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Open Access Research article

Is hospital discharge administrative data an appropriate source of information for cancer registries purposes? Some insights from four Spanish registries

Enrique Bernal-Delgado E1*, Carmen Martos2, Natalia Martínez1, María Dolores Chirlaque47, Mirari Márquez47, Carmen Navarro47, Lauro Hernando5, Joaquín Palomar5, Isabel Izarzugaza37, Nerea Larrañaga3, Olatz Mokoroa3, M Cres Tobalina3, Joseba Bidaurrazaga3, María José Sánchez67, Carmen Martínez67, Miguel Rodríguez67, Esther Pérez67 and Yoe Ling Chang67

Author Affiliations

1 Health Services Research Unit, Institute for Health Sciences in Aragon, Zaragoza, Spain

2 Zaragoza Cancer Registry, Department of Health, Zaragoza, Spain

3 Basque-Country Cancer Registry, Department of Health, Vitoria-Gasteiz, Spain

4 Murcia Cancer Registry at Public Health Department, Regional Health Council, Murcia, Spain

5 Planning and Health Financing Department, Regional Health Council, Murcia, Spain

6 Granada Cancer Registry, Andalusian School of Public Health, Granada, Spain

7 Network for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain

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BMC Health Services Research 2010, 10:9  doi:10.1186/1472-6963-10-9

Published: 8 January 2010

Abstract

Background

The use of hospital discharge administrative data (HDAD) has been recommended for automating, improving, even substituting, population-based cancer registries. The frequency of false positive and false negative cases recommends local validation.

Methods

The aim of this study was to detect newly diagnosed, false positive and false negative cases of cancer from hospital discharge claims, using four Spanish population-based cancer registries as the gold standard. Prostate cancer was used as a case study.

Results

A total of 2286 incident cases of prostate cancer registered in 2000 were used for validation. In the most sensitive algorithm (that using five diagnostic codes), estimates for Sensitivity ranged from 14.5% (CI95% 10.3-19.6) to 45.7% (CI95% 41.4-50.1). In the most predictive algorithm (that using five diagnostic and five surgical codes) Positive Predictive Value estimates ranged from 55.9% (CI95% 42.4-68.8) to 74.3% (CI95% 67.0-80.6). The most frequent reason for false positive cases was the number of prevalent cases inadequately considered as newly diagnosed cancers, ranging from 61.1% to 82.3% of false positive cases. The most frequent reason for false negative cases was related to the number of cases not attended in hospital settings. In this case, figures ranged from 34.4% to 69.7% of false negative cases, in the most predictive algorithm.

Conclusions

HDAD might be a helpful tool for cancer registries to reach their goals. The findings suggest that, for automating cancer registries, algorithms combining diagnoses and procedures are the best option. However, for cancer surveillance purposes, in those cancers like prostate cancer in which care is not only hospital-based, combining inpatient and outpatient information will be required.