#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

The impact of socioeconomic status on emergency department outcome in a low-income country setting: A registry-based analysis


Autoři: Vijay C. Kannan aff001;  Giannie N. Rasamimanana aff002;  Victor Novack aff003;  Lior Hassan aff003;  Teri A. Reynolds aff004
Působiště autorů: Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States of America aff001;  Emergency and Intensive Care Unit, Centre Hopitalier de Professeur Zagaga, Mahajanga, Madagascar aff002;  Clinical Research Center, Soroka University Hospital and Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheba, Israel aff003;  Department of Emergency Medicine, University of California, San Francisco, CA, United States of America aff004
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0223045

Souhrn

Background

The impact of socioeconomic status on health has been established via a broad body of literature, largely from high-income countries. Investigative efforts in low- and middle-income countries have suffered from a lack of reporting standardization required to draw comparisons across countries of varying economic strata. In this study we aimed to evaluate the impact of socioeconomic status on emergency department outcomes in a low-income African country using international data classification systems.

Methods

This was a retrospective cohort study was conducted at a tertiary care center in northern Madagascar. Data were abstracted from paper charts into an electronic registry using Integrated Public Use Microdata Series codes for occupation, Nam-Powers-Boyd (NPB) scores for socioeconomic status, and Clinical Classifications Software ICD-9 equivalents for diagnosis. Outcome was dichotomized to the combined disposition of death or transfer directly to operating theater (OT) versus discharge. We used t-tests to compare baseline characteristics between these groups. We used chi-square analysis to test the association between occupational class and diagnosis. Finally, multivariate logistic regression analysis was performed examining the impact of NPB score on death/OT outcome, adjusting for age, gender, diagnosis and occupation.

Results

5271 patients were seen during the 21-month study period with a death/OT rate of 9.7%. Older age and male gender were more common in death/OT patients (both p<0.001), and were shown to have positive odds ratios for this outcome in multivariate modeling (p<0.006 and <0.001). Occupational class was found to influence diagnosis for all classes (p<0.001) except Sales and Office. Adjusting for these 3 factors, we found a strong independent association between NPB quartile and death/OT outcome. Relative to the 1st quartile, the odds ratio in the 4th quartile was 2.9 (p = 0.004), the 3rd quartile 1.8 (p = 0.094), and the 2nd quartile 3.1 (p<0.001).

Conclusion

To our knowledge, this is the first Malagasy study describing the relationship between socioeconomic status on emergency care outcomes. We found a stronger effect on health in this setting than in high-income countries, highlighting an important healthcare disparity. By using standardized classification systems we hope this study will serve as a model to facilitate future comparative efforts.

Klíčová slova:

Professions – Death rates – Critical care and emergency medicine – Patients – Infectious diseases – Socioeconomic aspects of health – Madagascar – Global health


Zdroje

1. Signorello LB, Cohen SS, Williams DR, Munro HM, Hargreaves MK, Blot WJ. Socioeconomic Status, Race, and Mortality: A Prospective Cohort Study. Am J Public Health. 2014;104: e98–e107. doi: 10.2105/AJPH.2014.302156 25322291

2. Epstein AM, Stern RS, Weissman JS. Do the Poor Cost More? A Multihospital Study of Patients’ Socioeconomic Status and Use of Hospital Resources. In: http://dx.doi.org/10.1056/NEJM199004193221606 [Internet]. 14 Jan 2010 [cited 4 Oct 2017]. Available: http://www.nejm.org/doi/full/10.1056/NEJM199004193221606

3. Stringhini S, Rousson V, Viswanathan B, Gedeon J, Paccaud F, Bovet P. Association of Socioeconomic Status with Overall and Cause Specific Mortality in the Republic of Seychelles: Results from a Cohort Study in the African Region. PLOS ONE. 2014;9: e102858. doi: 10.1371/journal.pone.0102858 25057938

4. Kleindorfer Dawn O., Lindsell Christopher J., Broderick Joseph P., Flaherty Matthew L., Daniel Woo, Irene Ewing, et al. Community Socioeconomic Status and Prehospital Times in Acute Stroke and Transient Ischemic Attack. Stroke. 2006;37: 1508–1513. doi: 10.1161/01.STR.0000222933.94460.dd 16690898

5. Khan Y, Glazier RH, Moineddin R, Schull MJ. A Population-based Study of the Association Between Socioeconomic Status and Emergency Department Utilization in Ontario, Canada. Acad Emerg Med. 2011;18: 836–843. doi: 10.1111/j.1553-2712.2011.01127.x 21843219

6. Boyd M, Nam C. The Newest Nam-Powers-Boyd Occupational Scale: Development and Insights. [Internet]. Paper presented at at the Southern Demographic Association annual meeting, San Antonio Texas; 2015. Available: www.npb-ses.info

7. GDP per capita (current US$) | Data [Internet]. [cited 4 Oct 2017]. Available: https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?order=wbapi_data_value_2013+wbapi_data_value&sort=asc&year_high_desc=false

8. The World Factbook—Central Intelligence Agency [Internet]. [cited 9 Dec 2017]. Available: https://www.cia.gov/library/publications/the-world-factbook/rankorder/2172rank.html

9. High-quality health systems in the Sustainable Development Goals era: time for a revolution—The Lancet Global Health [Internet]. [cited 5 Sep 2019]. Available: https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(18)30386-3/fulltext

10. Hsia RY, Ozgediz D, Mutto M, Jayaraman S, Kyamanywa P, Kobusingye OC. Epidemiology of injuries presenting to the national hospital in Kampala, Uganda: implications for research and policy. Int J Emerg Med. 2010;3: 165–172. doi: 10.1007/s12245-010-0200-1 21031040

11. Sawe HR, Haeffele C, Mfinanga JA, Mwafongo VG, Reynolds TA. Predicting Fluid Responsiveness Using Bedside Ultrasound Measurements of the Inferior Vena Cava and Physician Gestalt in the Emergency Department of an Urban Public Hospital in Sub-Saharan Africa. PLOS ONE. 2016;11: e0162772. doi: 10.1371/journal.pone.0162772 27677085

12. WHO | Global Burden of Disease (GBD). In: WHO [Internet]. [cited 2 May 2013]. Available: http://www.who.int/healthinfo/global_burden_disease/en/index.html

13. Boudreaux ED, Emond SD, Clark S, Camargo CA. Acute Asthma Among Adults Presenting to the Emergency Department: The Role of Race/Ethnicity and Socioeconomic Status. Chest. 2003;124: 803–812. doi: 10.1378/chest.124.3.803 12970001

14. Westjem. Association of Insurance Status with Severity and Management in ED Patients with Asthma Exacerbation. In: The Western Journal of Emergency Medicine [Internet]. 3 Feb 2016 [cited 29 Dec 2017]. Available: http://westjem.com/brief-research-report/association-of-insurance-status-with-severity-and-management-in-ed-patients-with-asthma-exacerbation.html

15. Hendriks ME, Wit FWNM, Roos MTL, Brewster LM, Akande TM, Beer IH de, et al. Hypertension in Sub-Saharan Africa: Cross-Sectional Surveys in Four Rural and Urban Communities. PLOS ONE. 2012;7: e32638. doi: 10.1371/journal.pone.0032638 22427857

16. Westjem. Association of Insurance Status with Health Outcomes Following Traumatic Injury: Statewide Multicenter Analysis. In: The Western Journal of Emergency Medicine [Internet]. 27 May 2015 [cited 29 Dec 2017]. Available: http://westjem.com/original-research/association-of-insurance-status-with-health-outcomes-following-traumatic-injury-statewide-multicenter-analysis.html

17. Sayegh AJ, Swor R, Chu KH, Jackson R, Gitlin J, Domeier RM, et al. Does race or socioeconomic status predict adverse outcome after out of hospital cardiac arrest: a multi-center study. Resuscitation. 1999;40: 141–146. doi: 10.1016/s0300-9572(99)00026-x 10395396

18. Poverty Analysis—Measuring Inequality [Internet]. [cited 9 Dec 2017]. Available: https://www.worldbank.org/en/webarchives/archive?url=httpzzxxweb.worldbank.org/archive/website01294/WEB/0__MENUP.HTM&mdk=23218759

19. WHO | Thirteenth General Programme of Work. In: WHO [Internet]. [cited 5 May 2018]. Available: http://apps.who.int/gb/ebwha/pdf_files/WHA71/A71_4-en.pdf?ua=1


Článok vyšiel v časopise

PLOS One


2019 Číslo 10
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Aktuální možnosti diagnostiky a léčby litiáz
nový kurz
Autori: MUDr. Tomáš Ürge, PhD.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#