{"doc_desc":{"title":"SIGNAL FUNCTION","idno":"DDI-LIB-APHRC-LAS-SF-2021-v1.0","producers":[{"name":"African Population and Health Research Center","abbreviation":"APHRC","affiliation":"","role":"Documentation of the DDI"}],"prod_date":"2025-01-03","version_statement":{"version":"Version 1.0(JANUARY 2025)"}},"study_desc":{"title_statement":{"idno":"DDI-LIB-APHRC-LAS-SF-2021-v1.0","title":"Measuring Abortion Incidence, Cost, and Quality of Post-Abortion Care in Liberia","sub_title":"Signal Function -Liberia","alt_title":"SF"},"authoring_entity":[{"name":"Kenneth Juma","affiliation":"APHRC,Kenya "},{"name":"Boniface Ushie","affiliation":"APHRC,Kenya "},{"name":"","affiliation":""}],"oth_id":[{"name":"Clinton Health Access Initiative","affiliation":"CHAI","email":"","role":""}],"production_statement":{"producers":[{"name":"Bentoe Z. Tehoungue","affiliation":"Ministry of Health - Liberia","role":"Co-Investigator "},{"name":"Margaret Giorgio","affiliation":"Guttmacher Institute ","role":"Co-Investigator "},{"name":"Jesse Philbin","affiliation":"Guttmacher Institute ","role":"Co-Investigator "},{"name":"Hellen Akinyi","affiliation":"APHRC","role":"Data Documentarist "},{"name":"Dr. Moses Massaquoi","affiliation":"Clinton Health Access Initiative","role":"Co-Investigator "},{"name":"Nelson K. Dunbar","affiliation":"Ministry of Health - Liberia","role":"Co-Investigator "},{"name":"Vekeh Donzo","affiliation":"Clinton Health Access Initiative","role":"Co-Investigator "},{"name":"Lily Lu,","affiliation":"Clinton Health Access Initiative","role":"Co-Investigator "},{"name":"Matthew Nviiri","affiliation":"Clinton Health Access Initiative","role":"Co-Investigator "},{"name":"Ramatou Ouedraogo","affiliation":"APHRC","role":"Co-Investigator "},{"name":"Esther Mutuku","affiliation":"APHRC","role":"Co-Investigator "},{"name":"Stephanie Kung","affiliation":"Guttmacher Institute ","role":"Co-Investigator "},{"name":"Akin Bankole","affiliation":"Guttmacher Institute ","role":"Co-Investigator "}],"copyright":"Copyright \u00a9 APHRC, 2025","funding_agencies":[{"name":"Swedish International Development Cooperation Agency","abbreviation":"Sida","role":""}]},"series_statement":{"series_name":"Demographic and Health Survey [hh\/dhs]","series_info":"N\/A"},"version_statement":{"version_date":"2025-01-03","version_notes":"N\/A"},"study_info":{"abstract":"Unsafe abortion was one of the major causes of complications, leading to Liberia's high maternal mortality ratio (1,072 deaths per 100,000 live births). The Ministry of Health highly prioritized reducing the high rates of maternal and neonatal deaths in the country. Among national efforts to improve access to and quality of reproductive, maternal, neonatal, child, and adolescent health (RMNCAH) services was the prevention of unsafe abortion and morbidity and mortality from unsafe abortions because nearly 6 out of 10 girls were mothers before age 19. In addition, adolescent pregnancy contributed to high maternal mortality and high neonatal mortality. Nevertheless, there was little information available on abortion incidence, burden and costs of managing complications from unsafe abortions, and the quality of post-abortion care. Data were critical for government and civil society stakeholders to design effective policies and guidance to reduce maternal morbidity and mortality from unsafe abortions and to advocate for increased access to comprehensive abortion care (inclusive of safe abortion for legal indications and post-abortion care) in Liberia.\n\nObjectives: The overall aim of the study was to determine the incidence of induced abortions, severity and magnitude of abortion-related complications, quality of PAC, and cost burden of unsafe abortion on the health systems in Liberia.\n\nMethodology: A mixed-method cross-sectional design was applied to determine the incidence of abortion in Liberia. This research design was employed using the Abortion Incidence Complication Method (AICM). This widely applied indirect method had produced robust estimates of abortion incidence in a range of contexts. The study comprised five (5) different surveys, namely: 1) Health Facility Survey (HFS), 2) Prospective Morbidity Survey, 3) Knowledgeable Informant Survey, 4) Quality of PAC survey, and 5) Post Abortion Care (PAC) Costing Survey. The Health Facility Survey was implemented at sampled public facilities using a nationally representative, stratified, random sampling approach to determine the incidence of induced abortion and abortion complications in Liberia. The Health Facility Survey also included a quality survey to assess the quality of post-abortion care. The Prospective Morbidity Survey was about women seeking PAC in health facilities and providers, including a patient chart review to assess the severity of complications. It also collected data on decision-making, care-seeking pathways, and awareness of the country's abortion law. For the Knowledgeable Informant Survey, a sample of health sector stakeholders who were knowledgeable about abortion\/PAC in Liberia were interviewed. Data from this component generated the multiplier to inform the incidence of abortion. The PAC costing study targeted health facility administrators to estimate the costs of PAC at facilities and the national level.","coll_dates":[{"start":"2021-09-30","end":"2021-11-11","cycle":""}],"nation":[{"name":"Liberia","abbreviation":"Lib"}],"geog_coverage":"National coverage","analysis_unit":"Health facility Equipments","universe":"Health care providers who have been in the facility for more than 6months","notes":"General Information \nSignal Function Procedure\n MEDICAL EQUIPMENT & SUPPLIES\n MEDICINES & COMMODITIES","study_scope":"General Information \nSignal Function Procedure\n MEDICAL EQUIPMENT & SUPPLIES\n MEDICINES & COMMODITIES"},"method":{"data_collection":{"sampling_procedure":"We proposed a robust sample in this study in order to produce stable facility and patient-level estimates and to detect at least a 5% difference between this estimates with sufficient power (0.8), when comparing between different facility levels. We hypothesize proportion (p=0.18), confidence width (?) given by; \n\n\nSolving for  in the above equation gives the sample size \nIn this case, the known estimate p used as a sampling proportion was the proportion of facilities in Liberia (18%), that could offer Medical Abortion (MA) through the use of misoprostol for first- or second-trimester pregnancies [Clinton Health Access Initiative, 2019].\n\nAssuming a confidence interval of 95%, then, and the above proportion gives a sample size of; \n\nSince we have a finite population of 115 health facilities (we are drawing this sample from the sample for the HFS where total number is 115), we apply the finite Population Correction to the calculated sample size by;\n\nn = N*n \/ (n + N - 1),\n\nTherefore; n = 115*227 \/ (227+115-1) = 76.55\n\n\nTherefore, this study required a sample size of 77 health facilities.","sampling_deviation":"N\/A","coll_mode":"Face-to-face [f2f]","research_instrument":"It was written in english and The questionnaire collected information on staff availability, including staffing levels, staff training on comprehensive PAC, facility operation times, service provision for basic and comprehensive PAC, family planning and reproductive health services, contraceptive services, supplies, equipment, and infrastructure.","act_min":"The Interview was conducted by a team of field interviewers. Each team included  6 interviewers, in addition to 1 team lead.\n\nThe supervisor's role was to coordinate field data collection and manage teams. They also assigned tasks to interviewers, spot-checked work, maintained control documents, and sent completed questionnaires and progress reports to the central data portal.\nFrequent Field visits  were made after every two weeks for period of data collection   by the Study members","weight":"N\/A","cleaning_operations":"the software used was survey CTO for data colllection, the  data was later downloaded in STATA format.","method_notes":"N\/A"},"analysis_info":{"response_rate":"97.5%","sampling_error_estimates":"N\/A"}},"data_access":{"dataset_use":{"contact":[{"name":"African Population and Heath Research Center","affiliation":"APHRC","email":"datarequest@aphrc.org","uri":""}],"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n- the Identification of the Primary Investigator\n- the title of the survey (including country, acronym and year of implementation)\n- the survey reference number\n- the source and date of download","conditions":"All non-APHRC staff seeking to use data generated at the Center must obtain written approval to use the data from the Director of Research. This form is developed to assess applications for data use and facilitate responsible sharing of data with external partners\/collaborators\/researchers. By entering into this agreement, the undersigned agrees to use these data only for the purpose for which they were obtained and to abide by the conditions outlined below:\n\n1. Data Ownership: The data remain the property of APHRC; any unauthorized reproduction and sharing of the data is strictly prohibited. The user will, therefore, not release nor permit others to use or release the data to any other person without the written authorization from the Center.\n\n2. Purpose: The provided data must be used for the purpose specified in the Data Request Form; any other use not specified in the form must receive additional or separate authorization.\n\n3. Respondent Identifiers: The Center is committed to protecting the identity of the respondents who provide information in its research. All analytical data sets (both qualitative and quantitative) released by the Data Unit MUST are stripped of respondent identifiers to protect the identity of the respondents. By accepting to use APHRC data, the user is pledging that he\/she will not, under any circumstance, regenerate the identifiers or permit others to use the data to learn the identity of any individual, household or community included in any data set.\n\n4. Confidentiality pledge: The user will not use nor permit others to use the data to report any information in the data sets that could identify, directly or by inference, individuals or households.\n\n5. Reporting of errors or inconsistencies: The user will promptly notify the Head of the Statistics and Survey Unit any errors discovered in the data as soon as the errors are discovered.\n\n6. Publications resulting from APHRC data: The Center requires external collaborators to work with APHRC staff on all publications resulting from its data. In order to facilitate this, lead authors should send a detailed concept note of the paper (including the background, rationale, data, analytical methods, and preliminary findings) to the Principle Investigator (or Theme Leader) for the project (with a copy to the Director of Research), who will circulate the abstract to concerned researchers for possible expression of interest in participating in the publication as co-authors. Any exception to the involvement of APHRC staff should be approved by the Director of Research, APHRC.\n\n7. Security: The user will take responsibility for the security of the data by ensuring that the data are used and stored in a secure environment where access is password protected. This will ensure that non-authorized people should not have access to the data.\n\n8. Loss of privilege to use data: In the event that APHRC determines that the data user is in violation of the conditions for using the data, or if the user wishes to cancel this agreement, the user will destroy the data files provided to him\/her. APHRC retains the right to revoke this agreement or informs publishers to withhold publication of any work based wholly or in part on its data if the conditions for using the data are violated.\n\n9. Acknowledgement: Any work\/reports from this data must acknowledge APHRC as the source of these data. For example, the suggested acknowledgement for NUHDSS data is:\n\n\"This research uses livelihoods data collected under the longitudinal Nairobi Urban Health and Demographic Surveillance System (NUHDSS) since 2006. The NUHDSS is carried out by the African Population and Health Research Center in two slums settlements (Korogocho and Viwandani) in Nairobi City.\"\n\nAdditionally all funders, the study communities that provided the data, and staff who collected and analyzed or processed the data should be acknowledged.\n\n10. Deposit of Reports\/Papers: The user should submit electronic and paper copies of all publications generated using APHRC data to the Policy Engagement and Communications Department, with copies to the Director of Research.\n\n11. Change of contact details: The user will promptly inform the Director of Research of any change in your personal details as contained on this data request form.","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}}}