: 99%

Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study

Goyal

Zhang

et al. 2023

BMC Med Inform Decis Mak

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Introduction Adverse drug events (ADEs) are associated with poor outcomes and increased costs but may be prevented with prediction tools. With the National Institute of Health All of Us (AoU) database, we employed machine learning (ML) to predict selective serotonin reuptake inhibitor (SSRI)-associated bleeding. Methods The AoU program, beginning in 05/2018, continues to recruit ≥ 18 years old individuals across the United States. Participants completed surveys and consented to contribute electronic health record (EHR) for research. Using the EHR, we determined participants who were exposed to SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, vortioxetine). Features (n = 88) were selected with clinicians’ input and comprised sociodemographic, lifestyle, comorbidities, and medication use information. We identified bleeding events with validated EHR algorithms and applied logistic regression, decision tree, random forest, and extreme gradient boost to predict bleeding during SSRI exposure. We assessed model performance with area under the receiver operating characteristic curve statistic (AUC) and defined clinically significant features as resulting in > 0.01 decline in AUC after removal from the model, in three of four ML models. Results There were 10,362 participants exposed to SSRIs, with 9.6% experiencing a bleeding event during SSRI exposure. For each SSRI, performance across all four ML models was relatively consistent. AUCs from the best models ranged 0.632–0.698. Clinically significant features included health literacy for escitalopram, and bleeding history and socioeconomic status for all SSRIs. Conclusions We demonstrated feasibility of predicting ADEs using ML. Incorporating genomic features and drug interactions with deep learning models may improve ADE prediction.

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Changes in Provider Perceptions and Practices Regarding Dosing Units for Oral Liquid Medications

Lind,

Lovegrove,

Paul

et al. 2024

Academic Pediatrics

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Parental Factors Affecting Pediatric Medication Management in Underserved Communities

Cited by 4 publications

References 31 publications

A cross-sectional survey among parents to report challenges and barriers in the administration of medicines to children in United Arab Emirates

A cross-sectional survey among parents to report challenges and barriers in the administration of medicines to children in United Arab Emirates

Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study

Changes in Provider Perceptions and Practices Regarding Dosing Units for Oral Liquid Medications

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