Health Information Management Journal

Patient (or person) master index (PMI) data quality activities in public, acute healthcare facilities in the state of Victoria, Australia were evaluated in terms of health information management-information technology best practice including data standards and practice guidelines. The findings indicate that, whilst data quality and linkage activities are undertaken, many are limited in scope or effectiveness. In view of published evidence that: (i) duplicate patient files pose significant risks by reducing information available for clinical decision-making; and (ii) quality and clinical risk management require, as a measurable outcome, continuous monitoring of duplicate files, improvements to PMI data quality practices are recommended.

The objective of this research was to document the most common first-recorded adverse events of inpatient care for lung cancer in Victoria, Australia. The sample comprised record abstracts for 3642 admissions (overnight or longer) of adult patients with lung cancer, extracted from the Victorian Admitted Episodes Database for 2000–2001. The method involved analysis of diagnoses prefixed with ‘C’ (an indicator for diagnoses which arose only after hospitalisation), calculation of complication rates by intervention type, and analysis of complication type by intervention. Overall, 23% of episodes recorded at least one in-hospital complication, with highest rates for radiotherapy and surgical interventions. The highest surgical complication rates were for pneumonectomies, lobectomies, and lung resections. Nausea and vomiting were the most common first-recorded complications for both chemotherapy and radiotherapy. It was concluded that complications through the use of morbidity data may offer a timely and economical method for health care organisations to screen large numbers of patient episodes.

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 researcher to examine current process of care using State level hospital admissions datasets. Difficulties in accurately selecting the specified cohort were encountered, due to various interpretations of ICD codes and DRGs as well as the placement of codes to DRGs and different classifications used. These difficulties highlighted several issues regarding the relationships between ICD coding and DRGs in stroke and TIA and are the focus of this paper.