Background: Despite the increased policy attention on ethnic health inequities since the COVID-19 pandemic, research on ethnicity and healthcare utilisation in children has largely been overlooked.
Objectives: This scoping review aimed to describe and appraise the quantitative evidence on ethnic differences (unequal) and inequities (unequal, unfair and disproportionate to healthcare needs) in paediatric healthcare utilisation in the UK 2001-2021.
Methods: We searched Embase, Medline and grey literature sources and mapped the number of studies that found differences and inequities by ethnic group and healthcare utilisation outcome. We summarised the distribution of studies across various methodological parameters.
Results: The majority of the 61 included studies (n=54, 89%) identified ethnic differences or inequities in paediatric healthcare utilisation, though inequities were examined in fewer than half of studies (n=27, 44%). These studies mostly focused on primary and preventive care, and depending on whether ethnicity data were aggregated or disaggregated, findings were sometimes conflicting. Emergency and outpatient care were understudied, as were health conditions besides mental health and infectious disease. Studies used a range of ethnicity classification systems and lacked the use of theoretical frameworks. Children's ethnicity was often the explanatory factor of interest while parent/caregiver ethnicity was largely overlooked.
Discussion: While the current evidence base can assist policy makers to identify inequities in paediatric healthcare utilisation among certain ethnic groups, we outline recommendations to improve the validity, generalisability and comparability of research to better understand and thereby act on ethnic inequities in paediatric healthcare.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10313970 | PMC |
http://dx.doi.org/10.1136/archdischild-2022-324577 | DOI Listing |
BMC Health Serv Res
January 2025
Department of Pharmacy Practice, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur , Tamil Nadu, 603203, India.
Introduction: Several adverse drug reactions (ADRs) go unreported within a healthcare setting despite the risks they cause. We therefore decided to conduct this study in order to recognize the obstacles that hinder the healthcare professionals (HCPs) in a tertiary care hospital in Kattankulathur, Tamil Nadu from reporting ADRs and what strategies ought to be implemented.
Methods: We carried out a cross-sectional study among the HCPs such as doctors, pharmacists and nurses within our institution.
BMC Med Inform Decis Mak
January 2025
Great Ormond Street Institute of Child Health, University College London, London, UK.
Introduction: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).
Design: We applied document embedding algorithms to real-world paediatric intensive care (PICU) EHR data to extract patient-specific features from 1853 patients' PICU journeys using 647 unique lab tests and medication events. We evaluated the clinical utility of the patient features via a K-means clustering analysis.
BMC Public Health
January 2025
Advanced Wellbeing Research Centre, Sheffield Hallam University, Sheffield, UK.
Background: Workplace health screening rarely includes measures of cardiorespiratory fitness, despite it being a greater predictor of cardiovascular disease and all-cause mortality than other routinely measured risk factors. This study aimed to determine the comparative acceptability of using a novel seismocardiography device to measure cardiorespiratory fitness via VO max during a workplace health check.
Methods: Participants were invited to participate in workplace health screening sessions where VO max was assessed by both seismocardiography at rest and sub-maximal exercise testing, in order for acceptability of both to be compared across multiple domains.
BMC Public Health
January 2025
Center for Basic Medical Research, International University of Health and Welfare, 2600-1 Kitakanemaru, Ohtawara-City, Tochigi, 324-8501, Japan.
Background: Foreign workers are at risk for depression, and Vietnamese people tend to be reluctant to seek professional mental health care. Although Vietnamese people are the largest population among foreign workers in Japan, evidence concerning their help-seeking experiences and strategies to promote help-seeking in this population is lacking. This study aimed to identify the percentage of Vietnamese migrant workers in Japan who have sought help from healthcare professionals for depressive symptoms and to explore the factors related to their intentions to seek help from a psychiatrist.
View Article and Find Full Text PDFBackground: Drivers of COVID-19 severity are multifactorial and include multidimensional and potentially interacting factors encompassing viral determinants and host-related factors (i.e., demographics, pre-existing conditions and/or genetics), thus complicating the prediction of clinical outcomes for different severe acute respiratory syndrome coronavirus (SARS-CoV-2) variants.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!