Determining Costs, Cost Predictors, and Resource Requirements in Assisted Reproductive Technology Care Pathways: A Value-Based Fertility Care Costing Tool Using Time-Driven Activity-Based Costing

Author(s)

Leusder M1, van Elten H2, Ahaus K3, Hilders CGJM3, van Santbrink EJP4
1Erasmus University Rotterdam, Brielle, Netherlands, 2Nyenrode Business University, Nyenrode, Netherlands, 3Erasmus University Rotterdam, Rotterdam, Netherlands, 4Reinier de Graaf Gasthuis, Voorburg, Netherlands

Presentation Documents

OBJECTIVES:

The aim of this research was to determine the total costs of fertility care cycles for all patient pathways, identify cost predictors, and to stratify resource use per treatment option.

METHODS:

We developed a cost calculation tool using time-driven activity-based costing (TDABC), direct observations, and metro mapping, which incorporates patient-level input variables. We allocate all organizational costs to the fertility care pathway, from initial consultation to ongoing pregnancy, across all treatment options (IVF, ICSI, IUI, OI) at a Dutch clinic that follows European standards. We used direct observations (n=218) to determine activity durations, documented care paths using metro mapping, and validated them with experts.

RESULTS:

Our results indicate that fertility treatments show substantial cost variability and can significantly vary in duration when considering the patient journey from initial consultation to ongoing pregnancy. Total treatment cycles of ovulation induction, intra-uterine insemination, and in-vitro fertilization with or without ICSI range in resource utilization from €926 to €4,879 depending on treatment type and patient-level variables. Patient-level cost variation is greatest during lab phases of treatment and driven by the volume of material handled, staff experience levels, and the patient's case mix. Lab staff, lab disposables, and lab equipment together make up 39% of the average IVF cycle expenses, highlighting the importance of a motivated workforce and the potential benefits of technological investments. The generated cost information is being incorporated into a value-based healthcare dashboard to inform and motivate staff to adopt behaviors that reduce costs and improve outcomes.

CONCLUSIONS:

Our findings inform the management and reimbursement of fertility care, and the calculator tool we have created can be used by other clinics or modified for other settings. Our findings show that TDABC can estimate costs for complex, long and cyclical care paths, and can incorporate patient level variables and variation.

Conference/Value in Health Info

2023-05, ISPOR 2023, Boston, MA, USA

Value in Health, Volume 26, Issue 6, S2 (June 2023)

Code

HSD60

Topic

Economic Evaluation

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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