title: Prevalence and predictors of adverse events in older surgical patients: impact of the present on admission indicator.
abstract: OBJECTIVE
  to examine the effects of the present on admission (POA) indicator on the prevalence of and factors associated with postsurgical adverse events in older patients.
  
  
  METHODS
  this is a secondary data analysis of 82,898 surgical patients aged 65 years or older in 252 acute care hospitals in California in 2004. Four adverse events were counted using the Agency for Healthcare Research and Quality's Patient Safety Indicator (PSI) definitions with and without using the POA indicator. We also examined the effects of the POA indicator on the relationships between patient- and hospital-level factors and adverse events, using generalized linear mixed models.
  
  
  RESULTS
  the use of the POA indicator resulted in a marked reduction in the estimated rates of all 4 adverse event rates. Adjustment for POA conditions also influenced factors associated with adverse events. Compared with those with newly occurring adverse events only, admissions with only POA conditions were more likely to be admitted through the emergency department, be unplanned, and belong to patients with one or more preceding admissions or those with multiple admissions within the same year.
  
  
  CONCLUSIONS
  adverse event rates estimated from discharge abstracts using PSI methodology could be overstated when the POA indicator was not used. The POA indicator could influence predictors of adverse events. Studies on geriatric safety and outcomes using large administrative data sets should consider using the POA indicator. Further studies are needed on how to determine POA conditions.
authors.affiliation: Graduate School of Public Health, Seoul National University, 599 Kwanak-ro, Kwanak-gu, Seoul 151-742, South Korea. hk65@snu.ac.kr
authors.forename: Hongsoo
authors.initials: H
authors.lastname: Kim
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Capezuti
authors.forename: Christine
authors.initials: C
authors.lastname: Kovner
authors.forename: Zhonglin
authors.initials: Z
authors.lastname: Zhao
authors.forename: Kenneth
authors.initials: K
authors.lastname: Boockvar
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002140:California / Q000453:epidemiology; D002908:Chronic Disease; D005260:Female; D006761:Hospitals; D006801:Humans; D008297:Male; D017063:Outcome Assessment, Health Care / Q000379:methods; D010343:Patient Admission / Q000706:statistics & numerical data*; D010351:Patient Discharge / Q000706:statistics & numerical data; D011183:Postoperative Complications / Q000453:epidemiology*; D015995:Prevalence; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data; D017751:Safety Management / Q000592:standards*; D012737:Sex Factors; D013514:Surgical Procedures, Operative / Q000009:adverse effects* / Q000401:mortality