title: Predictors of nonadherence to national hospital quality measures for heart failure and pneumonia.
abstract: BACKGROUND
  Understanding factors associated with process measure nonadherence may improve both patient care and future measure design.
  
  
  METHODS
  We analyzed 3401 patients with heart failure and 2186 patients with pneumonia who were eligible for at least 1 National Hospital Quality Measure at an urban tertiary medical center from July 1, 2004, to June 30, 2008. We investigated the association of socioeconomic, demographic, clinical, and care delivery factors with process measure nonadherence, using multivariable analysis.
  
  
  RESULTS
  Demographic and socioeconomic variables were unrelated to heart failure measure adherence. Nonadherence with angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker use was more common in patients with renal failure (odds ratio [OR] 2.56; 95% confidence interval [CI], 1.46-4.49), and patients admitted to noncardiac units more often failed the heart failure all-or-none measure (OR 2.22; 95% CI, 1.79-2.75). Patients with pneumonia who were admitted via the emergency department were less likely to fail antibiotic timing (OR 0.41; 95% CI, 0.27-0.63), whereas those with a history of methicillin-resistant Staphylococcus aureus (OR 2.63; 95% CI, 1.31-5.28) or requiring intensive care unit admission (OR 11.4; 95% CI, 6.3-20.8) were more likely to fail the antibiotic selection measure.
  
  
  CONCLUSIONS
  Demographic and socioeconomic factors were generally unrelated to process measure nonadherence, demonstrating that excellent inpatient care can be delivered even to vulnerable populations. Clinical predictors suggest opportunities for improving both medical record documentation of appropriate exclusions and future measure specifications, especially for complex patients. Care delivery factors substantially affect process adherence.
authors.affiliation: Massachusetts General Hospital, Center for Quality and Safety, Department of Surgery, Harvard Medical School, Boston, 02114, USA. dshahian@partners.org
authors.forename: David M
authors.initials: DM
authors.lastname: Shahian
authors.forename: Paul
authors.initials: P
authors.lastname: Nordberg
authors.forename: Gregg S
authors.initials: GS
authors.lastname: Meyer
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Mort
authors.forename: Susan
authors.initials: S
authors.lastname: Atamian
authors.forename: Xiu
authors.initials: X
authors.lastname: Liu
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Karson
authors.forename: Hui
authors.initials: H
authors.lastname: Zheng
mesh_terms: D000328:Adult; D000368:Aged; D000806:Angiotensin-Converting Enzyme Inhibitors / Q000627:therapeutic use*; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D015897:Comorbidity; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D005260:Female; D019983:Guideline Adherence / Q000592:standards / Q000706:statistics & numerical data / Q000639:trends; D006333:Heart Failure / Q000188:drug therapy* / Q000453:epidemiology; D006786:Hospitals, Urban / Q000592:standards*; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D055624:Methicillin-Resistant Staphylococcus aureus; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D010343:Patient Admission; D011014:Pneumonia / Q000188:drug therapy* / Q000382:microbiology; D011237:Predictive Value of Tests; D017064:Process Assessment, Health Care / Q000379:methods; D019984:Quality Indicators, Health Care / Q000592:standards / Q000706:statistics & numerical data / Q000639:trends; D051437:Renal Insufficiency / Q000453:epidemiology; D016414:Resuscitation Orders; D018570:Risk Assessment; D012307:Risk Factors; D014481:United States / Q000453:epidemiology
chemical_list: D000806:Angiotensin-Converting Enzyme Inhibitors; D000900:Anti-Bacterial Agents