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Can Family Planning Service Statistics Be Used to Track Population-Level Outcomes?
The need for annual family planning program tracking data under the Family Planning 2020 (FP2020) initiative has contributed to renewed interest in family planning service statistics as a potential data source for annual estimates of the modern contraceptive prevalence rate (mCPR). We sought to asse...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Global Health: Science and Practice
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5878083/ https://www.ncbi.nlm.nih.gov/pubmed/29467167 http://dx.doi.org/10.9745/GHSP-D-17-00341 |
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author | Magnani, Robert J Ross, John Williamson, Jessica Weinberger, Michelle |
author_facet | Magnani, Robert J Ross, John Williamson, Jessica Weinberger, Michelle |
author_sort | Magnani, Robert J |
collection | PubMed |
description | The need for annual family planning program tracking data under the Family Planning 2020 (FP2020) initiative has contributed to renewed interest in family planning service statistics as a potential data source for annual estimates of the modern contraceptive prevalence rate (mCPR). We sought to assess (1) how well a set of commonly recorded data elements in routine service statistics systems could, with some fairly simple adjustments, track key population-level outcome indicators, and (2) whether some data elements performed better than others. We used data from 22 countries in Africa and Asia to analyze 3 data elements collected from service statistics: (1) number of contraceptive commodities distributed to clients, (2) number of family planning service visits, and (3) number of current contraceptive users. Data quality was assessed via analysis of mean square errors, using the United Nations Population Division World Contraceptive Use annual mCPR estimates as the “gold standard.” We also examined the magnitude of several components of measurement error: (1) variance, (2) level bias, and (3) slope (or trend) bias. Our results indicate modest levels of tracking error for data on commodities to clients (7%) and service visits (10%), and somewhat higher error rates for data on current users (19%). Variance and slope bias were relatively small for all data elements. Level bias was by far the largest contributor to tracking error. Paired comparisons of data elements in countries that collected at least 2 of the 3 data elements indicated a modest advantage of data on commodities to clients. None of the data elements considered was sufficiently accurate to be used to produce reliable stand-alone annual estimates of mCPR. However, the relatively low levels of variance and slope bias indicate that trends calculated from these 3 data elements can be productively used in conjunction with the Family Planning Estimation Tool (FPET) currently used to produce annual mCPR tracking estimates for FP2020. |
format | Online Article Text |
id | pubmed-5878083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Global Health: Science and Practice |
record_format | MEDLINE/PubMed |
spelling | pubmed-58780832018-05-09 Can Family Planning Service Statistics Be Used to Track Population-Level Outcomes? Magnani, Robert J Ross, John Williamson, Jessica Weinberger, Michelle Glob Health Sci Pract Original Articles The need for annual family planning program tracking data under the Family Planning 2020 (FP2020) initiative has contributed to renewed interest in family planning service statistics as a potential data source for annual estimates of the modern contraceptive prevalence rate (mCPR). We sought to assess (1) how well a set of commonly recorded data elements in routine service statistics systems could, with some fairly simple adjustments, track key population-level outcome indicators, and (2) whether some data elements performed better than others. We used data from 22 countries in Africa and Asia to analyze 3 data elements collected from service statistics: (1) number of contraceptive commodities distributed to clients, (2) number of family planning service visits, and (3) number of current contraceptive users. Data quality was assessed via analysis of mean square errors, using the United Nations Population Division World Contraceptive Use annual mCPR estimates as the “gold standard.” We also examined the magnitude of several components of measurement error: (1) variance, (2) level bias, and (3) slope (or trend) bias. Our results indicate modest levels of tracking error for data on commodities to clients (7%) and service visits (10%), and somewhat higher error rates for data on current users (19%). Variance and slope bias were relatively small for all data elements. Level bias was by far the largest contributor to tracking error. Paired comparisons of data elements in countries that collected at least 2 of the 3 data elements indicated a modest advantage of data on commodities to clients. None of the data elements considered was sufficiently accurate to be used to produce reliable stand-alone annual estimates of mCPR. However, the relatively low levels of variance and slope bias indicate that trends calculated from these 3 data elements can be productively used in conjunction with the Family Planning Estimation Tool (FPET) currently used to produce annual mCPR tracking estimates for FP2020. Global Health: Science and Practice 2018-03-21 /pmc/articles/PMC5878083/ /pubmed/29467167 http://dx.doi.org/10.9745/GHSP-D-17-00341 Text en © Magnani et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited. To view a copy of the license, visit http://creativecommons.org/licenses/by/4.0/. When linking to this article, please use the following permanent link: https://doi.org/10.9745/GHSP-D-17-00341 |
spellingShingle | Original Articles Magnani, Robert J Ross, John Williamson, Jessica Weinberger, Michelle Can Family Planning Service Statistics Be Used to Track Population-Level Outcomes? |
title | Can Family Planning Service Statistics Be Used to Track Population-Level Outcomes? |
title_full | Can Family Planning Service Statistics Be Used to Track Population-Level Outcomes? |
title_fullStr | Can Family Planning Service Statistics Be Used to Track Population-Level Outcomes? |
title_full_unstemmed | Can Family Planning Service Statistics Be Used to Track Population-Level Outcomes? |
title_short | Can Family Planning Service Statistics Be Used to Track Population-Level Outcomes? |
title_sort | can family planning service statistics be used to track population-level outcomes? |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5878083/ https://www.ncbi.nlm.nih.gov/pubmed/29467167 http://dx.doi.org/10.9745/GHSP-D-17-00341 |
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