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Open Access Research article

Indicators of breast cancer severity and appropriateness of surgery based on hospital administrative data in the Lazio Region, Italy

Patrizia Schifano1*, Paolo Papini2, Nera Agabiti2, Marina Scarinci3, Piero Borgia2 and Carlo A Perucci1

Author Affiliations

1 Department of Epidemiology, Health Local Unit RME, Rome, Italy

2 Agency of Public Health, Lazio Region, Italy

3 Department of Preventive Medicine, Health Local Unit RMD, Rome, Italy

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BMC Public Health 2006, 6:25  doi:10.1186/1471-2458-6-25

Published: 7 February 2006

Abstract

Background

Administrative data can serve as an easily available source for epidemiological and evaluation studies. The aim of this study is to evaluate the use of hospital administrative data to determine breast cancer severity and the appropriateness of surgical treatment.

Methods

the study population consisted of 398 patients randomly selected from a cohort of women hospitalized for first-time breast cancer surgery in the Lazio Region, Italy. Tumor severity was defined in three different ways: 1) tumor size; 2) clinical stage (TNM); 3) severity indicator based on HIS data (SI). Sensitivity, specificity, and positive predictive value (PPV) of the severity indicator in evaluating appropriateness of surgery were calculated. The accuracy of HIS data was measured using Kappa statistic.

Results

Most of 387 cases were classified as T1 and T2 (tumor size), more than 70% were in stage I or II and the SI classified 60% of cases in medium-low category. Variation from guidelines indications identified under and over treatments. The accuracy of the SI to predict under-treatment was relatively good (58% of all procedures classified as under-treatment using pT where also classified as such using SI), and even greater predicting over-treatment (88.2% of all procedures classified as over treatment using pT where also classified as such using SI). Agreement between clinical chart and hospital discharge reports was K = 0.35.

Conclusion

Our findings suggest that administrative data need to be used with caution when evaluating surgical appropriateness, mainly because of the limited ability of SI to predict tumor size and the questionable quality of HIS data as observed in other studies.