Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings. Issue 2 (December 2015)
- Record Type:
- Journal Article
- Title:
- Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings. Issue 2 (December 2015)
- Main Title:
- Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings
- Authors:
- Goudar, Shivaprasad
Stolka, Kristen
Koso-Thomas, Marion
Honnungar, Narayan
Mastiholi, Shivanand
Ramadurg, Umesh
Dhaded, Sangappa
Pasha, Omrana
Patel, Archana
Esamai, Fabian
Chomba, Elwyn
Garces, Ana
Althabe, Fernando
Carlo, Waldemar
Goldenberg, Robert
Hibberd, Patricia
Liechty, Edward
Krebs, Nancy
Hambidge, Michael
Moore, Janet
Wallace, Dennis
Derman, Richard
Bhalachandra, Kodkany
Bose, Carl - Abstract:
- Abstract 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. SitesAbstract 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. Trial registration number NCT01073475 … (more)
- Is Part Of:
- Reproductive health. Volume 12:Issue 2(2015)
- Journal:
- Reproductive health
- Issue:
- Volume 12:Issue 2(2015)
- Issue Display:
- Volume 12, Issue 2 (2015)
- Year:
- 2015
- Volume:
- 12
- Issue:
- 2
- Issue Sort Value:
- 2015-0012-0002-0000
- Page Start:
- 1
- Page End:
- 10
- Publication Date:
- 2015-12
- Subjects:
- data monitoring -- data quality -- maternal health -- newborn health -- perinatal registry -- metrics -- low-income countries
Reproductive health -- Periodicals
Birth control -- Periodicals
613.905 - Journal URLs:
- http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=251 ↗
http://link.springer.com/ ↗
https://www.reproductive-health-journal.com/home/ ↗ - DOI:
- 10.1186/1742-4755-12-S2-S2 ↗
- Languages:
- English
- ISSNs:
- 1742-4755
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 10034.xml