Kerry Innes

An evaluation of the quality of obstetric morbidity coding using an objective assessment tool, the Performance Indicators for Coding Quality (PICQ)

The Performance Indicators for Coding Quality (PICQ) is a data quality assessment tool developed by Australias 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.

SNOMED CT and Its Place in Health Information Management Practice

The Systematized Nomenclature of Medicine-Clinical Terminology (SNOMED CT) is a clinical terminology that describes and defines clinical entities. It facilitates input of clinical recording of clinical information in an electronic health record.

ICD-10-AM/ACHI/ACS and AR-DRG Development Services

The Department of Health and Ageing (DoHA) has contracted The University of Wollongong (UOW) until 30 June 2013 to refine the Australian Refined Diagnosis Related Group (AR-DRG)1 Classification System. The AR-DRG Classification System includes the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM), the Australian Classification of Health Interventions (ACHI), the Australian Coding Standards (ACS), and the AR-DRG classification. The ICD-10-AM/ACHI/ACS component is currently managed under a DoHA contract by the National Centre for Classification in Health (NCCH), The University of Sydney. The AR-DRG is managed by DoHA in Canberra. The AR-DRG Classification System is used to classify episodes of care in Australian hospitals. It is also used in about 10 other countries. The Centre for Health Service Development (CHSD) will develop the 2012 versions of these products, with a planned national implementation date of 1 July 2013 for both ICD-10-AM/ACHI/ACS and AR-DRG. Users of these classifications should not see any major alteration in the services provided as the transition takes place over the coming months. We will keep the HIM/clinical coder workforce informed of progress. The CHSD is a research centre of UOW’s Sydney Business School and will undertake its expanded role from the Sydney Business School headquarters in Liverpool Street, Sydney, and from its main centre at the UOW campus. The CHSD will receive more than

Australian coding standards for ICD-10-AM and ACHI

9 million over three years for the project, which is expected to involve about 20 staff positions. ‘This is a great opportunity for the CHSD, and it builds on the research we have been doing for more than a decade’ according to CHSD Director, Professor Kathy Eagar2.