Quality of diagnosis and procedure coding in ICD-10 administrative data.

OBJECTIVES: The International Classification of Disease, 10th Revision (ICD-10) was introduced worldwide beginning in the late 1990s. Because there have been no published data on the quality of coding using ICD-10, the aim of our analysis is to assess the quality of ICD-10 coding in routinely collected hospital discharge data from Australia, which began using ICD-10 in 1998. METHODS: Audit data from the years 1998-1999 (n = 7004) and 2000-2001 (n = 7631), excluding same-day chemotherapy and dialysis cases, were used in data analysis. Quality measures included prevalence comparisons, sensitivity, positive predictive value (PPV), and the kappa statistic. RESULTS: Comparison of the audit sample to public hospital discharges showed little difference in age and gender, with audited cases more likely to be overnight stays. There was no difference in the median number of hospital assigned diagnosis and procedure codes per discharge. Agreement of the principal diagnosis code was 85% at the 3-digit level and 79% at the 4-digit level in 1998-1999; this rate had improved to 87% and 81% in 2000-2001. Principal procedure code agreement was 85% in 1998-1999 and 83% in 2000-2001 at the 5-digit level, and 81% and 80% at the 7-digit level, respectively. Specific major diagnoses, comorbid diagnoses, major procedures, and minor procedures showed good-to-excellent coding quality. CONCLUSIONS: The transition to ICD-10 has occurred with no loss of data quality, with data showing a high level of reliability and adherence to coding standards. When consideration is given to the nature of the analysis, administrative data can provide highly reliable population-based estimates of hospitalization rates.

New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality.

BACKGROUND AND OBJECTIVE: The ICD-9-CM adaptation of the Charlson comorbidity score has been a valuable resource for health services researchers. With the transition into ICD-10 coding worldwide, an ICD-10 version of the Deyo adaptation was developed and validated using population-based hospital data from Victoria, Australia. METHODS: The algorithm was translated from ICD-9-CM into ICD-10-AM (Australian modification) in a multistep process. After a mapping algorithm was used to develop an initial translation, these codes were manually examined by the coding experts and a general physician for face validity. Because the ICD-10 system is country specific, our goal was to keep many of the translated code at the three-digit level for generalizability of the new index. RESULTS: There appears to be little difference in the distribution of the Charlson Index score between the two versions. A strong association between increasing index scores and mortality exists: the area under the ROC curve is 0.865 for the last year using the ICD-9-CM version and remains high, at 0.855, for the ICD-10 version. CONCLUSION: This work represents the first rigorous adaptation of the Charlson comorbidity index for use with ICD-10 data. In comparison with a well-established ICD-9-CM coding algorithm, it yields closely similar prevalence and prognosis information by comorbidity category.

Effects of increased private health insurance on hospital utilisation in Victoria.

The proportion of Victorians and Australians generally with private health insurance (PHI) increased from 31% in 1998 to 45% in 2001. We analysed a dataset containing all hospital separations throughout Victoria to determine whether changes in the level of private health insurance have had any impact on patterns of public and private hospital utilisation in Victoria. Total utilisation of private hospitals grew by 31% from 1998-99 to 2002-03, whereas utilisation of public hospitals increased by 18%. Total bed-days have increased in both private hospitals and public hospitals by 12%. The proportion of all separations at private hospitals has remained relatively stable between these 2 years, with 33% of all separations being private patients in private hospitals in 1998-99, increasing slightly to 35% by 2002-03. Analysis of a number of specific DRGs shows that patients with more severe disease are more likely to be seen at public hospitals; notably this trend has strengthened between 1998-99 and 2002-03. The number of patients treated in Victorian public hospitals has continued to grow, despite a rapid increase in the utilisation of private hospitals. Given the limited extent of the shift in caseload share between the two sectors, the effectiveness of the Commonwealth's subsidy of private health insurance as a mechanism to reduce pressure on the public sector needs to be carefully examined.

Congestive cardiac failure: urban and rural perspectives in Victoria.

OBJECTIVE: Effective and timely care for congestive cardiac failure (CCF) should reduce the risks of hospitalisation. The purpose of this study is to describe variations in rates of hospital admissions for CCF in Victoria as an indicator of the adequacy of primary care services. Detailed analyses identify trends in hospitalisations, urban/rural differentials and variations by the Primary Care Partnerships (PCP). SETTING: Acute care hospitals in Victoria. DESIGN: Routine analyses of age and sex standardised admission rates of CCF in Victoria using the Victorian Admitted Episodes Dataset from 1993-1994 to 2000-2001. SUBJECTS: All patients admitted to acute care hospitals in Victoria with the principal diagnosis of CCF between 1993-1994 and 2000-2001. RESULTS: There were 8359 admissions for CCF in Victoria with an average of 7.37 bed days in 2000-2001. There was a significantly higher admission rate for CCF in rural areas compared to metropolitan in 2000/200--(2.53/1000 (2.44-2.62) and 1.80/1000 (1.75-1.85))--respectively. Small area analyses identified 17 PCP (14 of which were rural) with significantly higher admission rate ratios of CCF compared to Victoria. CONCLUSION: Small area analyses of CCF have identified significant gaps in the management of CCF in the community. This may be a reflection of deficit in primary care availability, accessibility, or appropriateness. Detailed studies may be needed to determine the relative importance of these factors in Victoria for targeting specific interventions at the PCP level.