Interaction patterns of trauma providers are associated with length of stay.

Chen Y, Patel MB, McNaughton CD, Malin BA
J Am Med Inform Assoc. 2018 25 (7): 790-799

PMID: 29481625 · PMCID: PMC6016682 · DOI:10.1093/jamia/ocy009

Background - Trauma-related hospitalizations drive a high percentage of health care expenditure and inpatient resource consumption, which is directly related to length of stay (LOS). Robust and reliable interactions among health care employees can reduce LOS. However, there is little known about whether certain patterns of interactions exist and how they relate to LOS and its variability. The objective of this study is to learn interaction patterns and quantify the relationship to LOS within a mature trauma system and long-standing electronic medical record (EMR).

Methods - We adapted a spectral co-clustering methodology to infer the interaction patterns of health care employees based on the EMR of 5588 hospitalized adult trauma survivors. The relationship between interaction patterns and LOS was assessed via a negative binomial regression model. We further assessed the influence of potential confounders by age, number of health care encounters to date, number of access action types care providers committed to patient EMRs, month of admission, phenome-wide association study codes, procedure codes, and insurance status.

Results - Three types of interaction patterns were discovered. The first pattern exhibited the most collaboration between employees and was associated with the shortest LOS. Compared to this pattern, LOS for the second and third patterns was 0.61 days (Pā€‰=ā€‰0.014) and 0.43 days (Pā€‰=ā€‰0.037) longer, respectively. Although the 3 interaction patterns dealt with different numbers of patients in each admission month, our results suggest that care was provided for similar patients.

Discussion - The results of this study indicate there is an association between LOS and the extent to which health care employees interact in the care of an injured patient. The findings further suggest that there is merit in ascertaining the content of these interactions and the factors that induce these differences in interaction patterns within a trauma system.

MeSH Terms (13)

Adult Electronic Health Records Hospitalization Humans Interprofessional Relations Length of Stay Linear Models Medical Records Systems, Computerized Middle Aged Models, Statistical Personnel, Hospital Trauma Centers Traumatology

Connections (2)

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