The article discusses the Connecting Healthcare conference that was held in Sydney from 11-12 February 2009. The main aim of the conference was to highlight the need to bring together all patient information currently held separately and make it electronically available to both healthcare providers and the consumers.

This article briefly relates the experience of a clinical coder working in the private healthcare sector in the Australian state of New South Wales and questions whether it is possible to work in this environment while adhering to the Clinical Coders' Creed. Private facilities in Australia that handle acute, psychiatric, respite and rehabilitation cases, rely mainly upon health insurance funds for reimbursement for episodes of care, which are funded according to DRGs based on codes assigned by clinical coders. The point is made that while all coders strive to fully and accurately describe the clinical episode of care regardless of healthcare setting, a distinction can be drawn between public and private sector coding in relation to financial contracts, which form the basis of private health care. Therefore, it is recommended that private sector coders familiarise themselves with this "C" as well as the other seven "Cs" of the Clinical Coders' Creed.

The Performance Indicators for Coding Quality (PICQ) is a data quality assessment tool developed by Australia's National Centre for Classification in Health (NCCH). PICQ consists of a number of indicators covering all ICD-10-AM disease chapters, some procedure chapters from the Australian Classification of Health Intervention (ACHI) and some Australian Coding Standards (ACS). The indicators can be used to assess the coding quality of hospital morbidity data by monitoring compliance of coding conventions and ACS; this enables the identification of particular records that may be incorrectly coded, thus providing a measure of data quality. There are 31 obstetric indicators available for the ICD-10-AM Fourth Edition. Twenty of these 31 indicators were classified as Fatal, nine as Warning and two Relative. These indicators were used to examine coding quality of obstetric records in the 2004-2005 financial year Australian national hospital morbidity dataset. Records with obstetric disease or procedure codes listed anywhere in the code string were extracted and exported from the SPSS source file. Data were then imported into a Microsoft Access database table as per PICQ instructions, and run against all Fatal and Warning and Relative (N=31) obstetric PICQ 2006 Fourth Edition Indicators v.5 for the ICD-10- AM Fourth Edition. There were 689,905 gynaecological and obstetric records in the 2004-2005 financial year, of which 1.14% were found to have triggered Fatal degree errors, 3.78% Warning degree errors and 8.35% Relative degree errors. The types of errors include completeness, redundancy, specificity and sequencing problems. It was found that PICQ is a useful initial screening tool for the assessment of ICD-10-AM/ACHI coding quality. The overall quality of codes assigned to obstetric records in the 2004- 2005 Australian national morbidity dataset is of fair quality.

This study was two-fold in nature. Initially, it examined the information environment and the use of customary information tools to support medical handovers in a large metropolitan teaching hospital on four weekends (i.e. Friday night to Monday morning). Weekend medical handovers were found to involve sequences of handovers where patients were discussed at the discretion of the doctor handing over; no reliable discussion of all patients of concern occurred at any one handover, with few information tools being used; and after a set of weekend handovers, there was no complete picture on a Monday morning without an analysis of all patient progress notes. In a subsequent case study, three information tools specifically designed as intervention that attempted to enrich the information environment were evaluated. Results indicate that these tools did support greater continuity in who was discussed but not in what was discussed at handover. After the intervention, if a doctor discussed a patient at handover, that patient was more likely to be discussed at subsequent handovers. However, the picture at Monday morning remained fragmentary. The results are discussed in terms of the complexities inherent in the handover process.

It can be predicted that a substantial number of patients will seek medical care during a possible disaster, placing an increased strain on hospital resources, including health information services. With medical records playing a vital role in the identification of patients and documentation of patient care, the ability of the health information system to cope with this projected surge in demand needs to be addressed. This study was designed to investigate the expected use of specialised health information systems for disasters in Victorian hospitals during such contingencies. Specifically, this study investigated what type of specialised systems hospitals had in place at the time and whether a standard for specialised health information systems for disasters was needed. While 79% of responding hospitals reported having a specialised health information system for disasters, 91% of all responding hospitals reported that specialised health information systems for disasters were necessary. All specialised systems were paper-based, and 94% were based on the standard medical record format and content. Finally, 64% of hospitals believed that a Standard for specialised disaster medical records should be developed.