Evidence map›Paper›PMID 38355411›Full record

ArticleBMC emergency medicine2024

Healthcare risk stratification model for emergency departments based on drugs, income and comorbidities: the DICER-score.

Jesús Ruiz-Ramos, Emili Vela, David Monterde, Marta Blazquez-Andion, Mireia Puig-Campmany, Jordi Piera-Jiménez, Gerard Carot, Ana María Juanes-Borrego

Abstract read
In one paragraph

Article in BMC emergency medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jesús Ruiz-RamosPharmacy Department, Hospital Santa Creu i Sant Pau. Institut de Recerca Sant Pau (IR SANT PAU), Barcelona, Spain. jrzrms@gmail.com.
Emili VelaCatalan Health Service. Digitalization for the Sustainability of the Healthcare System (DS3). Institut d'Investigacions Biomèdiques de Bellvitge (IDIBELL), Barcelona, Spain.
David MonterdeCatalan Institute of Health, Digitalization for the Sustainability of the Healthcare System (DS3), Institut d'Investigacions Biomèdiques de Bellvitge (IDIBELL), Barcelona, Spain.
Marta Blazquez-AndionEmergency Department, Hospital Santa Creu i Sant Pau, Institut de Recerca Sant Pau (IR SANT PAU), Barcelona, Spain.
Mireia Puig-CampmanyEmergency Department, Hospital Santa Creu i Sant Pau, Institut de Recerca Sant Pau (IR SANT PAU), Barcelona, Spain.
Jordi Piera-JiménezCatalan Health Service. Digitalization for the Sustainability of the Healthcare System (DS3). Institut d'Investigacions Biomèdiques de Bellvitge (IDIBELL), Barcelona, Spain.
Gerard CarotCatalan Health Service. Digitalization for the Sustainability of the Healthcare System (DS3). Institut d'Investigacions Biomèdiques de Bellvitge (IDIBELL), Barcelona, Spain.
Ana María Juanes-BorregoPharmacy Department, Hospital Santa Creu i Sant Pau. Institut de Recerca Sant Pau (IR SANT PAU), Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring the last decade, the progressive increase in age and associated chronic comorbidities and polypharmacy. However, assessments of the risk of emergency department (ED) revisiting published to date often neglect patients' pharmacotherapy plans, thus overseeing the Drug-related problems (DRP) risks associated with the therapy burden. The aim of this study is to develop a predictive model for ED revisit, hospital admission, and mortality based on patient's characteristics and pharmacotherapy.

methodsRetrospective cohort study including adult patients visited in the ED (triage 1, 2, or 3) of multiple hospitals in Catalonia (Spain) during 2019. The primary endpoint was a composite of ED visits, hospital admission, or mortality 30 days after ED discharge. The study population was randomly split into a model development (60%) and validation (40%) datasets. The model included age, sex, income level, comorbidity burden, measured with the Adjusted Morbidity Groups (GMA), and number of medications. Forty-four medication groups, associated with medication-related health problems, were assessed using ATC codes. To assess the performance of the different variables, logistic regression was used to build multivariate models for ED revisits. The models were created using a "stepwise-forward" approach based on the Bayesian Information Criterion (BIC). Area under the curve of the receiving operating characteristics (AUCROC) curve for the primary endpoint was calculated.

results851.649 patients were included; 134.560 (15.8%) revisited the ED within 30 days from discharge, 15.2% were hospitalized and 9.1% died within 30 days from discharge. Four factors (sex, age, GMA, and income level) and 30 ATC groups were identified as risk factors and combined into a final score. The model showed an AUCROC values of 0.720 (95%CI:0.718-0.721) in the development cohort and 0.719 (95%CI.0.717-0.721) in the validation cohort. Three risk categories were generated, with the following scores and estimated risks: low risk: 18.3%; intermediate risk: 40.0%; and high risk: 62.6%.

conclusionThe DICER score allows identifying patients at high risk for ED revisit within 30 days based on sociodemographic, clinical, and pharmacotherapeutic characteristics, being a valuable tool to prioritize interventions on discharge.

Indexed as

Delivery of Health CareEmergency Service, HospitalAdultBayes TheoremComorbidityHumansRetrospective StudiesRisk AssessmentElderlyEmergency carePolypharmacy

Identifiers

PMID38355411
PMCPMC10865623

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.