Patient-level cost analysis of subfertility pathways in the Dutch healthcare system

Maura Leusder (), Hilco J. Elten, Kees Ahaus, Carina G. J. M. Hilders and Evert J. P. Santbrink
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Maura Leusder: Erasmus University Rotterdam
Hilco J. Elten: Vrije Universiteit Amsterdam
Kees Ahaus: Erasmus University Rotterdam
Carina G. J. M. Hilders: Erasmus University Rotterdam
Evert J. P. Santbrink: Reinier de Graaf Gasthuis

The European Journal of Health Economics, 2025, vol. 26, issue 6, No 3, 927-943

Abstract: Abstract Background Health economic evaluations require cost data as a key input, and reimbursement policies and systems should incentivize valuable care. Subfertility is a growing global phenomenon, and Dutch per-treatment DRGs alone do not support value-based decision-making because they don’t reflect patient-level variation or the impact of technologies on costs across entire patient pathways. Methods We present a real-world micro-costing analysis of subfertility patient pathways (n = 4.190) using time-driven activity-based costing (TDABC) and process mining in the Dutch healthcare system, and built a scalable and granular costing model. Results We find that pathways (13.203 treatments, 4.190 patients, 10 years) from referral to pregnancy and birth vary greatly in costs (mean €6.329, maximum €36.976) and duration (mean 25,5 months, maximum 8,59 years), with structural variation within treatments (and DRGs) of up to 65%. Patient-level variation is highest in laboratory phases, and causally related to patients’ cycle volume, type, and treatment methods. Large IVF or IVF-ICSI cycles are most common, and most valuable to patients and the healthcare system, but exceed their DRGs significantly (33%). We provide recommendations that reduce costs across patient pathways by €1.3 m in the Netherlands, to support value-based personalized care strategies. These findings are relevant to clinics following European protocols. Conclusions Fertility treatments like IVF feature significant cost variation due to the personalization of treatments, and rapidly evolving laboratory technologies. Incorporating cost granularity at the patient and treatment level (cycle volume, type, method) is critical for decision-making, economic analyses, and policy as both subfertility rates and treatment demand are rising.

Keywords: Costs; Subfertility; IVF; Personalized care; Value-based healthcare; Time-driven activity-based costing (search for similar items in EconPapers)
JEL-codes: D24 D61 I10 I11 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10198-024-01744-5

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