A new method for classifying patterns of prenatal care utilization using cluster analysis.
Objectives: The objectives of this study were: to 1) define patterns of prenatal care utilization using cluster analysis, 2) describe two alternative cluster solutions and compare these groupings to the Adequacy of Prenatal Care Utilization Index (APNCU), 3) compare the cluster solutions and the APN...
| Publicado en: | Maternal & Child Health Journal Vol. 8; no. 1; pp. 19 - 31 |
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| Autores principales: | , , |
| Formato: | algorithm equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Mar2004
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=106651751&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 106651751 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10927875 N9J jtl: Maternal & Child Health Journal issn: 10927875 maglogo: N pubinfo: dt: Mar2004 vid: 8 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 106651751 106651751 2004165473 10.1023/b:maci.0000019845.04353.78 NLM15125454 106651751 ppf: 19 ppct: 12 formats: fmt: @attributes: type: P tig: atl: A new method for classifying patterns of prenatal care utilization using cluster analysis. aug: au: Rosenberg D Handler A Furner S affil: Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, 1603 W. Taylor MC 923, Chicago, IL 60612; drose@uic.edu sug: subj: Cluster Analysis Utilization Health Resource Utilization Classification Prenatal Care Classification Prenatal Care Utilization Algorithms Birth Certificates Clinical Assessment Tools Cluster Analysis Methods Comparative Studies Data Analysis Software Data Analysis, Statistical Descriptive Statistics Female Gestational Age Infant, Newborn Maternal Age Methodological Research Pregnancy Pregnancy Outcomes Questionnaires Stratified Random Sample Surveys Time Factors Human Infant, Newborn: birth-1 month Female ab: Objectives: The objectives of this study were: to 1) define patterns of prenatal care utilization using cluster analysis, 2) describe two alternative cluster solutions and compare these groupings to the Adequacy of Prenatal Care Utilization Index (APNCU), 3) compare the cluster solutions and the APNCU with respect to maternal age and prematurity, and 4) discuss advantages and disadvantages of using cluster analysis to study prenatal care. Methods: The study sample included 3544 women in the 1988 National Maternal and Infant Health Survey for whom complete prenatal care visit data were available. Clustering was carried out in two stages, first employing nearest centroid sorting (the k means method), a nonhierarchical approach, and then using Ward's Minimum Variance Method, a hierarchical clustering technique. Results: Patterns of prenatal care defined by cluster analysis varied by timing of the first visit, total number of visits, and the rate of accumulation of visits, but this variation was different compared to that seen for the APNCU. While the cluster solutions and the APNCU identified a similar normative pattern of care, other patterns identified were quite different. In particular, the six-cluster solution differentiated among women who entered care at similar times, but accumulated visits at differing rates and experienced differing rates of preterm delivery. Conclusion: Cluster analysis is a new tool for studying prenatal care. Further studies are needed to refine the method and test whether the alternative perspective it provides will lead to new findings concerning the relationship of prenatal care and birth outcomes. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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