Assessing women’s satisfaction with family planning services in Mozambique

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Study Justification:
– The contraceptive prevalence rate in Mozambique is low at 11.3%.
– Family planning has a significant impact on women’s health and reducing maternal mortality.
– User satisfaction is important for the utilization of health services.
– Assessing women’s satisfaction with family planning services can help identify issues and improve service utilization.
Study Highlights:
– The study was conducted in 174 health facilities across all provinces in Mozambique.
– Overall, 86% of respondents were satisfied with family planning services.
– Insufficient supplies of oral contraceptives and low quality of healthcare provider/client interactions were identified as reasons for dissatisfaction.
Study Recommendations:
– Take defined actions at the level of health service provision to address the identified issues.
– Ensure improved satisfaction with and better utilization of family planning services in Mozambique.
Key Role Players:
– Health service providers
– Ministry of Health officials
– Community health workers
– Non-governmental organizations (NGOs)
– Women’s advocacy groups
Cost Items for Planning Recommendations:
– Training and capacity building for healthcare providers
– Procurement and distribution of sufficient supplies of oral contraceptives
– Improvement of healthcare provider/client interactions through training and support
– Information and education campaigns on family planning
– Monitoring and evaluation of service quality and user satisfaction

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because the study was conducted in a representative sample of 174 health facilities across all provinces in Mozambique. The study used exit interviews to assess women’s satisfaction with family planning services, and the results showed that 86% of respondents were satisfied. The study also identified specific issues such as insufficient supplies of oral contraceptives and low quality of healthcare provider/client interactions as reasons for women’s dissatisfaction. The conclusion suggests that defined actions at the level of health service provision are needed to address these issues and improve satisfaction with family planning services in Mozambique. To improve the evidence, it would be helpful to provide more details about the methodology used in the study, such as the sampling technique and data collection process. Additionally, including information about the sample size and demographic characteristics of the respondents would further strengthen the evidence.

Background The contraceptive prevalence rate in Mozambique was estimated as 11.3% in the last Demographic and Health Survey. The impact of family planning (FP) on women’s health and on the reduction of maternal mortality is well known. Methods Acknowledging the importance of user satisfaction in the utilisation of health services, exit interviews were used to assess women’s satisfaction with FP services in Mozambique. The survey, conducted in 174 health facilities, was representative at the national level, covered all provinces, and both urban and rural areas. Results Overall, 86% of respondents were satisfied with FP services, but issues such as insufficient supplies of oral contraceptives and the low quality of healthcare provider/client interactions were given as reasons for women’s dissatisfaction. Conclusion Defined actions at the level of health service provision are needed to tackle the identified issues and ensure improved satisfaction with, and better utilisation of, FP services in Mozambique.

This study was conducted in public primary level health facilities in both urban and rural areas across 11 provinces throughout the country. In 2011, Mozambique had a total of 1386 healthcare facilities, of which 1338 offered FP services on a regular basis. The sample of health facilities was drawn from all facilities that routinely offered FP services. A representative sample was selected, stratified by province and type of health facility. The health facilities were divided into four groups: ‘Class 1’ – District Hospitals, ‘Class 2’ – Health Centers Type I, ‘Class 3’ – Health Centers Type II and ‘Class 4’ – Health Posts. Of the total eligible health facilities, all 23 facilities from Class I were included and 151 facilities were selected from the remaining 1315 facilities, producing a final sample size of 174 health facilities. According to the relative weighting of the different types of health facilities providing FP services in each province, the total sample size was proportionally allocated in each of the 11 provinces. Class 2, 3 and 4 health facilities were randomly selected within each province. Women were sampled by selecting users who had left or were about to leave the FP service site on the interview day. The estimated number of women selected and interviewed in each facility was calculated according to the average number of clients seen in the last 7 days. The women to be interviewed were selected systematically by selecting every mth woman who was about to leave the FP services, where ‘m’ was based on the average number of consultations per day over the previous 7 days. A questionnaire was adapted from one used by the United Nations Population Fund and pre-tested locally. Data collectors were selected from maternal and child health nurses and trained in the use of the tool and data collection techniques. The data collection occurred in December 2011. A database was created using the Statistical Package for the Social Sciences (SPSS) V.17.0 (SPSS Inc., Chicago, IL, USA); this software was used for data entry. Ethical approval for the study was granted by the National Health Ethical Committee of Mozambique. To measure women’s satisfaction a composite variable ‘general satisfaction’, with an ordinal scale, was constructed by summing the ratings of the following three questions: (1) Did the woman feel well treated by the health provider? (2) Was the woman satisfied with the overall services and care in this health facility? (3) In the woman’s opinion, besides the nurse or doctor, did the other staff treat her well? These questions were rated as follows: −1 if No, 0 if failed to answer, and 1 if Yes. If the sum resulted in a negative value, then the user was considered to be ‘dissatisfied’ (No), between 0 and 1 as ‘somewhat satisfied’ and above 1 as ‘satisfied’ (Yes). Satisfaction was then analysed against the client and facility factors such as type of healthcare facility, the woman’s age, quality of provider/client interaction, user’s occupation, access to information on FP, duration of using contraceptive method, and waiting time at the health facility. The quality of provider/client interaction was a composite variable obtained by summing 10 different questions which were all binary coded. The resulting values were categorised into low (0–3), medium (4–6) and high quality of interaction (7–10) based on the number of positive answers. Although ordinary baseline logistic models can be applied to an analysis of the probability of categorical outcomes, they are not appropriate for ordinal outcomes such as satisfaction since they ignore the natural order of the categories or levels of the variable, resulting in a considerable loss of statistical power. Walker and Duncan,15 and later McCullagh,16 proposed the use of proportional odds models for the analysis of ordinal outcomes. A multiple logistic regression using a proportional odds assumption was applied to assess the effect of the covariates on general satisfaction (Table 3). Probabilities were summed from No to Yes across the satisfaction scale. We tested the proportional odds assumption using a Score test, which failed to reject it at the 5% significance level. Odds ratio estimates for the general dissatisfaction of family planning service users in Mozambique CI, confidence interval; OR, odds ratio; Ref., reference; STI, sexually transmitted infection. In this model, cumulative probabilities are expressed as functions of the explanatory variables. One key assumption of this model is that the regression coefficients or odds ratios (ORs) are identical for each of the k (k=1, 2, 3) cumulative probabilities, hence the name ‘proportional odds model’. The model for the kth category can be expressed as follows, for k=1, 2, where y represents the outcome variable (satisfaction) with three levels; αk represents the intercept term, which is ordered to reflect the order of the cumulative probabilities, x is a matrix containing the covariates or factors, and β is a parameter vector containing regression coefficients associated with the covariates in x. In this model, an OR can be obtained by exponentiation of the estimates in the vector β. This model was fitted using Statistical Analysis System (SAS) V.9.2.

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

1. Increase the availability of oral contraceptives: Address the issue of insufficient supplies of oral contraceptives by implementing a system to ensure a consistent and reliable supply of contraceptives in health facilities.

2. Improve the quality of healthcare provider/client interactions: Develop training programs for healthcare providers to enhance their communication and interpersonal skills when interacting with women seeking family planning services. This can help create a more supportive and respectful environment for women.

3. Strengthen health service provision: Implement measures to address the identified issues and ensure improved satisfaction with and better utilization of family planning services. This could involve improving infrastructure, staffing, and overall quality of care in health facilities.

4. Increase access to information on family planning: Develop and implement comprehensive information campaigns to increase awareness and knowledge about family planning methods, benefits, and available services. This can help empower women to make informed decisions about their reproductive health.

5. Reduce waiting time at health facilities: Explore strategies to streamline service delivery and reduce waiting times for women seeking family planning services. This could involve optimizing appointment scheduling systems, improving workflow processes, and increasing staffing levels.

These innovations aim to address the specific challenges identified in the study and improve access to maternal health services in Mozambique.
AI Innovations Description
The recommendation that can be developed into an innovation to improve access to maternal health based on the study “Assessing women’s satisfaction with family planning services in Mozambique” is to address the identified issues and ensure improved satisfaction with, and better utilization of, family planning (FP) services in Mozambique.

To achieve this, the following actions can be taken:

1. Increase the availability of oral contraceptives: Address the issue of insufficient supplies of oral contraceptives by ensuring a consistent and adequate supply of contraceptives in health facilities. This can be done through improved procurement and distribution systems.

2. Enhance healthcare provider/client interactions: Improve the quality of interactions between healthcare providers and clients by providing training and support to healthcare providers. This can include communication skills training, empathy training, and promoting client-centered care.

3. Strengthen health service provision: Take actions to improve the overall quality of healthcare services provided in health facilities. This can involve regular monitoring and evaluation of service delivery, ensuring adherence to clinical guidelines, and addressing any gaps or deficiencies in service provision.

4. Increase access to information on family planning: Improve access to information on family planning by providing education and awareness campaigns targeting women and communities. This can include providing accurate and comprehensive information on contraceptive methods, their benefits, and potential side effects.

5. Reduce waiting time at health facilities: Address the issue of long waiting times at health facilities by implementing strategies to improve efficiency and reduce waiting times. This can involve streamlining processes, optimizing appointment systems, and ensuring adequate staffing levels.

By implementing these recommendations, it is expected that access to maternal health services, particularly family planning services, will be improved in Mozambique. This can lead to better health outcomes for women, reduced maternal mortality, and improved overall reproductive health in the country.
AI Innovations Methodology
The study titled “Assessing women’s satisfaction with family planning services in Mozambique” aimed to evaluate women’s satisfaction with family planning (FP) services in Mozambique and identify areas for improvement. The methodology used in the study involved conducting exit interviews with women who had utilized FP services in 174 health facilities across urban and rural areas in Mozambique.

Here is a brief description of the methodology used in the study:

1. Sample selection: The sample of health facilities was drawn from all facilities that regularly offered FP services in Mozambique. The facilities were divided into four groups based on their classification. A representative sample was selected, stratified by province and type of health facility.

2. Participant selection: Women who had left or were about to leave the FP service site on the interview day were selected as participants. The number of women selected and interviewed in each facility was calculated based on the average number of clients seen in the last 7 days.

3. Data collection: A questionnaire adapted from the United Nations Population Fund was used to collect data on women’s satisfaction with FP services. Data collectors, trained in the use of the tool and data collection techniques, conducted the interviews. The data collection occurred in December 2011.

4. Data analysis: A composite variable called “general satisfaction” was constructed by summing the ratings of three questions related to women’s satisfaction with the health provider, overall services and care, and treatment by other staff. Satisfaction was categorized as “dissatisfied,” “somewhat satisfied,” or “satisfied.” Multiple logistic regression using a proportional odds assumption was applied to assess the effect of various factors on general satisfaction.

5. Statistical analysis: The proportional odds model was used to analyze the ordinal outcome of satisfaction. This model assumes that the regression coefficients or odds ratios are identical for each level of satisfaction. The model was fitted using the Statistical Analysis System (SAS) software.

The study found that overall, 86% of respondents were satisfied with FP services in Mozambique. However, issues such as insufficient supplies of oral contraceptives and low-quality healthcare provider/client interactions were identified as reasons for women’s dissatisfaction. The study recommended defined actions at the level of health service provision to address these issues and improve satisfaction with and utilization of FP services in Mozambique.

In summary, the methodology used in the study involved selecting a representative sample of health facilities, conducting exit interviews with women who had utilized FP services, analyzing the data using a proportional odds model, and identifying areas for improvement in FP services based on women’s satisfaction.

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