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French Claims Data as a Source of Information to Describe Cancer Incidence: Predictive Values of Two Identification Methods of Incident Prostate Cancers

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Abstract

Claims data from the “Programme de Médicalisation du Système d’Information” (PMSI) have been commonly used for several years to complement cancer registries and describe cancer incidence in France. It is less clear whether or not it is possible to use these data as an independent source of information to assess cancer incidence, in the absence of a regional cancer registry. Following a similar study on breast cancer, we present a study which aimed to evaluate two methods of identifying incident prostate cancer using claims data. These methods were developed using claims data from the Hospices Civils de Lyon (HCL) and their validity was tested against medical records. The first method (M1) identified incident patients as those who had at least one stay with a principal diagnosis of prostate cancer. The second method (M2) had a prostate cancer treatment code in addition to the criteria for the first method. Both methods of identification had similar results, indicating a low rate of false negatives (negative predictive values: M1=100 [CI95: 93.8–100], M2=98.6 [CI95: 90.1–99.6]) and a high rate of false positives (positive predictive values: M1=33.3 [CI95: 23.2–42.1], M2=33.7 [CI95: 24.2–43.2]). The sample size did not allow us to produce consistent estimates of sensitivity and specificity. Our results showed that an estimation of the number of incident cases of prostate cancer using both methods of identification would be biased because of the high rate of false positives. Statistical methods that correct identification errors should be used.

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Reference

  1. Comité National des Registres, Rapport d’activité 1996–1999. Direction Générale de la Santé, Inserm, Institut de Veille Sanitaire. 2000.

  2. Remontet, L., Esteve, J., Bouvier, A. M., Grosclaude, P., Launoy, G., Menegoz, F., et al., Cancer incidence and mortality in France over the period 1978–2000. Rev. Epidemiol. Sante Publique 51(1 Pt 1):3–30, 2003.

    Google Scholar 

  3. Circulaire DH/P.M.S.I. no. 303 du 24 juillet 1989 relative à la généralisation du programme de médicalisation des systèmes d’information (PMSI) et à l’organisation de l’information médicale dans les hôpitaux publics. Bulletin Officiel SAN no. 89/46.

  4. Circulaire no. 325 du 12 février 1990 relative aux modalités de mise en place des structures de gestion de l’information médicale dans les établissements hospitaliers publics et privés participant au service public.

  5. Schott, A. M., Hajri, T., Colin, C., Grateau, F., Gilly, F. N., Tissot, E., et al., Intérêt de l’utilisation du PMSI pour l’analyse d’activité cancérologique d’une structure de soins multidisciplinaires. L’expérience de la coordination de cancérologie des Hospices Civils de Lyon. Bull. Cancer 89(11):969–73, 2002.

    Google Scholar 

  6. Dussaucy, A., Viel, J. F., Mulin, B., Euvrard, J., and L’outil, P. M. S. I., Biais, sources d’erreurs et conséquences. Rev. Epidemiol. Sante Publique 42(4):345–358, 1994.

    Google Scholar 

  7. Lombrail, P., Minvielle, E., Comar, L., and Gottot, S., Programme de Médicalisation des Systèmes d’Information et épidémiologie : une liaison qui ne va pas de soi. Rev. Epidemiol. Sante Publique 42(4):334–44, 1994.

    Google Scholar 

  8. Couris, C. M., Les bases de données médico-administratives hospitalières comme source d’information permanente pour l’épidémiologie descriptive du cancer. Thèse de doctorat no. 234, Lyon, 2001.

  9. Couris, C. M., Schott, A. M., Ecochard, R., and Colin, C., A literature review to assess the use of claims databases in identifying cancer incident cases. Health Serv. Outcomes Res. Methodol. 4:49–63, 2003.

    Article  Google Scholar 

  10. Whittle, J., Steinberg, E. P., Anderson, G. F., and Herbert, R., Accuracy of medicare claims data for estimation of cancer incidence and resection rates among elderly Americans. Med. Care 29(12):1226–1236, 1991.

    Article  Google Scholar 

  11. McBean, A. M., Babish, J. D., and Warren, J. L., Determination of lung cancer incidence in the elderly using Medicare claims data. Am. J. Epidemiol. 137(2):226–234, 1993.

    Google Scholar 

  12. McBean, A. M., Warren, J. L., and Babish, J. D., Measuring the incidence of cancer in elderly Americans using Medicare claims data. Cancer 73(9):2417–2425, 1994.

    Article  Google Scholar 

  13. Solin, L. J., Legorreta, A., Schultz, D. J., Levin, H. A., Zatz, S., Goodman, R. L., Analysis of a claims database for the identification of patients with carcinoma of the breast. J. Med. Syst. 18(1):23–32, 1994.

    Article  Google Scholar 

  14. Solin, L. J., MacPherson, S., Schultz, D. J., and Hanchak, N. A., Evaluation of an algorithm to identify women with carcinoma of the breast. J. Med. Syst. 21(3):189–199, 1997.

    Article  Google Scholar 

  15. Leung, K. M., Hasan, A. G., Rees, K. S., Parker, R. G., and Legorreta, A. P., Patients with newly diagnosed carcinoma of the breast: validation of a claim-based identification algorithm. J. Clin. Epidemiol. 52(1):57–64, 1999.

    Article  Google Scholar 

  16. McClish, D. K., Penberthy, L., Whittemore, M., Newschaffer, C., Woolard, D., Desch, C. E., et al., Ability of Medicare claims data and cancer registries to identify cancer cases and treatment. Am. J. Epidemiol. 145(3):227–233, 1997.

    Google Scholar 

  17. Warren, J. L., Riley, G. F., McBean, A. M., and Hakim, R., Use of medicare data to identify incident breast cancer cases. Health Care Financ. Rev. 18(1):237–246, 1996.

    Google Scholar 

  18. Warren, J. L., Feuer, E., Potosky, A. L., Riley, G. F., and Lynch, C. F., Use of Medicare hospital and physician data to assess breast cancer incidence. Med. Care 37(5):445–456, 1999.

    Article  Google Scholar 

  19. Cooper, G. S., Yuan, Z., Stange, K. C., Dennis, L. K., Amini, S. B., and Rimm, A. A., The sensitivity of Medicare claims data for case ascertainment of six common cancers. Med. Care 37(5):436–444, 1999.

    Article  Google Scholar 

  20. Freeman, J. L., Zhang, D., Freeman, D. H., and Goodwin, J. S., An approach to identifying incident breast cancer cases using Medicare claims data. J. Clin. Epidemiol. 53(6):605–614, 2000.

    Article  Google Scholar 

  21. Wang, P. S., Walker, A. M., Tsuang, M. T., Orav, E. J., Levin, R., and Avorn, J., Finding incident breast cancer cases through US claims data and a state cancer registry. Cancer Causes Control 12(3):257–265, 2001.

    Article  Google Scholar 

  22. Couris, C. M., Foret-Dodelin, C., Rabilloud, M., Colin, C., Bobin, J. Y., Dargent, D., et al., Sensibilité et spécificité de deux méthodes d’identification des cancers du sein incidents dans les services spécialisés à partir des données médico-administratives. Rev. Epidemiol. Sante. Publique 52(2):151–160, 2004.

    Google Scholar 

  23. Cooper, G. S., Yuan, Z., Jethva, R. N., and Rimm, A. A., Determination of county-level prostate carcinoma incidence and detection rates with Medicare claims data. Cancer 92(1):102–109, 2001.

    Article  Google Scholar 

  24. Lacour, B., Laurent, J. F., Lenfant, M. H., Loeb, A., Peuvrel, P., Sauvage, M., et al., Manuel de procédures PMSI en cancérologie. Bull. Cancer 88(2):209–218, 2001.

    Google Scholar 

  25. Couris, C. M., Colin, C., Rabilloud, M., Schott, A. M., and Ecochard, R., Method of correction to assess the number of hospitalized incident breast cancer cases based on claims databases. J. Clin. Epidemiol. 55(4):386–391, 2002.

    Article  Google Scholar 

  26. Couris, C. M., Rabilloud, M., Colin, C., and Ecochard, R., Two-phase study to assess the number of cases based on claims databases: characteristics of the validation data set. Methods Inf. Med. 41(4):349–356, 2002.

    Google Scholar 

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Acknowledgements

The authors wish to thank doctors E. Morgon and P. Messy for their help and advice for the analysis of the French claims data. We also thank Ms. L. Ducharne for her effective management of contacts with departments.

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Correspondence to Chantal Marie Couris.

 

 

ANNEX I. Diagnosis Codes (ICD-10) and Procedure Codes (French Catalog of the Medical Acts, 2000) used for the Identification of Incident Prostate Cancer

 

Codes

Tumor diagnosis codes

C61, D075

Surgical procedures

J975, N320, N322, N324, N325, N326, N399, N400, N484, N501, N502, N573, N574, N622

Ultrasound procedures

N571

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Couris, C.M., Seigneurin, A., Bouzbid, S. et al. French Claims Data as a Source of Information to Describe Cancer Incidence: Predictive Values of Two Identification Methods of Incident Prostate Cancers. J Med Syst 30, 459–463 (2006). https://doi.org/10.1007/s10916-006-9028-x

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