{"title":"2003-2005年北领地围产期数据的聚类:分析和解释的含义","authors":"M. Steenkamp","doi":"10.1177/183335831404300105","DOIUrl":null,"url":null,"abstract":"Clustering in perinatal data can violate assumptions of independence, an important consideration for data analysis. Few published studies report on the extent of repeat births in routinely collected Australian perinatal data and the implications thereof for analysis and interpretation. This paper reports on a case study that examined the extent and implications of clustering in the Northern Territory Midwives Collection (NTMC) for the period 2003–2005. Data were obtained on 7,741 individual mothers giving birth to 8,707 babies in public hospitals during 2003–2005. Clusters of multiple pregnancies and repeat births were identified and the design effects for birth weight of Aboriginal and non-Aboriginal newborns were calculated. Of the mothers, 46.1% were Aboriginal. Of these, 13.2% had repeat singleton births; 0.4% had multiple pregnancies, and 0.3% had both. Of non-Aboriginal mothers, 8.7% had repeat singleton births; 1.2% had multiple pregnancies; and 0.3% had both. The design effect was 1.07 for Aboriginal newborns and 1.04 for non-Aboriginal newborns. The design effects indicate that the correct variance accounting for clustering is 4–7% larger than the incorrect variance ignoring clustering when three consecutive years of NT data are considered and an intracluster correlation coefficient of 0.48 is assumed for birth weight between twin and non-twin siblings. Depending on the outcome of interest, the impact of clustering should be considered in multivariate analysis of perinatal data, especially when such analyses involve more than one year's data, include large proportions of Aboriginal mothers and newborns, and groups with different rates of repeat births.","PeriodicalId":55068,"journal":{"name":"Health Information Management Journal","volume":"43 1","pages":"37 - 41"},"PeriodicalIF":2.7000,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/183335831404300105","citationCount":"4","resultStr":"{\"title\":\"Clustering in Northern Territory Perinatal Data for 2003–2005: Implications for Analysis and Interpretation\",\"authors\":\"M. Steenkamp\",\"doi\":\"10.1177/183335831404300105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Clustering in perinatal data can violate assumptions of independence, an important consideration for data analysis. Few published studies report on the extent of repeat births in routinely collected Australian perinatal data and the implications thereof for analysis and interpretation. This paper reports on a case study that examined the extent and implications of clustering in the Northern Territory Midwives Collection (NTMC) for the period 2003–2005. Data were obtained on 7,741 individual mothers giving birth to 8,707 babies in public hospitals during 2003–2005. Clusters of multiple pregnancies and repeat births were identified and the design effects for birth weight of Aboriginal and non-Aboriginal newborns were calculated. Of the mothers, 46.1% were Aboriginal. Of these, 13.2% had repeat singleton births; 0.4% had multiple pregnancies, and 0.3% had both. Of non-Aboriginal mothers, 8.7% had repeat singleton births; 1.2% had multiple pregnancies; and 0.3% had both. The design effect was 1.07 for Aboriginal newborns and 1.04 for non-Aboriginal newborns. The design effects indicate that the correct variance accounting for clustering is 4–7% larger than the incorrect variance ignoring clustering when three consecutive years of NT data are considered and an intracluster correlation coefficient of 0.48 is assumed for birth weight between twin and non-twin siblings. Depending on the outcome of interest, the impact of clustering should be considered in multivariate analysis of perinatal data, especially when such analyses involve more than one year's data, include large proportions of Aboriginal mothers and newborns, and groups with different rates of repeat births.\",\"PeriodicalId\":55068,\"journal\":{\"name\":\"Health Information Management Journal\",\"volume\":\"43 1\",\"pages\":\"37 - 41\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2014-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/183335831404300105\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health Information Management Journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/183335831404300105\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH POLICY & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Information Management Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/183335831404300105","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
Clustering in Northern Territory Perinatal Data for 2003–2005: Implications for Analysis and Interpretation
Clustering in perinatal data can violate assumptions of independence, an important consideration for data analysis. Few published studies report on the extent of repeat births in routinely collected Australian perinatal data and the implications thereof for analysis and interpretation. This paper reports on a case study that examined the extent and implications of clustering in the Northern Territory Midwives Collection (NTMC) for the period 2003–2005. Data were obtained on 7,741 individual mothers giving birth to 8,707 babies in public hospitals during 2003–2005. Clusters of multiple pregnancies and repeat births were identified and the design effects for birth weight of Aboriginal and non-Aboriginal newborns were calculated. Of the mothers, 46.1% were Aboriginal. Of these, 13.2% had repeat singleton births; 0.4% had multiple pregnancies, and 0.3% had both. Of non-Aboriginal mothers, 8.7% had repeat singleton births; 1.2% had multiple pregnancies; and 0.3% had both. The design effect was 1.07 for Aboriginal newborns and 1.04 for non-Aboriginal newborns. The design effects indicate that the correct variance accounting for clustering is 4–7% larger than the incorrect variance ignoring clustering when three consecutive years of NT data are considered and an intracluster correlation coefficient of 0.48 is assumed for birth weight between twin and non-twin siblings. Depending on the outcome of interest, the impact of clustering should be considered in multivariate analysis of perinatal data, especially when such analyses involve more than one year's data, include large proportions of Aboriginal mothers and newborns, and groups with different rates of repeat births.
期刊介绍:
The Health Information Management Journal (HIMJ) is the official peer-reviewed research journal of the Health Information Management Association of Australia (HIMAA).
HIMJ provides a forum for dissemination of original investigations and reviews covering a broad range of topics related to the management and communication of health information including: clinical and administrative health information systems at international, national, hospital and health practice levels; electronic health records; privacy and confidentiality; health classifications and terminologies; health systems, funding and resources management; consumer health informatics; public and population health information management; information technology implementation and evaluation and health information management education.