TY - JOUR
T1 - Cost-effectiveness of screening tools for identifying depression in early pregnancy: a decision tree model
AU - Heslin, Margaret
AU - Jin, Huajie
AU - Trevillion, Kylee
AU - Ling, Xiaoxiao
AU - Nath, Selina
AU - Barrett, Barbara
AU - Demilew, Jill
AU - Ryan, Elizabeth
AU - O'Connor, Sheila
AU - Sands , Polly
AU - Milgrom, Jeannette
AU - Bick, Debra
AU - Stanley, Nicky
AU - Hunter, Myra S.
AU - Howard, Louise
AU - Byford, Sarah
N1 - Funding Information:
This paper summarises independent research funded by the National Institute for Health Research (NIHR) under the Programme Grants for Applied Research programme (ESMI Programme: grant reference number RP-PG-1210–12002) and the National Institute for Health Research (NIHR)/Wellcome Trust Kings Clinical Research Facility and the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and Kings College London. D.B. is supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital NHS Foundation Trust (NIHR, CLAHRC-2013–10022). L.M.H. was also supported by a National Institute for Health Research (NIHR) Research Professorship (NIHR-RP-R32–011). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. The study team acknowledges the study delivery support given by the South London Clinical Research Network.
Funding Information:
LMH chaired the National Institute for Health and Care Excellence CG192 guidelines development group on antenatal and postnatal mental health in 2012–2014. LMH reports grants from NIHR, MRC, Nuffield and the Stefanou Foundation, UK. KT, MH and SB report funding by NIHR and the Stefanou Foundation, UK. XL is partially funded in her PhD programme by EPSRC, UK. MSH has nothing to disclose.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Background: Although the effectiveness of screening tools for detecting depression in pregnancy has been investigated, there is limited evidence on the cost-effectiveness. This is vital in providing full information to decision makers. This study aimed to explore the cost-effectiveness of different screening tools to identify depression in early pregnancy compared to no screening. Methods: A decision tree was developed to model the identification and treatment pathways of depression from the first antenatal appointment to 3-months postpartum using the Whooley questions, the Edinburgh Postnatal Depression Scale (EPDS) and the Whooley questions followed by the EPDS, compared to no screening. The economic evaluation took an NHS and Personal Social Services perspective. Model parameters were taken from a combination of sources including a cross-sectional survey investigating the diagnostic accuracy of screening tools, and other published literature. Cost-effectiveness was assessed in terms of the incremental cost per quality adjusted life years (QALYs). Cost-effectiveness planes and cost-effectiveness acceptability curves were produced using a net-benefit approach based on Monte Carlo simulations of cost-outcome data. Results: In a 4-way comparison, the Whooley, EPDS and Whooley followed by the EPDS each had a similar probability of being cost-effective at around 30% for willingness to pay values from £20,000–30,000 per QALY compared to around 20% for the no screen option. Conclusions: All three screening approaches tested had a higher probability of being cost-effective than the no-screen option. In the absence of a clear cost-effectiveness advantage for any one of the three screening options, the choice between the screening approaches could be made on other grounds, such as clinical burden of the screening options. Limitations include data availability and short time horizon, thus further research is needed. Clinical trials registration: N/A
AB - Background: Although the effectiveness of screening tools for detecting depression in pregnancy has been investigated, there is limited evidence on the cost-effectiveness. This is vital in providing full information to decision makers. This study aimed to explore the cost-effectiveness of different screening tools to identify depression in early pregnancy compared to no screening. Methods: A decision tree was developed to model the identification and treatment pathways of depression from the first antenatal appointment to 3-months postpartum using the Whooley questions, the Edinburgh Postnatal Depression Scale (EPDS) and the Whooley questions followed by the EPDS, compared to no screening. The economic evaluation took an NHS and Personal Social Services perspective. Model parameters were taken from a combination of sources including a cross-sectional survey investigating the diagnostic accuracy of screening tools, and other published literature. Cost-effectiveness was assessed in terms of the incremental cost per quality adjusted life years (QALYs). Cost-effectiveness planes and cost-effectiveness acceptability curves were produced using a net-benefit approach based on Monte Carlo simulations of cost-outcome data. Results: In a 4-way comparison, the Whooley, EPDS and Whooley followed by the EPDS each had a similar probability of being cost-effective at around 30% for willingness to pay values from £20,000–30,000 per QALY compared to around 20% for the no screen option. Conclusions: All three screening approaches tested had a higher probability of being cost-effective than the no-screen option. In the absence of a clear cost-effectiveness advantage for any one of the three screening options, the choice between the screening approaches could be made on other grounds, such as clinical burden of the screening options. Limitations include data availability and short time horizon, thus further research is needed. Clinical trials registration: N/A
UR - http://www.scopus.com/inward/record.url?scp=85131809449&partnerID=8YFLogxK
U2 - 10.1186/s12913-022-08115-x
DO - 10.1186/s12913-022-08115-x
M3 - Article
SN - 1472-6963
VL - 22
JO - BMC Health Services Research
JF - BMC Health Services Research
IS - 1
M1 - 774
ER -
