Katherine I Tierney1, Samuel Fishman2. 1. Department of Sociology, Western Michigan University, Kalamazoo, Michigan, USA. 2. Department of Sociology, Duke University, Durham, North Carolina, USA.
Abstract
OBJECTIVE: To investigate whether accounting for past patient composition in evaluations of the association between public quality reports and patient selectivity changes findings and conclusions. DATA SOURCES: Secondary data analysis of public reports of Assisted Reproductive Technology Clinic success rates between 2011 and 2018. STUDY DESIGN: Two sets of fixed effects models, (1) a standard fixed-effects model (FE) and (2) a dynamic panel model using structural equation modeling estimated with maximum-likelihood (ML-SEM) with one- and two-year lagged patient characteristics, are compared. The outcome variables are patient composition features associated with success rates, including two age categories and eight diagnoses of infertility. Two-year lagged success rates for any live birth and a singleton live birth are central predictor variables. DATA COLLECTION/EXTRACTION METHODS: Clinics with complete records for the 2011-2018 period were included (N = 303). PRINCIPAL FINDINGS: For live birth success rates, the two models show increases in the two-year lagged success rate is associated with a reduction in (1) the transformed percentage of patients with endometriosis (FE: β = -0.006, SE = 0.002, p < 0.01; ML-SEM: β = -0.005, SE = 0.002, p < 0.01) and (2) the percentage of patients with tubal diagnoses (FE: β = -0.090, SE = 0.017, p < 0.001; ML-SEM: β = -0.064, SE = 0.027, p < 0.05). For singleton birth success rates, the models show positive associations between the two-year lagged success rate and the percent of patients over 35 years old (FE: β = 0.219, SE = 0.033, p < 0.001; ML-SEM: β = 0.095, SE = 0.047, p < 0.05). Overall, the FE models show numerous significant associations with the two-year lagged success rate not observed in the ML-SEM models. Thus, the preferred and theoretically appropriate model (ML-SEM) and the more commonly used model (FE) yield different results. CONCLUSIONS: Researchers and policymakers should use models that account for past patient composition when evaluating the associations between quality reports and patient selectivity.
OBJECTIVE: To investigate whether accounting for past patient composition in evaluations of the association between public quality reports and patient selectivity changes findings and conclusions. DATA SOURCES: Secondary data analysis of public reports of Assisted Reproductive Technology Clinic success rates between 2011 and 2018. STUDY DESIGN: Two sets of fixed effects models, (1) a standard fixed-effects model (FE) and (2) a dynamic panel model using structural equation modeling estimated with maximum-likelihood (ML-SEM) with one- and two-year lagged patient characteristics, are compared. The outcome variables are patient composition features associated with success rates, including two age categories and eight diagnoses of infertility. Two-year lagged success rates for any live birth and a singleton live birth are central predictor variables. DATA COLLECTION/EXTRACTION METHODS: Clinics with complete records for the 2011-2018 period were included (N = 303). PRINCIPAL FINDINGS: For live birth success rates, the two models show increases in the two-year lagged success rate is associated with a reduction in (1) the transformed percentage of patients with endometriosis (FE: β = -0.006, SE = 0.002, p < 0.01; ML-SEM: β = -0.005, SE = 0.002, p < 0.01) and (2) the percentage of patients with tubal diagnoses (FE: β = -0.090, SE = 0.017, p < 0.001; ML-SEM: β = -0.064, SE = 0.027, p < 0.05). For singleton birth success rates, the models show positive associations between the two-year lagged success rate and the percent of patients over 35 years old (FE: β = 0.219, SE = 0.033, p < 0.001; ML-SEM: β = 0.095, SE = 0.047, p < 0.05). Overall, the FE models show numerous significant associations with the two-year lagged success rate not observed in the ML-SEM models. Thus, the preferred and theoretically appropriate model (ML-SEM) and the more commonly used model (FE) yield different results. CONCLUSIONS: Researchers and policymakers should use models that account for past patient composition when evaluating the associations between quality reports and patient selectivity.
Authors: Patricia Katz; Jonathan Showstack; James F Smith; Robert D Nachtigall; Susan G Millstein; Holly Wing; Michael L Eisenberg; Lauri A Pasch; Mary S Croughan; Nancy Adler Journal: Fertil Steril Date: 2010-12-04 Impact factor: 7.329
Authors: Georgina M Chambers; Van Phuong Hoang; Evelyn Lee; Michele Hansen; Elizabeth A Sullivan; Carol Bower; Michael Chapman Journal: JAMA Pediatr Date: 2014-11 Impact factor: 16.193