Health care organizations around the world are under increasing pressure to improve resource utilization and to become more cost effective. At the core of this problem is the lack of accurate cost information associated with specific medical interventions. Recently, time-driven activity-based costing is put forward as suitable, more precise costing method to provide detailed and dynamically cost insights in a complex environment such as hospitals (10, 18, 21). The purpose of this study was the application of a time-driven activity-based method in order to estimate the cost of childbirth at a maternal department. Moreover, this study sought to extend prior literature by showing how the TDABC costing method can be used to outline how cost variation is driven by specific patient and disease characteristics. Acting on the recommendations of Keel et al. (21), this study followed and reported the seven-step approach explicitly to deepen understanding of the costs incurred during the full cycle of care of a woman giving birth.
First, this study shows how time-driven activity-based costing starts from a documented process map, together with the inclusion of utilized resources and time estimates. Capacity cost rates were calculated for each resource and cost was estimated subsequently. We found that the vast majority of total cost of childbirth is driven by personnel costs. In particular, monitoring after birth was the activity along the pathway consuming most personnel resources and thus contributed heavily to overall cost.
Second, our time-driven activity-based analysis indicated that a substantial variability in costs of childbirth can be observed both between and within types of delivery. Type of delivery impacted the treatment path followed by patients and therefore resulted in different cost outcomes. In line with findings from prior literature, we found that overall cost of childbirth for women having a CS is higher than for a VD (17, 19, 23). This cost difference could be primarily attributed to higher personnel costs associated with a longer clinical visit and the monitoring after birth, as well as higher use of medical consumables for CS. Additionally, the results of this study revealed several patient characteristics that drive variability in childbirth cost. Within the group of VD, substantial cost fluctuations could be identified according to age, parity, number of gestation weeks and education attainment. Women over twenty-five years were shown to need more time at the first phase of labour than younger women, leading to a higher cost. These results could be explained by an increased weakness of muscles with aging, resulting in less effective and more extended contractions, which are consistent with prior studies (6, 17, 19, 24). Similarly, women giving birth to their first child and women delivering after more gestation weeks were also associated with a longer first phase. In contrast to multiparous women, nulliparous women do not easily have a spontaneous rupture of the membranes, clarifying a more prolonged first phase of labour (14). A higher birth weight associated with a slower labour explains the longer first phase for women delivering after more gestational weeks (14). Finally, a higher education attainment was found to lead to higher cost of birth because of overall prolonged time estimations over the complete clinical pathway, which also confirms prior documented research (6). Health awareness can lead to more care-seeking behaviour for maternal health services, explaining more clinical time needed for higher educated women (20). Within CS, similar cost variations could be identified according to age, parity and number of gestations weeks. Supporting prior literature, we found initial evidence that costs of CS increase along with a woman’s age, which could be explained by older women being more susceptible for complications and difficulties during CS, resulting in more clinical care and prolonged hospitalization (6, 17, 19, 25). Furthermore, this study suggested that women delivering their first child, and women giving birth after more than 40 gestation weeks had a higher cost. In contrast to VD, where higher cost was driven by a longer first phase, our findings however indicated that these women required prolonged aftercare and monitoring after birth. This could also be caused by an increased complexity and risk of major issues for women delivering after more gestation weeks and nulliparous status (13–15). Lastly, our results indicated that women having a lower education attainment have a higher cost of childbirth, primarily due to longer aftercare. The impact of this characteristic on costs differs for VD and the findings are moreover inconsistent with prior literature, where it is found that a higher education attainment is associated with increased costs for CS (6, 20). However, it is important to note that our outcome is based on only two observations and thus should not be generalized.
Our study provides new perspectives on the estimation of cost of childbirth in a hospital, and on the determinants driving cost variability. First, while a number of studies have already identified that age, parity and education attainment can drive variability in overall cost of childbirth, our study differs from existing studies in the use of the time-driven activity-based costing approach to analyse the impact of several patient and disease characteristics on cost of childbirth (6, 17–20, 26). In addition to providing more accurate cost estimates than traditional methods, this technique allows to exactly identify which activities and resources are most heavily impacted by these characteristics (Porter, 2010). Despite a growing popularity in other medical disciplines, we did not find any study that uses this technique to estimate and analyse cost variability in childbirth with one exception (9, 10, 18, 21–23). Odhiambo et al. (2019) implemented in their paper a time-driven activity-based approach to identify cost determinants of a CS. However, this study was performed in Rwanda, where health systems and quality of care are very different in comparison to more developed countries, and the study did not include VD in its scope. Second, our study is also relevant to many applications in other hospital treatments. By explicitly outlining the seven step-by-step approach of Kaplan and Porter, we could guide future initiatives aiming to set up similar short-series using time-driven activity based costing (9, 22).
However, there are also an important limitation to this study. The relatively small size of the sample limits the generalizability of the findings regarding cost estimations. In particular for CS, not many conclusions on the quantitative impact of patient characteristics on cost of birth can be drawn due to the limited number of observations. Nevertheless, this study shows that time-driven activity is a suitable costing method to estimate cost of childbirth and to account for cost variabilities. Future research could elaborate on this study by extending the sample frame. Such an extension could moreover allow researchers to apply statistical analyses to examine the impact of multiple characteristics on cost differences, thereby further investigating the proposed relationships.