OBJECTIVE: This study tests two hypotheses: that a given delivery is less likely to be by cesarean section (c-section) in an HMO (closed-panel health maintenance organization) or IPA (independent practice association), than in other settings; and that where HMO and IPA penetration is high, the probability of a c-section will be reduced for all deliveries, whether in prepaid groups or not. DATA SOURCES AND STUDY SETTING: A data set consisting of 104,595 obstetric deliveries in New York state in 1986 is analyzed. STUDY DESIGN: A series of probit regressions is estimated, in which the dependent variable is either the probability that a given delivery is by c-section, or that a given delivery will result in a c-section for dystocia or fetal distress. DATA COLLECTION/EXTRACTION METHODS: The Live Birth File is linked with SPARCS hospital discharge data and other variables. PRINCIPAL FINDINGS: HMO setting reduces the probability of a cesarean section by 2.5 to 3.0 percentage points. However, this result is likely to be partly an artifact of offsetting diagnostic labeling and of choice of method of delivery, given diagnosis; a better estimate of the effect of HMO setting is -1.3 percentage points. IPA setting appears to affect the probability of a cesarean section even less, perhaps not at all. And HMO and IPA penetration in a region, as measured by HMO and IPA deliveries, respectively, as a percent of all deliveries, has relatively large depressing effects on the probability of a cesarean section. CONCLUSIONS: Ceteris paribus, the probability of a c-section is lower for an HMO delivery than for a fee-for-service delivery; however, HMO effects are smaller than previously reported in the literature for other types of inpatient care. For IPA deliveries, the effects are still smaller, perhaps nil. However, HMO and IPA penetration, possibly measuring the degree of competition in obstetrics markets, have important effects on c-section rates, not only in HMO/IPA settings, but throughout an area. These results appear to have important implications for public policy.
OBJECTIVE: This study tests two hypotheses: that a given delivery is less likely to be by cesarean section (c-section) in an HMO (closed-panel health maintenance organization) or IPA (independent practice association), than in other settings; and that where HMO and IPA penetration is high, the probability of a c-section will be reduced for all deliveries, whether in prepaid groups or not. DATA SOURCES AND STUDY SETTING: A data set consisting of 104,595 obstetric deliveries in New York state in 1986 is analyzed. STUDY DESIGN: A series of probit regressions is estimated, in which the dependent variable is either the probability that a given delivery is by c-section, or that a given delivery will result in a c-section for dystocia or fetal distress. DATA COLLECTION/EXTRACTION METHODS: The Live Birth File is linked with SPARCS hospital discharge data and other variables. PRINCIPAL FINDINGS: HMO setting reduces the probability of a cesarean section by 2.5 to 3.0 percentage points. However, this result is likely to be partly an artifact of offsetting diagnostic labeling and of choice of method of delivery, given diagnosis; a better estimate of the effect of HMO setting is -1.3 percentage points. IPA setting appears to affect the probability of a cesarean section even less, perhaps not at all. And HMO and IPA penetration in a region, as measured by HMO and IPA deliveries, respectively, as a percent of all deliveries, has relatively large depressing effects on the probability of a cesarean section. CONCLUSIONS: Ceteris paribus, the probability of a c-section is lower for an HMO delivery than for a fee-for-service delivery; however, HMO effects are smaller than previously reported in the literature for other types of inpatient care. For IPA deliveries, the effects are still smaller, perhaps nil. However, HMO and IPA penetration, possibly measuring the degree of competition in obstetrics markets, have important effects on c-section rates, not only in HMO/IPA settings, but throughout an area. These results appear to have important implications for public policy.
Authors: R A Rosenblatt; S A Dobie; L G Hart; R Schneeweiss; D Gould; T R Raine; T J Benedetti; M J Pirani; E B Perrin Journal: Am J Public Health Date: 1997-03 Impact factor: 9.308