RESUMO
We demonstrate the use of dynamic longitudinal models to investigate error management in cardiac surgery. Case study data were collected from a multicentre study of the neonatal arterial switch operation (ASO). Information on two types of negative events, or 'errors', observed during surgery, major and minor events, was extracted from case studies. Each event was judged to be recovered from (compensated) or not (uncompensated). The aim of the study was to model compensation given the occurrence of past events within a case. Two models were developed, one for the probability of compensating for a major event and a second model for the probability of compensating for a minor event. Analyses based on dynamic logistic regression models suggest that the total number of preceding minor events, irrespective of compensation status, is negatively related with the ability to compensate for major events. The alternative use of random effects models is investigated for comparison purposes.
Assuntos
Procedimentos Cirúrgicos Cardíacos/efeitos adversos , Erros Médicos/estatística & dados numéricos , Avaliação de Resultados em Cuidados de Saúde/estatística & dados numéricos , Transposição dos Grandes Vasos/cirurgia , Feminino , Humanos , Recém-Nascido , Comunicação Interdisciplinar , Modelos Logísticos , Masculino , Modelos Estatísticos , Avaliação de Resultados em Cuidados de Saúde/métodos , Equipe de Assistência ao Paciente/normas , Probabilidade , Reino UnidoRESUMO
A robust likelihood approach for the analysis of overdispersed correlated count data that takes into account cluster varying covariates is proposed. We emphasise two characteristics of the proposed method: That the correlation structure satisfies the constraints on the second moments and that the estimation of the correlation structure guarantees consistent estimates of the regression coefficients. In addition we extend the mean specification to include within- and between-cluster effects. The method is illustrated through the analysis of data from two studies. In the first study, cross-sectional count data from a randomised controlled trial are analysed to evaluate the efficacy of a communication skills training programme. The second study involves longitudinal count data which represent counts of damaged hand joints in patients with psoriatic arthritis. Motivated by this study, we generalize our model to accommodate for a subpopulation of patients who are not susceptible to the development of damaged hand joints.
