Urban-rural difference in satisfaction with primary healthcare services in Ghana

BMC Health Services Research, Volume 17, No. 1, Year 2017

Interpretação

Background: Understanding regional variation in patient satisfaction about healthcare systems (PHCs) on the quality of services provided is instrumental to improving quality and developing a patient-centered healthcare system by making it more responsive especially to the cultural aspects of health demands of a population. Reaching to the innovative National Health Insurance Scheme (NHIS) in Ghana, surpassing several reforms in healthcare financing has been a milestone. However, the focus of NHIS is on the demand side of healthcare delivery. Studies focusing on the supply side of healthcare delivery, particularly the quality of service as perceived by the consumers are required. A growing number of studies have focused on regional differences of patient satisfaction in developed countries, however little research has been conducted concerning patient satisfaction in resource-poor settings like in Ghana. This study was therefore dedicated to examining the variation in satisfaction across rural and urban women in Ghana. Methods: Data for the present study were obtained from the latest demographic and health survey in Ghana (GDHS 2014). Participants were 3576 women aged between 15 and 49 years living in non-institutional settings in Ghana. Summary statistics in percentages was used to present respondents’ demographic, socioeconomic characteristics. Chi-square test was used to find association between urban-rural differentials with socio-economic variables. Multiple logistic regression was performed to measure the association of being satisfied with primary healthcare services with study variables. Model fitness was tested by pseudo R 2. Statistical significance was set at p < 0.05. Results: The findings in this study revealed that about 57.1% were satisfied with primary health care services. The urban and rural areas reported 57.6 and 56.6% respectively which showed no statistically significant difference (z = 0.64; p = 0.523; 95%CI: -0.022, 0.043). Bivariate analysis showed that region, highest level of education, wealth index and type of facility were significantly associated with location of residence (urban-rural areas). After adjusting for confounding variables using logistic regression, geographical location became a key factor of satisfaction with primary healthcare services by location of residence. In urban areas, respondents from Greater Accra had 64% increase in the level of satisfaction when compared to those in Western region (OR = 1.64; 95CI: 1.09-2.47), Upper East had 75% increase in satisfaction compared to Western region (OR = 1.75; 95%CI: 1.08-2.84), Northern had an estimated 44% reduction in satisfaction when compared to Western region (OR = 0.56; 95%CI: 0.34-0.92). However, rural areas in Central, Volta, Eastern, Ashanti, Brong Aghafo, Northern and Upper West region had 51, 81, 69, 46, 62, 75 and 61% reduction respectively in the level of satisfaction when compared to Western region. Conclusions: Patient satisfaction is an important indicator of health outcomes. Quality of care and measuring level of patient satisfaction has been found to be the most useful tool to predict utilization and compliance. In fact, satisfied patients are more likely than unsatisfied ones to continue using health care services. Our results suggest that policymakers need to better understand the determinants of satisfaction with the health system and how different socio-demographic groups perceive satisfaction with healthcare services so as to address health inequalities between urban and rural areas within the same country. Data for the present study were obtained from the latest demographic and health survey in Ghana (GDHS, 2014). The primary objective of the survey was to generate recent reliable information on fertility, family planning, infant and child mortality, maternal and child health, and nutrition. This information will enhance informed policy decisions and will be used for planning, monitoring, and evaluating programs related to reproductive health and health in general. The survey was implemented by the Ghana Statistical Service (GSS), the Ghana Health Service (GHS), and the National Public Health Reference Laboratory (NPHRL) of the GHS as part of the International Demographic and Health Survey program known as MEASURE DHS, which is currently active in 90 countries. The survey was conducted under the auspices of the United States Agency for International Development (USAID) with the technical assistance of ICF International, based in the USA. The Demographic and Health Surveys (DHSs) are free, public datasets, though researchers must register with MEASURE DHS and submit a request before access to DHS data is granted. This data request system ensures that all users understand and agree to basic data usage ethics standards. The survey lasted from early September to mid-December of 2014. Sampling technique involved a two-stage clustering encompassing both urban and rural areas across all ten administrative regions in the country. The first stage involved selecting clusters which are collections of enumeration areas (EAs). A total of 427 clusters were selected (216 in urban areas and 211 in rural areas). In the second stage, households were selected systematically from each EAs. A total of 12,831 households were selected for the survey and 11,835 households were finally interviewed successfully with a response rate of 99%. Further details are provided in the final report of the Ghana DHS 2014 report (GDHS 2014). The explanatory variables of primary interest were economic status, whereas patient satisfaction on various aspects of healthcare services in relation to area of residence (Rural and Urban areas), was entered as a dependent variable. A set of 13 items pertinent to the quality assessment of PHCs were extracted from the GDHS data set. The participants were inquired about their satisfaction on the following components to which they could answer as either YES or NO: 1) Satisfaction with the time to wait for your turn, 2) Satisfaction with the time spent in the consulting/examination room, 3) Satisfaction with the time to wait for tests to be performed, 4) Satisfaction with the time to wait for test results, 5) Satisfaction with the time at pharmacy/dispensary, 6) Satisfaction with staff when they listened to the respondent, 7) Satisfaction with staff when they explained what was wanted, 8) Satisfaction with staff when they gave advice on treatment, 9) Satisfaction with the cleanliness of the facility, 10) Satisfaction with the easiness of finding where to go, 11) Satisfaction with comfort and safety while waiting, 12) Satisfaction with privacy during the examination, 13) Satisfaction with confidentiality and protection of personal information. The scoring procedure involved summing the 13 items measuring satisfaction for a respondent to generate total satisfaction level. The mean was obtained and the variable was dichotomized to “satisfied” if a respondent scored at least the mean or “not satisfied” if a respondent scored below the mean respectively. Several covariates were included based on their relevance to the outcome variable: age (years) of respondents which are grouped in the interval; 15–19, 20–24, 25–29, 30–34, 35–39, 40–44 and 45–49.Geographical regions include; Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East and Upper West. In addition, educational attainment was measured as No education, Primary, Secondary and Higher.The wealth status was measure as: poorest, poorer, middle, richer and richest. Calculation of Wealth status: DHS provide no direct information on personal income; however, DHS employs a special technique to measure household wealth index and classify them into five groups: richest, richer, middle, poorer, and poorest. DHS programs employ wealth index as a proxy indicator for personal income status which is representative of an individual’s ability to afford personal healthcare needs. The process involves assigning wealth scores to household possessions e.g. floor, wall and roof material; type of cooking fuel; access to potable water and sanitation, ownership of radio, TV, refrigerator, motorcycle and others. Scoring is performed by principal components analysis, and based on their weighted wealth scores, households fall into five wealth quintiles ranging from poorest to richest. Measurement of wealth index is explained in detail elsewhere [1]. Educational attainment: Based on total years of completion of formal education, the following categories were used: No education, Primary, Secondary, and Higher. Before each interview, all participants gave informed consent to take part in the survey. The DHS program maintains strict standards for ensuring data anonymity and protecting the privacy of all participants. ICF International ensures that the survey complies with the U.S. Department of Health and Human Services regulations for the protection of human subjects, whilst the host country ensures that the survey complies with local laws and norms. Further approval for this study was not required since the data is secondary and is available in the public domain. More details regarding DHS data and ethical standards are available at: https://dhsprogram.com/What-We-Do/Protecting-the-Privacy-of-DHS-Survey-Respondents.cfm. Summary statistics in percentages was used to present respondents’ demographic and socioeconomic characteristics. Chi-square test was used to find association between urban-rural differentials with socio-economic variables. Multiple logistic regression was performed to measure the association of being satisfied with primary healthcare services with study variables. Model fitness was tested by pseudo R2. Statistical significance was set at 95% confidence interval. Data were analyzed using STATA (StataCorp, College Station, TX, USA) version 12 and SPSS version 21.

AI Digest

Study Justification:

– Understanding regional variation in patient satisfaction about healthcare systems is important for improving quality and developing a patient-centered healthcare system.
– Previous studies have focused on regional differences in patient satisfaction in developed countries, but little research has been conducted in resource-poor settings like Ghana.
– The study aims to examine the variation in satisfaction across rural and urban women in Ghana.

Highlights:

– The study found that about 57.1% of women in Ghana were satisfied with primary healthcare services.
– There was no statistically significant difference in satisfaction between urban and rural areas.
– Factors such as region, education level, wealth index, and type of facility were significantly associated with location of residence.
– Geographical location was found to be a key factor in satisfaction with primary healthcare services.

Recommendations for Lay Reader:

– Patient satisfaction is an important indicator of health outcomes.
– Policymakers need to better understand the determinants of satisfaction with the health system and how different socio-demographic groups perceive satisfaction with healthcare services.
– Addressing health inequalities between urban and rural areas within the same country is crucial.

Recommendations for Policy Maker:

– Further research is needed to explore the factors influencing patient satisfaction in different regions of Ghana.
– Policies should be developed to improve the quality of healthcare services and address the specific needs and preferences of different socio-demographic groups.
– Efforts should be made to reduce health inequalities between urban and rural areas.

Key Role Players:

– Ghana Statistical Service (GSS)
– Ghana Health Service (GHS)
– National Public Health Reference Laboratory (NPHRL)
– United States Agency for International Development (USAID)
– ICF International
– Researchers and healthcare professionals

Cost Items for Planning Recommendations:

– Research funding for further studies on patient satisfaction in different regions of Ghana
– Budget for developing and implementing policies to improve healthcare quality and address health inequalities
– Resources for training healthcare professionals on patient-centered care and cultural sensitivity

Força da prova

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study used data from the latest demographic and health survey in Ghana, which provides a representative sample of the population. The study employed statistical analysis techniques such as chi-square test and logistic regression to examine the association between satisfaction with primary healthcare services and various variables. However, the abstract does not provide information on the specific methodology used to collect the data, such as the survey instrument or sampling technique. Additionally, the abstract does not mention any limitations of the study. To improve the strength of the evidence, the authors could provide more details on the data collection methodology and acknowledge any limitations of the study.

Resumo

Data for the present study were obtained from the latest demographic and health survey in Ghana (GDHS, 2014). The primary objective of the survey was to generate recent reliable information on fertility, family planning, infant and child mortality, maternal and child health, and nutrition. This information will enhance informed policy decisions and will be used for planning, monitoring, and evaluating programs related to reproductive health and health in general. The survey was implemented by the Ghana Statistical Service (GSS), the Ghana Health Service (GHS), and the National Public Health Reference Laboratory (NPHRL) of the GHS as part of the International Demographic and Health Survey program known as MEASURE DHS, which is currently active in 90 countries. The survey was conducted under the auspices of the United States Agency for International Development (USAID) with the technical assistance of ICF International, based in the USA. The Demographic and Health Surveys (DHSs) are free, public datasets, though researchers must register with MEASURE DHS and submit a request before access to DHS data is granted. This data request system ensures that all users understand and agree to basic data usage ethics standards. The survey lasted from early September to mid-December of 2014. Sampling technique involved a two-stage clustering encompassing both urban and rural areas across all ten administrative regions in the country. The first stage involved selecting clusters which are collections of enumeration areas (EAs). A total of 427 clusters were selected (216 in urban areas and 211 in rural areas). In the second stage, households were selected systematically from each EAs. A total of 12,831 households were selected for the survey and 11,835 households were finally interviewed successfully with a response rate of 99%. Further details are provided in the final report of the Ghana DHS 2014 report (GDHS 2014). The explanatory variables of primary interest were economic status, whereas patient satisfaction on various aspects of healthcare services in relation to area of residence (Rural and Urban areas), was entered as a dependent variable. A set of 13 items pertinent to the quality assessment of PHCs were extracted from the GDHS data set. The participants were inquired about their satisfaction on the following components to which they could answer as either YES or NO: 1) Satisfaction with the time to wait for your turn, 2) Satisfaction with the time spent in the consulting/examination room, 3) Satisfaction with the time to wait for tests to be performed, 4) Satisfaction with the time to wait for test results, 5) Satisfaction with the time at pharmacy/dispensary, 6) Satisfaction with staff when they listened to the respondent, 7) Satisfaction with staff when they explained what was wanted, 8) Satisfaction with staff when they gave advice on treatment, 9) Satisfaction with the cleanliness of the facility, 10) Satisfaction with the easiness of finding where to go, 11) Satisfaction with comfort and safety while waiting, 12) Satisfaction with privacy during the examination, 13) Satisfaction with confidentiality and protection of personal information. The scoring procedure involved summing the 13 items measuring satisfaction for a respondent to generate total satisfaction level. The mean was obtained and the variable was dichotomized to “satisfied” if a respondent scored at least the mean or “not satisfied” if a respondent scored below the mean respectively. Several covariates were included based on their relevance to the outcome variable: age (years) of respondents which are grouped in the interval; 15–19, 20–24, 25–29, 30–34, 35–39, 40–44 and 45–49.Geographical regions include; Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East and Upper West. In addition, educational attainment was measured as No education, Primary, Secondary and Higher.The wealth status was measure as: poorest, poorer, middle, richer and richest. Calculation of Wealth status: DHS provide no direct information on personal income; however, DHS employs a special technique to measure household wealth index and classify them into five groups: richest, richer, middle, poorer, and poorest. DHS programs employ wealth index as a proxy indicator for personal income status which is representative of an individual’s ability to afford personal healthcare needs. The process involves assigning wealth scores to household possessions e.g. floor, wall and roof material; type of cooking fuel; access to potable water and sanitation, ownership of radio, TV, refrigerator, motorcycle and others. Scoring is performed by principal components analysis, and based on their weighted wealth scores, households fall into five wealth quintiles ranging from poorest to richest. Measurement of wealth index is explained in detail elsewhere [1]. Educational attainment: Based on total years of completion of formal education, the following categories were used: No education, Primary, Secondary, and Higher. Before each interview, all participants gave informed consent to take part in the survey. The DHS program maintains strict standards for ensuring data anonymity and protecting the privacy of all participants. ICF International ensures that the survey complies with the U.S. Department of Health and Human Services regulations for the protection of human subjects, whilst the host country ensures that the survey complies with local laws and norms. Further approval for this study was not required since the data is secondary and is available in the public domain. More details regarding DHS data and ethical standards are available at: https://dhsprogram.com/What-We-Do/Protecting-the-Privacy-of-DHS-Survey-Respondents.cfm. Summary statistics in percentages was used to present respondents’ demographic and socioeconomic characteristics. Chi-square test was used to find association between urban-rural differentials with socio-economic variables. Multiple logistic regression was performed to measure the association of being satisfied with primary healthcare services with study variables. Model fitness was tested by pseudo R2. Statistical significance was set at 95% confidence interval. Data were analyzed using STATA (StataCorp, College Station, TX, USA) version 12 and SPSS version 21.

Materiais

N/A

Inovações

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

1. Telemedicine: Implementing telemedicine services can help bridge the gap between urban and rural areas by allowing pregnant women in remote locations to access healthcare professionals through virtual consultations. This can provide timely advice, monitoring, and support during pregnancy.

2. Mobile clinics: Setting up mobile clinics that travel to rural areas can bring essential maternal healthcare services closer to women who may have limited access to healthcare facilities. These clinics can provide prenatal care, vaccinations, and other necessary services.

3. Community health workers: Training and deploying community health workers in rural areas can help educate and support pregnant women, provide basic prenatal care, and facilitate referrals to healthcare facilities when needed. These workers can also raise awareness about maternal health issues and promote preventive measures.

4. Health information systems: Developing and implementing digital health information systems can improve the coordination and management of maternal health services. This can help track and monitor pregnant women, ensure timely and appropriate care, and facilitate data-driven decision-making.

5. Public-private partnerships: Collaborating with private healthcare providers can help expand access to maternal health services, especially in underserved areas. Public-private partnerships can leverage the resources and expertise of both sectors to improve the availability and quality of care.

6. Maternal health financing schemes: Exploring innovative financing models, such as microinsurance or community-based health financing, can help make maternal health services more affordable and accessible to women in low-income settings. These schemes can provide financial protection and reduce the financial barriers to accessing care.

7. Maternal health education and awareness campaigns: Implementing targeted education and awareness campaigns can help improve knowledge and understanding of maternal health issues among women and communities. This can empower women to seek timely care, adopt healthy practices, and make informed decisions about their own health and the health of their babies.

It is important to note that the specific context and needs of Ghana should be taken into consideration when implementing these innovations.

AI Innovations Description

The study examined the variation in satisfaction with primary healthcare services across rural and urban women in Ghana. The findings showed that there was no statistically significant difference in satisfaction between urban and rural areas. However, there were regional differences within urban and rural areas.

In urban areas, respondents from Greater Accra had a 64% increase in satisfaction compared to those in the Western region. Similarly, respondents from the Upper East region had a 75% increase in satisfaction compared to the Western region. On the other hand, respondents from the Northern region had a 44% reduction in satisfaction compared to the Western region.

In rural areas, respondents from Central, Volta, Eastern, Ashanti, Brong Ahafo, Northern, and Upper West regions had reductions of 51%, 81%, 69%, 46%, 62%, 75%, and 61% respectively in the level of satisfaction compared to the Western region.

The study suggests that policymakers need to better understand the determinants of satisfaction with the health system and how different socio-demographic groups perceive satisfaction with healthcare services. This understanding can help address health inequalities between urban and rural areas within the same country.

The data for the study was obtained from the latest demographic and health survey in Ghana (GDHS 2014). The survey was implemented by the Ghana Statistical Service (GSS), the Ghana Health Service (GHS), and the National Public Health Reference Laboratory (NPHRL) of the GHS. The survey aimed to generate reliable information on various aspects of reproductive health and health in general. The survey used a two-stage clustering sampling technique to select households from both urban and rural areas across all ten administrative regions in Ghana.

The study used multiple logistic regression analysis to measure the association between satisfaction with primary healthcare services and various study variables. The analysis included demographic and socioeconomic variables such as age, geographical region, educational attainment, and wealth status.

Overall, the study highlights the importance of patient satisfaction as an indicator of health outcomes and the need to address regional differences in satisfaction with healthcare services to improve access to maternal health.

AI Innovations Methodology

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

1. Strengthen primary healthcare services: Focus on improving the quality and accessibility of primary healthcare services, especially in rural areas. This can include training healthcare providers, ensuring availability of essential medicines and equipment, and improving infrastructure.

2. Increase awareness and education: Implement targeted awareness campaigns to educate women and their families about the importance of maternal health and the available healthcare services. This can help overcome cultural barriers and increase utilization of maternal health services.

3. Enhance transportation and referral systems: Develop efficient transportation systems to facilitate access to healthcare facilities, particularly in remote areas. This can involve providing ambulances or other means of transportation for pregnant women in need of emergency care.

4. Strengthen community engagement: Engage local communities, including traditional birth attendants and community health workers, in promoting maternal health and encouraging women to seek timely healthcare services. This can help address cultural beliefs and practices that may hinder access to maternal health services.

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 access to maternal health, such as the number of antenatal care visits, skilled birth attendance, and postnatal care utilization.

2. Collect baseline data: Gather data on the current status of access to maternal health services, including the number of women utilizing these services, geographical distribution, and any existing barriers.

3. Implement interventions: Implement the recommended interventions in selected areas or communities. This could involve improving primary healthcare services, conducting awareness campaigns, and enhancing transportation systems.

4. Monitor and evaluate: Continuously monitor the implementation of interventions and collect data on the indicators identified in step 1. This can be done through surveys, interviews, or health facility records.

5. Analyze data: Analyze the collected data to assess the impact of the interventions on access to maternal health services. Compare the baseline data with the post-intervention data to identify any changes or improvements.

6. Adjust and refine: Based on the findings, make adjustments to the interventions as needed and refine the methodology for future implementation. This iterative process allows for continuous improvement and optimization of the interventions.

By following this methodology, policymakers and healthcare providers can gain insights into the effectiveness of the recommended interventions and make informed decisions to further improve access to maternal health services.

Autor

Dima Health

Statistics:

Citations: 30

Identifiers:

DOI: 10.1186/s12913-017-2745-7

Research Areas:

Disparities, Environmental, Food Security, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Ghana

Study Design:

Cross Sectional Study

Study Approach:

Mixed-methods, Quantitative, Systematic Review

Participants Gender:

Female

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