OBJECTIVES: Despite public reporting of wide variation in hospital cesarean delivery rates, few women access this information when deciding where to deliver. We hypothesized that making cesarean delivery rate data more easily accessible and understandable would increase the likelihood of women selecting a hospital with a low cesarean delivery rate. STUDY DESIGN: We conducted a randomized controlled trial of 18,293 users of the Ovia Health mobile apps in 2016-2017. All enrollees were given an explanation of cesarean delivery rate data, and those randomized to the intervention group were also given an interactive tool that presented those data for the 10 closest hospitals with obstetric services. Our outcome measures were enrollees' self-reported delivery hospital and views on cesarean delivery rates. METHODS: Intent-to-treat analysis using 2-sided Pearson's χ2 tests. RESULTS: There was no significant difference across the experimental groups in the proportion of women who selected hospitals with low cesarean delivery rates (7.0% control vs 6.8% intervention; P = .54). Women in the intervention group were more likely to believe that hospitals in their community had differing cesarean delivery rates (66.9% vs 55.9%; P <.001) and to report that they looked at cesarean delivery rates when choosing their hospital (44.5% vs 33.9%; P <.001). CONCLUSIONS: Providing women with an interactive tool to compare cesarean delivery rates across hospitals in their community improved women's familiarity with variation in cesarean delivery rates but did not increase their likelihood of selecting hospitals with lower rates.
RCT Entities:
OBJECTIVES: Despite public reporting of wide variation in hospital cesarean delivery rates, few women access this information when deciding where to deliver. We hypothesized that making cesarean delivery rate data more easily accessible and understandable would increase the likelihood of women selecting a hospital with a low cesarean delivery rate. STUDY DESIGN: We conducted a randomized controlled trial of 18,293 users of the Ovia Health mobile apps in 2016-2017. All enrollees were given an explanation of cesarean delivery rate data, and those randomized to the intervention group were also given an interactive tool that presented those data for the 10 closest hospitals with obstetric services. Our outcome measures were enrollees' self-reported delivery hospital and views on cesarean delivery rates. METHODS: Intent-to-treat analysis using 2-sided Pearson's χ2 tests. RESULTS: There was no significant difference across the experimental groups in the proportion of women who selected hospitals with low cesarean delivery rates (7.0% control vs 6.8% intervention; P = .54). Women in the intervention group were more likely to believe that hospitals in their community had differing cesarean delivery rates (66.9% vs 55.9%; P <.001) and to report that they looked at cesarean delivery rates when choosing their hospital (44.5% vs 33.9%; P <.001). CONCLUSIONS: Providing women with an interactive tool to compare cesarean delivery rates across hospitals in their community improved women's familiarity with variation in cesarean delivery rates but did not increase their likelihood of selecting hospitals with lower rates.
Authors: Whitney P Witt; Lauren E Wisk; Erika R Cheng; Kara Mandell; Debanjana Chatterjee; Fathima Wakeel; Amy L Godecker; Dakota Zarak Journal: Matern Child Health J Date: 2015-01
Authors: Isabel A Cáceres; Mariana Arcaya; Eugene Declercq; Candice M Belanoff; Vanitha Janakiraman; Bruce Cohen; Jeffrey Ecker; Lauren A Smith; S V Subramanian Journal: PLoS One Date: 2013-03-18 Impact factor: 3.240
Authors: Sarah L Goff; Penelope S Pekow; Katharine O White; Tara Lagu; Kathleen M Mazor; Peter K Lindenauer Journal: Trials Date: 2013-08-07 Impact factor: 2.279