Causes of maternal deaths and delays in care: Comparison between routine maternal death surveillance and response system and an obstetrician expert panel in Tanzania

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Study Justification:
– The study aimed to assess the adequacy of the Maternal Death Surveillance and Response (MDSR) system in Tanzania, which was introduced to reduce maternal mortality.
– By comparing the routine MDSR categorization of causes of death and delays to those assigned by an independent expert panel, the study aimed to identify any discrepancies or difficulties within the MDSR system.
Study Highlights:
– The study included 109 reviewed maternal deaths from two regions in Tanzania in 2018.
– The underlying causes of death and the three phases of delays were compared between the MDSR system and the expert panel.
– The study found that the MDSR committees performed reasonably well in assigning underlying causes of death, with agreement in 64.6% of cases.
– The expert panel identified more delays than reported in the MDSR system, indicating difficulties within MDSR teams to critically review deaths.
– The expert panel found human errors in management in 93.1% of deaths, while the MDSR system reported in 67.9% of deaths.
Recommendations for Lay Reader and Policy Maker:
– Strengthen the training and guidelines for MDSR committees to improve the consistency and accuracy of categorizing causes of maternal deaths.
– Provide additional support and resources to MDSR teams to enhance their ability to identify and address delays in care.
– Improve data collection and reporting processes within the MDSR system to ensure comprehensive and reliable information on maternal deaths.
Key Role Players Needed to Address Recommendations:
– Ministry of Health: Responsible for providing guidance, resources, and oversight to the MDSR system.
– MDSR Committees: Composed of a multidisciplinary team of clinical and non-clinical staff from health facilities, responsible for reviewing maternal deaths and recommending quality improvement actions.
– Obstetricians and Medical Experts: Provide expertise and guidance in categorizing causes of maternal deaths and identifying delays in care.
– Health Facility Staff: Responsible for accurate and timely reporting of maternal deaths to the MDSR system.
Cost Items to Include in Planning Recommendations:
– Training and Capacity Building: Budget for training programs to enhance the skills and knowledge of MDSR committee members in categorizing causes of death and identifying delays.
– Data Collection and Reporting Systems: Allocate resources for improving data collection tools, systems, and processes to ensure comprehensive and reliable reporting of maternal deaths.
– Support and Resources for MDSR Teams: Provide funding for additional staff, equipment, and supplies to support MDSR teams in their review and analysis of maternal deaths.
– Monitoring and Evaluation: Allocate resources for monitoring and evaluating the effectiveness of the MDSR system and the implementation of recommended improvements.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong, but there are some areas for improvement. The study design is cross-sectional, which limits the ability to establish causality. Additionally, the sample size is relatively small, with only 109 reviewed maternal deaths. To improve the strength of the evidence, future studies could consider using a larger sample size and a longitudinal design to better assess causality and trends over time. Furthermore, the abstract does not provide information on the representativeness of the sample, which could affect the generalizability of the findings. Including information on the demographic characteristics of the study population would help to address this limitation. Overall, the study provides valuable insights into the performance of the MDSR system in Tanzania, but further research is needed to strengthen the evidence base.

Background: To reduce maternal mortality Tanzania introduced Maternal Death Surveillance and Response (MDSR) system in 2015 as recommended by World Health Organization (WHO). All health facilities are to notify and review all maternal deaths inorder to recommend quality improvement actions to reduce deaths in future. The system relies on consistent and correct categorization of causes of maternal deaths and three phases of delays. To assess its adequacy we compared the routine MDSR categorization of causes of death and three phases of delays to those assigned by an independent expert panel with additional information from Verbal Autopsy (VA). Methods: Our cross-sectional study included 109 reviewed maternal deaths from two regions in Tanzania for the year 2018. We abstracted the underlying medical causes of death and the three phases of delays from MDSR system records. We interviewed bereaved families using the standard WHO VA questionnaire. The obstetrician expert panel assigned underlying causes of death based on information from medical files and VA according to International Classification of Disease to Death in Pregnancy Childbirth and Puerperium (ICD-MM). They assigned causes to nine ICD-MM groups and identified the three phases of delays. We used Cohen’s K statistic to compare causes of deaths and delays categorization. Results: Comparison of underlying causes was done for 99 deaths. While 109 and 84 deaths for expert panel and MDSR respectively were analyzed for delays because of missing data in MDSR system. Expert panel and MDSR system assigned the same underlying causes in 64(64.6%) deaths (K statistic 0.60). Agreement increased in 80 (80.8%) when causes were assigned by ICD-MM groups (K statistic 0.76). The obstetrician expert panel identified phase one delays in 74 (67.9%), phase two in 24 (22.0%) and phase three delays in all 101 (100%) deaths that were assessed for this delay while MDSR system identified delays in 42 (50.0%), 10 (11.9%) and 78 (92.9%).The expert panel found human errors in management in 94 (93.1%) while MDSR system reported in 53 (67.9%) deaths. Conclusions: MDSR committees performed reasonably well in assigning underlying causes of death. The obstetrician expert panel found more delays than reported in MDSR system indicating difficulties within MDSR teams to critically review deaths.

A cross-sectional study was conducted including 132 maternal deaths from two regions in Tanzania. The deaths had occurred between 1st January and 31st December 2018. Routine MDSR categorization of cause of deaths and the three phases of delay was compared with those assigned by an independent expert panel of obstetricians with additional information from VA. To compute the completeness of maternal deaths reported by the MDSR we used the number of infants that received Bacillus Calmette-Guerin (BCG) vaccine,as a proxy for live births as previously recommended, [19] to calculate the MMR for the two regions in 2018. The study was conducted in Lindi and Mtwara regions in Southern Tanzania with a total population of about 2 million [20]. The two regions have two regional referral hospitals, 12 district hospitals, four private/mission hospitals, 40 health centres and 399 dispensaries. The MMR in Lindi and Mtwara was 456 and 579 per 100,000 live births in 2013 [21]. The fertility rate is one of the lowest (3.8) in Tanzania. Most women, 80.8% in Lindi and 81.3% in Mtwara give birth in health facilities (dispensary, health centres and hospitals). Caesarean section rates are 6.0% in Lindi and 10.3% in Mtwara [5]. Each health facility that provides delivery services in Tanzania has a standard MDSR committee as stipulated in the guideline [6]. In regional and district hospitals, where most deaths occur, MDSR committees are composed of a multidisciplinary team of clinical and non-clinical staff such as obstetricians (if available), medical doctors, clinical officers, nurses and midwives from maternity wards, facility management, laboratory personnel and other supporting staff. The committee meets within 7 days after a suspected maternal death has occurred. Before the meeting, a designated person prepares a narrative summary using information from medical files, interviews of health care providers and relatives who cared for the woman. There is no clear guide on how and which relatives should be interviewed. During the meeting the summary is discussed and when necessary more information is obtained from medical files or health care providers who cared for the woman. Findings from the meeting are summarised in a maternal death reporting form which includes demographic characteristics, medical information, underlying medical cause of death, description of contributing medical and non-medical factors along the three phases of delays and a plan of action [6]. The MDSR guideline recommends the underlying medical cause of death to be categorized following ICD MM rules, but the training and the guideline does not provide a formal training on this. The reporting form in MDSR guideline has a short list of example of causes and ICD 10 codes to be used during reporting. (See Table 6 in Appendix). Our main outcome was the underlying medical cause of death defined as disease or condition that started the chain of events that led to death e.g. postpartum haemorrhage (PPH) [12] . Underlying causes of deaths are grouped into nine groups that are mutually exclusive, totally inclusive and descriptive of all underlying causes of maternal deaths. The groups are; 1) Pregnancy with abortive outcome, 2) Hypertensive disorders in pregnancy, childbirth and the puerperium, 3) Obstetric Haemorrhage 4) Pregnancy related infection, 5) Other obstetric complications, 6) Unanticipated complications of management, 7) Non-obstetric complications, 8) Unknown/undetermined and 9) Coincidental causes. As stipulated in Tanzania MDSR guideline, delays in health care seeking or provision of care deemed to have contributed to the maternal deaths were grouped using the three delays model, stipulating delays 1) to decide to seek care; 2) to reach health facilities for care including transport and 3) to receive appropriate care in facilities [6]. Several delays may contribute to one death. Phase one delays are delays at household and personal level that lead to late or lack of seeking care. It includes the time from the onset of disease at home until the decision to seek care is made by the woman, family or both. Phase two delays are concerned with access to health care such as availability of health facility, roads and transport issues, and constitute time from when the decision to seek care is made until arrival to proper health facility. Phase three delays occur in health facilities and are more concerned with time, equipment and supplies, structure, management errors, human resources and referral system, and constitutes time from admission until adequate treatment or care begins. Data collection followed three steps: 1) abstracting information from MDSR documents 2) performing VA and 3) independent obstetrician panel review. The first author AS, in close collaboration with regional Reproductive and Child Health Coordinators, abstracted information using a pre-defined checklist from maternal deaths narrative summaries, death review report forms and district monthly death report summaries (date of death, age, facility, village and cause of death). The field team (AS and VA interviewers) then traced families using demographic information such as names of the deceased woman, place of death, district and date of death, home address, name of village/street leader, name of husband/partner and other information, for VA interviews. Verbal Autopsy interviews were conducted using the translated standard questionnaire provided by WHO [18]. The questionnaire was piloted and the Swahili translation was reviewed and corrected accordingly. In addition to the standard inquiries, questions relating to the three phases of delay were added. The field team commenced the process of finding families for VA interviews by visiting and enquiring in the facility where death occurred or where the deceased woman attended antenatal clinic. They were then taken to the family through local government leaders. At the family’s home, after being introduced they explained in detail the purpose of VA. Then one of the interviewers identified person (s) that was (were) present during illness and death and conducted VA with them. Using the coded VA questionnaires as well as copies of available medical files a group of experts, consisting of three experienced obstetricians in MDSR reviewed all maternal deaths. Two of them were from Muhimbili University of Health and Allied Sciences and had never worked in the regions and one was from Mtwara regional hospital. The latter was included to help the panel understand the context better especially information in VA. The author, AS, was among the panel members and had previously been trained on using ICD-MM. All the three panel members neither conducted the VA interviews nor documented any information from the reviews. The three panel members reviewed all the deaths together by reading through the information in VA questionnaire and available medical files. Then they discussed the findings and made their decision by consensus. The cause of death was agreed if at least two of the panel members said the same cause of death. First, the expert panel went through VA questionnaires and determined the underlying cause from the information by consensus. Second, the panel went through the medical files and reviewed all available information. Based on these two sources, the panel determined the 1) underlying cause of death including the ICD coding, 2) contributing medical causes and 3) three phases of delays, all by consensus [12]. The three panel members reached consensus in all deaths that were reviewed even though there was a plan to consult another obstetrician in case of no agreement. This was never used since there was consensus in all deaths. Data were processed using MS Excel and then transferred to SPSS computer program version 25. Proportions of each underlying medical cause categorized by MDSR system and the expert panel of obstetricians were computed. Underlying medical causes and differences between the routine MDSR system and obstetricians panel were tabulated. As the routine MDSR system used a shortlist of ICD codes while the expert panel used the full number of ICD-MM codes and groups, comparison had to use a pragmatic approach. For example, when the obstetricians panel categorized a death to be caused by PPH due to atony, coagulopathy or retained placenta, this was considered to be in agreement if MDSR system categorized the same death as PPH (non traumatic). Also PPH (traumatic) for MDSR system was decided to be in agreement if obstetricians’ panel categorized the same case as PPH (vaginal tear, cervical tear, extension of uterine incision during caesarean section). Cohen’s K statistics were used to determine the level of agreement in categorizing the underlying causes and the three phases of delays. We defined < 0 as no agreement, 0–0.2 as slight agreement, 0.21–0.4 as fair, 0.41–0.6 as moderate, 0.61–0.8 as substantial and 0.81–1 as almost perfect agreement [22].

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Based on the provided information, here are some potential innovations that could be recommended to improve access to maternal health:

1. Strengthening the Maternal Death Surveillance and Response (MDSR) system: This could involve improving the consistency and accuracy of categorizing causes of maternal deaths and the three phases of delays. This could be achieved through standardized training and guidelines for MDSR committees, ensuring clear protocols for reviewing deaths, and providing ongoing support and supervision.

2. Enhancing the role of expert panels: The use of independent expert panels, such as the obstetrician panel in this study, could be expanded to improve the accuracy of cause of death categorization and identification of delays. These panels could provide additional expertise and perspectives to complement the work of MDSR committees.

3. Improving data collection and analysis: The study highlights the importance of complete and accurate data for assessing maternal deaths and delays. Innovations in data collection methods, such as the use of electronic health records or mobile technology, could help streamline the process and ensure comprehensive data capture. Additionally, advanced data analysis techniques, such as machine learning or artificial intelligence, could be explored to identify patterns and trends in maternal deaths and delays.

4. Strengthening community engagement and involvement: The study mentions the importance of involving families and community leaders in the MDSR process. Innovations could include community-based awareness campaigns, training programs for community health workers, and the establishment of community-led review committees to ensure that all maternal deaths are identified and reviewed.

5. Improving access to quality maternal healthcare services: The study highlights delays in seeking care, reaching health facilities, and receiving appropriate care as contributing factors to maternal deaths. Innovations could focus on improving transportation infrastructure, increasing the availability of skilled birth attendants and emergency obstetric care facilities, and addressing barriers to accessing healthcare services, such as financial constraints or cultural beliefs.

These are just a few potential innovations that could be considered to improve access to maternal health based on the information provided. It is important to note that the specific context and needs of Tanzania should be taken into account when implementing any recommendations.
AI Innovations Description
The study conducted in Tanzania compared the routine Maternal Death Surveillance and Response (MDSR) system with an independent expert panel of obstetricians to assess the adequacy of categorizing causes of maternal deaths and delays in care. The study included 132 maternal deaths from two regions in Tanzania that occurred in 2018. The MDSR system relies on consistent and correct categorization of causes of maternal deaths and three phases of delays. The expert panel used additional information from Verbal Autopsy (VA) and assigned causes of death based on information from medical files and VA according to the International Classification of Disease to Death in Pregnancy Childbirth and Puerperium (ICD-MM).

The study found that the MDSR committees performed reasonably well in assigning underlying causes of death, with 64.6% of deaths having the same underlying cause assigned by both the expert panel and the MDSR system. Agreement increased to 80.8% when causes were assigned by ICD-MM groups. However, the expert panel identified more delays than reported in the MDSR system, indicating difficulties within MDSR teams to critically review deaths. The expert panel identified phase one delays in 67.9% of deaths, phase two delays in 22.0% of deaths, and phase three delays in all deaths assessed for this delay. In comparison, the MDSR system identified delays in 50.0%, 11.9%, and 92.9% of deaths for phases one, two, and three, respectively. The expert panel also found more human errors in management compared to the MDSR system.

Based on these findings, a recommendation to improve access to maternal health would be to strengthen the training and capacity of MDSR teams to critically review deaths and accurately categorize causes of death and delays in care. This could include providing formal training on ICD-MM rules for categorizing causes of death and clear guidelines on how to conduct thorough reviews, including interviewing the appropriate relatives. Additionally, efforts should be made to address the identified human errors in management to improve the quality of care provided to pregnant women.
AI Innovations Methodology
The study conducted in Tanzania compared the routine Maternal Death Surveillance and Response (MDSR) system’s categorization of causes of maternal deaths and delays to those assigned by an independent expert panel of obstetricians. The methodology involved the following steps:

1. Study Population: The study included 132 maternal deaths from two regions in Tanzania that occurred between January 1st and December 31st, 2018.

2. Data Collection: Information on the underlying medical causes of death and the three phases of delays was abstracted from MDSR system records. Verbal Autopsy (VA) interviews were conducted with bereaved families using the standard WHO VA questionnaire.

3. Expert Panel Review: An independent panel of three experienced obstetricians reviewed all maternal deaths. They assigned underlying causes of death based on information from medical files and VA according to the International Classification of Disease to Death in Pregnancy Childbirth and Puerperium (ICD-MM). The panel also identified the three phases of delays.

4. Comparison and Analysis: The underlying causes of death and delays assigned by the MDSR system were compared to those assigned by the expert panel. Cohen’s K statistic was used to measure the level of agreement between the two categorizations.

5. Results: The study found that the MDSR committees performed reasonably well in assigning underlying causes of death, with a moderate level of agreement (K statistic 0.60). Agreement increased when causes were assigned by ICD-MM groups (K statistic 0.76). The expert panel identified more delays than reported in the MDSR system, indicating difficulties within MDSR teams to critically review deaths.

To simulate the impact of recommendations on improving access to maternal health, a potential methodology could include the following steps:

1. Identify Potential Recommendations: Based on the findings of the study and existing literature, identify potential recommendations to improve access to maternal health. These could include improving the training and guidelines for MDSR committees, enhancing the review process for maternal deaths, strengthening the three phases of delays identification, and improving communication and collaboration between MDSR teams and expert panels.

2. Define Simulation Parameters: Determine the specific parameters to be simulated, such as the number of health facilities, the population size, the baseline maternal mortality rate, and the expected impact of each recommendation on reducing maternal deaths and delays.

3. Develop a Simulation Model: Use a simulation modeling approach, such as system dynamics or agent-based modeling, to develop a model that incorporates the identified recommendations and their potential impact on improving access to maternal health. The model should consider factors such as the availability and quality of healthcare services, transportation infrastructure, community awareness and behavior, and the effectiveness of the recommended interventions.

4. Validate the Model: Validate the simulation model by comparing its outputs with real-world data on maternal mortality rates and access to maternal health services. Adjust the model parameters and assumptions as necessary to ensure its accuracy and reliability.

5. Simulate Scenarios: Run simulations using different scenarios to assess the potential impact of the recommendations on improving access to maternal health. Evaluate the outcomes, such as changes in maternal mortality rates, reductions in delays, and improvements in the categorization of causes of maternal deaths.

6. Analyze Results and Make Recommendations: Analyze the simulation results to identify the most effective recommendations for improving access to maternal health. Consider the feasibility, cost-effectiveness, and sustainability of each recommendation. Based on the findings, make evidence-based recommendations for policy and practice to improve maternal health outcomes.

By following this methodology, policymakers and healthcare professionals can gain insights into the potential impact of different recommendations on improving access to maternal health and make informed decisions to prioritize and implement effective interventions.

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