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Appl Clin Inform ; 6(1): 96-109, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-25848416

RESUMO

BACKGROUND: Hospital length of stay and discharge destination are important outcome measures in evaluating effectiveness and efficiency of health services. Although hospital administrative data are readily used as a data collection source in health services research, no research has assessed this data collection method against other commonly used methods. OBJECTIVE: Determine if administrative data from electronic patient management programs are an effective data collection method for key hospital outcome measures when compared with alternative hospital data collection methods. METHOD: Prospective observational study comparing the completeness of data capture and level of agreement between three data collection methods; manual data collection from ward-based sources, administrative data from an electronic patient management program (i.PM), and inpatient medical record review (gold standard) for hospital length of stay and discharge destination. RESULTS: Manual data collection from ward-based sources captured only 376 (69%) of the 542 inpatient episodes captured from the hospital administrative electronic patient management program. Administrative data from the electronic patient management program had the highest levels of agreement with inpatient medical record review for both length of stay (93.4%) and discharge destination (91%) data. CONCLUSION: This is the first paper to demonstrate differences between data collection methods for hospital length of stay and discharge destination. Administrative data from an electronic patient management program showed the highest level of completeness of capture and level of agreement with the gold standard of inpatient medical record review for both length of stay and discharge destination, and therefore may be an acceptable data collection method for these measures.


Assuntos
Coleta de Dados/métodos , Tempo de Internação/estatística & dados numéricos , Alta do Paciente/estatística & dados numéricos , Mineração de Dados , Tomada de Decisões , Feminino , Política de Saúde , Administração Hospitalar/estatística & dados numéricos , Humanos , Masculino , Pessoa de Meia-Idade , Avaliação de Resultados em Cuidados de Saúde
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