Quality of and barriers to routine childbirth care signal functions in primary level facilities of Tigray, Northern Ethiopia: Mixed method study

PLoS ONE, Volume 15, No. 6 June, Year 2020

Interpretation

Background Efforts to expand access to institutional delivery alone without quality of care do not guarantee better survival. However, little evidence documents the quality of childbirth care in Ethiopia, which limits our ability to improve quality. Therefore, this study assessed the quality of and barriers to routine childbirth care signal functions during intra-partum and immediate postpartum period. Methods A sequential explanatory mixed method study was conducted among 225 skilled birth attendants who attended 876 recently delivered women in primary level facilities. A multi stage sampling procedure was used for the quantitative phase whilst purposive sampling was used for the qualitative phase. The quantitative survey recruitment occurred in July to August 2018 and in April 2019 for the qualitative key informant interview and Focus Group Discussions (FGD). A validated quantitative tool from a previous validated measurement study was used to collect quantitative data, whereas an interview guide, informed by the literature and quantitative findings, was used to collect the qualitative data. Principal component analysis and a series of univariate and multivariate linear regression analysis were used to analyze the quantitative data. For the qualitative data, verbatim review of the data was iteratively followed by content analysis and triangulation with the quantitative results. Results This study showed that one out of five (20.7%, n = 181) mothers received high quality of care in primary level facilities. Primary hospitals (β = 1.27, 95% CI:0.80,1.84, p = 0.001), facilities which had staff rotation policies (β = 2.19, 95% CI:0.01,4.31, p = 0.019), maternal involvement in care decisions (β = 0.92, 95% CI:0.38,1.47, p = 0.001), facilities with maternal and newborn health quality improvement initiatives (β = 1.58, 95% CI:0.26, 3.43, p = 0.001), compassionate respectful maternity care training (β = 0.08, 95% CI: 0.07,0.88, p = 0.021), client flow for delivery (β = 0.19, 95% CI:-0.34, -0.04, p = 0.012), mentorship (β = 0.02, 95% CI:0.01, 0.78, p = 0.049), and providers’ satisfaction (β = 0.16, 95% CI:0.03, 0.29, p = 0.013) were predictors of quality of care. This is complemented by qualitative research findings that poor quality of care during delivery and immediate postpartum related to: work related burnout, gap between providers’ skill and knowledge, lack of enabling working environment, poor motivation scheme and issues related to retention, poor providers caring behavior, unable translate training into practice, mismatch between number of provider and facility client flow for delivery, and in availability of essential medicine and supplies. A facility based cross-sectional explanatory sequential mixed method study was conducted among recently delivered mothers in primary health care facilities of Tigray regional state, Northern Ethiopia. Tigray is the northern most region of Ethiopia with an estimated total population of 5,247,005 with 21.2% of the population living in urban areas and 50.3% being female [24]. The maternal and new born health care services in the region are provided mainly by emergency obstetric surgeons and obstetricians at hospitals and health centers by midwives, nurses, and health officers. The service is given free of charge in all public health facilities on a seven day per week 24 hours a day basis. As of 2016, in Tigray Region, there were 2 comprehensive specialized hospitals, 15 general hospitals, 23 primary hospitals, 214 health centers, and 718 health posts [25, 26]. a sample size calculation for the quantitative study component among recently delivered mothers was determined by a single population proportion with 95% confidence interval, margin of error (d) of 5% and taking 54.06% prevalence (P) of overall quality of delivery care in Arbaminch, south Ethiopia public health facilities [27]; design effect of 2 and adding 10% for non-response rate. A total of 881 mothers received routine intra-partum and immediate postpartum care signal functions from 40 primary level care facilities. Additionally, a total of 225 skilled birth attendants (SBAs) working in the study facilities at the time of data collection were included. A multi-stage sampling procedure was adopted to select the districts and primary level health facilities from each district. In the first stage, three of the seven zones were selected randomly. In the second stage, nine of the 22 districts were chosen and 6 primary hospitals were randomly selected. Thereafter, all health centers with their respective catchment primary level hospitals were included with the total sample size being distributed over each of the health facilities proportionate to their sample considering average number of deliveries per facility per month. All SBAs in the study were enrolled. Finally, all eligible recently delivered women were chosen by a systematic random method until the required sample size was achieved. A referred mother requiring care at a higher level facility for further management and/or delivered by cesarean section were excluded from this study. Client exit interview tracer indicators for routine childbirth care signal functions (care that should be provided for all mothers and newborns) utilized self-administered questionnaires, facility inventories, and interviews of providers to collect the quantitative data. A 40-item knowledge tests, as well as satisfaction of health workers and facility readiness surveys (i.e., availability of infrastructure; essential medications and commodities; guidelines; staff) were conducted. Tracer indicators for facility readiness were used from the WHO Service Availability and Readiness Assessment (SARA) list, previously reported indices [28]. Twelve data collectors and three supervisors worked as data collection teams. Data collectors had previous research experience and trained for two days. Data for this quantitative study was collected between July to August 2018. We developed semi-structured questionnaires to conduct key informant interviews (KII) and Focus Group Discussions (FGD). Participants for FGDs and KIIs were selected purposively. The key informant participants were medical directors from each of the primary level health facilities, woreda, and regional health bureau maternal and child health experts and unit head of maternity wards. We assumed that these KII could better inform us of barriers to provide childbirth care than other health workers. A total of twelve KIs were conducted. Probing questions were used for a better understanding where necessary. Each participant was interviewed individually at his/her place of work, with interview duration ranging from 20 to 35 minutes by a team of trained data collectors. After training, three researchers from the College of Health Sciences at Mekelle University and Tigray Health Research Institute conducted qualitative data collection from the 9th to 29th of April 2019. The semi-structured interview guide used can be found in S1 Appendix. After the interviews, three FGD were held for SBAs working at intra-partum and immediate postpartum care ranging from 60 to90 minutes. One interviewer and note taker were involved. Skilled birth attendants with clinical work experience of six months and below were excluded from the qualitative study. All interviews and discussions were audio recorded, then transcribed verbatim in Tigrigna (the local dialect) by two independent investigators. A third investigator checked the consistency of the transcripts and verified the transcripts by listening to the tapes again. They were subsequently translated into English prior to analysis. The primary outcome investigated was quality of routine childbirth and immediate postpartum care. It was measured as a continuous variable constructed as a composite variable from the total of 32 standards of quality process of care indicators. The routine intra-partum and immediate postpartum care signal functions used in this study are grounded in validated indicators in the Tigray regional state context. Detail of the measurement and validated tool findings is found in the recent article submitted for publication [29]. Principal component analysis (PCA), the most common technique of creating a single or composite quality index, which is a variable reduction method to obtain a smaller set of uncorrelated variables from a large list of correlated variables, was used. Each component is a linear combination of the observed variables optimally weighted to account for the maximum amount of variance [30]. Therefore, quality measures reflect the minimum standards of routine intra-partum and immediate postpartum care, irrespective of the type of health facilities where the delivery service is performed. According to the PCA, QoC was defined as a binary variable of “low” to “high” on a continuous scale from 0 to 100. If a mother’s review received 75% and above, it was termed as high QoC, and otherwise received low QoC. Details of the PCA tool for measuring QoC is found in S2 Appendix. The providers’ satisfaction variable was classified as “satisfied” (providers scored 75th percentile and above), whereas below the 75th percentile was considered “not satisfied”; facility readiness was categorized as adequately ready at the 75th percentile and above and below was considered inadequately ready). Details of the PCA tool for measuring providers’ satisfaction is found in the S3 Appendix. Knowledge of providers on intra-partum and immediate postpartum care signal functions was determined using a set of 31 multiple choice questions and 9 true or false questions. Each correct answer was valued at one point, and a wrong answer attracted no points. Questions that were not answered were treated as wrong answers. Ultimately, participants were evaluated out of 100, and grouped as either sufficient knowledge (median or higher) or insufficient knowledge (less than median value). First, we entered the data in to EPI data, cleaned and analyzed it using SPSS™ version 21 software. Descriptive statistics were used to summarize the characteristics of delivered mothers, facilities, and providers. Characteristics of the study population were presented with mean and standard deviation for variables with normal distribution. The normality of distribution of quantitative variables was tested by Kolmogorov–Smirnov test. We used linear regression analysis to assess the association between quality of care and explanatory variables. Simple linear regression analyses were conducted and those independent variables with p value of ≤ 0.25 were considered for multiple linear regression with the forward likelihood ratio method. Finally, statistical significance was considered if p < 0.05. Furthermore, an index score of PCA was done after checking the suitability of the data. The correlation coefficient was set at a cut-off point of 0.4 or above. The Kaiser-Meyer-Oklin value, which was used to assess sampling adequacy, was set at a cut-off point of 0.5 [30], while the Bartlett’s test of sphericity was used to support the factorability of the correlation matrix. Furthermore, a scree plot tests and eigenvalue of over 1.0, which represents the total variance explained by a factor, were used to inspect the plotting of each eigenvalue of the factors to find a point at which the shape of the curve changes direction and becomes horizontal. All factors above the break in the plot and/or with eigenvalues over 1.0 were retained for further analysis. Lastly, further analysis was done using the Vari-max method to minimize the number of variables with high loadings on each factor. Two researchers independently reviewed the audio recorded comments line- by- line and then agreed on a set of codes; broadly categorized into those related to the quantitative checklist and codes for other emerging issues. Both researchers then jointly coded all the open-ended comments. In cases where disagreements arose between researchers, further discussion took place until consensus was achieved. The data analysis was carried out in three stages. First, familiarization involving reading and re-reading the transcripts to aid understanding of the data. Second, organizing and coding the data. The coding was determined based on the quantitative results, to aid understanding how the quantitative findings were manifest. The coding was done using Atlas ti™7.5 software. Third, data from each code point were reviewed and summarized to reduce the number of words without losing the content or context of the text and to ensure contents were internally consistent. Then content analysis and triangulation of data were done through a continuous back and forth interpretation of findings. The study protocol was approved by the Institutional Research Review Board of Mekelle University’s College of Health Sciences and Community Services Ethical Review Committee (ERC 1436/2018). Permission was obtained from all relevant authorities in the Tigray Regional Health Bureau and health facilities. Informed consent was obtained from all participants prior to enrollment in the study. Parental or legal guardian consent was obtained for participants who were under 18 years of age. Data collection was conducted confidentially while data was de-identified and de-linked with storage in a secure location.

AI Digest

Study Justification:

– The study aimed to assess the quality of routine childbirth care in primary level facilities in Tigray, Northern Ethiopia.
– The study aimed to identify barriers to providing high-quality childbirth care.
– The study aimed to provide evidence on the current state of childbirth care in Ethiopia and inform efforts to improve quality.

Study Highlights:

– One out of five mothers (20.7%) received high-quality care in primary level facilities.
– Factors associated with higher quality of care included: primary hospitals, staff rotation policies, maternal involvement in care decisions, maternal and newborn health quality improvement initiatives, compassionate respectful maternity care training, client flow for delivery, mentorship, and providers’ satisfaction.
– Barriers to quality care included work-related burnout, gaps in providers’ skills and knowledge, lack of enabling working environment, poor motivation schemes and retention issues, poor providers’ caring behavior, inability to translate training into practice, mismatch between provider numbers and facility client flow, and unavailability of essential medicine and supplies.

Recommendations:

– Improve staffing and rotation policies in primary level facilities.
– Enhance maternal involvement in care decisions.
– Implement maternal and newborn health quality improvement initiatives.
– Provide compassionate respectful maternity care training.
– Improve client flow for delivery.
– Strengthen mentorship programs.
– Address issues related to providers’ satisfaction.
– Address work-related burnout among providers.
– Enhance providers’ skills and knowledge.
– Create enabling working environments.
– Develop effective motivation schemes and retention strategies.
– Improve providers’ caring behavior.
– Ensure translation of training into practice.
– Address mismatch between provider numbers and facility client flow.
– Ensure availability of essential medicine and supplies.

Key Role Players:

– Skilled birth attendants
– Medical directors of primary level health facilities
– Woreda and regional health bureau maternal and child health experts
– Unit heads of maternity wards
– Health facility managers
– Policy makers
– Regional health authorities

Cost Items for Planning Recommendations:

– Staffing and rotation policies: budget for hiring and training additional staff, implementing rotation policies, and ensuring adequate staffing levels.
– Maternal and newborn health quality improvement initiatives: budget for implementing quality improvement programs, training staff, and monitoring progress.
– Compassionate respectful maternity care training: budget for training programs and materials.
– Client flow for delivery: budget for improving facility infrastructure and logistics to accommodate increased client flow.
– Mentorship programs: budget for implementing mentorship programs and providing resources for mentors.
– Providers’ satisfaction: budget for implementing strategies to improve job satisfaction and address providers’ concerns.
– Work-related burnout: budget for implementing interventions to reduce burnout, such as counseling services and stress management programs.
– Providers’ skills and knowledge: budget for training programs and continuing education opportunities.
– Enabling working environments: budget for improving facility infrastructure, equipment, and supplies.
– Motivation schemes and retention strategies: budget for implementing incentive programs and addressing retention challenges.
– Providers’ caring behavior: budget for training programs and workshops on communication and empathy.
– Translation of training into practice: budget for monitoring and evaluation activities to ensure training is effectively implemented.
– Mismatch between provider numbers and facility client flow: budget for hiring additional staff and improving facility infrastructure.
– Availability of essential medicine and supplies: budget for procurement and distribution of essential items.
Please note that the above cost items are general categories and the actual cost will depend on the specific context and requirements of the recommendations.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a mixed method study conducted among skilled birth attendants and recently delivered women in primary level facilities in Tigray, Northern Ethiopia. The study used a multi-stage sampling procedure and collected both quantitative and qualitative data. The quantitative data was analyzed using statistical methods such as principal component analysis and linear regression analysis. The qualitative data was analyzed using content analysis. The study found that one out of five mothers received high quality of care in primary level facilities, and identified several predictors of quality of care. The abstract provides a detailed description of the study design, data collection methods, and analysis techniques used. However, it does not provide information on the limitations of the study or potential biases. To improve the evidence, the abstract could include a discussion of the limitations and potential biases, as well as recommendations for future research.

Abstract

A facility based cross-sectional explanatory sequential mixed method study was conducted among recently delivered mothers in primary health care facilities of Tigray regional state, Northern Ethiopia. Tigray is the northern most region of Ethiopia with an estimated total population of 5,247,005 with 21.2% of the population living in urban areas and 50.3% being female [24]. The maternal and new born health care services in the region are provided mainly by emergency obstetric surgeons and obstetricians at hospitals and health centers by midwives, nurses, and health officers. The service is given free of charge in all public health facilities on a seven day per week 24 hours a day basis. As of 2016, in Tigray Region, there were 2 comprehensive specialized hospitals, 15 general hospitals, 23 primary hospitals, 214 health centers, and 718 health posts [25, 26]. a sample size calculation for the quantitative study component among recently delivered mothers was determined by a single population proportion with 95% confidence interval, margin of error (d) of 5% and taking 54.06% prevalence (P) of overall quality of delivery care in Arbaminch, south Ethiopia public health facilities [27]; design effect of 2 and adding 10% for non-response rate. A total of 881 mothers received routine intra-partum and immediate postpartum care signal functions from 40 primary level care facilities. Additionally, a total of 225 skilled birth attendants (SBAs) working in the study facilities at the time of data collection were included. A multi-stage sampling procedure was adopted to select the districts and primary level health facilities from each district. In the first stage, three of the seven zones were selected randomly. In the second stage, nine of the 22 districts were chosen and 6 primary hospitals were randomly selected. Thereafter, all health centers with their respective catchment primary level hospitals were included with the total sample size being distributed over each of the health facilities proportionate to their sample considering average number of deliveries per facility per month. All SBAs in the study were enrolled. Finally, all eligible recently delivered women were chosen by a systematic random method until the required sample size was achieved. A referred mother requiring care at a higher level facility for further management and/or delivered by cesarean section were excluded from this study. Client exit interview tracer indicators for routine childbirth care signal functions (care that should be provided for all mothers and newborns) utilized self-administered questionnaires, facility inventories, and interviews of providers to collect the quantitative data. A 40-item knowledge tests, as well as satisfaction of health workers and facility readiness surveys (i.e., availability of infrastructure; essential medications and commodities; guidelines; staff) were conducted. Tracer indicators for facility readiness were used from the WHO Service Availability and Readiness Assessment (SARA) list, previously reported indices [28]. Twelve data collectors and three supervisors worked as data collection teams. Data collectors had previous research experience and trained for two days. Data for this quantitative study was collected between July to August 2018. We developed semi-structured questionnaires to conduct key informant interviews (KII) and Focus Group Discussions (FGD). Participants for FGDs and KIIs were selected purposively. The key informant participants were medical directors from each of the primary level health facilities, woreda, and regional health bureau maternal and child health experts and unit head of maternity wards. We assumed that these KII could better inform us of barriers to provide childbirth care than other health workers. A total of twelve KIs were conducted. Probing questions were used for a better understanding where necessary. Each participant was interviewed individually at his/her place of work, with interview duration ranging from 20 to 35 minutes by a team of trained data collectors. After training, three researchers from the College of Health Sciences at Mekelle University and Tigray Health Research Institute conducted qualitative data collection from the 9th to 29th of April 2019. The semi-structured interview guide used can be found in S1 Appendix. After the interviews, three FGD were held for SBAs working at intra-partum and immediate postpartum care ranging from 60 to90 minutes. One interviewer and note taker were involved. Skilled birth attendants with clinical work experience of six months and below were excluded from the qualitative study. All interviews and discussions were audio recorded, then transcribed verbatim in Tigrigna (the local dialect) by two independent investigators. A third investigator checked the consistency of the transcripts and verified the transcripts by listening to the tapes again. They were subsequently translated into English prior to analysis. The primary outcome investigated was quality of routine childbirth and immediate postpartum care. It was measured as a continuous variable constructed as a composite variable from the total of 32 standards of quality process of care indicators. The routine intra-partum and immediate postpartum care signal functions used in this study are grounded in validated indicators in the Tigray regional state context. Detail of the measurement and validated tool findings is found in the recent article submitted for publication [29]. Principal component analysis (PCA), the most common technique of creating a single or composite quality index, which is a variable reduction method to obtain a smaller set of uncorrelated variables from a large list of correlated variables, was used. Each component is a linear combination of the observed variables optimally weighted to account for the maximum amount of variance [30]. Therefore, quality measures reflect the minimum standards of routine intra-partum and immediate postpartum care, irrespective of the type of health facilities where the delivery service is performed. According to the PCA, QoC was defined as a binary variable of “low” to “high” on a continuous scale from 0 to 100. If a mother’s review received 75% and above, it was termed as high QoC, and otherwise received low QoC. Details of the PCA tool for measuring QoC is found in S2 Appendix. The providers’ satisfaction variable was classified as “satisfied” (providers scored 75th percentile and above), whereas below the 75th percentile was considered “not satisfied”; facility readiness was categorized as adequately ready at the 75th percentile and above and below was considered inadequately ready). Details of the PCA tool for measuring providers’ satisfaction is found in the S3 Appendix. Knowledge of providers on intra-partum and immediate postpartum care signal functions was determined using a set of 31 multiple choice questions and 9 true or false questions. Each correct answer was valued at one point, and a wrong answer attracted no points. Questions that were not answered were treated as wrong answers. Ultimately, participants were evaluated out of 100, and grouped as either sufficient knowledge (median or higher) or insufficient knowledge (less than median value). First, we entered the data in to EPI data, cleaned and analyzed it using SPSS™ version 21 software. Descriptive statistics were used to summarize the characteristics of delivered mothers, facilities, and providers. Characteristics of the study population were presented with mean and standard deviation for variables with normal distribution. The normality of distribution of quantitative variables was tested by Kolmogorov–Smirnov test. We used linear regression analysis to assess the association between quality of care and explanatory variables. Simple linear regression analyses were conducted and those independent variables with p value of ≤ 0.25 were considered for multiple linear regression with the forward likelihood ratio method. Finally, statistical significance was considered if p < 0.05. Furthermore, an index score of PCA was done after checking the suitability of the data. The correlation coefficient was set at a cut-off point of 0.4 or above. The Kaiser-Meyer-Oklin value, which was used to assess sampling adequacy, was set at a cut-off point of 0.5 [30], while the Bartlett’s test of sphericity was used to support the factorability of the correlation matrix. Furthermore, a scree plot tests and eigenvalue of over 1.0, which represents the total variance explained by a factor, were used to inspect the plotting of each eigenvalue of the factors to find a point at which the shape of the curve changes direction and becomes horizontal. All factors above the break in the plot and/or with eigenvalues over 1.0 were retained for further analysis. Lastly, further analysis was done using the Vari-max method to minimize the number of variables with high loadings on each factor. Two researchers independently reviewed the audio recorded comments line- by- line and then agreed on a set of codes; broadly categorized into those related to the quantitative checklist and codes for other emerging issues. Both researchers then jointly coded all the open-ended comments. In cases where disagreements arose between researchers, further discussion took place until consensus was achieved. The data analysis was carried out in three stages. First, familiarization involving reading and re-reading the transcripts to aid understanding of the data. Second, organizing and coding the data. The coding was determined based on the quantitative results, to aid understanding how the quantitative findings were manifest. The coding was done using Atlas ti™7.5 software. Third, data from each code point were reviewed and summarized to reduce the number of words without losing the content or context of the text and to ensure contents were internally consistent. Then content analysis and triangulation of data were done through a continuous back and forth interpretation of findings. The study protocol was approved by the Institutional Research Review Board of Mekelle University’s College of Health Sciences and Community Services Ethical Review Committee (ERC 1436/2018). Permission was obtained from all relevant authorities in the Tigray Regional Health Bureau and health facilities. Informed consent was obtained from all participants prior to enrollment in the study. Parental or legal guardian consent was obtained for participants who were under 18 years of age. Data collection was conducted confidentially while data was de-identified and de-linked with storage in a secure location.

Materials

Innovations

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

1. Telemedicine: Implementing telemedicine services can improve access to maternal health by allowing pregnant women in remote or underserved areas to consult with healthcare providers through video calls or phone calls. This can help address the issue of limited access to healthcare facilities.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information and guidance on maternal health can empower pregnant women to take control of their own health. These apps can provide educational resources, appointment reminders, and access to healthcare professionals for consultations.

3. Community health workers: Training and deploying community health workers who can provide basic maternal health services and education in rural or underserved areas can help bridge the gap in access to healthcare facilities. These workers can conduct antenatal visits, provide health education, and refer women to higher-level facilities when necessary.

4. Transportation solutions: Improving transportation infrastructure and implementing transportation solutions specifically for pregnant women can help overcome geographical barriers to accessing maternal health services. This can include providing ambulances or other means of transportation for pregnant women in remote areas to reach healthcare facilities in a timely manner.

5. Public-private partnerships: Collaborating with private healthcare providers to expand access to maternal health services can help alleviate the burden on public healthcare facilities. This can involve contracting private providers to offer services in underserved areas or subsidizing the cost of services for low-income women.

6. Task-shifting and training: Training healthcare workers at primary level facilities to provide comprehensive maternal health services, including emergency obstetric care, can improve access to life-saving interventions. This can help address the issue of limited availability of skilled birth attendants in certain areas.

7. Supply chain management: Implementing efficient supply chain management systems to ensure the availability of essential medicines, equipment, and supplies for maternal health services is crucial for improving access. This can involve using technology to track inventory, forecast demand, and streamline distribution.

8. Quality improvement initiatives: Implementing quality improvement initiatives, such as regular monitoring and evaluation of maternal health services, can help identify and address gaps in care. This can lead to improved quality of care and better outcomes for pregnant women.

It is important to note that the specific recommendations for improving access to maternal health should be based on a thorough analysis of the local context, including the healthcare infrastructure, resources, and cultural factors.

AI Innovations Description

Based on the description provided, the following recommendation can be developed into an innovation to improve access to maternal health:

1. Implement quality improvement initiatives: The study found that facilities with maternal and newborn health quality improvement initiatives were predictors of high-quality care. Therefore, implementing quality improvement initiatives in primary level facilities can help improve access to maternal health by ensuring that the care provided meets the necessary standards.

2. Provide compassionate respectful maternity care training: The study identified compassionate respectful maternity care training as a predictor of quality of care. Therefore, providing training to healthcare providers on how to provide compassionate and respectful care to mothers during childbirth can improve access to maternal health by creating a positive and supportive environment for mothers.

3. Improve client flow for delivery: The study found that client flow for delivery was a predictor of quality of care. Improving client flow by ensuring efficient and timely delivery services can help improve access to maternal health by reducing waiting times and ensuring that mothers receive the care they need in a timely manner.

4. Enhance provider satisfaction: The study found that provider satisfaction was a predictor of quality of care. Therefore, efforts should be made to enhance provider satisfaction by addressing issues related to work-related burnout, motivation, and retention. This can improve access to maternal health by ensuring that healthcare providers are motivated and satisfied in their work, leading to better quality care for mothers.

5. Address barriers related to knowledge and skills: The study identified gaps between providers’ skills and knowledge as a barrier to quality care. Addressing these gaps through training and continuous professional development can improve access to maternal health by ensuring that healthcare providers have the necessary knowledge and skills to provide high-quality care.

6. Improve availability of essential medicine and supplies: The study identified the unavailability of essential medicine and supplies as a barrier to quality care. Ensuring the availability of essential medicine and supplies in primary level facilities can improve access to maternal health by ensuring that mothers have access to the necessary resources for safe and effective childbirth.

By implementing these recommendations, it is possible to develop innovative solutions that can improve access to maternal health in the context of Tigray, Northern Ethiopia.

AI Innovations Methodology

Based on the provided description, here are some potential recommendations for improving access to maternal health:

1. Strengthening staff rotation policies: Facilities that had staff rotation policies were found to be predictors of quality of care. Implementing and enforcing staff rotation policies can help ensure that skilled birth attendants are regularly rotated to different facilities, reducing burnout and improving the quality of care.

2. Enhancing maternal involvement in care decisions: Facilities that involved mothers in care decisions were found to be predictors of quality of care. Promoting shared decision-making between healthcare providers and mothers can improve the overall experience and quality of care during childbirth.

3. Implementing maternal and newborn health quality improvement initiatives: Facilities with quality improvement initiatives specifically focused on maternal and newborn health were found to be predictors of quality of care. Investing in and implementing evidence-based quality improvement initiatives can help improve the overall quality of care provided during childbirth.

4. Providing compassionate respectful maternity care training: Facilities that provided training on compassionate respectful maternity care were found to be predictors of quality of care. Offering training programs that emphasize compassionate and respectful care can improve the overall experience and satisfaction of mothers during childbirth.

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 specific indicators that will be used to measure the impact of the recommendations. For example, indicators could include the percentage of mothers receiving high-quality care, the level of maternal involvement in care decisions, and the satisfaction of healthcare providers.

2. Collect baseline data: Gather baseline data on the current state of access to maternal health and the quality of care provided. This can be done through surveys, interviews, and facility assessments.

3. Implement the recommendations: Introduce the recommended interventions and initiatives in selected primary level facilities. This may involve training programs, policy changes, and infrastructure improvements.

4. Monitor and evaluate: Continuously monitor and evaluate the implementation of the recommendations. Collect data on the indicators identified in step 1 to assess the impact of the interventions on improving access to maternal health.

5. Analyze the data: Use statistical analysis techniques to analyze the collected data and determine the impact of the recommendations on the identified indicators. This may involve comparing pre- and post-intervention data, conducting regression analyses, and assessing statistical significance.

6. Interpret the results: Interpret the findings of the data analysis to understand the effectiveness of the recommendations in improving access to maternal health. Identify any challenges or barriers that may have affected the outcomes.

7. Adjust and refine: Based on the results and interpretation, make any necessary adjustments or refinements to the recommendations. This may involve scaling up successful interventions, addressing identified barriers, and modifying strategies as needed.

8. Repeat the process: Continuously repeat the monitoring, evaluation, and adjustment process to ensure ongoing improvement in access to maternal health. Regularly collect data, analyze the results, and make informed decisions based on the findings.

By following this methodology, it is possible to simulate the impact of the recommendations on improving access to maternal health and make evidence-based decisions to further enhance maternal healthcare services.

Authors & Co-Authors

Statistics:

Citations: 7

Authors: 5

Identifiers:

DOI: 10.1371/journal.pone.0234318

Research Areas:

Community Interventions, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Social Determinants, Workforce

Study Countries:

Ethiopia

Study Design:

Cross Sectional Study, Descriptive Study, Grounded Theory

Study Approach:

Mixed-methods, Qualitative, Quantitative

Participants Gender:

Female