title: Invasive Mechanical Ventilation in California Over 2000-2009: Implications for Emergency Medicine.
abstract: BACKGROUND
  Patients who require invasive mechanical ventilation (IMV) often represent a sequence of care between the emergency department (ED) and intensive care unit (ICU). Despite being the most populous state, little information exists to define patterns of IMV use within the state of California.
  
  
  METHODS
  We examined data from the masked Patient Discharge Database of California's Office of Statewide Health Planning and Development from 2000-2009. Adult patients who received IMV during their stay were identified using the International Classification of Diseases 9th Revision and Clinical Modification procedure codes (96.70, 96.71, 96.72). Patients were divided into age strata (18-34 yr, 35-64 yr, and >65 yr). Using descriptive statistics and regression analyses, for IMV discharges during the study period, we quantified the number of ED vs. non-ED based admissions; changes in patient characteristics and clinical outcome; evaluated the marginal costs for IMV; determined predictors for prolonged acute mechanical ventilation (PAMV, i.e. IMV>96 hr); and projected the number of IMV discharges and ED-based admissions by year 2020.
  
  
  RESULTS
  There were 696,634 IMV discharges available for analysis. From 2000-2009, IMV discharges increased by 2.8%/year: n=60,933 (293/100,000 persons) in 2000 to n=79,868 (328/100,000 persons) in 2009. While ED-based admissions grew by 3.8%/year, non-ED-based admissions remained stable (0%). During 2000-2009, fastest growth was noted for 1) the 35-64 year age strata; 2) Hispanics; 3) patients with non-Medicare public insurance; and 4) patients requiring PAMV. Average total patient cost-adjusted charges per hospital discharge increased by 29% from 2000 (from $42,528 to $60,215 in 2014 dollars) along with increases in the number of patients discharged to home and skilled nursing facilities. Higher marginal costs were noted for younger patients (ages 18-34 yr), non-whites, and publicly insured patients. Some of the strongest predictors for PAMV were age 35-64 years (OR=1.12; 95% CI [1.09-1.14], p<0.05); non-Whites; and non-Medicare public insurance. Our models suggest that by 2020, IMV discharges will grow to n=153,153 (377 IMV discharges/100,000 persons) with 99,095 admitted through the ED.
  
  
  CONCLUSIONS
  Based on sustained growth over the past decade, by the year 2020, we project a further increase to 153,153 IMV discharges with 99,095 admitted through the ED. Given limited ICU bed capacities, ongoing increases in the number and type of IMV patients have the potential to adversely affect California EDs that often admit patients to ICUs.
authors.affiliation: Anesthesiology and Perioperative Care Service, Veterans Affairs Palo Alto Health Care System ; Stanford University School of Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford, California.
authors.forename: Seshadri C
authors.initials: SC
authors.lastname: Mudumbai
authors.affiliation: Anesthesiology and Perioperative Care Service, Veterans Affairs Palo Alto Health Care System ; Stanford University School of Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford, California.
authors.forename: Juli
authors.initials: J
authors.lastname: Barr
authors.affiliation: Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Scott
authors.affiliation: Anesthesiology and Perioperative Care Service, Veterans Affairs Palo Alto Health Care System ; Stanford University School of Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford, California.
authors.forename: Edward R
authors.initials: ER
authors.lastname: Mariano
authors.affiliation: Anesthesiology and Perioperative Care Service, Veterans Affairs Palo Alto Health Care System ; Stanford University School of Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford, California.
authors.forename: Edward
authors.initials: E
authors.lastname: Bertaccini
authors.affiliation: George Washington School of Medicine, Washington, DC.
authors.forename: Hieu
authors.initials: H
authors.lastname: Nguyen
authors.affiliation: Hospital for Special Surgery, Weill Medical College of Cornell University.
authors.forename: Stavros G
authors.initials: SG
authors.lastname: Memtsoudis
authors.affiliation: Anesthesia Service, Veterans Affairs San Francisco Health Care System ; University of California, San Francisco, Department of Anesthesiology and Perioperative Care, California.
authors.forename: Brian
authors.initials: B
authors.lastname: Cason
authors.affiliation: Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System ; Stanford University School of Medicine, Department of Pediatrics.
authors.forename: Ciaran S
authors.initials: CS
authors.lastname: Phibbs
authors.affiliation: Center for Innovation to Implementation, Veterans Affairs Palo Alto Health Care System.
authors.forename: Todd
authors.initials: T
authors.lastname: Wagner
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002140:California; D016208:Databases, Factual / Q000706:statistics & numerical data; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005260:Female; D017721:Hospital Costs / Q000706:statistics & numerical data; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D012121:Respiration, Artificial / Q000191:economics / Q000706:statistics & numerical data*; D016896:Treatment Outcome; D055815:Young Adult