Skip to main content

An actuarial investigation into maternal out-of-hospital cost risk factors

  • Jananie William (a1), Catherine Chojenta (a2), Michael A. Martin (a1) and Deborah Loxton (a2)

This paper adopts an actuarial approach to identify the risk factors of government-funded maternal out-of-hospital costs in Australia, with a focus on women who experience adverse birth outcomes. We use a two-phase modelling methodology incorporating both classification and regression trees and generalised linear models on a data set that links administrative and longitudinal survey data from a large sample of women, to address maternal out-of-hospital costs. We find that adverse births are a statistically significant risk factor of out-of-hospital costs in both the delivery and postnatal periods. Furthermore, other significant cost risk factors are in-vitro fertilisation, specialist use, general practitioner use, area of residence and mental health factors (including anxiety, intense anxiety, postnatal depression and stress about own health) and the results vary by perinatal sub-period and the patient’s private health insurance status. We highlight these differences and use the results as an evidence base to inform public policy. Mental health policy is identified as a priority area for further investigation due to the dominance of these factors in many of the fitted models.

Corresponding author
*Correspondence to: Jananie William, Research School of Finance, Actuarial Studies and Statistics, College of Business and Economics, Australian National University, Canberra, ACT 0200, Australia. Tel: +61 2 6125 7311; E-mail:
Hide All
Alder, J., Fink, N., Bitzer, J., Hosli, I. & Holzgreve, W. (2007). Depression and anxiety during pregnancy: a risk factor for obstetric, fetal and neonatal outcome? A critical review of the literature. Journal of Maternal-Fetal & Neonatal Medicine, 20(3), 189209.
Australian Institute of Health and Welfare (2007). Health expenditure Australia 2005-06. In Australian Institute of Health and Welfare (Ed.), Health and Welfare Expenditure Series No. 30. Australian Institute of Health and Welfare, Canberra.
Australian Institute of Health and Welfare (2016). Health expenditure Australia 2014-15. In Australian Institute of Health and Welfare (Ed.), Health and Welfare Expenditure Series No. 57. Australian Institute of Health and Welfare, Canberra.
Australian Longitudinal Study for Women’s Health (ALSWH) (2014). Technical Report 2014. University of Queensland and The University of Newcastle, Newcastle.
Australian Prudential Regulatory Authority (2016). Private Health Insurance Membership Trends. APRA, Sydney.
Boyce, P. & Hickey, A. (2005). Psychosocial risk factors to major depression after childbirth. Social Psychiatry and Psychiatric Epidemiology, 40(8), 605612.
Brockman, M. & Wright, T. (1992). Statistical motor rating: Making effective use of your data. Journal of the Institute of Actuaries, 119, 457543.
Brown, W.J., Dobson, A.J., Bryson, L. & Byles, J.E. (1999). The Australian Longitudinal Study on Women’s Health: on the progress of the main cohort studies. Journal of Women’s Health & Gender-Based Medicine, 8(5), 681688.
Bryant, R. (2008). Improving Maternity Services in Australia. Department of Health and Ageing, Canberra.
Centre for Health Economics Research and Evaluation (2009). Extended Medicare Safety Net: review report, Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney.
Centre for Health Economics Research and Evaluation (2011). Extended Medicare Safety Net: review of capping arrangements report, Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney.
Chojenta, C. (2013). Prevalence, antecedents and perceptions of efficacy of treatments of postnatal depression in Australia. (PhD), University of Newcastle, Newcastle.
Chojenta, C., Loxton, D. & Lucke, J. (2012). How do previous mental health, social support, and stressful life events contribute to postnatal depression in a representative sample of Australian women? Journal of Midwifery & Women’s Health, 57(2), 145150.
Chojenta, C., Lucke, J., Forder, P. & Loxton, D. (2016). Maternal health factors as risks for postnatal depression: a prospective longitudinal study. PLoS One, 11(1), e0147246.
Chollet, D., Newman, J. & Sumner, A. (1996). The cost of poor birth outcomes in employer-sponsored health plans. Medical Care, 34(12), 12191234.
de Jong, P. & Heller, G.Z. (2008). Generalized Linear Models for Insurance Data (volume 17). Cambridge University Press, Cambridge, UK.
Ellis, R., Fiebig, D., Johar, M., Jones, G. & Savage, E. (2013). Explaining health care expenditure variation: large-sample evidence using linked survey and health administrative data. Health Economics, 22(9), 10931110.
Frees, E., Jin, X. & Lin, X. (2013). Actuarial applications of multivariate two-part regression models. Annals of Actuarial Science, 7(2), 258287.
Gilbert, W.M., Nesbitt, T.S. & Danielsen, B. (2003). The cost of prematurity: quantification by gestational age and birth weight. The American College of Obstetricians and Gynecologists, 102, 488492.
Gresham, E., Forder, P., Chojenta, C., Byles, J., Loxton, D. & Hure, A. (2015). Agreement between self-reported perinatal outcomes and administrative data in New South Wales, Australia. BMC Pregnancy & Childbirth, 15, 161.
Haberman, S. & Renshaw, A.E. (1996). Generalized linear models and actuarial science. The Statistician, 45(4), 407436.
Hedegaard, M. (2002). The effects of antenatal stress and anxiety on pregnancy outcome. Journal of Affective Disorders, 68(1), 9596.
Howson, C., Kinney, M. & Lawn, J. (2012). Born Too Soon: The Global Action Report on Preterm Birth. World Health Organisation, Geneva.
Johar, M., Jones, G. & Savage, E. (2012). Healthcare expenditure profile of older Australians: evidence from linked survey and health administrative data. Economic Papers, 31(4), 451463.
Luke, B., Bigger, H., Leurgans, S. & Sietsema, D. (1996). The cost of prematurity: a case-control study of twins vs singletons. American Journal of Public Health, 86(6), 809814.
Measey, M., Charles, A., d’Espaignet, E., Harrison, C., Deklerk, N. & Douglass, C. (2007). Aetiology of stillbirth: unexplored is not unexplained. Australian and New Zealand Journal of Public Health, 31(5), 444449.
Medicare Australia (2016). Medicare Benefits Schedule Book. Medicare Australia, Canberra.
Mistry, H., Heazell, A.E.P., Vincent, O. & Roberts, T. (2013). A structured review and exploration of the healthcare costs associated with stillbirth and a subsequent pregnancy in England and Wales. BMC Pregnancy & Childbirth, 13, 236.
O’Leary, C., Bower, C., Knuiman, M. & Stanley, F. (2007). Changing risks of stillbirth and neonatal mortality associated with maternal age in Western Australia 1984-2003. Paediatric and Perinatal Epidemiology, 21(6), 541549.
Powers, J. & Loxton, D. (2010). The impact of attrition in an 11-year prospective longitudinal study of younger women. Annals of Epidemiology, 20, 318321.
Powers, J., Loxton, D., O’Mara, A., Chojenta, C. & Ebert, L. (2013). Regardless of where they give birth, women living in non-metropolitan areas are less likely to have an epidural than their metropolitan counterparts. Women and Birth, 26(2), e77e81.
Ringborg, A., Berg, J., Norman, M., Westgren, M. & Jonsson, B. (2006). Preterm birth in Sweden: What are the average lengths of hospital stay and the associated inpatient costs? Acta Paediatrica, 95(12), 15501555.
Schmied, V., Johnson, M., Naidoo, N., Austin, M.P., Matthey, S., Kemp, L., Mills, A., Meade, T. & Yeo, A. (2013). Maternal mental health in Australia and New Zealand: a review of longitudinal studies. Women and Birth: Journal of the Australian College of Midwives, 26(3), 167178.
William, J., Chojenta, C., Martin, M. & Loxton, D. (2017). An actuarial investigation into maternal hospital cost risk factors for public patients. Annals of Actuarial Science, 1–24.
Wisborg, K., Barklin, A., Hedegaard, M. & Henriksen, T.B. (2008). Psychological stress during pregnancy and stillbirth: prospective study. BJOG: An International Journal of Obstetrics & Gynaecology, 115(7), 882885.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Annals of Actuarial Science
  • ISSN: 1748-4995
  • EISSN: 1748-5002
  • URL: /core/journals/annals-of-actuarial-science
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed