title: Cost and mortality impact of an algorithm-driven sepsis prediction system.
abstract: OBJECTIVE
  To compute the financial and mortality impact of InSight, an algorithm-driven biomarker, which forecasts the onset of sepsis with minimal use of electronic health record data.
  
  
  METHODS
  This study compares InSight with existing sepsis screening tools and computes the differential life and cost savings associated with its use in the inpatient setting. To do so, mortality reduction is obtained from an increase in the number of sepsis cases correctly identified by InSight. Early sepsis detection by InSight is also associated with a reduction in length-of-stay, from which cost savings are directly computed.
  
  
  RESULTS
  InSight identifies more true positive cases of severe sepsis, with fewer false alarms, than comparable methods. For an individual ICU with 50 beds, for example, it is determined that InSight annually saves 75 additional lives and reduces sepsis-related costs by $560,000.
  
  
  CONCLUSIONS
  InSight performance results are derived from analysis of a single-center cohort. Mortality reduction results rely on a simplified use case, which fixes prediction times at 0, 1, and 2 h before sepsis onset, likely leading to under-estimates of lives saved. The corresponding cost reduction numbers are based on national averages for daily patient length-of-stay cost.
  
  
  CONCLUSIONS
  InSight has the potential to reduce sepsis-related deaths and to lead to substantial cost savings for healthcare facilities.
authors.affiliation: a Dascena Inc. , Hayward , CA , USA.
authors.forename: Jacob
authors.initials: J
authors.lastname: Calvert
authors.affiliation: a Dascena Inc. , Hayward , CA , USA.
authors.forename: Jana
authors.initials: J
authors.lastname: Hoffman
authors.affiliation: b Department of Emergency Medicine , University of California San Francisco , San Francisco , CA , USA.
authors.forename: Christopher
authors.initials: C
authors.lastname: Barton
authors.affiliation: c Division of Critical Care Medicine, Department of Anesthesia and Perioperative Care , University of California San Francisco , San Francisco , CA , USA.
authors.forename: David
authors.initials: D
authors.lastname: Shimabukuro
authors.affiliation: d Adult Critical Care, Advocate Health , Oak Brook , IL , USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Ries
authors.affiliation: b Department of Emergency Medicine , University of California San Francisco , San Francisco , CA , USA.|e Department of Emergency Medicine , Kaiser Permanente South San Francisco Medical Center , South San Francisco , CA , USA.
authors.forename: Uli
authors.initials: U
authors.lastname: Chettipally
authors.affiliation: f Department of Clinical Informatics, Stanford University School of Medicine , Stanford , CA , USA.|g Department of Emergency Medicine , Kaiser Permanente Redwood City Medical Center , Redwood City , CA , USA.
authors.forename: Yaniv
authors.initials: Y
authors.lastname: Kerem
authors.affiliation: a Dascena Inc. , Hayward , CA , USA.
authors.forename: Melissa
authors.initials: M
authors.lastname: Jay
authors.affiliation: h Department of Bioengineering , University of California Berkeley , Berkeley , CA , USA.
authors.forename: Samson
authors.initials: S
authors.lastname: Mataraso
authors.affiliation: a Dascena Inc. , Hayward , CA , USA.
authors.forename: Ritankar
authors.initials: R
authors.lastname: Das
mesh_terms: D000367:Age Factors; D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000191:economics / Q000627:therapeutic use; D015415:Biomarkers; D002985:Clinical Protocols; D003362:Cost-Benefit Analysis; D006801:Humans; D007902:Length of Stay; D063305:Organ Dysfunction Scores; D012680:Sensitivity and Specificity; D018805:Sepsis / Q000175:diagnosis / Q000191:economics* / Q000401:mortality*; D012720:Severity of Illness Index; D055986:Vital Signs
chemical_list: D000900:Anti-Bacterial Agents; D015415:Biomarkers
keywords: Algorithm; Clinical decision support systems; Computer-assisted diagnosis; Length of stay; Medical informatics; Mortality reduction; Sepsis