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BackgroundObservational studies are increasingly being used for assessing therapeutic interventions. Case–control studies are generally considered to have greater risk of bias than cohort studies, but we lack evidence of differences in effect estimates between the 2 study types. We aimed to compare estimates between cohort and case–control studies in meta-analyses of observational studies of therapeutic interventions by using a meta-epidemiological study.MethodsWe used a random sample of meta-analyses of therapeutic interventions published in 2013 that included both cohort and case–control studies assessing a binary outcome. For each meta-analysis, the ratio of estimates (RE) was calculated by comparing the estimate in case–control studies to that in cohort studies. Then, we used random-effects meta-analysis to estimate a combined RE across meta-analyses. An RE < 1 indicated that case–control studies yielded larger estimates than cohort studies.ResultsThe final analysis included 23 meta-analyses: 138 cohort and 133 case–control studies. Treatment effect estimates did not significantly differ between case–control and cohort studies (combined RE 0.97 [95% CI 0.86–1.09]). Heterogeneity was low, with between–meta-analysis variance τ2 = 0.0049. Estimates did not differ between case–control and prospective or retrospective cohort studies (RE = 1.05 [95% CI 0.96–1.15] and RE = 0.99 [95% CI, 0.83–1.19], respectively). Sensitivity analysis of studies reporting adjusted estimates also revealed no significant difference (RE = 1.03 [95% CI 0.91–1.16]). Heterogeneity was also low for these analyses.ConclusionWe found no significant difference in treatment effect estimates between case–control and cohort studies assessing therapeutic interventions.

Background The quality of care in labor and delivery is traditionally measured through the Hospital Consumer Assessment of Healthcare Providers and Systems but less is known about the experiences of care reported by patients and caregivers on online sites that are more easily accessed by the public. Objective The aim of this study was to generate insight into the labor and delivery experience using hospital reviews on Yelp. Methods We identified all Yelp reviews of US hospitals posted online from May 2005 to March 2017. We used a machine learning tool, latent Dirichlet allocation, to identify 100 topics or themes within these reviews and used Pearson r to identify statistically significant correlations between topics and high (5-star) and low (1-star) ratings. Results A total of 1569 hospitals listed in the American Hospital Association directory had at least one Yelp posting, contributing a total of 41,095 Yelp reviews. Among those hospitals, 919 (59%) had at least one Yelp rating for labor and delivery services (median of 9 reviews), contributing a total of 6523 labor and delivery reviews. Reviews concentrated among 5-star (n=2643, 41%) and 1-star reviews (n=1934, 30%). Themes strongly associated with favorable ratings included the following: top-notch care (r=0.45, P<.001), describing staff as comforting (r=0.52, P<.001), the delivery experience (r=0.46, P<.001), modern and clean facilities (r=0.44, P<.001), and hospital food (r=0.38, P<.001). Themes strongly correlated with 1-star labor and delivery reviews included complaints to management (r=0.30, P<.001), a lack of agency among patients (r=0.47, P<.001), and issues with discharging from the hospital (r=0.32, P<.001). Conclusions Online review content about labor and delivery can provide meaningful information about patient satisfaction and experiences. Narratives from these reviews that are not otherwise captured in traditional surveys can direct efforts to improve the experience of obstetrical care.

BACKGROUND The quality of care in labor and delivery is traditionally measured through the Hospital Consumer Assessment of Healthcare Providers and Systems but less is known about the experiences of care reported by patients and caregivers on online sites that are more easily accessed by the public. OBJECTIVE The aim of this study was to generate insight into the labor and delivery experience using hospital reviews on Yelp. METHODS We identified all Yelp reviews of US hospitals posted online from May 2005 to March 2017. We used a machine learning tool, latent Dirichlet allocation, to identify 100 topics or themes within these reviews and used Pearson <i>r</i> to identify statistically significant correlations between topics and high (5-star) and low (1-star) ratings. RESULTS A total of 1569 hospitals listed in the American Hospital Association directory had at least one Yelp posting, contributing a total of 41,095 Yelp reviews. Among those hospitals, 919 (59%) had at least one Yelp rating for labor and delivery services (median of 9 reviews), contributing a total of 6523 labor and delivery reviews. Reviews concentrated among 5-star (n=2643, 41%) and 1-star reviews (n=1934, 30%). Themes strongly associated with favorable ratings included the following: top-notch care (<i>r</i>=0.45, <i>P</i>&lt;.001), describing staff as comforting (<i>r</i>=0.52, <i>P</i>&lt;.001), the delivery experience (<i>r</i>=0.46, <i>P</i>&lt;.001), modern and clean facilities (<i>r</i>=0.44, <i>P</i>&lt;.001), and hospital food (<i>r</i>=0.38, <i>P</i>&lt;.001). Themes strongly correlated with 1-star labor and delivery reviews included complaints to management (<i>r</i>=0.30, <i>P</i>&lt;.001), a lack of agency among patients (<i>r</i>=0.47, <i>P</i>&lt;.001), and issues with discharging from the hospital (<i>r</i>=0.32, <i>P</i>&lt;.001). CONCLUSIONS Online review content about labor and delivery can provide meaningful information about patient satisfaction and experiences. Narratives from these reviews that are not otherwise captured in traditional surveys can direct efforts to improve the experience of obstetrical care.