Has the income of the residential area impact on the use of intensive care?

Linking Sepsis with chronic arterial hypertension, diabetes mellitus, and socioeconomic factors in the United States: A scoping review

RATIONALE

Sepsis is a syndrome of life-threatening organ dysfunction caused by a dysregulated host immune response to infection. Social risk factors including location and poverty are associated with sepsis-related disparities. Understanding the social and biological phenotypes linked with the incidence of sepsis is warranted to identify the most at-risk populations. We aim to examine how factors in disadvantage influence health disparities related to sepsis.

METHODS

A scoping review was performed for English-language articles published in the United States from 1990 to 2022 on PubMed, Web of Science, and Scopus. Of the 2064 articles found, 139 met eligibility criteria and were included for review.

RESULTS

There is consistency across the literature of disproportionately higher rates of sepsis incidence, mortality, readmissions, and associated complications, in neighborhoods with socioeconomic disadvantage and significant poverty. Chronic arterial hypertension and diabetes mellitus also occur more frequently in the same geographic distribution as sepsis, suggesting a potential shared pathophysiology.

CONCLUSIONS

The distribution of chronic arterial hypertension, diabetes mellitus, social risk factors associated with socioeconomic disadvantage, and sepsis incidence, are clustered in specific geographical areas and linked by endothelial dysfunction. Such population factors can be utilized to create equitable interventions aimed at mitigating sepsis incidence and sepsis-related disparities.

Association Between Socioeconomic Status and Outcomes in Critical Care: A Systematic Review and Meta-Analysis

OBJECTIVES

Socioeconomic status is well established as a key determinant of inequalities in health outcomes. Existing literature examining the impact of socioeconomic status on outcomes in critical care has produced inconsistent findings. Our objective was to synthesize the available evidence on the association between socioeconomic status and outcomes in critical care.

DATA SOURCES

A systematic search of CINAHL, Ovid MEDLINE, and EMBASE was undertaken on September 13, 2022.

STUDY SELECTION

Observational cohort studies of adults assessing the association between socioeconomic status and critical care outcomes including mortality, length of stay, and functional outcomes were included. Two independent reviewers assessed titles, abstracts, and full texts against eligibility and quality criteria.

DATA EXTRACTION

Details of study methodology, population, exposure measures, and outcomes were extracted.

DATA SYNTHESIS

Thirty-eight studies met eligibility criteria for systematic review. Twenty-three studies reporting mortality to less than or equal to 30 days following critical care admission, and eight reporting length of stay, were included in meta-analysis. Random-effects pooled analysis showed that lower socioeconomic status was associated with higher mortality at less than or equal to 30 days following critical care admission, with pooled odds ratio of 1.13 (95% CIs, 1.05-1.22). Meta-analysis of ICU length of stay demonstrated no significant difference between socioeconomic groups. Socioeconomic status may also be associated with functional status and discharge destination following ICU admission.

CONCLUSIONS

Lower socioeconomic status was associated with higher mortality following admission to critical care.

Limiting ICU admission from emergency services and wards

INTRODUCTION

Decisions not to admit a patient to intensive care units (ICU) as a way of limiting life support treatment (LLST) is a practice that can affect the operation of the emergency services and the way in which patients die.

METHODS

Post hoc analysis of the ADENI-UCI study. The main variable analysed was the reason for refusal of admission to the ICU as a measure of LLST. For the present post hoc analysis, the registered patients were divided into 2 groups: the patients assessed in the intensive medicine services from the emergency department and the patients assessed from the conventional hospitalization areas. Student t was used in the comparative statistics when the mean values of the patient sub-cohorts were compared. Categorical variables were compared with the χ² tests.

RESULTS

The ADENI-ICU study included 2,284 decisions not to admit to the ICU as a measure of LLST. Estimated poor quality of life (p=.0158), the presence of severe chronic disease (P=.0169) and futility of treatment (P=.0006) were percentage decisions with greater weight within the population of hospitalized patients. The percentage of disagreement between the consulting physician and the intensivist was significantly lower in patients assessed from the emergency services (P=.0021).

CONCLUSIONS

There are appreciable differences in the reasons for consultation, as well as in those for refusal of admission to an ICU between the consultations made from an emergency department and a conventional hospitalization facility.

How does socioeconomic status affect the incidence of hospital-treated poisonings? A retrospective study

BACKGROUND

Hospital-treated poisonings have a good outcome in general. The role of regional differences and socioeconomic status has been established in intensive care admissions and various causes of death, but not yet in hospital-treated poisonings. We set out to determine whether the incidence of hospital-treated poisonings is affected by the annual income of the residential area.

METHODS

All poisonings in Northern Ostrobothnia region of Finland treated in Oulu University Hospital during 2013-2016 were studied. Oulu University Hospital is the primary hospital in the area. Postal code areas of the county were categorized on the basis of their median annual net income as low-, middle- and high-income areas.

RESULTS

A total of 2142 poisoning cases were studied. The number of individual patients was 1525. In the low-income areas, the crude incidence of poisonings was more than 2-fold when compared with the middle- and high-income areas. In adolescents aged 13 to 17 years, the incidence in the low-income areas was almost 3-fold compared with the other two categories at 335/100 000/year (95% CI, 236-463). Four patients (0.2%) died during the hospital stay and 50 patients (2.3%) died within 6 months from the last admission.

CONCLUSIONS

The incidence of hospital-treated poisoning was at least 2-fold in low-income areas when compared with middle- or high-income areas. For adolescent population from 13 to 17 years, the incidence in low-income areas was almost 3-fold when compared with other areas.

Use of prehospital emergency medical services according to income of residential area

Background

The increasing usage of emergency medical services (EMS) missions is a challenge in modern practice. This study was designed to examine the association of the income level of residential areas on the rate of EMS missions and the frequency of EMS use in these areas.

Methods

All EMS missions for adult patients (>18 years) encountered by one rescue department in Northern Finland between June 2015 and May 2017 were analysed. The area served was categorised into four categories, according to the median annual income of the postal code areas. EMS missions per 1000 person-years, rate of non-transport missions and the number of dispatches to frequent (>4 EMS calls/year and highly frequent (>10 calls/year)EMS users per area were investigated.

Results

There were 62 759 EMS missions, 34.8% of which resulted in non-transport. The crude rate of EMS dispatches was higher in the low-income area compared with other income areas (133.3 vs 108.9 vs 111.3 vs 73.6/1000 person-years) as well as the rate of high-frequency user dispatches (21.5 vs 11.5 vs 7.2 vs 4.3/1000-person years). The rate of non-transports missions was higher also (69.4 vs 43.4 vs 42.5. vs 30.6/1000 person-years). The highest crude rate of EMS use was found in people older than 65 years living in the lowest income areas (294.8/1000 person-years). After age adjustment, the highest rate of EMS use was found in rural areas with the lowest income (146.3/1000 person-years).

Conclusions

The rate of the EMS missions and non-transport missions differs significantly among different income areas. Resource usage was significantly higher in the low income areas. This information can be used in planning allocation of EMS and preventive healthcare resources.