Background
Although there has been some progress in Nigeria in reaching the maternal health Millennium Development Goals, there is still an urgent need to sustain and increase the quality, availability, and accessibility of maternal and child health commodities, given the failure to attain the standards set forth by the MDGs [
1]. A recent report by World Health Organization showed that there has been slow reduction of maternal mortality in Nigeria from 1350/100,000 in 1990 to 1170/100,000 in 2000 and 814/100,000 in 2015 [
1]. This is in contrast to United Nations Development fund for population report 0f 243/100,000 in 2014 [
2]. However, the Nigeria demographic and health survey estimated the maternal mortality to be 576/100,000 [
3]. These figures are mere estimates because of poor vital statistics and showed the burden of maternal mortality in Nigeria. This high rate of maternal mortality is closely associated with low utilization of reproductive health services and is highlighted in the Nigerian demographic and health survey (NDHS) 2013, where only 61% of pregnant women received antenatal care while only 38% of the deliveries are attended by skill birth attendants [
3]. The survey also showed that women in rural areas contributed 70% of the home deliveries without supervision when compared to women in urban areas which contributed 30% of the home deliveries. This may be related to low educational level and socioeconomic status of women in rural area compared to women in urban areas which were observed in the survey.
The importance of maternal mortality as a vital indicator in assessment of health and other aspects of growth and development informed its inclusion as one of the targets in the 5th millennium development goal. Reducing worldwide ratios will definitely go a long way in improving maternal health. Multiple interventions like skilled birth attendance, adequate emergency obstetrics care coverage, family planning and antenatal care have all been shown to be effective in reducing mortality rates, and their implementation has helped better the lives of women particularly in sub-Saharan Africa [
4]. However, absolute values for maternal mortality in hospitals are few which limit information surrounding the events. Mortality figures are by definition a negative endpoint irrespective of the interventions and this has led to the concept of maternal near miss.
The World Health Organization (WHO), define a maternal near miss as “a woman who nearly died but survived a complication that occurred during pregnancy, childbirth or within 42 days of termination of pregnancy” [
5]. The Near Miss tool is a useful tool in assessment of Obstetrics care and can provide a lead to the cascade of events that result to maternal deaths. Because more numbers are studied and surviving women can tell their story when compared to maternal mortality, it helps to identify remote and immediate factors that are associated with maternal morbidities and mortalities. “It also permits the development of preventive and educational programs with improved allocation of resources in order to achieve a reduction of both maternal morbidity and mortality” [
6]. Evaluations of maternal deaths and near miss cases provide opportunities to examine social, economic, and structural factors that increase the risk of maternal mortality and morbidities, and these findings can be used to plan interventions that are contextually appropriate. This will help in strengthening the health system for efficient management of cases.
The incidence ratio and other epidemiological parameters (which include mortality index, severe maternal outcome ratio and maternal near miss- mortality ratio) vary from region to region and country to country. Previously, different studies have used different criteria to determine the near miss rate. WHO has standardized the criteria to help in comparing, evaluation and implementations of programs targeted at reduction of maternal mortality and morbidities. David et al. noted a total near miss ratio of 20/ 1000 and maternal mortality ratio of 254/100, 000 and near miss fatality rate of 11.2/1000 in a study in Mozambique [
7]. This is comparable to findings by Nelissen et al. in Tanzania (near miss incidence ratio of 23.6/1000, maternal mortality ratio of 350/100, 000, and near miss fatality of 12.9%) [
8].
Oladapo et al. in a nationwide multicenter study in Nigeria recorded a total near miss ratio of 15.8/ 1000 and maternal mortality ratio of 1088/100, 000 [
9]. The classical triad of delays (Delay 1: Deciding to seek care; Delay 2: Identifying and reaching the medical facility; Delay 3: Receiving adequate and appropriate treatment) propounded by Thaddeus and Maine [
10] were noted and accompanied by several instances of inappropriate management consistent with findings by other studies [
11,
12]. These delays are compounded by socio-cultural and economic factors. This is perhaps the first nationwide attempt to capture the actual near miss and maternal mortality in Nigeria. Previous data has relied on estimates which may not be very accurate thus leading to faulty planning and implementation.
However, there were two important omissions in their study. The centres were all located in the urban areas. The socio-demographic and medical characteristics of women in urban and rural areas may vary. Studies in Nigeria have shown that the proportion of skilled birth attendants are heavily weighted in favor of urban area [
13]. Secondly, all the hospital were government institutions which account for only 23% of all deliveries in the country [
3].
These hospitals are funded by the state and do not depend entirely on incomes generated by the hospitals. The characteristics of health indices in private versus public hospitals; rural versus urban areas may vary. Our study was aimed at evaluating the near miss and maternal mortality in a non-government tertiary health institution in rural Niger-Delta region of Nigeria using the Nigeria Near Miss protocol adapted from WHO Near Miss protocol [
5,
14]. This will help to determine the pattern of severe maternal outcome, near miss indicators, patients and healthcare factors associated with these morbidities and mortalities in rural areas and private referral hospital in Nigeria.
Result
During the study period, there were 307 deliveries; 262 live births and 45 stillbirths. A total number of 57 severe maternal outcome was recorded; 52 women had a near miss event while 5 women died as a result of complications of pregnancy. This gives a severe maternal outcome ratio of 218/1000 live births and maternal near miss incident ratio of 198/1000. The maternal mortality rate was 1908/100,000 live births. The maternal near miss mortality ratio was 11.4: 1 while the mortality index was 8.8%.
Among the women with severe maternal outcome, 50/57 (91.2%) were currently married while 5/57(8.8%) were not married. Majority 55/57(96.5%) were Christians while 2/57(3.5%) were Muslims. Three out of the five (60%) of the maternal death was in the age category of 20–24 years. Table
2 and
3 shows the other socio-demographic characteristics of the patients and selected reproductive characteristics.
Table 2
Socio-demographic characteristics of the subjects
Age range |
< 20 | 2 | 3.5 | 2 | 0 |
20–24 | 11 | 19.3 | 8 | 3 |
25–29 | 19 | 33.3 | 18 | 1 |
30–34 | 18 | 31.6 | 17 | 1 |
35–39 | 7 | 12.3 | 7 | 0 |
≥ 40 | 0 | 0 | 0 | 0 |
Occupation |
Unemployed | 21 | 36.8 | 19 | 2 |
Unskilled | 17 | 29.8 | 16 | 1 |
Semi skilled | 14 | 24.6 | 12 | 2 |
Professional | 5 | 8.8 | 5 | 0 |
Educational level |
No formal education | 2 | 3.5 | 1 | 1 |
Primary | 16 | 28.1 | 16 | 0 |
Secondary | 30 | 52.6 | 27 | 3 |
Post secondary | 9 | 15.8 | 8 | 1 |
Marital status | | | | |
Married | 52 | 91.2 | 48 | 4 |
Not married | 5 | 8.8 | 4 | 1 |
Religion |
Christianity | 55 | 96.5 | 50 | 5 |
Islam | 2 | 3.5 | 2 | 0 |
Table 3
Selected reproductive characteristics of the subjects
Total number of pregnancies |
N = 57 | |
1 | 14 | 24.6 | 12 | 2 | 14.3 |
2–4 | 26 | 45.6 | 25 | 1 | 3.8 |
≥5 | 17 | 29.8 | 15 | 2 | 11.8 |
Booking status at our hospital |
Booked | 12 | 21.1 | 11 | 1 | 0.08 |
Unbooked | 45 | 78.9 | 41 | 4 | 8.9 |
Referral status |
Booked at the hospital | 12 | 21.1 | 11 | 1 | 0.08 |
Not referred | 27 | 47.3 | 25 | 2 | 7.4 |
Referred before labor | 5 | 8.8 | 5 | 0 | 0 |
Referred during labor | 10 | 17.5 | 8 | 2 | 20 |
Referred postpartum | 3 | 5.3 | 3 | 0 | 0 |
Trimmester at presentation |
1 | 9 | 15.8 | 8 | 1 | 12.5 |
2 | 11 | 19.3 | 10 | 1 | 9.1 |
3 | 34 | 59.6 | 31 | 3 | 8.8 |
Postpartum | 3 | 5.3 | 3 | 0 | 0 |
Hypertensive disorders of pregnancy contributed 16(28.1%) of the severe maternal outcome (SMO) while Obstetrics hemorrhage and abortive outcome each contributed 14(24.6%) of the SMO. Eclampsia and severe preeclampsia were the most frequent disease entity each contributing 8(14%) of severe SMO.
Abortive outcome (early pregnancy bleeding) was the leading cause of maternal mortality contributing 2(40%) of the maternal mortality from ectopic pregnancy and abortion related haemorrhage. It also has the highest mortality index of 14.3%. The distribution of the primary cause of the SMO is shown in Table
4. The 5(100%) of the maternal mortality were due to direct obstetric causes. Eclampsia, ruptured uterus and obstructed labour each contributed to one maternal death.
Table 4
The distribution of primary causes of severe maternal outcome
Obstetrics hemorrhage | 14 | 24.6 | 13 | 1 | 7.1 |
Placenta praevia | 1 | 1.8 | 1 | 0 | 0 |
Abruptio placentae | 3 | 5.3 | 3 | 0 | 0 |
Ruptured uterus | 7 | 12.3 | 6 | 1 | 14.3 |
Postpartum hemorrhage | 3 | 5.2 | 3 | 0 | 0 |
Infection | 1 | 1.8 | 1 | 0 | 0 |
Peuperal genital tract sepsis | 1 | 1.8 | 1 | 0 | 0 |
Hypertensive disorders | 16 | 28.0 | 15 | 1 | 6.3 |
Severe preeclampsia | 8 | 14.0 | 8 | 0 | 0 |
Eclampsia | 8 | 14.0 | 7 | 1 | 12.5 |
Prolonged obstructed labor | 10 | 17.5 | 9 | 1 | 10 |
Abortive outcome | 14 | 24.6 | 12 | 2 | 14.3 |
Abortion related haemrrhage | 5 | 8.8 | 4 | 1 | 20 |
Abortion related infection | 2 | 3.5 | 2 | 0 | 0 |
Ruptured ectopic pregnancy | 7 | 12.3 | 6 | 1 | 14.3 |
Severe malaria/anaemia | 2 | 3.5 | 2 | 0 | 0 |
There was variable lag between time of diagnosis and intervention in most of the cases. Only 6(10.5%) received treatment within 30 min after diagnosis while 19(33.3%) waited for greater than 240 min before they received intervention. 4(80%) of the mortality were noted in the greater than 240 min group. There is statistical significant association between time of intervention and final maternal outcome (
p-value = 0.003). This is shown in Table
5.
Table 5
Time interval between diagnosis and intervention in minutes
< 30 | 6 | 10.5 | 6 | 0 | 0.003 |
31–60 | 16 | 28.1 | 16 | 0 | |
61–120 | 7 | 12.3 | 6 | 1 | |
121–180 | 5 | 8.8 | 5 | 0 | |
181–240 | 4 | 7.0 | 4 | 0 | |
>240 | 19 | 33.3 | 15 | 4 | |
TOTAL | 57 | 100 | 52 | 5 | |
Delays in management were noted in 46(80.7%) of all the cases. Administrative delays were noted in 20 cases and non-availability of blood products 7(12.3) being the leading problems. Patients related delays were noted in 44 cases. Late presentation 22(38.6%), inability to pay 10(17.5%) and lack of transportation 9(15.8%) were the most frequent patient related problems. Different delays are shown in Table
6.
Table 6
Patient and health institution delays
No power supply | 3 | 5.3 |
No transpaort and or communication | 9 | 15.8 |
Non availability of blood/blood products | 7 | 12.3 |
Absence/lack of equipment | 1 | 1.7 |
No administrative problem | 37 | 64.9 |
Total | 57 | 100 |
Patient oriented problem | Frequency(n = 57) | Percentage |
Late presentation | 22 | 38.6 |
Refusal of treatment | 12 | 21.1 |
Inability to pay | 10 | 17.5 |
No patient related problem | 13 | 22.8 |
Total | 57 | 100 |
Medical personnel problem | Frequency(n = 57) | Percentage |
Delay in treatment | 20 | 35.1 |
No assessment by senior doctor | 6 | 10.5 |
Poor monitoring | 1 | 1.8 |
None | 30 | 52.6 |
Total | 57 | 100 |
Discussion
Our study is one of the few studies in Nigeria that evaluated Near miss morbidities. To the best of our knowledge, this is the first study on near miss in a private health institution and in a rural area in Nigeria. This has highlighted the burden of severe maternal outcome in the rural settings in Nigeria. It also showed the gaps and strength of a tertiary private hospital in rural Nigeria.
The near miss incident rate of 198/1000 and SMO 218/1000 recorded in this study is higher than the values 16/1000 and 27/1000 recorded in Nigeria near miss network [
9] and near miss ratio of 28.6/1000 recorded by Tuncalp et al. in Accra Ghana [
15]. It is also higher than 28.6/10000 reported by Neilsson et al. rural settings in Tanzania [
7]. Even far lower values have been recorded in developed countries [
16,
17]. The reason may be because only few hospitals in rural areas of Nigeria offer comprehensive obstetrics emergency care. Most secondary health institutions in rural Nigeria offer poor services to the populace because of the weak health sector and lack of political will. These health institutions are characterized by poorly motivated staff due to poor remuneration and delay in payment of salary. Other contributing factors to poor services include lack of equipment and infrastructure and high attrition of staff to health institutions in urban areas.
In addition, most deliveries in rural areas occur at home while some women are managed by traditional birth attendants who may have a high threshold for referral of high risk women only when there is severe complication and impeding maternal death as evidenced low number of uncomplicated pregnancies managed in the institution during the study period.
The maternal mortality rate of 1900/100,000 is far higher than the national estimates of 547/100,000
3. One of the reasons for this observation may be connected to the high percentage of severe cases. Lower rates of maternal mortality have been recorded in studies in other developing countries [
18,
19].
The mortality index of 8.8% recorded implies that for every 10 patients that have severe maternal outcome, one is likely going to die from the complications of pregnancy. It is lower than 41% observed by Nigeria near miss network study which was carried out in public hospitals [
10]. This may be related to more bureaucratic bottle necks in public hospitals in Nigeria and early involvement of consultants in the management of the cases in private hospitals. Similar values have been reported in studies in other developing countries [
20]. A study by Adisasmita et al. also noted less mortality index in private hospitals compared to public hospitals [
21].
The pattern of primary causes of near miss in this study mirrors observations of several studies with hypertensive disorders and hemorrhage being the leading causes [
7‐
9,
11,
12]. However with respect to mortality, we recorded highest mortality index in the abortive/early pregnancy bleeding. This is different from several other studies where Eclampsia had the highest case specific mortality index [
7‐
9]. This may be explained by the routine use of MgSO4 in our center which reduced the mortality associated with Eclampsia. The only patient that died from Eclampsia presented late with multiple organ dysfunction. A study in Sagamu, south west Nigeria where Eclampsia was the leading cause of mortality noted that most patients with Eclampsia did not receive MgSo4 which is consistent with observations from other studies outside Nigeria. [
12].
Contrary to other studies, there was no mortality as a result of primary postpartum hemorrhage in our study [
9,
11]. This may be explained by aggressive management and prevention of cases. Active management of third stage is offered routinely to all women that deliver in the Centre. In addition, we give prophylactic doses of misoprostol to high risk patients.
The case specific mortality index in our study was highest with early pregnancy bleeding (14.3%). It also contributed 24.7% of the severe maternal outcome. This is worrisome and will need further studies to determine the cause of high incidence and mortality. This may be connected with the characteristics of the patients which include young age, delayed recognition and awareness of complications, unmet need for contraception, high dependent level and lack of access to health facilities. The various levels of delays noted in our study may have contributed to the mortalities.
Significant delays were observed at various levels in this study. This is consistent with the Nigeria near miss network study observation and (WHO STUDY) [
9,
17]. This means there is need to shift from quantity to quality of care to reduce mortality. The findings of no maternal death among women who received treatment within 30 min of presentation and 80% of the mortality occurring among those with greater than 240 min of delay before treatment implies that reduction of the time interval from diagnosis to intervention may reduce the mortality. This means that type three delay is a very potential target for reduction of maternal mortality in rural areas of Nigeria.
We infer that for substantive reduction in maternal mortality, the hospitals must institute mechanisms to reduce the type 3 delay. This includes twenty four hour emergency services without emphasis on fee for service in the few hours after presentation, partnering with government and other stakeholders in developing community health insurance services, and 24 h blood bank services. It also includes periodic evaluation of staff attitude to work. There is a need for periodic reviews to identify the different challenges in the management of women with severe maternal outcome.
The low utilization of a tertiary institution for routine reproductive health services is also a source of worry. This may be related to high patronage of unskilled birth attendants and home deliveries as evidenced by the high percentage of unbooked patients and late referral of women with life threatening pregnancy complications. The issue of unemployment and low education should be addressed to empower these women to make informed choices. There is need for increased awareness, reorientation of populace in rural settings to increase the uptake of EMOC in rural areas.
Our study has some limitations. This a single hospital studies in a rural setting, so there should be some caution in interpretation of the study. We did not ascertain the reasons for late presentations which would have aided in understanding factors remote from our Centre that endangered the life of these women. There is also need to follow up on the study and carry necessary intervention to reduce the lapses in the management of these women.
Conclusion
This study clearly showed the high burden of near miss in rural areas of Nigeria and unmet need for reproductive health services. Any long and short term health planning should bear in mind the challenges and peculiarities of rural settings. There are few government hospitals in rural areas and most of them offer poor services as a result of poor motivation of staff and lack of equipment hence private hospitals has a huge potential in offering reproductive health services in the rural settings. The issues of delays must be addressed to reduce pregnancy related deaths in rural areas.
Private hospitals depend on fees for sustenance and collaboration with government and other stakeholders will help in reduction of the burden of severe maternal outcome. Health care financing is critical to any plan to increase uptake of EMOC and community insurance program will help to capture those women not included in the national health insurance scheme.
It also showed that pattern of mortalities and characteristics of these women differ from urban areas. Many women do not have access to reproductive health services including antenatal care. These should be made accessible and affordable.
Different levels of delays abound and contribute to the disease burden. The hospitals offering comprehensive EMOC should reduce the delays using different mechanisms to reduce mortality and complications in the management of these women.
There should be better communication between different levels of care and emphasis should be on early identification and referral of women for prompt management.
Critical infrastructure should be put in place and there should be incentives for healthcare personnel working in rural areas. Socio-cultural factors should be explored to increase utilization of health facilities in rural areas.
Acknowledgements
The authors appreciate the support of the staff of department of Obstetrics and Gynecology, Madonna University Teaching Hospital Elele.