Shyamala G. Nadathur

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It is important to factor-in the characteristics of patients that may affect treatment, outcome and resource when making clinical and administrative decisions, plans or policies. For some two and half decades there have been efforts to construct and refine instruments that endeavour to capture the concept of comorbidity. This paper focuses on such(More)
The selection of cohorts from national and state databases in Australia usually relies on patient diagnoses according to International Classification of Disease (ICD) codes and/or Diagnosis Related Groups (DRGs). The aim of this study was to select a specific cohort consisting of stroke and transient ischaemic attack (TIA) episodes, thereby allowing the(More)
Mandatory and standardised administrative data collections are prevalent in the largely public-funded acute sector. In these systems the data collections are used for financial, performance monitoring and reporting purposes. This paper comments on the infrastructure and standards that have been established to support data collection activities, audit and(More)
Information about the number and types of non-principal diagnoses (NPDs) would make an important contribution to prediction of outcome and hence patient management. The study reported here is based on analysis of three fiscal years of the Victorian public hospital transient ischaemic attack (TIA) and stroke admissions. The incidence of NPDs and(More)
This study uses hospital administrative data to ascertain the differences in the patient characteristics, process and outcomes of care between the Emergency Department (ED) triage categories of patients admitted from an ED presentation into a large metropolitan teaching hospital with a Stroke Care Unit. Bayesian Networks (BNs) derived from the(More)
dAtA MInInG In tHe HeAltH doMAIn As information systems are becoming more commonplace, healthcare routinely generates large clinical and administrative datasets in the process of patient care (Bates et al. AbstrAct Large datasets are regularly collected in biomedicine and healthcare (here referred to as the 'health domain'). These datasets have some unique(More)
Strategically there is a need to not only take a clinical process view of health care delivery but also identify the appropriate information to support the processes. When considering the clinical process view, the challenge for continuous quality improvement is to eliminate inappropriate process steps, and continuously document performance/outcome. The(More)
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