From planning to practice: Building the national network for the surveillance of severe maternal morbidity

BMC Public Health, Volume 11, Year 2011

Interpretation

Background: Improving maternal health is one of the Millennium Development Goals for 2015. Recently some progress has been achieved in reducing mortality. On the other hand, in developed regions, maternal death is a relatively rare event compared to the number of cases of morbidity; hence studying maternal morbidity has become more relevant. Electronic surveillance systems may improve research by facilitating complete data reporting and reducing the time required for data collection and analysis. Therefore the purpose of this study was to describe the methods used in elaborating and implementing the National Network for the Surveillance of Severe Maternal Morbidity in Brazil. Methods. The project consisted of a multicenter, cross-sectional study for the surveillance of severe maternal morbidity including near-miss, in Brazil. Results: Following the development of a conceptual framework, centers were selected for inclusion in the network, consensus meetings were held among the centers, an electronic data collection system was identified, specific software and hardware tools were developed, research material was prepared, and the implementation process was initiated and analyzed. Conclusion: The conceptual framework developed for this network was based on the experience acquired in various studies carried out in the area over recent years and encompasses maternal and perinatal health. It is innovative especially in the context of a developing country. The implementation of the project represents the first step towards this planned management. The system online elaborated for this surveillance network may be used in further studies in reproductive and perinatal health. © 2011 Haddad et al; licensee BioMed Central Ltd. In 2002, research was initiated at the University of Campinas, Brazil, focusing on severe maternal morbidity. The transition from studying death to studying maternal morbidity followed a worldwide trend, considering the absolute number of deaths is relatively small compared to the number of cases of morbidity. Data on maternal morbidity are more accessible and reliable for the evaluation of quality in obstetrical care. Within this scope, a study was conducted to evaluate the applicability of different concepts of severe maternal morbidity and of a severity score to identify cases of maternal morbidity [9]. Elaborating further on the concept that routine health data would be useful for systematically identifying the occurrence of complications associated with pregnancy, the National Health Service’s Hospital Information System was evaluated. Data routinely collected from medical records of women with conditions suggestive of severe maternal morbidity were selected, and the diagnoses and procedures used in such cases were described in order to identify factors associated with the occurrence of maternal death [15]. Next, further evaluations on maternal morbidity were performed using data from demographic health surveys. The importance of the use of validated questionnaires for obtaining information on morbidity and the regional differences in the prevalence of morbidity were also highlighted [11]. Considering that the early identification of cases of maternal morbidity would allow a more appropriate way of monitoring, managing and preventing deaths [28], the proposal to establish the National Network for Surveillance of Severe Maternal Morbidity was developed as a research proposal [27]. The project is a multicenter, cross-sectional study to be implemented in referral obstetrical units in all geographical regions of Brazil. Over a 12-month period, prospective surveillance and data collection was planned to be performed to identify cases of maternal near-miss and potentially life-threatening conditions in accordance with the new criteria defined by WHO [5]. To determine the number of collaborating centers to be included in the study, sample size was calculated according to the number of deliveries that would have to be covered to identify cases of near-miss. Based on a previously reported incidence of 8 cases for 1000 deliveries [9], approximately 70,000 deliveries would have to be monitored. This number was believed to be sufficient to validate the new criteria issued by WHO [5]. The study population is composed of all the women admitted to the participating hospitals during the study period who suffer organ dysfunction (that will be a near-miss case or a maternal death, Table Table1)1) or presenting potentially life-threatening conditions (Table (Table2),2), who die or are transferred to other healthcare services because they require more specialized services or procedures. Potentially life-threatening maternal conditions WHO criteria for maternal near miss5 During the data collection period, at each participating hospital, local coordinators perform a daily review of all admitted women, looking for cases with any of the conditions indicative of severity (Table (Table2).2). The lists of patients with these diagnoses are sent for review and data collection following the patient’s discharge from hospital, death or transfer to another hospital. Data unavailable from the record is obtained from the attending team. Data are collected on demographic and obstetrical characteristics, primary determinant of severe morbidity (the first complication in the chain of events that led to severe maternal morbidity), length of hospitalization, occurrence of any criteria of maternal near-miss, perinatal outcome and condition of the woman at discharge from hospital. The data are collected on a pre-coded form and are then sent electronically to the database. The manually completed forms are filed in such a way as to be easily accessible for inspection during technical quality control visits. After the general proposal was ready, a meeting was held during a national congress of the Brazilian Federation of Societies of Gynecology and Obstetrics in November 2007 where representatives of several healthcare institutions from around the country were present. The proposal to establish a National Network for Surveillance of Severe Maternal Morbidity was presented and those interested in participating applied for that. Before the project could be implemented, the proposal was submitted for public funding and, following approval, an invitation letter was sent to all interested institutions, together with a summary of the planned objectives and methods. In addition, a form designed to obtain information on the characteristics of the collaborating center was also sent to the local investigator. Basically, it had information on identification and location of the institution, nature and complexity level of the hospital, population covered, number of beds in the maternity department, availability of resources for more specialized care (blood bank, obstetrical and neonatal intensive care units, specialist care for high risk pregnancies, availability of other medical or surgical specialities, ultrasonography, laboratory, anesthetists available round the clock, resources for the parenteral administration of antibiotics, oxytocin and magnesium sulphate, resources for general anesthesia, mechanical ventilation, cardiorespiratory resuscitation of adults and newborn infants, hysterectomy), number of deliveries performed annually (minimum number required above 1,000 deliveries/year), availability of broadband internet connection, data on the prevalence of some obstetrical interventions based on scientific evidence performed during delivery, and availability of written protocols of procedures in the service. Additionally telephone contacts occurred between the principal investigator and the person responsible for the institution. As a result of these different approaches, 35 institutions from all over Brazil applied for participating in the study. Evaluation of their characteristics and geographical distribution led to the selection of 27 institutions that fulfilled all the inclusion criteria. Following selection of the centers, a meeting was held in August 2008 with the principal investigators from each center at the project headquarters in Campinas. At this time, a term of agreement was signed by all attendants to compose a Brazilian Network for Studies in Reproductive and Perinatal Health. The objective of this alliance was to proceed to develop further studies in the future in the matter, using the same multicenter strategy of achieving regional diversity in a developing country with continental extensions. The meeting lasted for two days when the research proposal was reviewed and discussed, the concepts of near miss and severe maternal morbidity were presented, the data collection forms were structured and the concept of developing an electronic data collection system was introduced. A copy of the proposal was provided to each center, to be evaluated and approved locally. The coordinating center had the research protocol approved by the local institutional review board (Committee of Ethics in Research from the School of Medical Sciences, University of Campinas – Approval letter CEP 097/2009), and then by the national IRB. The viability of the entire project depended on approval of the request for funding submitted to the National Research Council (CNPq)/Department of Science and Technology (DECIT). Initially, the plan was to develop software and a customized data management system control system for the study. Nevertheless, due to some practical constraints, it was decided to use a system that had already been developed and that would be cheaper to maintain. Therefore, a free, open source, online data entry system was selected (OpenClinica®) [29], which is available for use in clinical trials, was selected. This internet-based system consists of an electronic platform for data entry and management of data and is designed to support all types of clinical studies in a variety of locations [29]. The system permits autonomy in creating forms, in analyzing and storing data and in stratifying the right of access to be granted to users working in the same study (Figure (Figure11). Sample screens from the online data entry and management system: A. Cover sheet for the study in OpenClinica; B. Form for the management of all subjects; C. Form for data entry on criteria for maternal near-miss.

AI Digest

Study Justification:

– Improving maternal health is a global goal, and studying maternal morbidity is crucial in achieving this goal.
– Maternal morbidity is more common than maternal mortality, making it a relevant area of study.
– Electronic surveillance systems can improve research by facilitating complete data reporting and reducing data collection and analysis time.

Study Highlights:

– The study focused on building the National Network for the Surveillance of Severe Maternal Morbidity in Brazil.
– A conceptual framework was developed based on previous studies in the field.
– Centers were selected for inclusion in the network, consensus meetings were held, and an electronic data collection system was identified.
– Specific software and hardware tools were developed, research material was prepared, and the implementation process was initiated and analyzed.

Study Recommendations:

– The study recommends the establishment and implementation of the National Network for the Surveillance of Severe Maternal Morbidity.
– The developed conceptual framework can be used in further studies in reproductive and perinatal health.
– The online surveillance system created for this network can be utilized in future research.

Key Role Players:

– Researchers and scientists involved in maternal health and morbidity studies.
– Healthcare institutions and hospitals participating in the network.
– National and local government agencies responsible for funding and policy-making in healthcare.

Cost Items for Planning Recommendations:

– Development and maintenance of the electronic data collection system.
– Research material preparation and distribution.
– Training and capacity building for healthcare professionals involved in data collection.
– Travel and accommodation expenses for meetings and conferences.
– Administrative and logistical support for the network’s operations.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, as it describes the methods used in elaborating and implementing the National Network for the Surveillance of Severe Maternal Morbidity in Brazil. However, to improve the evidence, the abstract could provide more specific details about the study design, sample size, data collection methods, and statistical analysis. Additionally, including information about the results and conclusions of the study would further strengthen the evidence.

Abstract

In 2002, research was initiated at the University of Campinas, Brazil, focusing on severe maternal morbidity. The transition from studying death to studying maternal morbidity followed a worldwide trend, considering the absolute number of deaths is relatively small compared to the number of cases of morbidity. Data on maternal morbidity are more accessible and reliable for the evaluation of quality in obstetrical care. Within this scope, a study was conducted to evaluate the applicability of different concepts of severe maternal morbidity and of a severity score to identify cases of maternal morbidity [9]. Elaborating further on the concept that routine health data would be useful for systematically identifying the occurrence of complications associated with pregnancy, the National Health Service’s Hospital Information System was evaluated. Data routinely collected from medical records of women with conditions suggestive of severe maternal morbidity were selected, and the diagnoses and procedures used in such cases were described in order to identify factors associated with the occurrence of maternal death [15]. Next, further evaluations on maternal morbidity were performed using data from demographic health surveys. The importance of the use of validated questionnaires for obtaining information on morbidity and the regional differences in the prevalence of morbidity were also highlighted [11]. Considering that the early identification of cases of maternal morbidity would allow a more appropriate way of monitoring, managing and preventing deaths [28], the proposal to establish the National Network for Surveillance of Severe Maternal Morbidity was developed as a research proposal [27]. The project is a multicenter, cross-sectional study to be implemented in referral obstetrical units in all geographical regions of Brazil. Over a 12-month period, prospective surveillance and data collection was planned to be performed to identify cases of maternal near-miss and potentially life-threatening conditions in accordance with the new criteria defined by WHO [5]. To determine the number of collaborating centers to be included in the study, sample size was calculated according to the number of deliveries that would have to be covered to identify cases of near-miss. Based on a previously reported incidence of 8 cases for 1000 deliveries [9], approximately 70,000 deliveries would have to be monitored. This number was believed to be sufficient to validate the new criteria issued by WHO [5]. The study population is composed of all the women admitted to the participating hospitals during the study period who suffer organ dysfunction (that will be a near-miss case or a maternal death, Table Table1)1) or presenting potentially life-threatening conditions (Table (Table2),2), who die or are transferred to other healthcare services because they require more specialized services or procedures. Potentially life-threatening maternal conditions WHO criteria for maternal near miss5 During the data collection period, at each participating hospital, local coordinators perform a daily review of all admitted women, looking for cases with any of the conditions indicative of severity (Table (Table2).2). The lists of patients with these diagnoses are sent for review and data collection following the patient’s discharge from hospital, death or transfer to another hospital. Data unavailable from the record is obtained from the attending team. Data are collected on demographic and obstetrical characteristics, primary determinant of severe morbidity (the first complication in the chain of events that led to severe maternal morbidity), length of hospitalization, occurrence of any criteria of maternal near-miss, perinatal outcome and condition of the woman at discharge from hospital. The data are collected on a pre-coded form and are then sent electronically to the database. The manually completed forms are filed in such a way as to be easily accessible for inspection during technical quality control visits. After the general proposal was ready, a meeting was held during a national congress of the Brazilian Federation of Societies of Gynecology and Obstetrics in November 2007 where representatives of several healthcare institutions from around the country were present. The proposal to establish a National Network for Surveillance of Severe Maternal Morbidity was presented and those interested in participating applied for that. Before the project could be implemented, the proposal was submitted for public funding and, following approval, an invitation letter was sent to all interested institutions, together with a summary of the planned objectives and methods. In addition, a form designed to obtain information on the characteristics of the collaborating center was also sent to the local investigator. Basically, it had information on identification and location of the institution, nature and complexity level of the hospital, population covered, number of beds in the maternity department, availability of resources for more specialized care (blood bank, obstetrical and neonatal intensive care units, specialist care for high risk pregnancies, availability of other medical or surgical specialities, ultrasonography, laboratory, anesthetists available round the clock, resources for the parenteral administration of antibiotics, oxytocin and magnesium sulphate, resources for general anesthesia, mechanical ventilation, cardiorespiratory resuscitation of adults and newborn infants, hysterectomy), number of deliveries performed annually (minimum number required above 1,000 deliveries/year), availability of broadband internet connection, data on the prevalence of some obstetrical interventions based on scientific evidence performed during delivery, and availability of written protocols of procedures in the service. Additionally telephone contacts occurred between the principal investigator and the person responsible for the institution. As a result of these different approaches, 35 institutions from all over Brazil applied for participating in the study. Evaluation of their characteristics and geographical distribution led to the selection of 27 institutions that fulfilled all the inclusion criteria. Following selection of the centers, a meeting was held in August 2008 with the principal investigators from each center at the project headquarters in Campinas. At this time, a term of agreement was signed by all attendants to compose a Brazilian Network for Studies in Reproductive and Perinatal Health. The objective of this alliance was to proceed to develop further studies in the future in the matter, using the same multicenter strategy of achieving regional diversity in a developing country with continental extensions. The meeting lasted for two days when the research proposal was reviewed and discussed, the concepts of near miss and severe maternal morbidity were presented, the data collection forms were structured and the concept of developing an electronic data collection system was introduced. A copy of the proposal was provided to each center, to be evaluated and approved locally. The coordinating center had the research protocol approved by the local institutional review board (Committee of Ethics in Research from the School of Medical Sciences, University of Campinas – Approval letter CEP 097/2009), and then by the national IRB. The viability of the entire project depended on approval of the request for funding submitted to the National Research Council (CNPq)/Department of Science and Technology (DECIT). Initially, the plan was to develop software and a customized data management system control system for the study. Nevertheless, due to some practical constraints, it was decided to use a system that had already been developed and that would be cheaper to maintain. Therefore, a free, open source, online data entry system was selected (OpenClinica®) [29], which is available for use in clinical trials, was selected. This internet-based system consists of an electronic platform for data entry and management of data and is designed to support all types of clinical studies in a variety of locations [29]. The system permits autonomy in creating forms, in analyzing and storing data and in stratifying the right of access to be granted to users working in the same study (Figure (Figure11). Sample screens from the online data entry and management system: A. Cover sheet for the study in OpenClinica; B. Form for the management of all subjects; C. Form for data entry on criteria for maternal near-miss.

Materials

N/A

Innovations

Some potential innovations to improve access to maternal health based on the provided information include:

1. Electronic surveillance systems: Implementing electronic surveillance systems can facilitate complete data reporting and reduce the time required for data collection and analysis. This innovation can improve research on maternal morbidity and help identify cases of severe maternal morbidity more efficiently.

2. National Network for the Surveillance of Severe Maternal Morbidity: Establishing a national network for surveillance can help monitor, manage, and prevent maternal deaths by identifying cases of maternal near-miss and potentially life-threatening conditions. This network can involve multiple referral obstetrical units across different geographical regions, ensuring comprehensive coverage.

3. Online data collection system: Utilizing an online data entry system, such as OpenClinica, can streamline data collection and management for the surveillance network. This system allows for the creation of forms, analysis and storage of data, and controlled access for users working on the study.

4. Collaboration and coordination: Building alliances and collaborations among healthcare institutions and researchers can enhance the development of studies in reproductive and perinatal health. This approach promotes regional diversity and knowledge sharing in a developing country with large geographical extensions.

5. Use of validated questionnaires: Incorporating validated questionnaires can provide reliable information on maternal morbidity and highlight regional differences in prevalence. This innovation can contribute to a better understanding of maternal health and guide targeted interventions.

6. Public funding and approval processes: Seeking public funding and obtaining necessary approvals from institutional review boards and national research councils are crucial steps in implementing maternal health projects. These processes ensure financial support and ethical considerations for the innovation.

Overall, these innovations aim to improve access to maternal health by enhancing data collection, surveillance, collaboration, and knowledge dissemination in the field of maternal morbidity.

AI Innovations Description

The recommendation to improve access to maternal health is to develop a national network for the surveillance of severe maternal morbidity. This network would utilize electronic surveillance systems to facilitate complete data reporting and reduce the time required for data collection and analysis. The network would involve multiple centers across the country and would implement a standardized data collection system. Specific software and hardware tools would be developed to support the network’s operations. The implementation of this network would allow for the early identification of cases of maternal morbidity, leading to more effective monitoring, management, and prevention of maternal deaths. The system developed for this network could also be used in further studies in reproductive and perinatal health.

AI Innovations Methodology

To improve access to maternal health, here are some potential recommendations:

1. Telemedicine: Implementing telemedicine programs can provide remote access to healthcare professionals for prenatal care, consultations, and monitoring of high-risk pregnancies. This can be especially beneficial in rural or underserved areas where access to healthcare facilities is limited.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information and resources on maternal health, such as prenatal care guidelines, nutrition advice, and appointment reminders, can help educate and empower pregnant women to take better care of their health.

3. Community health workers: Training and deploying community health workers who can provide basic maternal health services, education, and support to pregnant women in their communities can improve access to care, especially in areas with limited healthcare infrastructure.

4. Transportation support: Establishing transportation services or subsidies for pregnant women to reach healthcare facilities can help overcome geographical barriers and ensure timely access to prenatal care and emergency obstetric services.

5. Public-private partnerships: Collaborating with private healthcare providers and organizations to expand access to maternal health services can help bridge gaps in service delivery and increase the availability of quality care.

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

1. Define the indicators: Identify key indicators to measure the impact of the recommendations, such as the number of pregnant women receiving prenatal care, the reduction in maternal mortality rates, the increase in the number of high-risk pregnancies identified and managed, and the improvement in overall maternal health outcomes.

2. Collect baseline data: Gather existing data on the current state of maternal health access and outcomes in the target population or region. This can include data on healthcare facility availability, utilization rates, maternal mortality rates, and other relevant indicators.

3. Develop a simulation model: Create a simulation model that incorporates the recommended interventions and their potential impact on the identified indicators. This model should consider factors such as population demographics, healthcare infrastructure, and resource availability.

4. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to assess the potential impact of the recommendations. Adjust the parameters of the interventions, such as the coverage of telemedicine services or the number of community health workers deployed, to explore different scenarios and their potential outcomes.

5. Analyze results: Analyze the results of the simulations to determine the potential impact of the recommendations on improving access to maternal health. Assess the changes in the identified indicators and compare them to the baseline data to understand the potential benefits and challenges of implementing the recommendations.

6. Refine and validate the model: Refine the simulation model based on the analysis of the results and validate it using real-world data and feedback from experts in the field. This will help ensure the accuracy and reliability of the model for future use.

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

Author

Dima Health

Statistics:

Citations: 34

Identifiers:

DOI: 10.1186/1471-2458-11-283

Research Areas:

Community Interventions, Disparities, Health System and Policy, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Technology and Innovations

Study Design:

Cohort Study, Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female