Breast cancer incidence using administrative data: correction with sensitivity and specificity.

OBJECTIVE: To estimate breast cancer incidence in the general population using a method that corrects for lack of sensitivity and specificity in the identification of incident breast cancer in inpatient claims data. STUDY DESIGN AND SETTINGS: Two-phase study: phase 1 to identify incident cases in claims data, and phase 2 to estimate sensitivity and specificity in a subset of the population. Two algorithms (1: principal diagnosis; 2: principal diagnosis+specific surgery procedures) were used to identify incident cases in claims of women aged 20 years or older, living in a French district covered by a cancer registry. Sensitivity and specificity were estimated in one district and used to correct incident cases identified. RESULTS: The sensitivity and specificity for algorithms 1 and 2 were 69.0% and 99.89%, and 64.4% and 99.93%, respectively. In contrast to specificity, the sensitivity for both algorithms was lower for women younger than 40 years and older than 65 years. Cases reported by cancer registries were closer to cases identified with algorithm 2 (-3.2% to +20.1%) and to corrected numbers with algorithm 1 (-1% to +15%). CONCLUSION: To obtain reliable estimates of breast cancer incidence in the general population, sensitivity and specificity, which reflect medical and coding practice variations, are necessary.

French claims data as a source of information to describe cancer incidence: predictive values of two identification methods of incident prostate cancers.

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.

[Analysis of the medical activity related to cancer in a network of multidisciplinary hospitals using claims databases, the reseau Concorde Oncology Network]. / Estimation et analyse de l'activité cancérologique d'un ensemble d'établissements participant à un réseau régional à partir des données du PMSI, le réseau Concorde.

Recently, to answer patients, caregivers and professionals needs, the "Plan Cancer" has been presented by the French Government. This plan is intended to improve quality of care in cancer patients and finally, patients' survival and quality of life. This planned strategy stresses the importance of organized interactions between hospitals and between the various health professionals. Measuring the number of patients with cancer and the activity related to cancer in large networks of multidisciplinary hospitals has became a real challenge in France for organizational, quality of care and economic reasons. Many University Hospitals in France have chosen to face this question by using the French DRG based information system called PMSI. It allows estimating the proportion of hospital stays concerned by cancers that are identified with algorithms based on ICD 10. However, French databases of hospital discharges do not allow patients identification. We collected data on hospital stays and patients in a subset of an organized network focused on cancer care and composed of 55 public or private hospitals in the Rhone-Alpes area. We used these data to estimate the number of patients who had been hospitalized within the network in 2000. Approximately 110,000 hospital stays were related with a diagnostic of cancer, corresponding to a number of patients within a range of 30345 to 35700. In absence of communicating files between hospitals, claims databases are an interesting source of information for cancer burden. The recent implementation of a procedure allowing the linkage of data concerning each patient should permit better estimates in the future. The main limitation will remain the possibility of a hospital to participate to more than one network.