Jennifer Bailit1, Joanne Garrett. 1. MetroHealth Medical Center, Case Western Reserve University, Cleveland, Ohio 44109-1998, USA. jbailit@metrohealth.org
Abstract
OBJECTIVE: To compare the two published methods of cesarean delivery rate risk adjustment to determine which should be recommended as a national standard. METHODS: We used 2 years of Washington State Birth Events Record Data (1997 and 1998) to estimate hospitals' risk-adjusted cesarean delivery rates using two different methods: 1) logistic regression modeling and 2) direct standardization. After exclusions, there were 123,850 births and 67 hospitals. Ranked lists of hospitals were produced by each methodology and compared using the Spearman correlation. We used kappa statistics to compare the top 25% and the bottom 25% of the rankings. RESULTS: The Spearman correlation for the ranked lists was strong (.84, P <.001). The kappa(s) were .67 for the top 25% and .69 for the bottom 25%. By the logistic regression method, 19 hospitals had rates significantly higher than expected and 15 had rates significantly lower than expected. Because the direct standardization method had 57% of hospitals with no births in at least one of the risk strata, we could not determine whether these hospitals were statistical outliers. CONCLUSION: Both methods ranked hospitals similarly. If cesarean delivery rate risk adjustment for all hospitals is desirable, the logistic regression method has the advantage of being able to determine if different rates are significantly above or below expected. However, if comparing only two large hospitals is the goal, direct standardization may be simpler to implement, provided all risk strata have at least one delivery.
OBJECTIVE: To compare the two published methods of cesarean delivery rate risk adjustment to determine which should be recommended as a national standard. METHODS: We used 2 years of Washington State Birth Events Record Data (1997 and 1998) to estimate hospitals' risk-adjusted cesarean delivery rates using two different methods: 1) logistic regression modeling and 2) direct standardization. After exclusions, there were 123,850 births and 67 hospitals. Ranked lists of hospitals were produced by each methodology and compared using the Spearman correlation. We used kappa statistics to compare the top 25% and the bottom 25% of the rankings. RESULTS: The Spearman correlation for the ranked lists was strong (.84, P <.001). The kappa(s) were .67 for the top 25% and .69 for the bottom 25%. By the logistic regression method, 19 hospitals had rates significantly higher than expected and 15 had rates significantly lower than expected. Because the direct standardization method had 57% of hospitals with no births in at least one of the risk strata, we could not determine whether these hospitals were statistical outliers. CONCLUSION: Both methods ranked hospitals similarly. If cesarean delivery rate risk adjustment for all hospitals is desirable, the logistic regression method has the advantage of being able to determine if different rates are significantly above or below expected. However, if comparing only two large hospitals is the goal, direct standardization may be simpler to implement, provided all risk strata have at least one delivery.
Authors: Gianpaolo Maso; Salvatore Alberico; Lorenzo Monasta; Luca Ronfani; Marcella Montico; Caterina Businelli; Valentina Soini; Monica Piccoli; Carmine Gigli; Daniele Domini; Claudio Fiscella; Sara Casarsa; Carlo Zompicchiatti; Michela De Agostinis; Attilio D'Atri; Raffaela Mugittu; Santo La Valle; Cristina Di Leonardo; Valter Adamo; Silvia Smiroldo; Giovanni Del Frate; Monica Olivuzzi; Silvio Giove; Maria Parente; Daniele Bassini; Simona Melazzini; Secondo Guaschino; Francesco De Seta; Sergio Demarini; Laura Travan; Diego Marchesoni; Alberto Rossi; Giorgio Simon; Sandro Zicari; Giorgio Tamburlini Journal: PLoS One Date: 2013-06-05 Impact factor: 3.240