title: Electronic health record use, intensity of hospital care, and patient outcomes.
abstract: OBJECTIVE
  Previous studies have suggested that weekend hospital care is inferior to weekday care and that this difference may be related to diminished care intensity. The purpose of this study was to determine whether a metric for measuring intensity of hospital care based on use of the electronic health record was associated with patient-level outcomes.
  
  
  METHODS
  We performed a cohort study of hospitalizations at an academic medical center. Intensity of care was defined as the hourly number of provider accessions of the electronic health record, termed "electronic health record interactions." Hospitalizations were categorized on the basis of the mean difference in electronic health record interactions between the first Friday and the first Saturday of hospitalization. We used regression models to determine the association of these categories with patient outcomes after adjusting for covariates.
  
  
  RESULTS
  Electronic health record interactions decreased from Friday to Saturday in 77% of the 9051 hospitalizations included in the study. Compared with hospitalizations with no change in Friday to Saturday electronic health record interactions, the relative lengths of stay for hospitalizations with a small, moderate, and large decrease in electronic health record interactions were 1.05 (95% confidence interval [CI], 1.00-1.10), 1.11 (95% CI, 1.05-1.17), and 1.25 (95% CI, 1.15-1.35), respectively. Although a large decrease in electronic health record interactions was associated with in-hospital mortality, these findings were not significant after risk adjustment (odds ratio 1.74, 95% CI, 0.93-3.25).
  
  
  CONCLUSIONS
  Intensity of inpatient care, measured by electronic health record interactions, significantly diminished from Friday to Saturday, and this decrease was associated with length of stay. Hospitals should consider monitoring and correcting temporal fluctuations in care intensity.
authors: Department of Population Health, New York University School of Medicine, New York; Department of Medicine, New York University Langone Medical Center, New York. Electronic address: saul.blecker@nyumc.org.
authors: Saul
authors: S
authors: Blecker
authors: Department of Population Health, New York University School of Medicine, New York.
authors: Keith
authors: K
authors: Goldfeld
authors: Department of Population Health, New York University School of Medicine, New York.
authors: Naeun
authors: N
authors: Park
authors: Department of Medicine, New York University Langone Medical Center, New York.
authors: Daniel
authors: D
authors: Shine
authors: Department of Medicine, New York University Langone Medical Center, New York.
authors: Jonathan S
authors: JS
authors: Austrian
authors: Department of Population Health, New York University School of Medicine, New York; Department of Medicine, New York University Langone Medical Center, New York.
authors: R Scott
authors: RS
authors: Braithwaite
authors: Department of Medicine, New York University Langone Medical Center, New York.
authors: Martha J
authors: MJ
authors: Radford
authors: Department of Population Health, New York University School of Medicine, New York.
authors: Marc N
authors: MN
authors: Gourevitch
mesh_terms: D000046:Academic Medical Centers / Q000706:statistics & numerical data; D000328:Adult; D000368:Aged; D015331:Cohort Studies; D015986:Confounding Factors, Epidemiologic; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005260:Female; D006302:Health Services Research; D017052:Hospital Mortality; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D009518:New York; D016017:Odds Ratio; D010043:Outcome and Process Assessment, Health Care; D012044:Regression Analysis
keywords: Electronic health record; Hospital medicine