Elsevier

Early Human Development

Volume 82, Issue 2, February 2006, Pages 85-95
Early Human Development

Estimates of the cost and length of stay changes that can be attributed to one-week increases in gestational age for premature infants

https://doi.org/10.1016/j.earlhumdev.2006.01.001Get rights and content

Abstract

Objective

To estimate the potential savings, both in terms of costs and lengths of stay, of one-week increases in gestational age for premature infants. The purpose is to provide population-based data that can be used to assess the potential savings of interventions that delay premature delivery.

Data

Cohort data for all births in California in 1998–2000 that linked vital records data with those from hospital discharge abstracts, including those of neonatal transport. All infants with a gestational age between 24 and 37 weeks were included. There were 193,167 infants in the sample after deleting cases with incomplete data or gestational age that was inconsistent with birth weight.

Methods

Hospital costs were estimated by adjusting charges by hospital-specific costs-to-charges ratios. Data were aggregated across transport into episodes of care. Mean and median potential savings were calculated for increasing gestational age, in one-week intervals. The 25th and 75th percentiles were used to estimate ranges.

Results

The results are presented in matrix format, for starting gestational ages of 24–34 weeks, with ending gestational ages of 25 to 37 weeks. Costs and lengths of stay decreased with gestational age from a median of $216,814 (92 days) at 24 weeks to $591 (2 days) at 37 weeks. The potential savings from delaying premature labor are quite large; the median savings for a 2 week increase in gestational age were between $28,870 and $64,021 for gestational ages below 33 weeks, with larger savings for longer delays in delivery. Delaying deliveries < 29 weeks to term (37 weeks) resulted in savings of over $122,000 per case, with the savings being over $206,000 for deliveries < 26 weeks.

Conclusions

These results provide population-based data that can be applied to clinical trials data to assess the impacts on costs and lengths of stay of interventions that delay premature labor. They show that the potential savings of delaying premature labor are quite large, especially for extremely premature deliveries.

Introduction

Medical and technological advances in the care of infants have resulted in dramatic reductions in neonatal mortality, especially for low birth weight (< 2500 g) and very low birth weight (< 1500 g) infants [1], [2]. While birth weight specific survival has improved markedly, rates of prematurity and extreme prematurity have remained relatively stable over time. While many interventions have been tried, until recently there was relatively little that could be done to prevent premature labor [3]. However, the recent report that 17 alpha-hydroxyprogesterone caproate therapy significantly increased gestation in mothers who had had a previous preterm birth gives hope that other successful therapies may be in the offing [4].

While clinical trials can demonstrate effectiveness, the very large variations in the costs of care for premature infants can result in substantial uncertainty about the cost-effectiveness of interventions [5]. Even trials with hundreds of infants will not have very many infants of any given weight or gestational age at birth. Clinical trials are further biased because they tend to occur in large academic medical centers which tend to have better outcomes than other hospitals [6]. This will affect the neonatal cost estimates because most extremely premature infants die in the first few days. Thus, having population-based estimates with large samples would provide a better basis for estimating the cost-effectiveness of any successful perinatal intervention to prevent or delay premature labor. Gilbert et al. reported neonatal costs by week of gestation for all births in California for 1996 [7]. But, they only reported the mean and median costs, with no information about the distribution of costs at each week of gestation. The purpose of this study is to provide population-based estimates of the costs of neonatal care by week of gestation and use information on the distributions of costs to provide plausible ranges on the potential shifts in costs that may arise as a result of interventions that delay premature labor. These are provided for both neonatal costs and neonatal lengths of stay.

Section snippets

Methods

Following approval of this study by the Stanford University Institutional Review Board and the California Department of Health and Human Services Committee for the Protection of Human Subjects, linked data were obtained for the 1998–2000 California birth cohorts. These data link the California Office of Statewide Health Planning and Development (OSHPD) infant hospital discharge summaries to the infant vital statistics data (birth and death certificate data). Infant hospital discharge summaries

Results

There were a total of 264,870 cases in the linked data with a gestational age between 24 and 37 completed weeks. We deleted 354 cases with a birth weight < 500 g. 33,296 cases were deleted due to incomplete cost or length of stay information, or if they were identified as having a non-creditable cost estimate. A total of 38,054 cases were deleted because they failed the gestational age criteria described above. The resulting final sample was 193,167 infants.

Table 1 reports the distributions of

Discussion

This analysis provides summaries of the neonatal costs and lengths of stay by week of gestation from a large, population-based dataset. These data provide more reliable information on which to base estimates of the cost-effectiveness of interventions to prevent or delay premature labor than can be obtained from the relatively small samples of randomized controlled trials. Further, because these data were population-based, they were not subject to any bias with respect to the types of hospitals

Acknowledgment

This work was supported by the National Institutes of Health, grant HD-36914 (National Institute of Child Health and Human Development and Agency for Healthcare Research and Quality).

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