RESUMO
OBJECTIVE: To develop a method to allow a hospital to compare its performance using its entire patient population to the outcomes of very similar patients treated elsewhere. DATA SOURCES/SETTING: Medicare claims in orthopedics and common general, gynecologic, and urologic surgery from Illinois, New York, and Texas from 2004 to 2006. STUDY DESIGN: Using two example "focal" hospitals, each hospital's patients were matched to 10 very similar patients selected from 619 other hospitals. DATA COLLECTION/EXTRACTION METHODS: All patients were used at each focal hospital, and we found the 10 closest matched patients from control hospitals with exactly the same principal procedure as each focal patient. PRINCIPAL FINDINGS: We achieved exact matches on all procedures and very close matches for other patient characteristics for both hospitals. There were few to no differences between each hospital's patients and their matched control patients on most patient characteristics, yet large and significant differences were observed for mortality, failure-to-rescue, and cost. CONCLUSION: Indirect standardization matching can produce fair audits of quality and cost, allowing for a comprehensive, transparent, and relevant assessment of all patients at a focal hospital. With this approach, hospitals will be better able to benchmark their performance and determine where quality improvement is most needed.
Assuntos
Custos Hospitalares/estatística & dados numéricos , Medicare/estatística & dados numéricos , Avaliação de Resultados em Cuidados de Saúde/tendências , Qualidade da Assistência à Saúde/estatística & dados numéricos , Benchmarking/métodos , Humanos , Illinois , Modelos Estatísticos , New York , Avaliação de Resultados em Cuidados de Saúde/estatística & dados numéricos , Risco , Texas , Estados UnidosRESUMO
OBJECTIVE: Develop an improved method for auditing hospital cost and quality tailored to a specific hospital's patient population. DATA SOURCES/SETTING: Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, New York, and Texas between 2004 and 2006. STUDY DESIGN: A template of 300 representative patients from a single index hospital was constructed and used to match 300 patients at 43 hospitals that had a minimum of 500 patients over a 3-year study period. DATA COLLECTION/EXTRACTION METHODS: From each of 43 hospitals we chose 300 patients most resembling the template using multivariate matching. PRINCIPAL FINDINGS: We found close matches on procedures and patient characteristics, far more balanced than would be expected in a randomized trial. There were little to no differences between the index hospital's template and the 43 hospitals on most patient characteristics yet large and significant differences in mortality, failure-to-rescue, and cost. CONCLUSION: Matching can produce fair, directly standardized audits. From the perspective of the index hospital, "hospital-specific" template matching provides the fairness of direct standardization with the specific institutional relevance of indirect standardization. Using this approach, hospitals will be better able to examine their performance, and better determine why they are achieving the results they observe.
Assuntos
Benchmarking/métodos , Auditoria Financeira/métodos , Custos Hospitalares/estatística & dados numéricos , Medicare/economia , Medicare/estatística & dados numéricos , Avaliação de Resultados em Cuidados de Saúde/estatística & dados numéricos , Qualidade da Assistência à Saúde/estatística & dados numéricos , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Illinois , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , New York , Texas , Estados UnidosRESUMO
OBJECTIVE: Develop an improved method for auditing hospital cost and quality. DATA SOURCES/SETTING: Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, Texas, and New York between 2004 and 2006. STUDY DESIGN: A template of 300 representative patients was constructed and then used to match 300 patients at hospitals that had a minimum of 500 patients over a 3-year study period. DATA COLLECTION/EXTRACTION METHODS: From each of 217 hospitals we chose 300 patients most resembling the template using multivariate matching. PRINCIPAL FINDINGS: The matching algorithm found close matches on procedures and patient characteristics, far more balanced than measured covariates would be in a randomized clinical trial. These matched samples displayed little to no differences across hospitals in common patient characteristics yet found large and statistically significant hospital variation in mortality, complications, failure-to-rescue, readmissions, length of stay, ICU days, cost, and surgical procedure length. Similar patients at different hospitals had substantially different outcomes. CONCLUSION: The template-matched sample can produce fair, directly standardized audits that evaluate hospitals on patients with similar characteristics, thereby making benchmarking more believable. Through examining matched samples of individual patients, administrators can better detect poor performance at their hospitals and better understand why these problems are occurring.