Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-17T14:36:35.442Z Has data issue: false hasContentIssue false
  • English
  • Français

DEVELOPMENT OF MULTIVARIATE QUALITY CONTROL AND QUALITY ASSURANCE MODELS FOR ANTENATAL CARE SERVICE IN INDONESIA

Part of: Multivariate analysis Applications

Published online by Cambridge University Press:  14 September 2020

DEWI ANGGRAINI Open the ORCID record for DEWI ANGGRAINI [Opens in a new window]
DEWI ANGGRAINI*
Affiliation:
Faculty of Mathematics and Natural Sciences, Lambung Mangkurat University, Banjarbaru, 70714, Indonesia
*
e-mail: dewi.anggraini@ulm.ac.id
Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'

Keywords

neonatal mortality rateantenatal care servicesdevelopment of foetal growthstatistical quality assurance systemsdata measuring and recording modelrisk assessment

MSC classification

Primary: 62P10: Applications to biology and medical sciences
Secondary: 62H10: Distribution of statistics
Type
Abstracts of Australasian PhD Theses
Information
Bulletin of the Australian Mathematical Society , Volume 103 , Issue 2 , April 2021 , pp. 346 - 348
Check for updates
Copyright
© 2020 Australian Mathematical Publishing Association Inc.

Footnotes

Thesis submitted to RMIT University in February 2019; degree approved on 14 May 2019; supervisors Mali Abdollahian and Kaye Marion.

References

Anggraini, D., Abdollahian, M. and Marion, K., ‘Review of low birth weight prediction models in Indonesia’, Int. J. Adv. Res. Sci. Eng. Technol. 3(4) (2015), 105–111.Google Scholar
Anggraini, D., Abdollahian, M. and Marion, K., ‘Accuracy assessment on prediction models for fetal weight based on maternal fundal height’, in: Information Technology: New Generations (Springer, Cham, 2016), 859–868.CrossRefGoogle Scholar
Anggraini, D., Abdollahian, M. and Marion, K., ‘Foetal weight prediction models at a given gestational age in the absence of ultrasound facilities: application in Indonesia’, BMC Pregnancy Childb. 18(1) (2018), Article ID 436, 12 pages.10.1186/s12884-018-2047-zCrossRefGoogle Scholar
Anggraini, D., Abdollahian, M., Marion, K., Meilania, G. T., Asmu’i, and Annisa, A. S., ‘Improving the information availability and accessibility of antenatal measurements to ensure safe delivery: a research-based policy recommendation to reduce neonatal mortality in Indonesia’, Int. J. Womens Health 12 (2020), 369–380.CrossRefGoogle ScholarPubMed
Anggraini, D., Abdollahian, M., Marion, K., Nuryani, S., Ramadhan, F., Rahayu, R. P., Rachman, I. R. and Wurianto, W., ‘The impact of scientific and technical training on improving routine collection of antenatal care data for maternal and foetal risk assessment: a case study in the province of South Kalimantan, Indonesia’, J. Pregnancy 2018 (2018), Article ID 9240157, 13 pages.10.1155/2018/9240157CrossRefGoogle ScholarPubMed
Anggraini, D., Abdollahian, M., Marion, K., Nuryani, S., Ramadhan, F., Rahayu, R. P., Rachman, I. R. and Wurianto, W., ‘The impact of scientific and technical training on improving database adequacy for foetal growth chart development in limited-resource settings: a case study in the province of South Kalimantan, Indonesia’, J. Pregnancy 2019 (2019), Article ID 8540637, 10 pages.CrossRefGoogle Scholar