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 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 14  |  Issue : 2  |  Page : 234-238

Study of “three delay model” of maternal morbidity and mortality in two tertiary care hospitals of Belagavi


Department of Community Medicine, Jawaharlal Nehru Medical College, KAHER, Belgaum, Karnataka, India

Date of Submission07-Sep-2020
Date of Acceptance03-May-2021
Date of Web Publication31-May-2021

Correspondence Address:
Dr. Jyoti Singh
Department of Community Medicine, Jawaharlal Nehru Medical College, KAHER, Belgaum, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/kleuhsj.kleuhsj_280_20

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  Abstract 


INTRODUCTION: Every year millions of women around the world suffer from pregnancy, childbirth, and postpartum complication. Approximately 810 women die every day worldwide from preventable causes related to pregnancy and delivery. The concept of severe acute maternal morbidity or near miss was aptly developed for the present health-care system. The World Health Organization (WHO) has defined “near-miss” as a woman, who is close to death, survives a complication that occurred during pregnancy, delivery, or up to 42 days after the termination of her pregnancy. The important causes of maternal mortality and morbidity have been summarized as the three delays. These delays have been identified to understand the gap in access to adequate obstetric management. Delays in access to quality care have been identified as one of the important determinants of preventable maternal death. The present study was planned to assess the “three delay model” leading to the occurrence of severe maternal outcome (SMO) in two tertiary care hospitals of Belagavi, Karnataka, as proposed by the WHO near-miss approach.
OBJECTIVE: This study aimed to study the “three delay model” leading to maternal morbidity and mortality in two tertiary care hospitals of Belagavi.
MATERIALS AND METHODS: A cross-sectional study was conducted in two major tertiary care hospitals of Belagavi, namely KLE Dr Prabhakar Kore Charitable Hospital and Belagavi Institute of Medical Sciences Hospital for a duration of 1 year among antepartum, intrapartum, and postpartum mothers experiencing SMO. A sample of 200 was calculated based on the prevalence of previous maternal near-miss (MNM) incidence ratio. To assess the MNM cases, “Modified Facility Based MNM Review Form” was used.
RESULTS: Out of 200 MNM cases, 145 (72.5%) subjects belonged to the age group of 21–30 years and 17 (8.5%) of the women were aged ≥31 years. The mean ± standard deviation age of the study participant was 25.0 ± 4.45 years. Based on the obstetric profile of the study subject, it was noted that 139 (69.5%) participants had presented to the study hospitals as unbooked cases and 93 (46.5%) were primigravida. Majority (160, 80.0%) of the MNM women had presented as referred cases. The MNM incidence ratio in the present study was recorded as 12.05/1000 live births with a MNM: maternal death ratio of 3.3:1. All types of delays were noted among the study participant in our study. Type I delay that consisted of lack of awareness and resources was seen in 134 (67.0%) MNM cases, followed by 130 (65.0%) experiencing Type II delay comprising logistics delay between home and health-care facility and in between the health facilities along with lack of communication network and the third type of delay being observed at the referring health facility in all the referred study participant. Assessment of association between maternal outcome and the “3 delay model” by use of logistic regression analysis suggested that women who faced any kind of delay (I, II, and III) during their pregnancy were more likely to end up with poor maternal outcomes.
CONCLUSION AND RECOMMENDATION: The present study aimed to assess the delays that lead to poor maternal outcomes. The current study revealed the deficiencies that need to be tackled and taken care of on an urgent basis. Hence, there must be a multidisciplinary approach to manage the high-risk maternal cases for timely intervention and management and reduce the burden of maternal morbidity and mortality on a global scale.

Keywords: Maternal near miss, severe maternal outcome, three delay model, World Health Organization


How to cite this article:
Singh J, Metgud CS. Study of “three delay model” of maternal morbidity and mortality in two tertiary care hospitals of Belagavi. Indian J Health Sci Biomed Res 2021;14:234-8

How to cite this URL:
Singh J, Metgud CS. Study of “three delay model” of maternal morbidity and mortality in two tertiary care hospitals of Belagavi. Indian J Health Sci Biomed Res [serial online] 2021 [cited 2021 Jun 17];14:234-8. Available from: https://www.ijournalhs.org/text.asp?2021/14/2/234/317403




  Introduction Top


Worldwide, approximately 810 women die every day from preventable causes related to pregnancy and delivery.[1] Sustainable Development Goal-3 has a target to reduce the global maternal mortality rate to <70/1,00,000 births by 2030. The maternal health inequalities are not only between countries but also within countries and between rich and poor women residing in villages, cities, and slums. Layers of maternal health inequalities can be traced in the provision of maternal care services as well as across socioeconomic gradient in India.[2] Since 1990, though maternal deaths worldwide have dropped by 47%, the number of maternal deaths in developing countries like India remains high.[3] Conventionally, the evaluation of woman's health and determination of the quality of obstetric care has always been analyzed by estimating the maternal deaths. While some of these women die, a proportion of luckier ones narrowly escape death and are termed as “Near Miss Cases.” By evaluating these cases with severe maternal morbidities and mortalities (both “near-miss” cases and maternal deaths), much can be learned about the processes in place to deal with maternal morbidities. Maternal near-miss (MNM) cases are defined as “a woman who nearly died but survived a complication that occurred during pregnancy, childbirth or within 42 days of termination of pregnancy.”[4] The important causes of maternal mortality and morbidity have been summarized as the three delays. These delays have been identified to understand the gap in access to adequate obstetric management. Delays in access to quality care have been identified as one of the important determinants of preventable maternal death. Thaddeus and Maine's three delays' model that describes the multiple factors that drive maternal mortality has proven to be an effective tool to evaluate the circumstances surrounding access to and appropriateness of emergency obstetric and newborn care.[5] First delay is being undecided to seek care by woman or her family as danger signs are usually not identified early and they are unaware of the need of care. Second delay comprises logistics causing a delay in reaching the health-care facilities. Third delay is the 'delay in receiving adequate facility at the center resulting from errors in diagnosis, clinical decision making, lack of medical supplies, and of staff proficiency in the management of obstetric emergencies. In developing countries, about 75% of the women with severe obstetric morbidity are usually in a critical condition upon arrival, underscoring the significance of the first two delays.[3] The present study was planned with an idea to assess the “three delay model” leading to the occurrence of severe maternal outcome (SMO) in two tertiary care hospitals of Belagavi, Karnataka, as proposed by the World Health Organization (WHO) near-miss approach.

Objective

This study aimed to study the “three delay model” leading to maternal morbidity and mortality in two tertiary care hospitals of Belagavi.


  Materials and Methods Top


This cross-sectional study was conducted in two major tertiary care facilities of Belagavi city: “KLE Dr. Prabhakar Kore Charitable Hospital” and “Belagavi Institute of Medical Sciences Hospital.” The study population consisted of antepartum, intrapartum, and postpartum mothers experiencing SMO in both the tertiary care hospitals. The sample size was calculated on the basis of incidence ratio of MNM in India and was found to be 200 using the formula 4pq/d2, taking prevalence of 20% from previous study.[6] Institutional Ethical Committees of Jawaharlal Nehru Medical College (MDC/DOME/23, dated 24.11.2018) and Belagavi Institute of Medical Sciences (BIMS-IEC/47/2018-19, dated 14.11.2018). Data collection was done by means of personal interviews by the researcher in the hospital setting. Written informed consent was obtained from all the study participants before the onset of data collection and data confidentiality was maintained. Sociodemographic profile and obstetric details of the study participants were collected using a predesigned pretested pro forma. To assess the delay faced by the MNM cases, “Modified Facility Based MNM Review Form” was adopted. The form is based on the WHO MNM Criteria 2009. All the women who suffered severe life-threatening conditions and fulfilled WHO's MNM criteria were identified and the three types of delays were assessed in detail.

Statistical analysis

Data were coded and entered in an Excel sheet. Data were analyzed using IBM SPSS software Windows Trial version 25 (Chicago, IL, USA). Descriptive statistics were expressed as percentage. Chi-square test was used to find the association between variables. P ≤ 0.05 was considered to be statistically significant. Univariate and mulitivariate logistic regression models were applied to find the association between maternal outcome and the three delays.


  Results Top


The present study was conducted on 200 women who met with WHO's MNM criteria 2009. It was noted that 38 (19.0%) women belonged to the age group of 18–20 years, 83 (41.5%) belonged to 21–25 years, 62 (31.0%) were aged between 26 and 30 years, and 17 (8.5%) participant were above the age of 30 years. The mean ± standard deviation (SD) age of the study subject was 25.0 ± 4.45 years with a range of 18–40 years and the median age was 24.0 years. Majority (139, 69.5%) of the study subjects followed Hinduism and 40 (20%) were Muslims, with 10.5% following Christianity and Jainism. Literacy status of the study participant revealed that 181 (90.5%) were literates, out of which 81 (40.5%) had received primary level of education and 100 (50.0%) had received high school education and above. It was observed that 185 (92.5%) were homemakers and 15 (7.5%) women were employed. Among the subjects who were employed, majority were agricultural laborers or self-employed. Based on the socioeconomic status, it was found that 12 (6.0%) belonged to Class I, 29 (14.5%) to Class II, 54 (27.0%) to Class III, 68 (34.0%) to Class IV, and 37 (18.5%) belonged to Class V socioeconomic status according to Modified B. G. Prasad's Classification.

Out of the total MNM cases studied, majority (160, 80.0%) were referred to the study hospital and 40 (20.0%) had presented directly to the hospital as self-referral case. Among them, 61 (30.5%) were booked cases of the study hospitals and the remaining 139 (69.5%) were unbooked cases. Nearly 70% of the MNM cases were booked cases of primary health centers, taluka hospitals, and private nursing homes. According to the time taken by the study subject to reach the health facility, the mean ± SD duration taken by MNM case to reach the fifirst health facility was 12.1 ± 10.24 hrs and from fifirst to the current health facility was 12.01 ± 12.5 hrs. Majority (167, 83.5%) of the women were admitted to the study hospitals as MNM cases and the remaining 33 (16.5%) women who were admitted with underlying disorders related to gestation became later MNM cases during the course of their hospital stay.

Among the study participants, 93 (46.5%) were primigravida and 107 (53.5%) were multigravida. About 144 (72.0%) MNM cases were in their antenatal period of gestation at the time of admission. Out of these, 26 (13.0%) were ≤22 weeks of gestation, 42 (21.0%) were between >22 weeks and ≤34 weeks, 41 (20.5%) were between >34 weeks and ≤37 weeks, 34 (17.0%) were between >37 weeks and ≤42 weeks, and only 1 (0.5%) woman was >42 weeks of gestation. Only 4 (2.0%) women were referred during intranatal period, followed by 47 (23.5%) in postnatal and 5 (2.5%) women in postabortal period. It was noticed that more than two-third (76.5%) of the MNM cases had obstetric cause as the primary event. These obstetric primary events eventually led to other secondary obstetric or nonobstetric MNM events.

The present study recorded that women with life-threatening condition were 200 consisting of 153 MNM cases and 47 maternal deaths. The prevalence rate of MNM cases/1000 deliveries on arrival and during hospitalization was 11.21 and 2.21, respectively. MNM incidence ratio was 12.05 per 1000 live births. The MNM: maternal death ratio in our study was 3.3:1, which means for every maternal death, we have three women experiencing severe maternal morbidity. Our study highlighted that nearly 2/3rd of the MNM cases had complete recovery at the time of discharge. We noted death among 47 (28.1%) women during the course of management. The remaining 29 women went home against medical advice and 4 were discharged on request. However, out of 146 women who delivered during the study period, nearly half 78 (53.4%) had good fetal outcomes, whereas 68 (46.6%) had bad fetal outcomes.

On assessing the “Three delay model,” it was reflected that 134 (67.0%) MNM cases were having Type I delay which comprises personal/family issues like deciding to seek appropriate medical help for an obstetric emergency. Type I delay can be due to lack of resources (13, 9.7%), lack of awareness (11, 8.2%), or both (110, 88.1%). None of the MNM cases gave a history of previous poor experience of health care neither refusal of admission or treatment in the health facility. Type II delay which means reaching an appropriate obstetric facility was observed in 130 (65.0%) women. Out of 200 MNM cases, 151 (75.5%) of women were not from Belagavi Taluka . Delay between home to first health care facility was observed in 116 (36.5%) and between the health care facilities was seen among 113 (35.5%) women. Nearly 89 (28.0%) women had a lack of communication network due to poor roads and infrastructure and out of 160 MNM cases who were referred, Type III delay which means receiving adequate care when a facility is reached was observed in all of them. Nearly 108 (35.2%) MNM cases were referred due to lack of blood product, followed by 101 (32.9%) women due to lack of instrument and medicine at the previous health facility and 98 (31.9%) participants were referred due to infrastructure issue.

Association between the type of delays and poor maternal outcome revealed that Type I delay comprising lack of awareness and resources showed a significant association with poor maternal prognosis (χ2 = 8.538, P = 0.003 and χ2 = 7.694, P = 0.006, respectively) and this difference was found to be statistically significant (P < 0.05) [Graph 1]. Delay with health-care facilities was observed statistically significant association (χ2 = 14.823, P < 0.001) [Graph 2]. Type III delay due to lack of instrument/medicine, infrastructure issue, and lack of blood product also highlighted significant association with poor maternal outcomes (χ2 = 7.60, P = 0.006; χ2 = 7.07, P = 0.008 and χ2 = 3.241, P = 0.0072, respectively) [Graph 2] and [Graph 3].



On further univariate logistic regression analysis, the important delays leading to bad maternal outcomes were suggestive of the fact that women with Type I delay were approximately three times more likely to face poor maternal consequences. The delay between health-care facilities reflected that women with this delay in reaching from one health facility to another faced four times more chance of attaining mortality. Lack of instrument/medicine and infrastructure issue had 2.5 times of being at higher risk of bad maternal consequences [Table 1].
Table 1: Univariate logistic regression analysis

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On application of multivariate logistic regression analysis, the present study highlighted that women experiencing a delay between health-care facilities were seven times more likely to have poor maternal outcomes compared to the women who did not face the delay [P < 0.001] [Table 2].
Table 2: Multivariate logistic regression analysis

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  Discussion Top


The present study was a cross-sectional study conducted in two tertiary care hospitals of Belagavi to assess the delays faced by women that led to potentially life-threatening conditions. Type I delay was identified in almost two-third (67.0%) of the MNM cases, Type II delay was noted in 65.0% of cases, and Type III delay in all the participants. Our findings were dissimilar to the study conducted in Raipur that observed Type I, Type II, and Type III delays in 44.0%, 36.0%, and 19.9% study participants, respectively.[7] The delays influencing the maternal outcome were lack of awareness, lack of resources, delay between health-care facilities, lack of instrument/medicine, lack of blood product, and infrastructure issue (P < 0.05 in each type of delay). According to univariate logistic regression analysis, the MNM cases experiencing Type I, II, and III delays were three times, four times, and two times more likely to face poor maternal outcomes compared to the ones who did not. On multivariate logistic regression analysis, Type II delay in our study highlighted that women experiencing a delay between health-care facilities were seven times more likely to have poor maternal outcomes compared to the women who did not face the delay. This was similar to a study conducted in West Bengal that showed a statistically significant association between Type I and Type II delays and the obstetric near-miss event with P < 0.001 in each type of delay.[8] Another study conducted in West Bengal also noted higher Type II delay (adjusted odds ratio [AOR] with 95% confidence interval [CI]; 1.7 [1.11–1.96]) as compared to its counterparts.[9] This is similar to the present study that observed Type II delay components such as the delay between health facilities as directly associated with the poor maternal outcome with a statistically significant P value (AOR with 95% CI; 7.648 [2.581–22.666]). Another study done in Egypt reflected women who experience delay between health facilities were six times more likely to have MNM condition compared with women who did not (OR = 6.19, 95% CI = 2.88–10.35), followed by those with first delay (OR = 3.43, 95% CI = 1.54–7.52) and those with second delay (OR = 2.51, 95% CI = 1.11–5.68).[10] However, our study did not reflect any significant association between the third type of delay and bad maternal outcomes on multivariate analysis. This was found similar to the West Bengal study that also reported no significant association (P = 0.312) between the third type of delay with near-miss event.[8]

Strength and limitation

Both the major tertiary care facilities catering to Belagavi district were included in the study. Hence, the sample formed an important representation of the entire district. The limitation of the study was that this was a hospital-based study and some detail could not be obtained completely from the study participant owing to their declining health condition.


  Conclusion Top


The present study highlighted the gaps in the current health scenario. It revealed that the delays in seeking health care due to lack of awareness/resources and nonavailability of transport facilities between health-care facilities with interruption in communication linkage proved to be the major contributors of poor prognosis in the study region. They play a crucial role in increasing the disease burden. Hence, the overall assessment of association between poor maternal outcomes and the “3 delay model” by use of logistic regression analysis models suggested that women who faced any kind of delay during their pregnancy were 2.5–7 times more likely to end up with poor maternal consequences.

Recommendation

There is a need of proper training of health-care workers at the grass-root level for early and prompt identification of potentially life-threatening conditions and strengthening of referring health facilities, mainly focusing on the peripheral levels with better communication network link between the facilities, especially in rural settings. Creation of awareness among the general population regarding the importance of routine antenatal checkups and educating and sensitizing the young mothers and their health-seeking behavior must be quintessential.

Acknowledgment

The authors would like to thank the staff of KLE Charitable Hospital and Belagavi Institute of Medical Sciences Hospital and the study participants for their kind cooperation and support.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
World Health Organization. Maternal Mortality. 2019. Available from: https://www.who.int/news-room/fact-sheets/detail/ maternal-mortality [Last accessed on 2018 Aug 25].  Back to cited text no. 1
    
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Kaur M, Gupta M, Pandara Purayil V, Rana M, Chakrapani V. Contribution of social factors to maternal deaths in urban India: Use of care pathway and delay models. PLoS One 2018;13:e0203209.  Back to cited text no. 2
    
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Chhabra P. Maternal near miss: An indicator for maternal health and maternal care. Indian J Community Med 2014;39:132-7.  Back to cited text no. 3
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Ojha V, Chaurasia A, Singh S, Sachan N, Siddiqui S. Evaluation of maternal near miss cases in tertiary care centre. N Indian J OBGYN 2019;6:45-8.  Back to cited text no. 4
    
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Chavane LA, Bailey P, Loquiha O, Dgedge M, Aerts M, Temmerman M. Maternal death and delays in accessing emergency obstetric care in Mozambique. BMC Pregnancy Childbirth 2018;18:71.  Back to cited text no. 5
    
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Abha S, Chandrashekhar S, Sonal D. Maternal near miss: A valuable contribution in maternal care. J Obstet Gynaecol India 2016;66:217-22.  Back to cited text no. 7
    
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Kumar R, Tewari A. “Near-Miss obstetric events” and its clinico-social correlates in a secondary referral unit of Burdwan District in West Bengal. Indian J Public Health 2018;62:235-8.  Back to cited text no. 8
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Kanchan SK, Paswan B, Anand A, Mondal NA. Praying until death: Revisiting three delays model to contextualize the socio-cultural factors associated with maternal deaths in a region with high prevalence of eclampsia in India. BioMed Cent Pregnancy Childbirth 2019;19:1-11.  Back to cited text no. 9
    
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Abdel-Raheema SS, Al-Attara GS, Mahrana DG, Qayeda MH, Alib ZH, Othman RA. Delays associated with maternal near-miss cases admitted in Women's Health Hospital, Assiut University. J Curr Med Res Pract 2017;2:1-9.  Back to cited text no. 10
    



 
 
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