Year : 2022 | Volume
: 12 | Issue : 6 | Page : 289--290
Three delays for maternal near miss in India
Payel Roy, Dinesh Prasad Sahu, Binod Kumar Behera
Department of Community Medicine and Family Medicine, All India Institute of Medical Sciences, Bhubaneswar, Odisha, India
Dr. Dinesh Prasad Sahu
Third Floor Academic Block, All India Institute of Medical Sciences, Bhubaneswar - 751 019, Odisha
|How to cite this article:|
Roy P, Sahu DP, Behera BK. Three delays for maternal near miss in India.Curr Med Res Pract 2022;12:289-290
|How to cite this URL:|
Roy P, Sahu DP, Behera BK. Three delays for maternal near miss in India. Curr Med Res Pract [serial online] 2022 [cited 2023 Apr 2 ];12:289-290
Available from: http://www.cmrpjournal.org/text.asp?2022/12/6/289/366175
Agarwal N, Jain V, Bagga R, Sikka P, Chopra S, Jain K, et al. Socio-behavioural determinants of maternal near miss: A prospective case control study from a tertiary care centre of India. J Obstet Gynaecol 2022;42:1043-7.
The article is a case–control study to find out the socio-behavioural determinants of a rare event, maternal near miss (MNM). The study focusses on the impact of the three delays on the severe maternal outcomes (SMO = MNM + maternal death [MD]) which includes both MNM and MDs. It was done in a tertiary care centre with a sample size of 300, case: control = 1: 2 (100 cases, 200 controls). The World Health Organization (WHO) near-miss criteria were applied to select the cases of MNM. The women who had the same obstetrical complications but could not reach the near-miss state within 1 week of enrolment were taken as control. A primary objective was to identify the delays in the level of care for the MNM cases in PGIMER, Chandigarh. The secondary objective was to compare the delays in the level of care between MD group and MNM. Those who were delayed in the first level of care, 59% of them were from MNM group and 41% were from the control group whereas 65% were in the death group (P < 0.003). The delay in second level of care (>1 h) amongst the MNM group was 26% higher (36%) compared to the control group (10%), but in the death group, it was 60% (P < 0.001). The difference between the delay in first phase of the third level of care amongst MNM and the control group was 17.5% (P < 0.001). Amongst the other variables, lack of knowledge (P = 0.001) and not knowing where to seek care (P = 0.021) came out to be statistically significant. There was no statistically significant difference between near-miss cases and control group for the non-availability of decision maker and the cost of transport.
Low and lower-middle-income countries contribute 94% of all MDs. India alone accounts for over 20% of the global MDs even though it has only 16% of world population. The prevalence of maternal near-miss cases varied from 4.2 to 120 per 1000 LB.
The study clearly addressed a focussed topic i.e., socio-behavioural determinants of MNM but the objective of the study was not in synchrony with the study title. Only the three-delay factor in MNM was assessed as per the objective. Although the study design was a prospective case–control study, the study duration was lacking in the article. The case and control selection procedures were not mentioned clearly, though mentioned WHO near-miss criteria were used. Duration or time frame of case and control selection, age group and parity were missing. Hence, misclassification bias could have happened. Even proper inclusion and exclusion criteria for selection of the participants were also explicitly not mentioned in the article. Cases and controls were not matched in the study even for the universal confounders also. Matching could have been done for the age to adjust for the confounder. There is also a chance that some patients died on the way to the hospital; they are not included in the study. There was no mention regarding the measurement of the exposure status i.e., how delay was assessed amongst the cases and controls. The time of assessment of exposure was also not mentioned. There was high chance of recall bias if the assessment was delayed. Sample size calculation was not mentioned i.e., how they had come to the conclusion of 300 as sample size (100 cases and 200 control) was not clearly mentioned. The sampling procedure was also not defined which could be a source of selection bias and also made the external validity of the study questionable. The operational definitions for the delays and its justifications were not mentioned. The results of the study cannot be relied on for many reasons. First, the odds ratio is not mentioned in the article. Second, confounders were not adjusted at either at the level of methodology or the level of analysis. Although it was a case–control study but results were represented like analytical cross-sectional one showing delays in different health-care levels amongst the near miss, control, and death group expressed in percentages with their P values. The representation of data in the table was not done in an ideal manner, the comparison between the maternal near-miss group and control or death group should have been done in two separate tables. In the statistical analysis part, the author mentioned Student's t-test and Mann-Whitney U-test, but were not reflected anywhere in the result section. The study with the same data was published in another journal (The Journal of Maternal-Foetal And Neonatal Medicine) on 9th March 2021. Limitations of the study should have been mentioned. Finally, sample taken in the study may not be representative of the study population, so the generalisability of the study is doubtful.
In the present study, the first level delay was maximum i.e., 59%, whereas 2nd and 3rd level delay was 36% and 49%, respectively, amongst the near-miss cases. In a prospective cross-sectional study in Pakistan by Yunus et al., the delay in deciding to seek care – was the major delay. Another study in Brazil has shown that 26.4% of patients in the death group had delay in seeking care compared to 11.4% in the near-miss group. The maternal near-miss cases were only 5.5%. A study by Shah et al. in Pakistan showed that 94% of the women had more than one delay, 71% were at first level and 73% at second level. A study on the three delay model of maternal morbidity and mortality in two tertiary care hospitals of Belagavi, Karnataka, by Singh and Metgud has found out that phase 3 delay was in all the patients (100%), phase 1 delay was 67% and phase 2 delay was 65%. Another similar study by Mohammed et al. after 10 years of analysis of MDs using three-delay model has shown that the maximum delay was in the 3rd phase (34.8%).
Per thousand deliveries near miss is seen amongst 7 pregnant women. Near-miss cases are more common than MDs. Hence, a review of MNM cases is likely to yield valuable information regarding severe morbidity, which could lead to death of the mother, if not intervened properly and in time. Investigating the cases of severe morbidity may be less threatening to service providers as the woman survived. The women are available for interview as they finally survived about the care they received and problem they faced. All near misses should be an example of free lessons and opportunities to improve the quality of service provision.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
|1||Maternal Mortality. Available from: https://www.who.int/news-room/fact-sheets/detail/maternal-mortality. [Last accessed on 2022 May 23].|
|2||AbouZahr C, Wardlaw T. Maternal mortality at the end of a decade: Signs of progress? Bull World Health Organ 2001;79:561-8.|
|3||Kulkarni R, Kshirsagar H, Begum S, Patil A, Chauhan S. Maternal near miss events in India. Indian J Med Res 2021;154:573-82.|
|4||Agarwal N, Jain V, Bagga R, Sikka P, Chopra S, Jain K. Near miss: Determinants of maternal near miss and perinatal outcomes: A prospective case control study from a tertiary care Center of India. J Matern Fetal Neonatal Med 2022;35:5909-16.|
|5||Yunus S, Kauser S, Ali S. Three 'Delays' as a framework for critical analysis of maternal near miss and maternal mortality. J South Asian Fed Obstet Gynaecol 2013;5:57-9.|
|6||Pacagnella RC, Cecatti JG, Parpinelli MA, Sousa MH, Haddad SM, Costa ML, et al. Delays in receiving obstetric care and poor maternal outcomes: Results from a national multicentre cross-sectional study. BMC Pregnancy Childbirth 2014;14:159.|
|7||Shah N, Hossain N, Shoaib R, Hussain A, Gillani R, Khan NH. Socio-demographic characteristics and the three delays of maternal mortality. J Coll Physicians Surg Pak 2009;19:95-8.|
|8||Singh J, Metgud CS. Study of “three delay model” of maternal morbidity and mortality in two tertiary care hospitals of Belagavi. Indian Journal of Health Sciences and Biomedical Research (KLEU). 2021;14:234.|
|9||Mohammed MM, El Gelany S, Eladwy AR, Ali EI, Gadelrab MT, Ibrahim EM, et al. A ten year analysis of maternal deaths in a tertiary hospital using the three delays model. BMC Pregnancy Childbirth 2020;20:585.|