RESUMO
BACKGROUND: Hospital performance measures based on patient mortality and readmission have indicated modest rates of agreement. We examined if combining clinical data on laboratory tests and vital signs with administrative data leads to improved agreement with each other, and with other measures of hospital performance in the nation's largest integrated health care system. METHODS: We used patient-level administrative and clinical data, and hospital-level data on quality indicators, for 2007-2010 from the Veterans Health Administration (VA). For patients admitted for acute myocardial infarction (AMI), heart failure (HF) and pneumonia we examined changes in hospital performance on 30-d mortality and 30-d readmission rates as a result of adding clinical data to administrative data. We evaluated whether this enhancement yielded improved measures of hospital quality, based on concordance with other hospital quality indicators. RESULTS: For 30-d mortality, data enhancement improved model performance, and significantly changed hospital performance profiles; for 30-d readmission, the impact was modest. Concordance between enhanced measures of both outcomes, and with other hospital quality measures - including Joint Commission process measures, VA Surgical Quality Improvement Program (VASQIP) mortality and morbidity, and case volume - remained poor. CONCLUSIONS: Adding laboratory tests and vital signs to measure hospital performance on mortality and readmission did not improve the poor rates of agreement across hospital quality indicators in the VA. INTERPRETATION: Efforts to improve risk adjustment models should continue; however, evidence of validation should precede their use as reliable measures of quality.
Assuntos
Documentação/métodos , Disseminação de Informação/métodos , Indicadores de Qualidade em Assistência à Saúde/tendências , Qualidade da Assistência à Saúde/normas , Adulto , Idoso , Bases de Dados Factuais/tendências , Feminino , Insuficiência Cardíaca/epidemiologia , Insuficiência Cardíaca/mortalidade , Mortalidade Hospitalar , Humanos , Masculino , Informática Médica/métodos , Informática Médica/tendências , Pessoa de Meia-Idade , Infarto do Miocárdio/epidemiologia , Infarto do Miocárdio/mortalidade , Alta do Paciente/estatística & dados numéricos , Readmissão do Paciente/estatística & dados numéricos , Pneumonia/epidemiologia , Pneumonia/mortalidade , Estados Unidos/epidemiologia , United States Department of Veterans Affairs/organização & administração , United States Department of Veterans Affairs/estatística & dados numéricosRESUMO
OBJECTIVES: To examine the change in use of high-risk medications for the elderly (HRME), as defined by the National Committee on Quality Assurance's Healthcare Effectiveness Data and Information Set (HEDIS) quality measure (HEDIS HRME), by older outpatient veterans over a 3-year period and to identify risk factors for HEDIS HRME exposure overall and for the most commonly used drug classes. DESIGN: Longitudinal retrospective database analysis. SETTING: Outpatient clinics within the Department of Veterans Affairs (VA). PARTICIPANTS: Veterans aged 65 by October 1, 2003, and who received VA care at least once each year until September 30, 2006. MEASUREMENTS: Rates of use of HEDIS HRME overall and according to specific drug classes each year from fiscal year 2004 (FY04) to FY06. RESULTS: In a cohort of 1,567,467, high-risk medication exposure fell from 13.1% to 12.3% between FY04 and FY06 (P<.001). High-risk antihistamines (e.g., diphenhydramine), opioid analgesics (e.g., propoxyphene), skeletal muscle relaxants (e.g., cyclobenzaprine), psychotropics (e.g., long half-life benzodiazepines), endocrine (e.g., estrogen), and cardiac medications (e.g., short-acting nifedipine) had modest but statistically significant (P<.001) reductions (range -3.8% to -16.0%); nitrofurantoin demonstrated a statistically significant increase (+36.5%; P<.001). Overall HEDIS HRME exposure was more likely for men, Hispanics, those receiving more medications, those with psychiatric comorbidity, and those without prior geriatric care. Exposure was lower for individuals exempt from copayment. Similar associations were seen between ethnicity, polypharmacy, psychiatric comorbidity, access-to-care factors, and use of individual HEDIS HRME classes. CONCLUSION: HEDIS HRME drug exposure decreased slightly in an integrated healthcare system. Risk factors for exposure were not consistent across drug groups. Future studies should examine whether interventions to further reduce HEDIS HRME use improve health outcomes.