Obstetric Patients with Repetitious Hospital Location Transfers Have Prolonged Stays.


There is a general belief that the workflow of surrounding location transfers between locations documented in electronic health record (EHR) during hospitalization is associated with a patient's length of stay (LOS). However, this belief has had little formal investigation in a data-driven manner. Location transfers in patients' hospitalization are hypothesized to be related to LOS. The objective of this study is to assess this relationship, using data derived from the EHR system of a large hospital system, with a focus on the obstetric setting - a clinical environment that exhibits wide swing in resource utilization. We designed a data-driven framework to infer patterns of location transfers and developed a zero-truncated negative binomial model, adjusting for demographics and billed diagnoses, to learn the association between patterns of location transfers and LOS. Indicative factors found to be of indicative of location transfer patterns were further investigated via their odds ratios, Pearson Correlation Coefficients, and Chi-squared test. We evaluated our approach with two years of data on from 5,774 obstetric inpatient encounters from the EHR system of Northwestern Memorial Hospital. The results indicated that the average LOS for patients with patterns of repetitious location transfers (RLTs) was 4.25 days (95% confidence interval [4.02, 4.47]) longer than patients with no RLT. This difference reduced to 3.62 days (95% confidence interval [3.61, 3.64]) after adjusting for age, race and billed diagnoses. We further discovered 21 indicative factors of RLT (statistically significant with a significance level of 0.05), in the form of billed diagnosis codes, each of which exhibited an odds ratio larger than 4. This study suggests that RLT patterns are associated with a prolonged LOS in the obstetric setting. As such, healthcare organizations may need to pay more attention to patients with RLTs to refine location transfers workflow and to boost efficiency in obstetric care.