Analysis of the Severe Maternal Outcomes between Resource-Poor and Resource-Rich Hospitals in China’s Hunan Province from 2012 to 2018

Joint Authors

Xiong, Lili
Zeng, Mengjun
Wang, Aihua
Xie, Donghua
Kong, Fanjuan
Liu, Zhiyu

Source

BioMed Research International

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-11-12

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Medicine

Abstract EN

Background.

This facility-based study analyzed the epidemiology and incidence of maternal near miss (MNM) and mortality by hospital level as part of Hunan Province’s efforts to raise the quality of hospital care for women.

Methods.

We used data for MNM and mortality cases for 2012–2018 from 17 hospitals (12 resource-poor facilities, five resource-rich facilities) that receive referrals for obstetric complications in Hunan Province.

Data were drawn from China’s National Maternal Near Miss Surveillance System and collected using the World Health Organization near miss tool.

We calculated the ratio of severe maternal outcomes (SMO) (i.e., MNM and maternal death (MD) cases), mortality index (MI), and MNM to mortality ratio (MNM : MD), and epidemiological factors, organ dysfunction, and maternal complications stratified by hospital level.

The chi-square tests to examine differences between groups and total ratios and 95% CI were calculated.

Results.

There were 518 SMO cases (489 MNM and 29 MD) among 279407 live births (LBs) and 1299 SMO cases (1262 MNM and 37 MD) among 232386 LBs in resource-poor and resource-rich facilities.

The total MNM ratio in resource-poor and resource-rich hospitals was 1.75 (95% CI: 1.60–1.91) and 5.43 (95% CI: 5.14–5.74) per 1000 LBs, respectively.

There were differences in SMO cases between resource-poor and resource-rich hospitals in maternal age, education, parity, antenatal visits, and history of cesarean sections.

In MNM cases, coagulation dysfunction was the main organ dysfunction (resource-poor hospitals: 59.10%; resource-rich hospitals: 79.32%), and the main maternal complications were obstetric hemorrhage (resource-poor hospitals: 71.98%) and hepatopathy (resource-rich hospitals: 69.49%).

For MD cases, the main maternal complications were neurologic dysfunction (resource-poor hospitals: 41.38%) and coagulation dysfunction (resource-rich hospitals: 42.55%).

Anemia was the main maternal complication for SMO cases in both resource-poor (69.69%) and resource-rich (68.59%) hospitals.

Conclusions.

MNM and MD are higher in resource-rich hospitals compared with resource-poor hospitals.

The obstetric emergency capacity of resource-rich hospitals is higher than that of resource-poor hospitals.

Future government policies should consider upgrading the obstetric emergency treatment capacity in resource-poor hospitals or to redistinguish the social functions of different medical institutions.

American Psychological Association (APA)

Xiong, Lili& Zeng, Mengjun& Wang, Aihua& Xie, Donghua& Kong, Fanjuan& Liu, Zhiyu. 2020. Analysis of the Severe Maternal Outcomes between Resource-Poor and Resource-Rich Hospitals in China’s Hunan Province from 2012 to 2018. BioMed Research International،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1135969

Modern Language Association (MLA)

Xiong, Lili…[et al.]. Analysis of the Severe Maternal Outcomes between Resource-Poor and Resource-Rich Hospitals in China’s Hunan Province from 2012 to 2018. BioMed Research International No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1135969

American Medical Association (AMA)

Xiong, Lili& Zeng, Mengjun& Wang, Aihua& Xie, Donghua& Kong, Fanjuan& Liu, Zhiyu. Analysis of the Severe Maternal Outcomes between Resource-Poor and Resource-Rich Hospitals in China’s Hunan Province from 2012 to 2018. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1135969

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1135969