Validity of verbal autopsy method to determine causes of death among adults in the urban setting of Ethiopia

BMC Medical Research Methodology, Volume 12, Year 2012

Interpretation

Background: Verbal autopsy has been widely used to estimate causes of death in settings with inadequate vital registries, but little is known about its validity. This analysis was part of Addis Ababa Mortality Surveillance Program to examine the validity of verbal autopsy for determining causes of death compared with hospital medical records among adults in the urban setting of Ethiopia. Methods: This validation study consisted of comparison of verbal autopsy final diagnosis with hospital diagnosis taken as a “gold standard”. In public and private hospitals of Addis Ababa, 20,152 adult deaths (15 years and above) were recorded between 2007 and 2010. With the same period, a verbal autopsy was conducted for 4,776 adult deaths of which, 1,356 were deceased in any of Addis Ababa hospitals. Then, verbal autopsy and hospital data sets were merged using the variables; full name of the deceased, sex, address, age, place and date of death. We calculated sensitivity, specificity and positive predictive values with 95% confidence interval. Results: After merging, a total of 335 adult deaths were captured. For communicable diseases, the values of sensitivity, specificity and positive predictive values of verbal autopsy diagnosis were 79%, 78% and 68% respectively. For non-communicable diseases, sensitivity of the verbal autopsy diagnoses was 69%, specificity 78% and positive predictive value 79%. Regarding injury, sensitivity of the verbal autopsy diagnoses was 70%, specificity 98% and positive predictive value 83%. Higher sensitivity was achieved for HIV/AIDS and tuberculosis, but lower specificity with relatively more false positives. Conclusion: These findings may indicate the potential of verbal autopsy to provide cost-effective information to guide policy on communicable and non communicable diseases double burden among adults in Ethiopia. Thus, a well structured verbal autopsy method, followed by qualified physician reviews could be capable of providing reasonable cause specific mortality estimates in Ethiopia. However, the limited generalizability of this study due to the fact that matched verbal autopsy deaths were all in-hospital deaths in an urban center, thus results may not be generalizable to rural home deaths. Such application and refinement of existing verbal autopsy methods holds out the possibility of obtaining replicable, sustainable and internationally comparable mortality statistics of known quality. Similar validation studies need to be undertaken considering the limitation of medical records as “gold standard” since records may not be confirmed using laboratory investigations or medical technologies. The validation studies need to address child and maternal causes of death and possibly all underlying causes of death. This validation study was part of Addis Ababa Mortality Surveillance Program (AAMSP) the then project and in place since 2001 in Addis Ababa, Ethiopia. We validated verbal autopsy data with hospital data of the program during 2007 to 2010. The sampling frame for this verbal autopsy method; the burial surveillance was conducted in all cemeteries (n ≈ 89) of Addis Ababa since 2001. Since cremation is not practiced in Addis Ababa, burials of deaths are conducted at religious or municipality based cemeteries. In principle thus, the burial surveillance captures all deceased residents of Addis Ababa, although biases exist because residents may die and/or be buried outside the capital just as non-residents may be buried inside Addis Ababa. Some of these biases are mostly identified and corrected while others inevitably go unnoticed. The surveillance registration was conducted by cemetery based clerks who were regularly trained and supervised. Approximately, 20,000 deaths per year were reported by these cemetery clerks. However, due to financial and logistic reasons; randomly 10% of the deaths were drawn from the burial database for verbal autopsy interview. We employed retrospective reviews of burials with verbal autopsy technique and retrospective reviews of hospital records in Addis Ababa, Ethiopia. Three pairs of field workers who are non health professionals who were trained in the technique visited households of the deceased (minimum one month and maximum three months after the funeral) and selected a respondent who was the person most closely associated with the deceased during the terminal illness. The interview was carried out in Amharic (the national language) once its purpose had been fully explained and consent obtained. Field workers were recruited locally to ensure a common cultural background with the local community. All had completed secondary school, were experienced in conducting surveys, and had demonstrated the ability to conduct a verbal autopsy interview with insight and empathy. The first several interviews of each field worker were carefully monitored and supervised by field coordinators and researchers. Thereafter, weekly feedback sessions were held on a regular basis, providing an opportunity to appraise the quality of information recorded [3]. The completeness of the VA was approximately 85% where refusal accounts nearly 3%, loss of address 6%, unavailability of the care givers with repeated visit 2% and wrong address 4% which may introduce bias in mortality estimations. The verbal autopsy questionnaire, adapted from a standardized WHO and INDEPTH Network [17,18] was translated into Amharic, back translated into English and modified to reflect culturally recognized accepted terms. The questionnaire was divided into four main parts: an open section where the informant freely describes the symptoms and signs preceding death, and their sequence; followed by a closed section in which a basic filtering question, when answered positively, leads to a more detailed enquiry of the particular symptom. Further sections address identification of the caregivers, use of modern and traditional treatments, and lifestyle practices of the deceased. The physician review method was used to determine causes of death. Three physicians were participating in the review process which were second or third year internal medicine residents of Addis Ababa University recruited to join the university after serving two or more years as a General Practitioner (GP) in any of the public hospitals. We provided them trainings and annual refreshments on the standard verbal autopsy method. First, each completed questionnaire was reviewed independently by two physicians. If the same diagnosis was reached, this was accepted as the ‘underlying cause of death’, where not, a third physician made a further blind and independent assessment. If two out of three diagnoses corresponded, this would be accepted; otherwise, the three physicians would set for panel, where consensus achieved would be accepted, if not, the cause of death would be described as ‘undetermined’. In the review process, almost 10% of the verbal autopsy questionnaires required a third physician review for communicable and non communicable major disease categories, but <1% for injury. Less than 1% of the major disease categories required physicians’ panel. Regarding specific causes of deaths, generally <2% of the verbal autopsy questionnaires required third physicians; and <1% required panel. Finally, the research assistant with health background would assign ICD-10 codes according to the international classification of diseases, 10th revision [19]. Double data entry was done to all the cases, for both the verbal autopsy interview and physician review. Once the data entry was completed, a data manager using STATA driven .do files had been conducting a thorough data cleaning. For the purpose of this paper, we adapted the 2006 Global Burden of Disease classification of causes of death as follows; communicable diseases, non communicable causes, and injuries [20]. A retrospective record review of deaths in 43 public and private hospitals of Addis Ababa from 2007 to 2010 was conducted to validate causes of death reported by verbal autopsy. Nearly, 20,000 adult deaths (15 years and above) of Addis Ababa residents were captured during the study period. Each hospital assigned reviewers who are permanent staffs in the hospitals and centrally three nurses were coordinating, supervising and checking the completeness of the report. Hospital records were assessed by hospital clerks blind to the verbal autopsy diagnosis. Collected information of validation relevant includes full name, age, sex, and date of death, name of the hospital, and full address of the deceased and the principal cause of death. The data collectors and coordinators had prior relevant experience and provided extensive training on proper review of the medical records and registration books and the use of the data abstraction form. To capture deaths and complete the relevant information in the hospitals, every attempt was made from patient records and death registry books for patients who died during the study period. In the hospitals diagnosing causes of death was performed by physicians considering patients' history, physical examination, laboratory results and imaging investigations. Only diseases responsible for the death were considered as cause/s of death. Finally, cause of death was coded by nurse coordinators according to the international classification of diseases, 10th revision (ICD-10) [19]. We have listed below specific causes of death with the corresponding ICD-10 assigned. Cause of Death List: ICD - 10 code; HIV/AIDS: B20–B24; Tuberculosis: A15–A19, B90; Respiratory infections: J00–J06, J10–J18, J20–J22, H65–H66; Meningitis: A39, G00, G03; Malignant neoplasm: C00–C97; Diabetes Mellitus: E10–E14; Cardiovascular diseases: I00–I99; Hypertension: I10–I13; Stroke: I60–I69; Respiratory diseases: J30–J98; Digestive diseases: K20–K92; Chronic Liver Disease: K70, K74; Peptic Ulcer Disease: K25–K27; Genitourinary Diseases: N00–N64, N75–N98; Unintentional injuries: V01–X59, Y40–Y86, Y88, Y89; Road traffic accidents: V01–V04, V06, V09–V80, V87, V89, V99; Intentional injuries (Suicide…): X60–Y09, Y35–Y36, Y870, Y871. Data were double entered to Access Microsoft office and cleaned using STATA .do files. The 2006 Global Burden of Diseases classification was adapted to classify cause of deaths in our study. This classification categorized diseases into; communicable diseases, non-communicable diseases and all injuries [20]. Verbal Autopsy interview was conducted after obtaining verbal informed consent from the kin or caregiver of the deceased after explaining the purpose and the procedure of the study. Information sheet prepared in English and translated to local language had been provided. Permission for the study had been also obtained from local authorities. Protocol of the program was approved by Institutional Review Board (IRB) of Medical Faculty, Addis Ababa University, and the Ethiopian Science and Technology Agency. Government and institutional officials, religious leaders at each level had been communicated. Individual information was accessible only to the research team and is kept confidential. The validation consisted of a comparison of verbal autopsy final diagnosis with hospital diagnosis taken as a “gold standard”, followed by calculation of their sensitivity, specificity and positive predictive values. The sensitivity of a verbal autopsy for a particular cause of death such as HIV/AIDS is the proportion of the deceased whose verbal autopsy cause of death is correctly identified as HIV/AIDS out of all those who truly died from HIV/AIDS, while the specificity is the proportion whose cause of death is identified as not HIV/AIDS among those who truly did not die from HIV/AIDS [2]. Verbal autopsy and hospital data sets were merged using the variables; deceased full name, sex, address, age, place of death and date of death. First we found 1356 deaths occurred in hospitals which were reported with verbal autopsy during 2007 to 2010 period. We merged this verbal autopsy data set with hospital data (n = 20,152, age 15 years and above). Finally, we found 335 deaths for this analysis. This was basically due to the incompleteness of the hospital records and registry books; and differences with age, addresses, and deceased full name, place of death or date of death during merging that might introduce bias. The number of causes of death could be greater than the number of deceased adults in the verbal autopsy and hospital diagnosis since we used two or more causes of death (multiple causes of death) and treated independently. Sensitivity, specificity and positive predictive value analysis was performed for 3 major categories of diseases; communicable diseases, non communicable diseases and injuries and for each of the major diseases under each category such as HIV/AIDS, tuberculosis, malignant neoplasm, cardiovascular diseases etc. We used chi-squared test to compare proportions between selected verbal autopsy adult deaths, selected hospital adult deaths. Finally, to show the actual causes of death distribution “actual verbal autopsy diagnoses” and for comparison and completeness of this study, cause specific mortality proportion findings of the double mortality burden study included [10]. The current and the former study were from the same study area, data source and study period.

AI Digest

Study Justification:

– Verbal autopsy has been widely used to estimate causes of death in settings with inadequate vital registries.
– Little is known about the validity of verbal autopsy as a method for determining causes of death.
– This study aimed to examine the validity of verbal autopsy compared with hospital medical records in an urban setting in Ethiopia.

Highlights:

– The study found that the sensitivity, specificity, and positive predictive values of verbal autopsy diagnosis were generally high for communicable diseases, non-communicable diseases, and injuries.
– Higher sensitivity was achieved for HIV/AIDS and tuberculosis, but lower specificity with more false positives.
– The findings suggest that verbal autopsy could provide cost-effective information to guide policy on communicable and non-communicable diseases in Ethiopia.
– A well-structured verbal autopsy method, followed by qualified physician reviews, could provide reasonable cause-specific mortality estimates in Ethiopia.

Recommendations:

– Similar validation studies should be undertaken to address the limitations of medical records as a “gold standard” for cause of death determination.
– Validation studies should also consider child and maternal causes of death and all underlying causes of death.
– Application and refinement of existing verbal autopsy methods can lead to replicable, sustainable, and internationally comparable mortality statistics of known quality.

Key Role Players:

– Researchers and data collectors
– Field coordinators and supervisors
– Physicians for reviewing verbal autopsy questionnaires
– Nurse coordinators for coding causes of death
– Data manager for data cleaning
– Institutional Review Board (IRB) for approval
– Government and institutional officials for communication and support
– Local authorities and religious leaders for permission and support

Cost Items for Planning Recommendations:

– Training and refreshments for field workers, physicians, and coordinators
– Data entry and cleaning
– Communication and support from government and institutional officials
– Printing and translation of information sheets
– Institutional Review Board (IRB) approval process
– Travel and logistics for data collection
– Equipment and supplies for data collection and coding

Strength of Evidence

N/A

Abstract

This validation study was part of Addis Ababa Mortality Surveillance Program (AAMSP) the then project and in place since 2001 in Addis Ababa, Ethiopia. We validated verbal autopsy data with hospital data of the program during 2007 to 2010. The sampling frame for this verbal autopsy method; the burial surveillance was conducted in all cemeteries (n ≈ 89) of Addis Ababa since 2001. Since cremation is not practiced in Addis Ababa, burials of deaths are conducted at religious or municipality based cemeteries. In principle thus, the burial surveillance captures all deceased residents of Addis Ababa, although biases exist because residents may die and/or be buried outside the capital just as non-residents may be buried inside Addis Ababa. Some of these biases are mostly identified and corrected while others inevitably go unnoticed. The surveillance registration was conducted by cemetery based clerks who were regularly trained and supervised. Approximately, 20,000 deaths per year were reported by these cemetery clerks. However, due to financial and logistic reasons; randomly 10% of the deaths were drawn from the burial database for verbal autopsy interview. We employed retrospective reviews of burials with verbal autopsy technique and retrospective reviews of hospital records in Addis Ababa, Ethiopia. Three pairs of field workers who are non health professionals who were trained in the technique visited households of the deceased (minimum one month and maximum three months after the funeral) and selected a respondent who was the person most closely associated with the deceased during the terminal illness. The interview was carried out in Amharic (the national language) once its purpose had been fully explained and consent obtained. Field workers were recruited locally to ensure a common cultural background with the local community. All had completed secondary school, were experienced in conducting surveys, and had demonstrated the ability to conduct a verbal autopsy interview with insight and empathy. The first several interviews of each field worker were carefully monitored and supervised by field coordinators and researchers. Thereafter, weekly feedback sessions were held on a regular basis, providing an opportunity to appraise the quality of information recorded [3]. The completeness of the VA was approximately 85% where refusal accounts nearly 3%, loss of address 6%, unavailability of the care givers with repeated visit 2% and wrong address 4% which may introduce bias in mortality estimations. The verbal autopsy questionnaire, adapted from a standardized WHO and INDEPTH Network [17,18] was translated into Amharic, back translated into English and modified to reflect culturally recognized accepted terms. The questionnaire was divided into four main parts: an open section where the informant freely describes the symptoms and signs preceding death, and their sequence; followed by a closed section in which a basic filtering question, when answered positively, leads to a more detailed enquiry of the particular symptom. Further sections address identification of the caregivers, use of modern and traditional treatments, and lifestyle practices of the deceased. The physician review method was used to determine causes of death. Three physicians were participating in the review process which were second or third year internal medicine residents of Addis Ababa University recruited to join the university after serving two or more years as a General Practitioner (GP) in any of the public hospitals. We provided them trainings and annual refreshments on the standard verbal autopsy method. First, each completed questionnaire was reviewed independently by two physicians. If the same diagnosis was reached, this was accepted as the ‘underlying cause of death’, where not, a third physician made a further blind and independent assessment. If two out of three diagnoses corresponded, this would be accepted; otherwise, the three physicians would set for panel, where consensus achieved would be accepted, if not, the cause of death would be described as ‘undetermined’. In the review process, almost 10% of the verbal autopsy questionnaires required a third physician review for communicable and non communicable major disease categories, but <1% for injury. Less than 1% of the major disease categories required physicians’ panel. Regarding specific causes of deaths, generally <2% of the verbal autopsy questionnaires required third physicians; and <1% required panel. Finally, the research assistant with health background would assign ICD-10 codes according to the international classification of diseases, 10th revision [19]. Double data entry was done to all the cases, for both the verbal autopsy interview and physician review. Once the data entry was completed, a data manager using STATA driven .do files had been conducting a thorough data cleaning. For the purpose of this paper, we adapted the 2006 Global Burden of Disease classification of causes of death as follows; communicable diseases, non communicable causes, and injuries [20]. A retrospective record review of deaths in 43 public and private hospitals of Addis Ababa from 2007 to 2010 was conducted to validate causes of death reported by verbal autopsy. Nearly, 20,000 adult deaths (15 years and above) of Addis Ababa residents were captured during the study period. Each hospital assigned reviewers who are permanent staffs in the hospitals and centrally three nurses were coordinating, supervising and checking the completeness of the report. Hospital records were assessed by hospital clerks blind to the verbal autopsy diagnosis. Collected information of validation relevant includes full name, age, sex, and date of death, name of the hospital, and full address of the deceased and the principal cause of death. The data collectors and coordinators had prior relevant experience and provided extensive training on proper review of the medical records and registration books and the use of the data abstraction form. To capture deaths and complete the relevant information in the hospitals, every attempt was made from patient records and death registry books for patients who died during the study period. In the hospitals diagnosing causes of death was performed by physicians considering patients' history, physical examination, laboratory results and imaging investigations. Only diseases responsible for the death were considered as cause/s of death. Finally, cause of death was coded by nurse coordinators according to the international classification of diseases, 10th revision (ICD-10) [19]. We have listed below specific causes of death with the corresponding ICD-10 assigned. Cause of Death List: ICD – 10 code; HIV/AIDS: B20–B24; Tuberculosis: A15–A19, B90; Respiratory infections: J00–J06, J10–J18, J20–J22, H65–H66; Meningitis: A39, G00, G03; Malignant neoplasm: C00–C97; Diabetes Mellitus: E10–E14; Cardiovascular diseases: I00–I99; Hypertension: I10–I13; Stroke: I60–I69; Respiratory diseases: J30–J98; Digestive diseases: K20–K92; Chronic Liver Disease: K70, K74; Peptic Ulcer Disease: K25–K27; Genitourinary Diseases: N00–N64, N75–N98; Unintentional injuries: V01–X59, Y40–Y86, Y88, Y89; Road traffic accidents: V01–V04, V06, V09–V80, V87, V89, V99; Intentional injuries (Suicide…): X60–Y09, Y35–Y36, Y870, Y871. Data were double entered to Access Microsoft office and cleaned using STATA .do files. The 2006 Global Burden of Diseases classification was adapted to classify cause of deaths in our study. This classification categorized diseases into; communicable diseases, non-communicable diseases and all injuries [20]. Verbal Autopsy interview was conducted after obtaining verbal informed consent from the kin or caregiver of the deceased after explaining the purpose and the procedure of the study. Information sheet prepared in English and translated to local language had been provided. Permission for the study had been also obtained from local authorities. Protocol of the program was approved by Institutional Review Board (IRB) of Medical Faculty, Addis Ababa University, and the Ethiopian Science and Technology Agency. Government and institutional officials, religious leaders at each level had been communicated. Individual information was accessible only to the research team and is kept confidential. The validation consisted of a comparison of verbal autopsy final diagnosis with hospital diagnosis taken as a “gold standard”, followed by calculation of their sensitivity, specificity and positive predictive values. The sensitivity of a verbal autopsy for a particular cause of death such as HIV/AIDS is the proportion of the deceased whose verbal autopsy cause of death is correctly identified as HIV/AIDS out of all those who truly died from HIV/AIDS, while the specificity is the proportion whose cause of death is identified as not HIV/AIDS among those who truly did not die from HIV/AIDS [2]. Verbal autopsy and hospital data sets were merged using the variables; deceased full name, sex, address, age, place of death and date of death. First we found 1356 deaths occurred in hospitals which were reported with verbal autopsy during 2007 to 2010 period. We merged this verbal autopsy data set with hospital data (n = 20,152, age 15 years and above). Finally, we found 335 deaths for this analysis. This was basically due to the incompleteness of the hospital records and registry books; and differences with age, addresses, and deceased full name, place of death or date of death during merging that might introduce bias. The number of causes of death could be greater than the number of deceased adults in the verbal autopsy and hospital diagnosis since we used two or more causes of death (multiple causes of death) and treated independently. Sensitivity, specificity and positive predictive value analysis was performed for 3 major categories of diseases; communicable diseases, non communicable diseases and injuries and for each of the major diseases under each category such as HIV/AIDS, tuberculosis, malignant neoplasm, cardiovascular diseases etc. We used chi-squared test to compare proportions between selected verbal autopsy adult deaths, selected hospital adult deaths. Finally, to show the actual causes of death distribution “actual verbal autopsy diagnoses” and for comparison and completeness of this study, cause specific mortality proportion findings of the double mortality burden study included [10]. The current and the former study were from the same study area, data source and study period.

Materials

N/A

Innovations

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

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide pregnant women with access to important health information, appointment reminders, and emergency services. These apps can also facilitate communication between healthcare providers and pregnant women, allowing for remote consultations and monitoring.

2. Telemedicine: Establish telemedicine services that enable pregnant women in remote or underserved areas to consult with healthcare professionals through video calls. This can help overcome geographical barriers and provide timely access to prenatal care and advice.

3. Community Health Workers: Train and deploy community health workers to provide maternal health education, support, and basic healthcare services to pregnant women in rural or marginalized communities. These workers can act as a bridge between the community and formal healthcare system, improving access to care and promoting healthy behaviors.

4. Maternal Health Vouchers: Implement voucher programs that provide pregnant women with financial assistance to access essential maternal health services, such as antenatal care, skilled birth attendance, and postnatal care. These vouchers can be distributed through community health centers or local organizations.

5. Maternal Health Clinics: Establish dedicated maternal health clinics in areas with high maternal mortality rates. These clinics can provide comprehensive prenatal, delivery, and postnatal care services, ensuring that pregnant women receive the specialized care they need.

6. Transportation Support: Develop transportation initiatives that provide pregnant women with affordable and reliable transportation to healthcare facilities. This can include subsidized transportation services, community-based transportation networks, or partnerships with local transportation providers.

7. Maternal Health Education Programs: Implement targeted education programs that focus on improving maternal health knowledge and promoting healthy behaviors among pregnant women and their families. These programs can be delivered through community workshops, mobile apps, or multimedia campaigns.

8. Maternal Health Hotlines: Establish toll-free hotlines staffed by trained healthcare professionals who can provide information, advice, and support to pregnant women. These hotlines can be available 24/7 and offer services in multiple languages to ensure accessibility.

9. Maternal Health Monitoring Systems: Develop and implement digital monitoring systems that track the health status of pregnant women and provide real-time alerts to healthcare providers in case of complications or emergencies. These systems can help identify high-risk pregnancies and ensure timely interventions.

10. Public-Private Partnerships: Foster collaborations between government agencies, healthcare providers, and private sector organizations to improve access to maternal health services. These partnerships can leverage resources, expertise, and technology to expand service coverage and enhance the quality of care.

It is important to note that the specific context and needs of the target population should be considered when implementing these innovations.

AI Innovations Description

The recommendation that can be developed into an innovation to improve access to maternal health based on the described study is to implement a well-structured verbal autopsy method for determining causes of maternal deaths. This method would involve conducting verbal autopsy interviews with caregivers or kin of deceased mothers to gather information about the symptoms and signs preceding death, as well as their medical history and lifestyle practices. The collected data would then be reviewed by qualified physicians to determine the underlying cause of death.

By implementing this verbal autopsy method, policymakers and healthcare providers can obtain cost-effective information about the causes of maternal deaths, which can help guide interventions and policies to improve maternal health outcomes. This method can provide valuable insights into the specific causes of maternal deaths, such as communicable diseases, non-communicable diseases, and injuries, allowing for targeted interventions and prevention strategies.

It is important to note that further validation studies need to be undertaken to ensure the accuracy and reliability of the verbal autopsy method for maternal deaths. Additionally, efforts should be made to address the limitations of using medical records as a “gold standard” for validation, as these records may not always be confirmed using laboratory investigations or medical technologies.

AI Innovations Methodology

Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Strengthening healthcare infrastructure: Investing in the improvement of healthcare facilities, including hospitals, clinics, and maternity centers, can help ensure that pregnant women have access to quality maternal healthcare services.

2. Increasing healthcare workforce: Training and deploying more skilled healthcare professionals, such as doctors, nurses, midwives, and community health workers, can help address the shortage of healthcare providers and improve access to maternal health services.

3. Enhancing transportation systems: Improving transportation infrastructure, such as roads and ambulances, can help overcome geographical barriers and enable pregnant women to reach healthcare facilities in a timely manner.

4. Promoting community-based interventions: Implementing community-based programs, such as mobile clinics, health education campaigns, and community health worker initiatives, can help raise awareness about maternal health and provide essential services closer to where women live.

5. Strengthening referral systems: Establishing effective referral systems between primary healthcare facilities and higher-level hospitals can ensure that pregnant women with complications receive timely and appropriate care.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could be developed as follows:

1. Define indicators: Identify key indicators to measure the impact of the recommendations, such as the number of pregnant women accessing antenatal care, the percentage of deliveries attended by skilled birth attendants, and the maternal mortality rate.

2. Collect baseline data: Gather data on the current status of maternal health access in the target population, including information on healthcare infrastructure, healthcare workforce, transportation systems, and community-based interventions.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on the selected indicators. The model should consider factors such as population size, geographical distribution, and existing healthcare resources.

4. Input data and parameters: Input the baseline data and parameters into the simulation model, including information on the target population, the implementation timeline for the recommendations, and the expected changes in healthcare infrastructure, workforce, transportation systems, and community-based interventions.

5. Run simulations: Run multiple simulations using different scenarios, varying the parameters to assess the potential impact of the recommendations on the selected indicators. This could include scenarios with different levels of investment in healthcare infrastructure, varying numbers of healthcare providers, and different coverage levels of community-based interventions.

6. Analyze results: Analyze the simulation results to determine the potential impact of the recommendations on improving access to maternal health. Assess the changes in the selected indicators and compare them to the baseline data to understand the effectiveness of the proposed interventions.

7. 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 of maternal health. This will help ensure the accuracy and reliability of the simulation results.

8. Communicate findings: Present the findings of the simulation study to relevant stakeholders, including policymakers, healthcare providers, and community leaders. Use the results to advocate for the implementation of the recommended interventions and to guide decision-making processes related to improving access to maternal health.

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

Authors & Co-Authors

Statistics:

Citations: 30

Authors: 4

Identifiers:

DOI: 10.1186/1471-2288-12-130

Research Areas:

Cancer, Community Interventions, Disability, Health System and Policy, Infectious Diseases, Maternal and Child Health, Mental Health, Noncommunicable Diseases, Technology and Innovations, Violence and Injury

Study Countries:

Ethiopia

Study Design:

Cohort Study, Cross Sectional Study

Study Approach:

Quantitative