Development of a validation algorithm for 'present on admission' flagging.

BACKGROUND: The use of routine hospital data for understanding patterns of adverse outcomes has been limited in the past by the fact that pre-existing and post-admission conditions have been indistinguishable. The use of a 'Present on Admission' (or POA) indicator to distinguish pre-existing or co-morbid conditions from those arising during the episode of care has been advocated in the US for many years as a tool to support quality assurance activities and improve the accuracy of risk adjustment methodologies. The USA, Australia and Canada now all assign a flag to indicate the timing of onset of diagnoses. For quality improvement purposes, it is the 'not-POA' diagnoses (that is, those acquired in hospital) that are of interest. METHODS: Our objective was to develop an algorithm for assessing the validity of assignment of 'not-POA' flags. We undertook expert review of the International Classification of Diseases, 10th Revision, Australian Modification (ICD-10-AM) to identify conditions that could not be plausibly hospital-acquired. The resulting computer algorithm was tested against all diagnoses flagged as complications in the Victorian (Australia) Admitted Episodes Dataset, 2005/06. Measures reported include rates of appropriate assignment of the new Australian 'Condition Onset' flag by ICD chapter, and patterns of invalid flagging. RESULTS: Of 18,418 diagnosis codes reviewed, 93.4% (n = 17,195) reflected agreement on status for flagging by at least 2 of 3 reviewers (including 64.4% unanimous agreement; Fleiss' Kappa: 0.61). In tests of the new algorithm, 96.14% of all hospital-acquired diagnosis codes flagged were found to be valid in the Victorian records analysed. A lower proportion of individual codes was judged to be acceptably flagged (76.2%), but this reflected a high proportion of codes used <5 times in the data set (789/1035 invalid codes). CONCLUSION: An indicator variable about the timing of occurrence of diagnoses can greatly expand the use of routinely coded data for hospital quality improvement programmes. The data-cleaning instrument developed and tested here can help guide coding practice in those health systems considering this change in hospital coding. The algorithm embodies principles for development of coding standards and coder education that would result in improved data validity for routine use of non-POA information.

Do we have enough information? How ICD-10-AM Activity codes measure up.

This research explored the usage of activity codes introduced into the International Statistical Classification of Diseases and Related Health Problems, Tenth revision, Australian Modification (ICD-10-AM) Third Edition and examined the data quality of activity coding, explicitly, completeness and specificity. Injury separations for years 2001/02 to 2005/06 specifying a 'true injury' were extracted for descriptive analyses. Part A investigated the usage of activity codes and compared the usage of the 236 activity codes available in the Activity block (U50-U73) present in the ICD-10-AM Third Edition against the 16 codes present in the second edition. Part B examined the level of completeness of external cause coding and the degree of activity coding specificity in the 2005/06 dataset. It was found that the additional activity codes were used extensively with only 46 codes seldom assigned. Codes present in the second edition were extensively used in the third and fourth editions and the new additional activity codes represent 10% of all activity codes assigned per year. All five datasets demonstrated high levels of completeness, recording completeness levels greater than 97%, where missing activity codes attributed to the majority of missing codes. Fourteen out of the 24 activity categories demonstrated a strong reliance on non-specific codes and Team ball sports and Wheeled non-motor sports illustrated that activity codes assigned lacked detail in the code. Clinicians and coders need to acknowledge the importance of quality clinical documentation for research and policy-making purposes so that circumstances surrounding injury events can be coded to the highest level of specificity to improve injury prevention and control activities. Missing activity codes and the abundance of non-specific coding hinders the usefulness of the data.

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 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.

Care of patients with stomas: the pouch change procedure.

This article discusses basic stoma care in relation to management of the pouch change procedure in a ward-based setting immediately following planned stoma-forming surgery. The article highlights psychological and practical preparation of the patient. It describes the equipment that is needed to change a pouch and examines the rationale and evidence base for the procedure.

Creating the evidence base: the journey from practice to research.

The ability to deliver accurate, evidence-based information when helping patients make decisions about their care is fundamental to the role of the clinical nurse specialist. For patients with ulcerative colitis who are considering surgery to form an ileo-anal pouch, it is essential to give them information about the psychosocial, as well as the physical, effects of such surgery. As many of these patients are of working age, understanding the likely consequences for paid employment is a priority. However, very little evidence is available on this subject. The authors therefore decided to develop a research study aimed at filling this gap. A proposal to conduct a phenomenological study into the subsequent employment experiences of patients who have undergone ileo-anal pouch formation has been developed. This article seeks to explore how the research idea and its methodology stemmed from practice and highlights the importance of seeing research and practice as complementary components of good nursing care.