Analysis of Interrupted Time Series Mortality Trends: An Example to Evaluate Regionalized Perinatal Care.
Interrupted time series designs are frequently employed to evaluate program impact. Analysis strategies to determine if shifts have occurred are not well known. The case where statistical fluctuations (errors) may be assumed independent is considered, and a segmented regression methodology presented...
| Publicado en: | American Journal of Public Health Vol. 71; no. 1; pp. 38 - 47 |
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| Autores principales: | , , |
| Formato: | Artículo |
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American Public Health Association
Jan1981
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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=hlh&AN=4945601&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 4945601 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00900036 APH jtl: American Journal of Public Health issn: 00900036 maglogo: N pubinfo: dt: Jan1981 vid: 71 iid: 1 pid: 44 pub: American Public Health Association artinfo: ui: 4945601 10.2105/AJPH.71.1.38 ppf: 38 ppct: 9 formats: tig: atl: Analysis of Interrupted Time Series Mortality Trends: An Example to Evaluate Regionalized Perinatal Care. aug: au: Gillings, Dennis Makuc, Diane Siegel, Earl affil: Associate Professor, Department of Biostatistics, School of Public Health 201H, University of North Carolina, Chapel Hill, NC 27514. Statistician, Office of Deputy Assistant Secretary for Planning and Evaluation/Health, Dept. of HHS, Washington, DC. Professor, Department of Maternal and Child Health, School of Public Health, University of North Carolina, Chapel Hill. su: Mortality Perinatal death Maternal health services Perinatal care Neonatal mortality Prenatal care Postnatal care Racial differences North Carolina sug: subj: North Carolina Mortality Perinatal death Maternal health services Perinatal care Neonatal mortality Prenatal care Postnatal care Racial differences ab: Interrupted time series designs are frequently employed to evaluate program impact. Analysis strategies to determine if shifts have occurred are not well known. The case where statistical fluctuations (errors) may be assumed independent is considered, and a segmented regression methodology presented. The method discussed is applied to the assessment of changes in local and state perinatal postneonatal mortality to identify historical trends and will be used to evaluate the impact of the North Carolina Regionalized Perinatal Care Program when seven years of postprogram mortality data become available. The perinatal program region is contrasted with a control region to provide a basis for interpretation of differences noted. Relevant segmented regression models provided good fits to the data and highlighted mortality trends over the last 30 years. Considerable racial differences in these trends were identified, particularly for postneonatal mortality. Segmented regression is considered relevant for the analysis of interrupted time series designs in other applications when errors can be taken to be independent. Thus, the methodology may be regarded as a general statistical tool for evaluation purposes. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 1981 holdings: @attributes: islocal: N |
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