2008
DOI: 10.1111/j.1475-6773.2008.00873.x
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Accuracy of Physician Billing Claims for Identifying Acute Respiratory Infections in Primary Care

Abstract: Objective. To assess the accuracy of physician billing claims for identifying acute respiratory infections in primary care. Study Setting. Nine primary care physician practices in Montreal, Canada (2002-2005. Study Design. A validation study was carried out to compare diagnoses in 3,526 physician billing claims with diagnoses documented in the corresponding patient medical records. Data Collection. In-office medical record abstraction. Principal Findings. Claims had a high positive predictive value (PPV), nega… Show more

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Cited by 51 publications
(36 citation statements)
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“…In a prior study, positive predictive values of claims-based coding algorithms for pneumonia identification ranged from 72.6% to 80.8%, with sensitivity ranging from 47.8% to 66.2% and specificity ranging from 98.7% to 99.1% (33). Similar estimates were provided for other ARTIs using claims data (34). We feel that low sensitivity would result in conservative estimates of ARTI rates but would not bias our results, as there is no reason to suspect that coding practices would have changed over the study period.…”
Section: Discussionsupporting
confidence: 51%
“…In a prior study, positive predictive values of claims-based coding algorithms for pneumonia identification ranged from 72.6% to 80.8%, with sensitivity ranging from 47.8% to 66.2% and specificity ranging from 98.7% to 99.1% (33). Similar estimates were provided for other ARTIs using claims data (34). We feel that low sensitivity would result in conservative estimates of ARTI rates but would not bias our results, as there is no reason to suspect that coding practices would have changed over the study period.…”
Section: Discussionsupporting
confidence: 51%
“…Failure to adjust adequately for the severity of these conditions, which may also be associated with higher doses of opioids, may lead to an overestimation of the adverse effects of opioids. Other comorbidities that increase the risk of injury may also have been underestimated using medical service billing diagnostic codes, which have been shown to have high specificity but lower sensitivity 42,43 …”
Section: Discussionmentioning
confidence: 99%
“…), who has previous experience conducting validation studies 33,34 and performing statistical adjustment for verification bias, 35 assessed the risk of bias and applicability of each included study using the Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2) tool. QUADAS-2 focuses on 4 domains: patient selection, index test, reference test, and patient flow and timing of testing.…”
Section: Risk Of Bias Assessmentmentioning
confidence: 99%