In recent years there has been a steady increase in the number of patients being discharged within five days of coronary artery bypass graft surgery. The ability to be able to predict those patients likely to be discharged within five days of surgery is important to improve the individual patient pathway, plan resources and surgical activity, and also to achieve current policy objectives. Guided by the theory of Stress, Appraisal and Coping (Lazarus and Folkman, 1984), the aim of this observational study was to develop and validate local multivariate models from preoperative patient variables for the purpose of predicting postoperative length of stay and discharge within five days of surgery. The study also investigated the influence of previously neglected psychological variables on these outcomes. The study was conducted in two phases: Phase I A cross-sectional survey design was used for univariate and multivariate analyses of thirty one empirically or theoretically derived variables. Previously collected data was retrospectively analysed for 1043 consecutive patients undergoing first time isolated coronary artery bypass graft surgery at a single National Health Service trust during 2005. By univariate analysis twenty variables were found to be associated with postoperative length of stay as a continuous variable, and as a categorical dichotomy of either less than or equal to five days or more than five days. Multivariate analysis of these variables showed that both postoperative length of stay and discharge within five days of surgery were poorly predicted. However, the models developed were much better at predicting postoperative lengths of stay greater than five days. Phase II Another cohort of 503 patients was used to prospectively validate the models. The potential influence of perceived stress and health locus of control was also investigated. These variables were not associated with either outcome. This study identified areas for further research, including the potential of other psychosocial variables to improve the predictive ability of the models. This would increase the utility of the models in practice and contribute to improvements in both the quality of the patient journey and the business objectives of healthcare organisations.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:520940 |
| Date | January 2010 |
| Creators | Burrough, Michelle Geraldine |
| Publisher | City University London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://openaccess.city.ac.uk/12135/ |
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