Preference assessment of prenatal diagnosis for Down syndrome: is 35 years a rational cutoff?

OBJECTIVE: To compare the perceptions of miscarriage and birth of a child with Down syndrome among pregnant women and to evaluate the implications of these preferences for the traditional 35-year old maternal age risk boundary. METHODS: An interviewer-administered survey was given to 186 pregnant women receiving antepartum care at a university hospital. Preferences, as reflected by utilities, for birth of a child with Down syndrome and pregnancy miscarriage, stratified by patient characteristics, were assessed. RESULTS: The utility for the birth of a child with Down syndrome decreased (p < 0.001) as clinical severity increased from mild (0.78) to severe (0.65). Miscarriage of a pregnancy had a mean utility of 0.76 +/- 0.31. Women who desired prenatal diagnosis had a utility value for miscarriage (0.79 +/- 0.28) that was significantly higher than for the birth of a child with Down syndrome of unknown severity (0.73 +/- 0.27). In multivariable logistic regression, desire for prenatal diagnosis was the only factor associated with a preference of miscarriage over birth of an affected child (odds ratio 2.26, 95% confidence interval 1.03, 4.96). CONCLUSION: Women who desire prenatal diagnosis do not perceive the birth of a child with Down syndrome and a pregnancy miscarriage to be equivalent health states. This finding calls into question the rationale of the 35-year-old maternal age criterion and suggests that actual patient preferences should be better incorporated into the decision to offer definitive prenatal diagnosis.

Risk adjustment for interhospital comparison of primary cesarean rates.

OBJECTIVE: To create a method of controlling for case mix so that inferences could be made about variation in cesarean rates among hospitals. METHODS: A total of 160,753 births from 1991 Illinois birth certificate data were analyzed. A multivariate model of characteristics independently associated with cesarean delivery was developed from a random 25% sample, validated on the other 75%, and used to create a probability of cesarean delivery for each woman. The validated model was used to calculate a predicted primary cesarean delivery rate for the 154 hospitals in Illinois that did at least 100 deliveries per year. RESULTS: The final model included both medical and sociodemographic risk factors and predicted primary cesarean rates accurately over a full range of rates. Thirty-five hospitals (23%) had actual rates that were higher than their individual predicted 95% confidence interval (CI). Eighty-nine hospitals (58%) had actual rates within predicted CIs. Thirty hospitals (20%) had actual rates that were lower than the predicted 95% CI. Twenty-three percent of hospitals with actual rates greater than predicted rates were not in the top quartile of actual rates. Twenty-seven percent of hospitals with actual rates in the top quartile were doing cesarean deliveries appropriate for the risk status of the population served. CONCLUSION: Risk adjusting for hospital case mix more accurately identifies outlier hospitals than raw, unadjusted primary cesarean delivery rates. We believe that risk adjusting should be the first step in understanding variations in primary cesarean delivery rates.

Quality assessment of perinatal regionalization by multivariate analysis: Illinois, 1991-1993.

OBJECTIVE: To identify (1) those elements in the infrastructure of a regionalized perinatal network that have independent effects on the variation in perinatal mortality among nontertiary units (member level I and II hospitals) and (2) shortcomings, if any, in a traditional perinatal data base that impede quality assessment of contemporary regionalized care. METHODS: We analyzed perinatal surveillance data for 3 years, from 1991 to 1993, in the state of Illinois, representing more than 190,000 annual births. Fetal death and neonatal mortality rates for the 97 nontertiary hospitals studied were the dependent variables of interest. Two sets of independent variables were studied, those assessing the maternal sociobehavioral risk of populations served and those assessing the network infrastructure (defined as the facilities of member hospitals and their function within the regionalized network). We used multivariate analysis to partition the variation in hospital rates of perinatal mortality into two components, one attributable to maternal sociobehavioral risk and the other to the network infrastructure. RESULTS: Maternal sociobehavioral risk alone explained 73% of the variation in hospital fetal death rates and 38% of that in hospital neonatal mortality rates. When controlling for maternal sociobehavioral risk, rates of inborn very low birth weight (VLBW) deliveries (P < .001) and neonatal transport (P = .01) had independent effects on the variation in hospital fetal death rate; rates of inborn VLBW deliveries (P < .001), neonatal transport (P < .001), and proportion of VLBW infants transported out (P = .029) had independent effects on the variation in hospital neonatal mortality rate. CONCLUSIONS: In this mature statewide network, the rate of inborn VLBW deliveries exerted the strongest independent effect on variation in level I and II hospital rates of both fetal death and neonatal mortality. However, that there was such a large effect from maternal sociobehavioral risk alone has important public health implications. Additions and modifications to traditional perinatal surveillance are suggested better to assess the quality of regionalization in a contemporary health care environment.