دورية أكاديمية
Administrative Algorithms to identify Avascular necrosis of bone among patients undergoing upper or lower extremity magnetic resonance imaging: a validation study
| العنوان: | Administrative Algorithms to identify Avascular necrosis of bone among patients undergoing upper or lower extremity magnetic resonance imaging: a validation study |
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| المؤلفون: | Barbhaiya, Medha, Dong, Yan, Sparks, Jeffrey A., Losina, Elena, Costenbader, Karen H., Katz, Jeffrey N. |
| المصدر: | Barbhaiya, Medha, Yan Dong, Jeffrey A. Sparks, Elena Losina, Karen H. Costenbader, and Jeffrey N. Katz. 2017. “Administrative Algorithms to identify Avascular necrosis of bone among patients undergoing upper or lower extremity magnetic resonance imaging: a validation study.” BMC Musculoskeletal Disorders 18 (1): 268. doi:10.1186/s12891-017-1626-x. http://dx.doi.org/10.1186/s12891-017-1626-xTest. |
| بيانات النشر: | BioMed Central, 2017. |
| سنة النشر: | 2017 |
| المجموعة: | HMS Scholarly Articles SPH Scholarly Articles |
| مصطلحات موضوعية: | Avascular necrosis, Avn, Osteonecrosis, Epidemiology, Magnetic, Resonance Imaging, MRI, administrative data, validation |
| الوصف: | Background: Studies of the epidemiology and outcomes of avascular necrosis (AVN) require accurate case-finding methods. The aim of this study was to evaluate performance characteristics of a claims-based algorithm designed to identify AVN cases in administrative data. Methods: Using a centralized patient registry from a US academic medical center, we identified all adults aged ≥18 years who underwent magnetic resonance imaging (MRI) of an upper/lower extremity joint during the 1.5 year study period. A radiologist report confirming AVN on MRI served as the gold standard. We examined the sensitivity, specificity, positive predictive value (PPV) and positive likelihood ratio (LR+) of four algorithms (A-D) using International Classification of Diseases, 9th edition (ICD-9) codes for AVN. The algorithms ranged from least stringent (Algorithm A, requiring ≥1 ICD-9 code for AVN [733.4X]) to most stringent (Algorithm D, requiring ≥3 ICD-9 codes, each at least 30 days apart). Results: Among 8200 patients who underwent MRI, 83 (1.0% [95% CI 0.78–1.22]) had AVN by gold standard. Algorithm A yielded the highest sensitivity (81.9%, 95% CI 72.0–89.5), with PPV of 66.0% (95% CI 56.0–75.1). The PPV of algorithm D increased to 82.2% (95% CI 67.9–92.0), although sensitivity decreased to 44.6% (95% CI 33.7–55.9). All four algorithms had specificities >99%. Conclusion: An algorithm that uses a single billing code to screen for AVN among those who had MRI has the highest sensitivity and is best suited for studies in which further medical record review confirming AVN is feasible. Algorithms using multiple billing codes are recommended for use in administrative databases when further AVN validation is not feasible. |
| نوع الوثيقة: | Journal Article |
| اللغة: | English |
| العلاقة: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5477300/pdfTest/; BMC Musculoskeletal Disorders |
| DOI: | 10.1186/s12891-017-1626-x |
| الوصول الحر: | http://nrs.harvard.edu/urn-3:HUL.InstRepos:33490950Test |
| حقوق: | open URL: http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAATest |
| رقم الانضمام: | edshld.1.33490950 |
| قاعدة البيانات: | Digital Access to Scholarship at Harvard (DASH) |
| DOI: | 10.1186/s12891-017-1626-x |
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