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Record W2947447398 · doi:10.1093/pch/pxz066.109

110 Differences in Pediatric Visits to Emergency and Pediatric Emergency Departments are Linked to Socioeconomic Status

2019· article· en· W2947447398 on OpenAlexaboutno aff
Quang Van Ngo, Monica Toma

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTriageSocioeconomic statusEmergency departmentSpecialtyPopulationMedical emergencyEmergency medicineFamily medicinePediatricsEnvironmental healthNursing

Abstract

fetched live from OpenAlex

In large urban centers with tertiary level hospital systems, families have the choice to bring their children to pediatric emergency departments (PEDs) or general emergency departments (GEDs). Many factors influence this decision, including the availability of specialty care and geographic convenience. However, barriers to accessing care, such as cost of transportation, lack of primary care and lower education may disproportionately affect those of lower socioeconomic status (SES), which further disadvantages a population that experiences poorer health outcomes as a result. Planning and delivery of pediatric acute care should be informed by how low SES families use emergency care but this is still unknown. The primary objective of this study was to determine if there were differences between pediatrics patients that visited a pediatric emergency department (PED) versus a general emergency department (GED), when both were available in the same city. It was hypothesized that pediatric patients with lower socioeconomic status would be less likely to access pediatric emergency care, instead prioritizing geographic convenience. A retrospective chart review was conducted of all pediatric visits to general emergency departments (GEDs) in a large tertiary level hospital system which included a pediatric emergency department (PED). A period of 6 months from January to June, 2015 was chosen in order to capture the seasonal variation of pediatric visits. A randomly sampled population of comparable visits to the local PED was then used to compare key demographic and medical characteristics, including age and gender, postal code, acuity at presentation (as measured by the Canadian Triage and Acuity Scale), chief complaints and time of registration. Postal code data was gathered in order to determine socioeconomic status, which had been determined prior in a local study examining geographic distribution of poverty in the city. A total of 4053 pediatric visits were documented to the 3 urban GEDs over the 6 month study period. A random sample of the same number of patients that visited the PED over the same study period was used as a comparator. When compared to children going to GEDs, children at the PED were more likely to be younger in age. Infants under the age of 1 year made up 29% of PED visits, compared to 10.7%/8.9%/11.1% at the other 3 sites. This trend was similar in children aged 2–4. Children represented a smaller proportion of overnight visits in the PED when compared to children visiting the GED (9.4% vs. 15.5%/12.8%/14.5%). Acuity, as measured by the Canadian Triage and Acuity Scale (CTAS), differed only at the downtown GED when compared with the PED (CTAS 1 1.7% vs. 0.6%). Types of chief complaints appeared to be equally represented across all GEDs and the PED. When postal codes were mapped to locations of hospitals, it appeared that GEDs tended to draw from their immediate local vicinity, whereas the PED showed a much more distributed patient base. This data also suggests that higher SES families present to the PED whereas lower SES patients stay at their local hospitals. Children presenting to the PED tended to be younger, represent a potential perception that young children require specialty care. The trend of the most acutely ill patients being overly represented at the downtown GED may relate to this population being of low SES with poorer health outcomes. The PED catchment area appears to correlate with higher SES populations, which may be related to access to transportation or awareness of specialist availability. These findings have implications for planning and delivery of pediatric acute care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.295
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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