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Aim: Length of stay (LOS) is an outcome measure and is assumed to be related to quality. The objective of this study is to examine the quality of birth care and risk factors associated with LOS after birth. Methods: A nationwide population‐based Turkish Demographic and Health Survey (TDHS) was used for the year 2018. A total of 1849 women ages 15–49 were included. Explanatory factor analysis and machine learning predictors such as Random Forest, Support Vector Machine, Neural Network, k‐Nearest Neighbor, and Naïve Bayes were used to identify the quality of birth care and risk factors associated with LOS after birth. Results: As a result of the explanatory factor analysis, factor structures of quality of birth care, antenatal check‐ups and supplements, and risk factors associated with birth were obtained using the Categorical Component Analysis method. The type of delivery, place of delivery, age, and type of place, which are under the quality of birth care, and risk factors associated with birth factors were found to be the variables that had the highest impact on LOS estimation. Random forest (Accuracy = 0.5789), support vector machine (radial) (Accuracy = 0.5766), and neural network (Accuracy = 0.5750) models outperformed, respectively. Conclusion: Type of delivery which is an indicator of quality of birth care is a strong predictor of LOS after birth according to the Random Forest model. We demonstrated that machine learning techniques offer precise LOS prediction after birth. Further studies assessing the effect of quality of birth care on predicting LOS at birth would be beneficial. [ABSTRACT FROM AUTHOR]

City hospitals (integrated health campuses) are a remarkable health policy action that has recently been implemented to meet the increasing public health needs. Health care professionals work in a collaborative atmosphere and provide interprofessional care on health campuses. This study is designed to explore the confirmatory factor structure of the Initial Attitudes towards Integrated Health Care (ATIHC) scale in Turkish health professionals, which was used to evaluate the attitudes of health professionals, consisting of senior managers and specialist physicians, towards city hospitals. Data were gathered from 196 health professionals, including senior managers and specialist physicians, working in a city hospital located in the rural part of the country. Confirmatory factor analysis (CFA) was used to analyze the data through the first-order and second-order stages. The performance of the second-order CFA model is meaningful (p < 0.00001) and acceptable ( X 2 /df = 1663/430 = 3.8; RMSEA = 0.12), and the goodness-of-fit indices are good (CFI = 0.92; NFI = 0.89; IFI = 0.92). The ATIHC scale, which consists of four latent variables under the second-order latent "attitudes" variable, better represents the sample, and health care quality and efficiency (β = 1.03, p < 0.01) and coordination of care components (β = 1.02, p < 0.01) are the prominent factors in explaining the attitudes of health professionals towards city hospitals. The Turkish version of ATIHC is a reliable and valid instrument for measuring the attitudes of health professionals towards city hospitals. [ABSTRACT FROM AUTHOR]