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Families in high mortality settings need regular contact with high quality services, but existing population-based measurements of contacts do not reflect quality. To address this, in 2012, we designed linked household and frontline worker surveys for Gombe State, Nigeria, Ethiopia, and Uttar Pradesh, India. Using reported frequency and content of contacts, we present a method for estimating the population level coverage of high quality contacts. Methods and Findings Linked cluster-based household and frontline health worker surveys were performed. Interviews were conducted in 40, 80 and 80 clusters in Gombe, Ethiopia, and Uttar Pradesh, respectively, including 348, 533, and 604 eligible women and 20, 76, and 55 skilled birth attendants. High quality contacts were defined as contacts during which recommended set of processes for routine health care were met. In Gombe, 61% (95% confidence interval 50- 72) of women had at least one antenatal contact, 22% (14-29) delivered with a skilled birth attendant, 7% (4-9) had a post-partum check and 4% (2-8) of newborns had a post-natal check. Coverage of high quality contacts was reduced to 11% (6-16), 8% (5-11), 0%, and 0% respectively. In Ethiopia, 56% (49-63) had at least one antenatal contact, 15% (11-22) delivered with a skilled birth attendant, 3% (2-6) had a post-partum check and 4% (2-6) of newborns had a post-natal check. Coverage of high quality contacts was 4% (2-6), 4% (2- 6), 0%, and 0%, respectively. In Uttar Pradesh 74% (69-79) had at least one antenatal contact, 76% (71-80) delivered with a skilled birth attendant, 54% (48-59) had a post-partum check and 19% (15-23) of newborns had a post-natal check. Coverage of high quality contacts was 6% (4-8), 4% (2-6), 0%, and 0% respectively. Conclusions Measuring content of care to reflect the quality of contacts can reveal missed opportunities to deliver best possible health care.
This study was performed in Gombe State of north east Nigeria, the regions of Oromia, Tigray, Amhara and Southern Nations Nationalities and Peoples (SNNP) in Ethiopia, and in six districts (Jhansi, Hardoi, CSM Nagar, Maharanjganj, Sultanpur, Raebarailly) in the state of Uttar Pradesh in India. These three geographies are settings where the Bill & Melinda Gates Foundation funds community based demand and supply side innovations to improve outcomes for mothers and newborns.[16] While these study areas are geographically diverse they each represent predominantly rural settings with high fertility and high maternal and newborn mortality (Table 2). 1 Nigerian Bureau of Statistics, Nigeria: Social Statistics of Nigeria, 2012 2 IDEAS baseline survey 3 The National Literacy Survey, June 2010, National Bureau of Statistics, Nigeria. www.nigerianstat.gov.ng 4 Nigerian Demographic and Health Survey preliminary report, 2013 http://dhsprogram.com/pubs/pdf/PR41/PR41.pdf 5 UNICEF (2011) Country factsheets. www.unicef.org/infobycountry/ethiopia_statistics.html 6 Indian population Census 2011, www.census2011.co.in/census/state/uttarpradesh.html 7 http://www.unicef.org/nigeria/ng_publications_advocacybrochure.pdf [for north east Nigeria as a whole] 8 United Nations Maternal Mortality Estimation Inter-agency group http://www.maternalmortalitydata.org/ 9 Annual health survey bulletin 2011–12: Uttar Pradesh. http://www.censusindia.gov.in/vital_statistics/AHSBulletins/files2012/Uttar%20Pradesh_Bulletin%202011-12.pdf 10 Population Reference Bureau at http://www.un.org/esa/population/meetings/EGM-Fertility2009/Haub.pdf 11Annual Abstract of Statistics 2011, National Bureau of Statistics, Nigeria. In each of these study settings, baseline surveys were carried out in 2012 as part of an ongoing study to investigate the extent to which innovations that were intended to enhance contacts between families and frontline workers (community based volunteers for maternal and newborn health, and health staff at primary level health facilities) lead to an increase in the coverage of life-saving interventions; follow-up data collection in the same settings is planned for 2015. The study combined a cluster based household survey with a survey of the frontline health workers and facilities (health posts and primary health facilities) assigned to provide routine maternal and newborn health services to those households before implementation of the innovations. These baseline data are presented here. Gombe State has 11 local government areas, and population statistics are available from the National Population Commission for enumeration areas throughout the State. The baseline survey included 40 clusters selected from 10 of the 11 local government areas in Gombe State (excluding Gombe Town). Clusters were defined as segmented enumeration areas. Cluster sampling was performed by listing all enumeration areas within the 10 local government areas, cumulating their population size, and systematically selecting 40 from the list with probability proportional to size. All households in selected enumeration areas were listed, and enumeration areas segmented into groups of 75 or fewer households: field teams randomly selected one segment from each enumeration area as the cluster to be surveyed. All households within the selected cluster were visited (Fig 1). For each cluster, community level volunteers (for example, Traditional Birth Attendants or Federation of Muslim Women Association of Nigeria volunteers) were identified and listed and a simple random sample of up to 3 volunteers selected for interview about recent maternal and newborn health care they had provided. The primary health centre assigned to provide routine antenatal, intra-partum and post-natal care to the selected cluster was also surveyed, and the nurse who carried out the last delivery recorded in the maternity register interviewed (the frontline health worker and facility surveys). Ethiopia is organised by region, zone, woreda (district), kebele (similar to a ward; lowest level of census population data) and gote (proxy for village). The baseline survey included 80 clusters, a cluster being defined as a segmented gote. The 80 clusters were systematically sampled from 76 woreda across four regions of Ethiopia (Amhara, Oromia, SNNP and Tigray). Sampling was performed by listing all woreda geographically from north to south of the country, listing kebeles and their population size alphabetically within each woreda, and 80 kebele sampled with probability proportional to population size. Gotes within each of these 80 kebele were listed and one gote per kebele selected using simple random sampling. At each selected gote, all households were listed and gotes segmented into groups of 75 or fewer households: field teams randomly selected one segment from each gote as the cluster to be surveyed. All households within each selected cluster were visited (Fig 2). For each sampled cluster, the community level volunteers were identified and listed and a simple random sample of up to 3 volunteers selected for interview about recent health care they had provided. The health post assigned to the village was surveyed, and the health extension worker on duty interviewed. The primary health centre assigned to provide routine antenatal, intra-partum and post-natal care to the selected cluster was also surveyed, and the nurse who attended the last delivery recorded in the maternity register interviewed (the frontline health worker and facility surveys). Uttar Pradesh is organised by district, block, and village. Population data is available at the village level from the 2001 Census. The baseline survey included 80 clusters, a cluster being defined as a segmented village. Sampling was performed by listing all villages from 51 blocks spread across six districts in Uttar Pradesh, cumulating their population size and systematically selecting 80 villages with probability proportional to size. All households in sampled villages were listed, and villages segmented into groups of 75 or fewer households: field teams randomly selected one segment from the selected village as the cluster to be surveyed. All households within the selected cluster were visited (Fig 3). For each sampled cluster, the community level volunteers (Accredited Social Health Activists and Anganwadi workers) were identified and listed and a simple random sample of up to 3 volunteers selected for interview about recent maternal and newborn health care they had provided. The primary health centre or community health centre assigned to provide routine antenatal, intra-partum and post-natal care to the selected cluster was also surveyed, and the nurse who attended the last delivery recorded in the maternity register interviewed (the frontline health worker and facility surveys). Survey clusters were allocated to teams of five interviewers and one supervisor, and each cluster was scheduled to be completed within two working days. In Gombe State and Uttar Pradesh all data were collected using handheld personal digital devices (PDAs). In Ethiopia frontline health worker and health facility data were collected using PDAs and household data collected using paper based questionnaires, which were double entered and reconciled. In all three countries the household questionnaire was modular and applied by interviewers who were allocated five to eight households per day depending on country and circumstance. At every household in the selected cluster the interviewer identified the household head or representative and, after obtaining informed written consent, recorded information about household socio-economic characteristics and completed a household roster of all usual residents. Every resident woman aged 13–49 years was then interviewed individually by the same interviewer and asked questions about her access to health care in the last year, and a detailed set of questions if she reported that she had had a live birth in the 12 months prior to survey. The frontline health worker questionnaire included questions about training and supervision, routine activities carried out, availability of supplies, workload during the last month and a detailed set of questions about behaviours during the last birth they attended. The facility questionnaire included a check list of staff, equipment, drugs, and infrastructure items present on the day of survey, and data extraction from maternity registers to ascertain facility workload during the last six months. All survey tools were pre-tested, and implemented in Hausa (Gombe State, Nigeria), Amharic (Amhara and SNNP regions, Ethiopia), Oromifa (Oromia region, Ethiopia) and Tigrinya (Tigray region, Ethiopia), and Hindi (State of Uttar Pradesh, India). Data were analysed in STATA 12 (www.stata.com) using svy commands to adjust for the cluster sampling design. In each geography, the sample selection was expected to result in interviews with at least 350 women who had a live birth in the previous 12 months: this number was sufficient to estimate, with 90% power and 95% confidence, percentage points of coverage of all contact and content indicators across the continuum of care with approximately five percent precision, assuming a cluster design effect of 1.4. Initially, contact and content indicators were calculated separately. Four contact coverage estimates were defined: (1) the percent of women with a live birth in the previous 12 months who had at least one antenatal care visit during that pregnancy; (2) the percent of women with a live birth in the previous 12 months who were attended at birth by a skilled birth attendant; (3) the percent of women with a live birth in the previous 12 months who had a post-partum check within 48 hours of birth; (4) the percent of newborns born alive in the previous 12 months whose mother reported that they had a post-natal check within 48 hours of birth. Amongst the same group of women with a live birth in the previous 12 months, the reported frequency with which each of the processes to define content of care (Table 1) occurred was calculated for all women, and then also calculated restricted to those women who had a contact. Finally, point estimates for contacts were combined with those for processes to generate population level estimates of high quality contacts, being: (1) the percent of women who had at least one antenatal care visit and for whom all eight antenatal processes were met; (2) the percent of women who were attended at birth by a skilled birth attendant and received active management of third stage of labour (AMTSL); (3) the percent of women who had a post-partum check within 48 hours of birth and for whom all five post-partum processes were met; (4) the percent of newborns who had a post-natal check within 48 hours of birth and for whom all five post-natal processes were met. These calculations were all carried out using household data with the exception of the intra-partum process AMTSL (which includes controlled cord traction, uterine massage, and administration of a prophylactic uterotonic). Women from the general population are often not able to report on the behaviours of birth attendants during delivery. To address this, efforts to link data sources have been proposed.[17, 18] In this analysis we linked skilled birth attendant responses about whether or not they had performed controlled cord traction, uterine massage and administered a prophylactic uterotonic at the last birth they attended (from the frontline health worker survey), to the household level coverage of delivery with a skilled birth attendant (household survey). In Nigeria, national level approval was obtained from the National Health Research Ethics Committee, Federal Ministry of Health, Abuja, and in Gombe State from the State Ministry of Health in both Gombe and Abuja. In Ethiopia, national level support was obtained from the Ministry of Health in Ethiopia, and ethical approval from the Ministry of Science and Technology; at the Regional level, approval was granted by the Regional IRBs in Amhara, Oromia, SNNP, and Tigray. In Uttar Pradesh, approval was obtained from SPECT-ERB, an independent Ethical Review Board, and written permission from the National Rural Health Mission of Uttar Pradesh. Ethical approval was also obtained from LSHTM (reference 6088). All respondents provided informed, voluntary written consent to be interviewed. In addition, written carer consent was also obtained for the small number of household survey respondents under the age of 16 years.
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