The Experts below are selected from a list of 15162 Experts worldwide ranked by ideXlab platform
Ann Madsen - One of the best experts on this subject based on the ideXlab platform.
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understanding perinatal death a systematic analysis of new york city fetal and neonatal death Vital Record data and implications for improvement 2007 2011
Maternal and Child Health Journal, 2014Co-Authors: Erica J Lee, Melissa Gambatese, Elizabeth M Begier, Antonio Soto, Tara Das, Ann MadsenAbstract:We aimed to compare demographic, medical, and cause-of-death information reported for third-trimester fetal and neonatal death Vital Records collected in New York City (NYC) before and after implementation of the revised fetal death certificate to identify: (1) the limitations of combining fetal and neonatal death Records for the purpose of perinatal death prevention; and (2) improvement opportunities for fetal death Vital Records registration. Using Chi squared tests, we compared data completeness and cause-of-death information between third-trimester NYC fetal (n = 1,930) and neonatal deaths (n = 735) from 2007 to 2011. We also compared fetal death data before and after the 2011 implementation of the 2003 United States (US) Standard Report of Fetal Death and an electronic reporting system. Compared with neonatal deaths, fetal death data were generally less complete (P < 0.0001). Fetal death data much more frequently reported an ill-defined cause of death (67 vs. 5 %). Most ill-defined reported causes of fetal death (73 %) were attributed to stillbirth synonyms (e.g., “fetal demise”). Ill-defined causes of fetal death decreased from 68 to 61 % (P < 0.01) after 2011. Both data completeness and ill-defined causes of death varied widely by hospital. In NYC, fetal deaths lack demographic, medical, and cause-of-death information compared with neonatal deaths, with implications for research that uses combined perinatal mortality data sets. Electronic implementation of the US Standard Report of Fetal Death minimally improved cause-of-death information. Substantial variability by hospital suggests opportunities for improvement exist.
Erica J Lee - One of the best experts on this subject based on the ideXlab platform.
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understanding perinatal death a systematic analysis of new york city fetal and neonatal death Vital Record data and implications for improvement 2007 2011
Maternal and Child Health Journal, 2014Co-Authors: Erica J Lee, Melissa Gambatese, Elizabeth M Begier, Antonio Soto, Tara Das, Ann MadsenAbstract:We aimed to compare demographic, medical, and cause-of-death information reported for third-trimester fetal and neonatal death Vital Records collected in New York City (NYC) before and after implementation of the revised fetal death certificate to identify: (1) the limitations of combining fetal and neonatal death Records for the purpose of perinatal death prevention; and (2) improvement opportunities for fetal death Vital Records registration. Using Chi squared tests, we compared data completeness and cause-of-death information between third-trimester NYC fetal (n = 1,930) and neonatal deaths (n = 735) from 2007 to 2011. We also compared fetal death data before and after the 2011 implementation of the 2003 United States (US) Standard Report of Fetal Death and an electronic reporting system. Compared with neonatal deaths, fetal death data were generally less complete (P < 0.0001). Fetal death data much more frequently reported an ill-defined cause of death (67 vs. 5 %). Most ill-defined reported causes of fetal death (73 %) were attributed to stillbirth synonyms (e.g., “fetal demise”). Ill-defined causes of fetal death decreased from 68 to 61 % (P < 0.01) after 2011. Both data completeness and ill-defined causes of death varied widely by hospital. In NYC, fetal deaths lack demographic, medical, and cause-of-death information compared with neonatal deaths, with implications for research that uses combined perinatal mortality data sets. Electronic implementation of the US Standard Report of Fetal Death minimally improved cause-of-death information. Substantial variability by hospital suggests opportunities for improvement exist.
Tara Das - One of the best experts on this subject based on the ideXlab platform.
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understanding perinatal death a systematic analysis of new york city fetal and neonatal death Vital Record data and implications for improvement 2007 2011
Maternal and Child Health Journal, 2014Co-Authors: Erica J Lee, Melissa Gambatese, Elizabeth M Begier, Antonio Soto, Tara Das, Ann MadsenAbstract:We aimed to compare demographic, medical, and cause-of-death information reported for third-trimester fetal and neonatal death Vital Records collected in New York City (NYC) before and after implementation of the revised fetal death certificate to identify: (1) the limitations of combining fetal and neonatal death Records for the purpose of perinatal death prevention; and (2) improvement opportunities for fetal death Vital Records registration. Using Chi squared tests, we compared data completeness and cause-of-death information between third-trimester NYC fetal (n = 1,930) and neonatal deaths (n = 735) from 2007 to 2011. We also compared fetal death data before and after the 2011 implementation of the 2003 United States (US) Standard Report of Fetal Death and an electronic reporting system. Compared with neonatal deaths, fetal death data were generally less complete (P < 0.0001). Fetal death data much more frequently reported an ill-defined cause of death (67 vs. 5 %). Most ill-defined reported causes of fetal death (73 %) were attributed to stillbirth synonyms (e.g., “fetal demise”). Ill-defined causes of fetal death decreased from 68 to 61 % (P < 0.01) after 2011. Both data completeness and ill-defined causes of death varied widely by hospital. In NYC, fetal deaths lack demographic, medical, and cause-of-death information compared with neonatal deaths, with implications for research that uses combined perinatal mortality data sets. Electronic implementation of the US Standard Report of Fetal Death minimally improved cause-of-death information. Substantial variability by hospital suggests opportunities for improvement exist.
Melissa Gambatese - One of the best experts on this subject based on the ideXlab platform.
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understanding perinatal death a systematic analysis of new york city fetal and neonatal death Vital Record data and implications for improvement 2007 2011
Maternal and Child Health Journal, 2014Co-Authors: Erica J Lee, Melissa Gambatese, Elizabeth M Begier, Antonio Soto, Tara Das, Ann MadsenAbstract:We aimed to compare demographic, medical, and cause-of-death information reported for third-trimester fetal and neonatal death Vital Records collected in New York City (NYC) before and after implementation of the revised fetal death certificate to identify: (1) the limitations of combining fetal and neonatal death Records for the purpose of perinatal death prevention; and (2) improvement opportunities for fetal death Vital Records registration. Using Chi squared tests, we compared data completeness and cause-of-death information between third-trimester NYC fetal (n = 1,930) and neonatal deaths (n = 735) from 2007 to 2011. We also compared fetal death data before and after the 2011 implementation of the 2003 United States (US) Standard Report of Fetal Death and an electronic reporting system. Compared with neonatal deaths, fetal death data were generally less complete (P < 0.0001). Fetal death data much more frequently reported an ill-defined cause of death (67 vs. 5 %). Most ill-defined reported causes of fetal death (73 %) were attributed to stillbirth synonyms (e.g., “fetal demise”). Ill-defined causes of fetal death decreased from 68 to 61 % (P < 0.01) after 2011. Both data completeness and ill-defined causes of death varied widely by hospital. In NYC, fetal deaths lack demographic, medical, and cause-of-death information compared with neonatal deaths, with implications for research that uses combined perinatal mortality data sets. Electronic implementation of the US Standard Report of Fetal Death minimally improved cause-of-death information. Substantial variability by hospital suggests opportunities for improvement exist.
Elizabeth M Begier - One of the best experts on this subject based on the ideXlab platform.
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understanding perinatal death a systematic analysis of new york city fetal and neonatal death Vital Record data and implications for improvement 2007 2011
Maternal and Child Health Journal, 2014Co-Authors: Erica J Lee, Melissa Gambatese, Elizabeth M Begier, Antonio Soto, Tara Das, Ann MadsenAbstract:We aimed to compare demographic, medical, and cause-of-death information reported for third-trimester fetal and neonatal death Vital Records collected in New York City (NYC) before and after implementation of the revised fetal death certificate to identify: (1) the limitations of combining fetal and neonatal death Records for the purpose of perinatal death prevention; and (2) improvement opportunities for fetal death Vital Records registration. Using Chi squared tests, we compared data completeness and cause-of-death information between third-trimester NYC fetal (n = 1,930) and neonatal deaths (n = 735) from 2007 to 2011. We also compared fetal death data before and after the 2011 implementation of the 2003 United States (US) Standard Report of Fetal Death and an electronic reporting system. Compared with neonatal deaths, fetal death data were generally less complete (P < 0.0001). Fetal death data much more frequently reported an ill-defined cause of death (67 vs. 5 %). Most ill-defined reported causes of fetal death (73 %) were attributed to stillbirth synonyms (e.g., “fetal demise”). Ill-defined causes of fetal death decreased from 68 to 61 % (P < 0.01) after 2011. Both data completeness and ill-defined causes of death varied widely by hospital. In NYC, fetal deaths lack demographic, medical, and cause-of-death information compared with neonatal deaths, with implications for research that uses combined perinatal mortality data sets. Electronic implementation of the US Standard Report of Fetal Death minimally improved cause-of-death information. Substantial variability by hospital suggests opportunities for improvement exist.
