title: Screening inpatient quality using post-discharge events.
abstract: BACKGROUND
  Decreasing hospital lengths of stay (LOS) hamper efforts to detect and to definitively treat complications of care. Patients leave before some complications are identified.
  
  
  OBJECTIVE
  To develop a computerized method to screen for hospital complications using readily available administrative data from outpatient and nonacute care within 90 days of discharge.
  
  
  METHODS
  We developed the Complications Screening Program for Outpatient data (CSP-O) by using diagnosis and procedure codes from Medicare Part A and B claims to define 50 complication screens. Seventeen apply to specific procedural cases, and 33 apply to all adult, acute, medical, or surgical hospitalizations. The CSP-O algorithm examined outpatient, physician office, home health agency, and hospice claims within 90 days following discharge.
  
  
  METHODS
  Seven hundred thirty nine thousand, two hundred and forty eight discharges of Medicare beneficiaries (age range, > or = 65 years) were admitted to 515 hospitals nationwide in 1994.
  
  
  RESULTS
  Complete 90-day, post-discharge windows were present for 62.8% of all and 68.5% of procedural cases. The 33 general screens flagged 13.6% of all cases; only 1.8% of procedural cases were flagged by the 17 procedural screens. When we allowed the CSP-O algorithm to scan information from acute hospital readmissions, flag rates rose to 32.8% for general and 8.7% for procedural complications. Controlling for patient and hospital characteristics, flag rates were considerably higher among the very old and at small and for-profit institutions.
  
  
  CONCLUSIONS
  Whereas several CSP-O findings have construct validity, limitations of claims raise concerns. Regardless of the CSPO's ultimate utility, examining post-discharge experiences to identify inpatient complications remains important as LOSs fall.
authors.affiliation: Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA. liezzoni@bidmc.harvard.edu
authors.forename: L I
authors.initials: LI
authors.lastname: Iezzoni
authors.forename: Y D
authors.initials: YD
authors.lastname: Mackiernan
authors.forename: M J
authors.initials: MJ
authors.lastname: Cahalane
authors.forename: R S
authors.initials: RS
authors.lastname: Phillips
authors.forename: R B
authors.initials: RB
authors.lastname: Davis
authors.forename: K
authors.initials: K
authors.lastname: Miller
mesh_terms: D000359:Aftercare / Q000706:statistics & numerical data; D000368:Aged; D000369:Aged, 80 and over; D003428:Cross Infection / Q000453:epidemiology; D005260:Female; D006761:Hospitals / Q000592:standards*; D006801:Humans; D007049:Iatrogenic Disease / Q000453:epidemiology*; D007902:Length of Stay; D008297:Male; D008403:Mass Screening; D015999:Multivariate Analysis; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D010351:Patient Discharge; D011183:Postoperative Complications / Q000453:epidemiology; D013997:Time Factors