Evidence map›Paper›PMID 36761333›Full record

ArticleFrontiers in public health2022

Ten-year hospitalization trends in Mexico: Examining the profile of national and transient and migrants.

René Leyva-Flores, Belkis Aracena-Genao, Nirma D Bustamante, Ietza Bojorquez, Ricardo Cortés-Alcalá, Diana Gómez-López, Miguel Adonai Pérez-Sastré

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
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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

7 authors at 5 institutions in 2 countries.

René Leyva-FloresCenter for Research in Health Systems (CISS), National Institute of Public Health (INSP), Cuernavaca, Morelos, Mexico.
Belkis Aracena-GenaoCenter for Research in Nutrition and Health (CINyS), National Institute of Public Health (INSP), Cuernavaca, Morelos, Mexico.
Nirma D BustamanteCenters for Disease Control and Prevention, Atlanta, GA, United States.
Ietza BojorquezMigration and Health, El Colegio de la Frontera Norte, Tijuana, Baja California, Mexico.
Ricardo Cortés-AlcaláMinistry of Health (Secretaría de Salud), Mexico City, Mexico.
Diana Gómez-LópezIndependent Public Health Researcher, Mexico City, Mexico.
Miguel Adonai Pérez-SastréFaculty of Medicine, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico.
Instituto Nacional de Salud Pública · MXCenters for Disease Control and Prevention · USEl Colegio de la Frontera Norte · MXSecretaria de Salud · MXUniversidad Nacional Autónoma de México · MX

Funding

NCEZID CDC HHS R43 CK000493
6 · The paper itself

Abstract

Aim: In Mexico, as in other societies, migrants are seen as over-users of health services. However, the extent, distribution, and trends of use over time are unknown. Evidence is needed to inform health policies and improve health services for foreign patients. The objective of this study was to examine factors associated with the distribution and trends of Mexican and foreign resident hospitalizations in Mexican public hospitals from 2010 to 2020. Methods: A graphical and statistical analysis (descriptive and correlational) of discharge trends in public hospitals was carried out. Hospitalization trends were analyzed by country of habitual residence (Mexico, US, Central and South America, and Other Continents), age, sex, primary discharge category, and region of service delivery. Adjusted Poisson modeling was used to examine the factors associated with annual hospitalizations of Mexican and foreign residents. Results: Between 2010 and 2020, there were 26,780,808 hospitalizations in Mexican public hospitals. Of these, 0.05% were of foreign residents. Hospitalizations for Mexican residents remained stable from 2010 to 2019, while those for foreign residents trended upward over the same period. In 2020, hospitalizations of Mexican residents fell by 36.6%, while foreign resident hospitalizations fell by 348.8%. The distribution of hospitalizations by sex was higher among females for all categories of habitual residence, except among US residents. Obstetric discharges were the most common reason for hospitalization among Mexican residents (42.45%), Central and South American residents (42.24%), and residents from Other Continents (13.73%). The average hospital stay was 2 days. Poisson regression confirmed these results, showing that hospitalizations was higher among women (except among foreign residents) and in the ≤ 17 age group. Poisson modeling also showed that trauma injury was the leading cause of discharge for foreign residents after obstetric causes. Discussion: It is unlikely the upward trend in hospitalizations among foreign residents in Mexico from 2010 to 2019 affected the Mexican public health system, given the small proportion (0.05%) of hospitalizations and the brief length of hospital stay. The increased number of hospitalizations during the study period may be explained by local and national measures to facilitate foreign residents' access to hospital services, while the decrease in hospital utilization in 2020 is likely associated with COVID-19. Geographic location and the most frequent primary discharge categories of hospitalizations within each population could provide evidence for modifications to public health policy in Mexico.

Indexed as

COVID-19Transients and MigrantsFemaleHospitalizationHumansLength of StayMexicoPregnancyCentral Americahealth services accessibilityhospitalizationsMexicoSouth Americatransients and migrantsUnited States

Identifiers

PMID36761333
PMCPMC9905618
OpenAlexW4317914849

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.