<b><span style="font-family:Verdana;">Introduction:</span></b><span style="font-family:Verdana;"> Preventable maternal and newborn mortalities still occur in local com...<b><span style="font-family:Verdana;">Introduction:</span></b><span style="font-family:Verdana;"> Preventable maternal and newborn mortalities still occur in local communities in Kenya since access to maternal and newborn healthcare services remains a big challenge. Barriers to access in resource-constrained settings have not been examined adequately in literature. The World Health Organization (WHO) has 6 building blocks for strengthening healthcare systems that informed this study. This paper examines how user-side and institutional factors influence access and use of Maternal and Newborn Healthcare (MNH) Services in Matayos sub-County-Busia County. <b></b></span><b><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"></span></b><b> </b><span style="font-family:Verdana;">A mixed method approach, with an ethnographic inquiry and a descriptive cross-sectional design, was adopted to assess access to MNH services in Matayos-Busia County, Western Kenya. Postpartum women who had delivered within the previous 12 months and health care providers in the study area were recruited as respondents. A total of 348 postpartum women were selected through stratified systematic random sampling for the survey. Purposive sampling was used to select postpartum women, conventional and traditional health care providers for 16 in-depth interviews and 7 focus group discussions. Data were analyzed using descriptive and inferential statistics. Qualitative data analysis was done thematically. <b></b></span><b><b><span style="font-family:Verdana;">Results</span><span style="font-family:Verdana;">:</span></b><span style="font-family:Verdana;"></span></b><span style="font-family:Verdana;"> Institutional delivery was low at 68% and family planning at 75% although demand for services was high at 99%. User-side barriers to access included shared beliefs and practices in the community;high direct transport costs from home;and high costs for missing drugs and other supplies in hospitals. Middle (5</span><sup展开更多
<strong>Introduction:</strong> Improving maternal and newborn survival needs robust data on patterns of morbidity and mortality from well-characterized cohorts. It is equally important for researchers to d...<strong>Introduction:</strong> Improving maternal and newborn survival needs robust data on patterns of morbidity and mortality from well-characterized cohorts. It is equally important for researchers to document and understand the contextual challenges of data collection and how they are addressed. <strong>Methods:</strong> This was a prospective cohort study implemented from December 2012 to August 2014 in Matiari, Pakistan. A total of 11,315 pregnancies were enrolled. Participants were approached at home for sequential data collection through the standard pretested structured questionnaires. Some indicators were sourced through health facility records. Information on field challenges gathered through field diaries and minutes of meetings with field staff. <strong>Results:</strong> Inaccurate reporting of last menstrual period (LMP) dates caused difficulties in the planning and completion of antenatal data collection visits at scheduled gestational weeks. We documented ultrasound reports wherever available, relied on quickening technique, and implemented a seasonal event calendar to help mothers’ recall their LMP. Health system coordinators of public sector and private healthcare providers were individually approached for maximum data collection. But an unregulated private health system with poor record maintenance and health care providers’ reluctance for cooperation posed a greater challenge in data collection. <strong>Conclusions:</strong> Within a broader understanding of the health systems and socio-cultural environment, temporal and spatial feasibility of data collection should be considered thoroughly at the early stages of study designing, planning, resource allocation, and implementation. Pre-defined regular and need-based meetings with each tier of data collection teams and study managers help to reinvigorate field execution plans and optimize both quantity and quality of study data.展开更多
文摘<b><span style="font-family:Verdana;">Introduction:</span></b><span style="font-family:Verdana;"> Preventable maternal and newborn mortalities still occur in local communities in Kenya since access to maternal and newborn healthcare services remains a big challenge. Barriers to access in resource-constrained settings have not been examined adequately in literature. The World Health Organization (WHO) has 6 building blocks for strengthening healthcare systems that informed this study. This paper examines how user-side and institutional factors influence access and use of Maternal and Newborn Healthcare (MNH) Services in Matayos sub-County-Busia County. <b></b></span><b><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"></span></b><b> </b><span style="font-family:Verdana;">A mixed method approach, with an ethnographic inquiry and a descriptive cross-sectional design, was adopted to assess access to MNH services in Matayos-Busia County, Western Kenya. Postpartum women who had delivered within the previous 12 months and health care providers in the study area were recruited as respondents. A total of 348 postpartum women were selected through stratified systematic random sampling for the survey. Purposive sampling was used to select postpartum women, conventional and traditional health care providers for 16 in-depth interviews and 7 focus group discussions. Data were analyzed using descriptive and inferential statistics. Qualitative data analysis was done thematically. <b></b></span><b><b><span style="font-family:Verdana;">Results</span><span style="font-family:Verdana;">:</span></b><span style="font-family:Verdana;"></span></b><span style="font-family:Verdana;"> Institutional delivery was low at 68% and family planning at 75% although demand for services was high at 99%. User-side barriers to access included shared beliefs and practices in the community;high direct transport costs from home;and high costs for missing drugs and other supplies in hospitals. Middle (5</span><sup
文摘<strong>Introduction:</strong> Improving maternal and newborn survival needs robust data on patterns of morbidity and mortality from well-characterized cohorts. It is equally important for researchers to document and understand the contextual challenges of data collection and how they are addressed. <strong>Methods:</strong> This was a prospective cohort study implemented from December 2012 to August 2014 in Matiari, Pakistan. A total of 11,315 pregnancies were enrolled. Participants were approached at home for sequential data collection through the standard pretested structured questionnaires. Some indicators were sourced through health facility records. Information on field challenges gathered through field diaries and minutes of meetings with field staff. <strong>Results:</strong> Inaccurate reporting of last menstrual period (LMP) dates caused difficulties in the planning and completion of antenatal data collection visits at scheduled gestational weeks. We documented ultrasound reports wherever available, relied on quickening technique, and implemented a seasonal event calendar to help mothers’ recall their LMP. Health system coordinators of public sector and private healthcare providers were individually approached for maximum data collection. But an unregulated private health system with poor record maintenance and health care providers’ reluctance for cooperation posed a greater challenge in data collection. <strong>Conclusions:</strong> Within a broader understanding of the health systems and socio-cultural environment, temporal and spatial feasibility of data collection should be considered thoroughly at the early stages of study designing, planning, resource allocation, and implementation. Pre-defined regular and need-based meetings with each tier of data collection teams and study managers help to reinvigorate field execution plans and optimize both quantity and quality of study data.
