title: Structured implicit review: a new method for monitoring nursing care quality.
abstract: BACKGROUND
  Nurses' independent decisions about assessment, treatment, and nursing interventions for hospitalized patients are important determinants of quality of care. Physician peer implicit review of medical records has been central to Medicare quality management and is considered the gold standard for reviewing physician care, but peer implicit review of nursing processes of care has not received similar attention.
  
  
  OBJECTIVE
  The objective of this study was to develop and evaluate nurse structured implicit review (SIR) methods.
  
  
  METHODS
  We developed SIR instruments for rating the quality of inpatient nursing care for congestive heart failure (CHF) and cerebrovascular accident (CVA). Nurse reviewers used the SIR form to rate a nationally representative sample of randomly selected medical records for each disease from 297 acute care hospitals in 5 states (collected by the RAND-HCFA Prospective Payment System study).
  
  
  METHODS
  The study subjects were elderly Medicare inpatients with CHF (n = 291) or CVA (n = 283).
  
  
  METHODS
  We developed and tested scales reflecting domains of nursing process, evaluated interrater and interitem reliability, and assessed the extent to which items and scales predicted overall ratings of the quality of nursing care.
  
  
  RESULTS
  Interrater reliability for 14 of 16 scales (CHF) or 10 of 16 scales (CVA) was > or = 0.40. Interitem reliability was > 0.80 for all but 1 scale (both diseases). Functional Assessment, Physical Assessment, and Medication Tracking ratings were the strongest predictors of overall nursing quality ratings (P < 0.001 for each).
  
  
  CONCLUSIONS
  Nurse peer review with SIR has adequate interrater and excellent scale reliabilities and can be a valuable tool for assessing nurse performance.
authors.affiliation: RAND Health, Santa Monica, California 90407-2138, USA. mpearson@rand.org
authors.forename: M L
authors.initials: ML
authors.lastname: Pearson
authors.forename: J L
authors.initials: JL
authors.lastname: Lee
authors.forename: B L
authors.initials: BL
authors.lastname: Chang
authors.forename: M
authors.initials: M
authors.lastname: Elliott
authors.forename: K L
authors.initials: KL
authors.lastname: Kahn
authors.forename: L V
authors.initials: LV
authors.lastname: Rubenstein
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002140:California; D005260:Female; D005431:Florida; D006333:Heart Failure / Q000451:nursing*; D006801:Humans; D007196:Indiana; D008297:Male; D009731:Nursing Audit / Q000379:methods*; D015403:Nursing Evaluation Research; D009736:Nursing Process / Q000592:standards; D009738:Nursing Service, Hospital / Q000592:standards*; D015588:Observer Variation; D010414:Pennsylvania; D011237:Predictive Value of Tests; D011785:Quality Assurance, Health Care / Q000379:methods*; D020521:Stroke / Q000451:nursing*; D013781:Texas