Our objective was to investigate the utility of existing data sources for identifying cases of amyotrophic lateral sclerosis (ALS) and related motor neuron diseases (MND) in the State of Georgia. Data were acquired fr...
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Our objective was to investigate the utility of existing data sources for identifying cases of amyotrophic lateral sclerosis (ALS) and related motor neuron diseases (MND) in the State of Georgia. Data were acquired from Medicare, Medicaid, Veterans Administration, Emory Healthcare, community neurologists, the ALS Association, and mortality records for ALS/MND patients residing in Georgia during 2001--2005. A neurologist used abstracted medical records to verify the diagnosis of ALS/MND. The positive predictive value (PPV) of an icd code for a verified diagnosis of ALS was estimated. Simple ''rules'' were developed to improve PPV. Results showed that a total of 2413 unique potential cases were identified in existing data sources. Medical records of 579 cases were available for review;the diagnosis of ALS (or a related MND) was confirmed in 486 (PPV == 84%) cases. Predictive rules, which permitted classification of similar to 80% of the chart-reviewed population, improved PPV to 96--98%. In conclusion, existing data sources are useful for identifying cases of ALS/MND;most data sources contribute a substantial number of unique cases. Predictive algorithms may permit correct classification of a large proportion of cases without the need for verification based on medical record review.
Objective. To determine the accuracy of International Classification of Diseases (icd) code 714 for rheumatoid arthritis (RA) diagnosis in a Veterans Administration (VA) hospital database and to examine the effects of...
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Objective. To determine the accuracy of International Classification of Diseases (icd) code 714 for rheumatoid arthritis (RA) diagnosis in a Veterans Administration (VA) hospital database and to examine the effects of adding laboratory and pharmacy data to icd code 714 on accuracy of RA diagnosis. Methods. We drew a random sample of patients from all Minneapolis VA rheumatology clinic patients who had at least 1 rheumatology clinic visit between January 2001 and July 2002. Charts of 184 patients were reviewed. The gold standard for RA diagnosis was chart documentation of RA diagnosis by a rheumatologist on greater than or equal to2 visits >6 weeks apart. The data definitions of RA diagnosis included presence of icd code 714 alone or various combinations of icd code 714, a positive rheumatoid factor (RF), and prescription for a disease-modifying antirheumatic drug (DMARD). Accuracy of data definitions of RA was assessed by calculating sensitivity, specificity, positive and negative predictive values, and area under the receiver operator characteristics curve. Results. Diagnosis by icd code 714 had 100% sensitivity, but specificity was only 55% because of a false-positive rate of 34%. The addition of a positive RF and/or a DMARD prescription to icd code 714 dramatically improved specificity to 83-97% and positive predictive value to 81-97%;however, sensitivity decreased to 76-88%. Diagnosis by icd 714 alone had the highest negative predicative value of 100%. The area under the curve was the greatest when both icd code 714 and a positive RF were included, and the least when icd code alone was used. Conclusion. icd code 714 in the VA administrative database is a very sensitive screening tool for identifying patients with RA in the rheumatology clinic population. Addition of the presence of a DMARD prescription and/or a positive RF to selection criteria improves specificity of the diagnosis.
Background The number of cases of pleural mesothelioma in France has varied substantially according to methods of assessment. Materials and Methods We collected information from certifying physicians about 316 subject...
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Background The number of cases of pleural mesothelioma in France has varied substantially according to methods of assessment. Materials and Methods We collected information from certifying physicians about 316 subjects who died between 1 July 1992 and 30 June 1993 in three regions of France with a cause of death coded as icd-9 category 163. The icd codes selected as the cause of death for 178 deaths between 1 January 1987 and 31 December 1992 histologically confirmed and diagnosed as pleural mesothelioma by an expert committee were examined. Finally, we used this information to estimate the number of deaths from pleural. mesothelioma in France in 1992. Results In Part I, 45% (men: 54%;women: 28%) of the cases coded as icd-9 section 163 were definitely or probably mesothelioma;18% (men: 16%;women: 21%) possibly mesothelioma;and 37% (men: 30%;women: 51%) other tumors, primarily adenocarcinoma metastases. In Part II, 74% of the confirmed pleural mesotheliomas were coded in category 163 (men: 75%;women: 70%). Extrapolation nationwide indicated that 902 deaths were coded as icd-9 163 in 1992: 521 cases involved definite or probable mesothelioma and 724 definite, probable, and possible cases. Conclusions The analysis of this sample suggests that estimating the number of mesothelioma cases from the cause-of-death statistics may overestimate their incidence, but that death certificates appeared to report the diagnosis of histologically confirmed mesothelioma accurately. (C) 2002 Wiley-Liss, Inc.
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