Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings
- Autores
- Goudar, Shivaprasad S.; Stolka, Kristen B.; Koso Thomas, Marion; Honnungar, Narayan V.; Mastiholi, Shivanand C.; Ramadurg, Umesh Y.; Dhaded, Sangappa M.; Pasha, Omrana; Patel, Archana; Esamai, Fabian; Chomba, Elwyn; Garces, Ana; Althabe, Fernando; Carlo, Waldemar A.; Goldenberg, Robert L.; Hibberd, Patricia L.; Liechty, Edward A.; Krebs, Nancy F.; Hambidge, Michael K.; Moore, Janet L.; Wallace, Dennis D.; Derman, Richard J; Bhalachandra, Kodkany S.; Bose, Carl L.
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- BACKGROUND: To describe quantitative data quality monitoring and performance metrics adopted by the Global Network´s (GN) Maternal Newborn Health Registry (MNHR), a maternal and perinatal population-based registry (MPPBR) based in low and middle income countries (LMICs). METHODS: Ongoing prospective, population-based data on all pregnancy outcomes within defined geographical locations participating in the GN have been collected since 2008. Data quality metrics were defined and are implemented at the cluster, site and the central level to ensure data quality. Quantitative performance metrics are described for data collected between 2010 and 2013. RESULTS: Delivery outcome rates over 95% illustrate that all sites are successful in following patients from pregnancy through delivery. Examples of specific performance metric reports illustrate how both the metrics and reporting process are used to identify cluster-level and site-level quality issues and illustrate how those metrics track over time. Other summary reports (e.g. the increasing proportion of measured birth weight compared to estimated and missing birth weight) illustrate how a site has improved quality over time. CONCLUSION: High quality MPPBRs such as the MNHR provide key information on pregnancy outcomes to local and international health officials where civil registration systems are lacking. The MNHR has measures in place to monitor data collection procedures and improve the quality of data collected. Sites have increasingly achieved acceptable values of performance metrics over time, indicating improvements in data quality, but the quality control program must continue to evolve to optimize the use of the MNHR to assess the impact of community interventions in research protocols in pregnancy and perinatal health.
Fil: Goudar, Shivaprasad S.. KLE University. Jawaharlal Nehru Medical College; India
Fil: Stolka, Kristen B.. Research Triangle Institute International; Estados Unidos
Fil: Koso Thomas, Marion. Eunice Kennedy Shriver National Institute of Child Health and Human Development; Estados Unidos
Fil: Honnungar, Narayan V.. KLE University. Jawaharlal Nehru Medical College; India
Fil: Mastiholi, Shivanand C.. KLE University. Jawaharlal Nehru Medical College; India
Fil: Ramadurg, Umesh Y.. S. Nijalingappa Medical College; India
Fil: Dhaded, Sangappa M.. KLE University. Jawaharlal Nehru Medical College; India
Fil: Pasha, Omrana. Aga Khan University; Pakistán
Fil: Patel, Archana. Indira Gandhi Government Medical College and Lata Medical Research Foundation; India
Fil: Esamai, Fabian. University School of Medicine; Kenia
Fil: Chomba, Elwyn. University of Zambia; Zambia
Fil: Garces, Ana. Universidad de San Carlos; Guatemala
Fil: Althabe, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Carlo, Waldemar A.. University of Alabama at Birmingahm; Estados Unidos
Fil: Goldenberg, Robert L.. Columbia University; Estados Unidos
Fil: Hibberd, Patricia L.. Massachusetts General Hospital for Children; Estados Unidos
Fil: Liechty, Edward A.. Indiana University; Estados Unidos
Fil: Krebs, Nancy F.. University of Colorado School of Medicine; Estados Unidos
Fil: Hambidge, Michael K.. University of Colorado School of Medicine; Estados Unidos
Fil: Moore, Janet L.. Research Triangle Institute International; Estados Unidos
Fil: Wallace, Dennis D.. Research Triangle Institute International; Estados Unidos
Fil: Derman, Richard J. Christiana Care Health Services; Estados Unidos
Fil: Bhalachandra, Kodkany S.. KLE University. Jawaharlal Nehru Medical College; India
Fil: Bose, Carl L.. University of North Carolina; Estados Unidos - Materia
- Newborn health
- Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/44502
Ver los metadatos del registro completo
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Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settingsGoudar, Shivaprasad S.Stolka, Kristen B.Koso Thomas, MarionHonnungar, Narayan V.Mastiholi, Shivanand C.Ramadurg, Umesh Y.Dhaded, Sangappa M.Pasha, OmranaPatel, ArchanaEsamai, FabianChomba, ElwynGarces, AnaAlthabe, FernandoCarlo, Waldemar A.Goldenberg, Robert L.Hibberd, Patricia L.Liechty, Edward A.Krebs, Nancy F.Hambidge, Michael K.Moore, Janet L.Wallace, Dennis D.Derman, Richard JBhalachandra, Kodkany S.Bose, Carl L.Newborn healthhttps://purl.org/becyt/ford/3.2https://purl.org/becyt/ford/3BACKGROUND: To describe quantitative data quality monitoring and performance metrics adopted by the Global Network´s (GN) Maternal Newborn Health Registry (MNHR), a maternal and perinatal population-based registry (MPPBR) based in low and middle income countries (LMICs). METHODS: Ongoing prospective, population-based data on all pregnancy outcomes within defined geographical locations participating in the GN have been collected since 2008. Data quality metrics were defined and are implemented at the cluster, site and the central level to ensure data quality. Quantitative performance metrics are described for data collected between 2010 and 2013. RESULTS: Delivery outcome rates over 95% illustrate that all sites are successful in following patients from pregnancy through delivery. Examples of specific performance metric reports illustrate how both the metrics and reporting process are used to identify cluster-level and site-level quality issues and illustrate how those metrics track over time. Other summary reports (e.g. the increasing proportion of measured birth weight compared to estimated and missing birth weight) illustrate how a site has improved quality over time. CONCLUSION: High quality MPPBRs such as the MNHR provide key information on pregnancy outcomes to local and international health officials where civil registration systems are lacking. The MNHR has measures in place to monitor data collection procedures and improve the quality of data collected. Sites have increasingly achieved acceptable values of performance metrics over time, indicating improvements in data quality, but the quality control program must continue to evolve to optimize the use of the MNHR to assess the impact of community interventions in research protocols in pregnancy and perinatal health.Fil: Goudar, Shivaprasad S.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Stolka, Kristen B.. Research Triangle Institute International; Estados UnidosFil: Koso Thomas, Marion. Eunice Kennedy Shriver National Institute of Child Health and Human Development; Estados UnidosFil: Honnungar, Narayan V.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Mastiholi, Shivanand C.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Ramadurg, Umesh Y.. S. Nijalingappa Medical College; IndiaFil: Dhaded, Sangappa M.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Pasha, Omrana. Aga Khan University; PakistánFil: Patel, Archana. Indira Gandhi Government Medical College and Lata Medical Research Foundation; IndiaFil: Esamai, Fabian. University School of Medicine; KeniaFil: Chomba, Elwyn. University of Zambia; ZambiaFil: Garces, Ana. Universidad de San Carlos; GuatemalaFil: Althabe, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Carlo, Waldemar A.. University of Alabama at Birmingahm; Estados UnidosFil: Goldenberg, Robert L.. Columbia University; Estados UnidosFil: Hibberd, Patricia L.. Massachusetts General Hospital for Children; Estados UnidosFil: Liechty, Edward A.. Indiana University; Estados UnidosFil: Krebs, Nancy F.. University of Colorado School of Medicine; Estados UnidosFil: Hambidge, Michael K.. University of Colorado School of Medicine; Estados UnidosFil: Moore, Janet L.. Research Triangle Institute International; Estados UnidosFil: Wallace, Dennis D.. Research Triangle Institute International; Estados UnidosFil: Derman, Richard J. Christiana Care Health Services; Estados UnidosFil: Bhalachandra, Kodkany S.. KLE University. Jawaharlal Nehru Medical College; IndiaFil: Bose, Carl L.. University of North Carolina; Estados UnidosBioMed Central2015-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/44502Goudar, Shivaprasad S.; Stolka, Kristen B.; Koso Thomas, Marion; Honnungar, Narayan V.; Mastiholi, Shivanand C.; et al.; Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings; BioMed Central; Reproductive Health; 12; Supl. 2; 6-2015; 1-101742-4755CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://reproductive-health-journal.biomedcentral.com/articles/10.1186/1742-4755-12-S2-S2info:eu-repo/semantics/altIdentifier/doi/10.1186/1742-4755-12-S2-S2info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:35:23Zoai:ri.conicet.gov.ar:11336/44502instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:35:24.156CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings |
| title |
Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings |
| spellingShingle |
Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings Goudar, Shivaprasad S. Newborn health |
| title_short |
Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings |
| title_full |
Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings |
| title_fullStr |
Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings |
| title_full_unstemmed |
Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings |
| title_sort |
Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings |
| dc.creator.none.fl_str_mv |
Goudar, Shivaprasad S. Stolka, Kristen B. Koso Thomas, Marion Honnungar, Narayan V. Mastiholi, Shivanand C. Ramadurg, Umesh Y. Dhaded, Sangappa M. Pasha, Omrana Patel, Archana Esamai, Fabian Chomba, Elwyn Garces, Ana Althabe, Fernando Carlo, Waldemar A. Goldenberg, Robert L. Hibberd, Patricia L. Liechty, Edward A. Krebs, Nancy F. Hambidge, Michael K. Moore, Janet L. Wallace, Dennis D. Derman, Richard J Bhalachandra, Kodkany S. Bose, Carl L. |
| author |
Goudar, Shivaprasad S. |
| author_facet |
Goudar, Shivaprasad S. Stolka, Kristen B. Koso Thomas, Marion Honnungar, Narayan V. Mastiholi, Shivanand C. Ramadurg, Umesh Y. Dhaded, Sangappa M. Pasha, Omrana Patel, Archana Esamai, Fabian Chomba, Elwyn Garces, Ana Althabe, Fernando Carlo, Waldemar A. Goldenberg, Robert L. Hibberd, Patricia L. Liechty, Edward A. Krebs, Nancy F. Hambidge, Michael K. Moore, Janet L. Wallace, Dennis D. Derman, Richard J Bhalachandra, Kodkany S. Bose, Carl L. |
| author_role |
author |
| author2 |
Stolka, Kristen B. Koso Thomas, Marion Honnungar, Narayan V. Mastiholi, Shivanand C. Ramadurg, Umesh Y. Dhaded, Sangappa M. Pasha, Omrana Patel, Archana Esamai, Fabian Chomba, Elwyn Garces, Ana Althabe, Fernando Carlo, Waldemar A. Goldenberg, Robert L. Hibberd, Patricia L. Liechty, Edward A. Krebs, Nancy F. Hambidge, Michael K. Moore, Janet L. Wallace, Dennis D. Derman, Richard J Bhalachandra, Kodkany S. Bose, Carl L. |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Newborn health |
| topic |
Newborn health |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/3.2 https://purl.org/becyt/ford/3 |
| dc.description.none.fl_txt_mv |
BACKGROUND: To describe quantitative data quality monitoring and performance metrics adopted by the Global Network´s (GN) Maternal Newborn Health Registry (MNHR), a maternal and perinatal population-based registry (MPPBR) based in low and middle income countries (LMICs). METHODS: Ongoing prospective, population-based data on all pregnancy outcomes within defined geographical locations participating in the GN have been collected since 2008. Data quality metrics were defined and are implemented at the cluster, site and the central level to ensure data quality. Quantitative performance metrics are described for data collected between 2010 and 2013. RESULTS: Delivery outcome rates over 95% illustrate that all sites are successful in following patients from pregnancy through delivery. Examples of specific performance metric reports illustrate how both the metrics and reporting process are used to identify cluster-level and site-level quality issues and illustrate how those metrics track over time. Other summary reports (e.g. the increasing proportion of measured birth weight compared to estimated and missing birth weight) illustrate how a site has improved quality over time. CONCLUSION: High quality MPPBRs such as the MNHR provide key information on pregnancy outcomes to local and international health officials where civil registration systems are lacking. The MNHR has measures in place to monitor data collection procedures and improve the quality of data collected. Sites have increasingly achieved acceptable values of performance metrics over time, indicating improvements in data quality, but the quality control program must continue to evolve to optimize the use of the MNHR to assess the impact of community interventions in research protocols in pregnancy and perinatal health. Fil: Goudar, Shivaprasad S.. KLE University. Jawaharlal Nehru Medical College; India Fil: Stolka, Kristen B.. Research Triangle Institute International; Estados Unidos Fil: Koso Thomas, Marion. Eunice Kennedy Shriver National Institute of Child Health and Human Development; Estados Unidos Fil: Honnungar, Narayan V.. KLE University. Jawaharlal Nehru Medical College; India Fil: Mastiholi, Shivanand C.. KLE University. Jawaharlal Nehru Medical College; India Fil: Ramadurg, Umesh Y.. S. Nijalingappa Medical College; India Fil: Dhaded, Sangappa M.. KLE University. Jawaharlal Nehru Medical College; India Fil: Pasha, Omrana. Aga Khan University; Pakistán Fil: Patel, Archana. Indira Gandhi Government Medical College and Lata Medical Research Foundation; India Fil: Esamai, Fabian. University School of Medicine; Kenia Fil: Chomba, Elwyn. University of Zambia; Zambia Fil: Garces, Ana. Universidad de San Carlos; Guatemala Fil: Althabe, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Efectividad Clínica y Sanitaria; Argentina Fil: Carlo, Waldemar A.. University of Alabama at Birmingahm; Estados Unidos Fil: Goldenberg, Robert L.. Columbia University; Estados Unidos Fil: Hibberd, Patricia L.. Massachusetts General Hospital for Children; Estados Unidos Fil: Liechty, Edward A.. Indiana University; Estados Unidos Fil: Krebs, Nancy F.. University of Colorado School of Medicine; Estados Unidos Fil: Hambidge, Michael K.. University of Colorado School of Medicine; Estados Unidos Fil: Moore, Janet L.. Research Triangle Institute International; Estados Unidos Fil: Wallace, Dennis D.. Research Triangle Institute International; Estados Unidos Fil: Derman, Richard J. Christiana Care Health Services; Estados Unidos Fil: Bhalachandra, Kodkany S.. KLE University. Jawaharlal Nehru Medical College; India Fil: Bose, Carl L.. University of North Carolina; Estados Unidos |
| description |
BACKGROUND: To describe quantitative data quality monitoring and performance metrics adopted by the Global Network´s (GN) Maternal Newborn Health Registry (MNHR), a maternal and perinatal population-based registry (MPPBR) based in low and middle income countries (LMICs). METHODS: Ongoing prospective, population-based data on all pregnancy outcomes within defined geographical locations participating in the GN have been collected since 2008. Data quality metrics were defined and are implemented at the cluster, site and the central level to ensure data quality. Quantitative performance metrics are described for data collected between 2010 and 2013. RESULTS: Delivery outcome rates over 95% illustrate that all sites are successful in following patients from pregnancy through delivery. Examples of specific performance metric reports illustrate how both the metrics and reporting process are used to identify cluster-level and site-level quality issues and illustrate how those metrics track over time. Other summary reports (e.g. the increasing proportion of measured birth weight compared to estimated and missing birth weight) illustrate how a site has improved quality over time. CONCLUSION: High quality MPPBRs such as the MNHR provide key information on pregnancy outcomes to local and international health officials where civil registration systems are lacking. The MNHR has measures in place to monitor data collection procedures and improve the quality of data collected. Sites have increasingly achieved acceptable values of performance metrics over time, indicating improvements in data quality, but the quality control program must continue to evolve to optimize the use of the MNHR to assess the impact of community interventions in research protocols in pregnancy and perinatal health. |
| publishDate |
2015 |
| dc.date.none.fl_str_mv |
2015-06 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
| status_str |
publishedVersion |
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http://hdl.handle.net/11336/44502 Goudar, Shivaprasad S.; Stolka, Kristen B.; Koso Thomas, Marion; Honnungar, Narayan V.; Mastiholi, Shivanand C.; et al.; Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings; BioMed Central; Reproductive Health; 12; Supl. 2; 6-2015; 1-10 1742-4755 CONICET Digital CONICET |
| url |
http://hdl.handle.net/11336/44502 |
| identifier_str_mv |
Goudar, Shivaprasad S.; Stolka, Kristen B.; Koso Thomas, Marion; Honnungar, Narayan V.; Mastiholi, Shivanand C.; et al.; Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings; BioMed Central; Reproductive Health; 12; Supl. 2; 6-2015; 1-10 1742-4755 CONICET Digital CONICET |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
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info:eu-repo/semantics/altIdentifier/url/https://reproductive-health-journal.biomedcentral.com/articles/10.1186/1742-4755-12-S2-S2 info:eu-repo/semantics/altIdentifier/doi/10.1186/1742-4755-12-S2-S2 |
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info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/2.5/ar/ |
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openAccess |
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application/pdf application/pdf |
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BioMed Central |
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BioMed Central |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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