Brook I Martin1, Jon D Lurie, Anna N A Tosteson, Richard A Deyo, Tor D Tosteson, James N Weinstein, Sohail K Mirza. 1. *Dartmouth Institute for Health Policy & Clinical Practice, and the Department of Orthopaedic Surgery, Geisel School of Medicine at Dartmouth, Lebanon, NH †Departments of Medicine and Orthopaedics, The Dartmouth Institute, Lebanon, NH ‡Departments of Medicine and Community and Family Medicine, The Dartmouth Institute, Lebanon, NH §Departments of Family Medicine, Medicine, and Public Health & Preventive Medicine, Oregon Health & Science University, Portland, OR ¶Departments of Community and Family Medicine, The Dartmouth Institute, Lebanon, NH ‖Departments of Orthopaedics and Community and Family Medicine, The Dartmouth Institute, Lebanon, NH; and **Department of Orthopaedics, The Dartmouth Institute, Lebanon, NH.
Abstract
STUDY DESIGN: Retrospective analysis of Medicare claims linked to a multicenter clinical trial. OBJECTIVE: The Spine Patient Outcomes Research Trial (SPORT) provided a unique opportunity to examine the validity of a claims-based algorithm for grouping patients by surgical indication. SPORT enrolled patients for lumbar disc herniation, spinal stenosis, and degenerative spondylolisthesis. We compared the surgical indication derived from Medicare claims with that provided by SPORT surgeons, the "gold standard." SUMMARY OF BACKGROUND DATA: Administrative data are frequently used to report procedure rates, surgical safety outcomes, and costs in the management of spinal surgery. However, the accuracy of using diagnosis codes to classify patients by surgical indication has not been examined. METHODS: Medicare claims were link to beneficiaries enrolled in SPORT. The sensitivity and specificity of 3 claims-based approaches to group patients on the basis of surgical indications were examined: (1) using the first listed diagnosis; (2) using all diagnoses independently; and (3) using a diagnosis hierarchy on the basis of the support for fusion surgery. RESULTS: Medicare claims were obtained from 376 SPORT participants, including 21 with disc herniation, 183 with spinal stenosis, and 172 with degenerative spondylolisthesis. The hierarchical coding algorithm was the most accurate approach for classifying patients by surgical indication, with sensitivities of 76.2%, 88.1%, and 84.3% for disc herniation, spinal stenosis, and degenerative spondylolisthesis cohorts, respectively. The specificity was 98.3% for disc herniation, 83.2% for spinal stenosis, and 90.7% for degenerative spondylolisthesis. Misclassifications were primarily due to codes attributing more complex pathology to the case. CONCLUSION: Standardized approaches for using claims data to group patients accurately by surgical indications have widespread interest. We found that a hierarchical coding approach correctly classified more than 90% of spine patients into their respective SPORT cohorts. Therefore, claims data seem to be a reasonably valid approach to classifying patients by surgical indication. LEVEL OF EVIDENCE: 3.
STUDY DESIGN: Retrospective analysis of Medicare claims linked to a multicenter clinical trial. OBJECTIVE: The Spine Patient Outcomes Research Trial (SPORT) provided a unique opportunity to examine the validity of a claims-based algorithm for grouping patients by surgical indication. SPORT enrolled patients for lumbar disc herniation, spinal stenosis, and degenerative spondylolisthesis. We compared the surgical indication derived from Medicare claims with that provided by SPORT surgeons, the "gold standard." SUMMARY OF BACKGROUND DATA: Administrative data are frequently used to report procedure rates, surgical safety outcomes, and costs in the management of spinal surgery. However, the accuracy of using diagnosis codes to classify patients by surgical indication has not been examined. METHODS: Medicare claims were link to beneficiaries enrolled in SPORT. The sensitivity and specificity of 3 claims-based approaches to group patients on the basis of surgical indications were examined: (1) using the first listed diagnosis; (2) using all diagnoses independently; and (3) using a diagnosis hierarchy on the basis of the support for fusion surgery. RESULTS: Medicare claims were obtained from 376 SPORT participants, including 21 with disc herniation, 183 with spinal stenosis, and 172 with degenerative spondylolisthesis. The hierarchical coding algorithm was the most accurate approach for classifying patients by surgical indication, with sensitivities of 76.2%, 88.1%, and 84.3% for disc herniation, spinal stenosis, and degenerative spondylolisthesis cohorts, respectively. The specificity was 98.3% for disc herniation, 83.2% for spinal stenosis, and 90.7% for degenerative spondylolisthesis. Misclassifications were primarily due to codes attributing more complex pathology to the case. CONCLUSION: Standardized approaches for using claims data to group patients accurately by surgical indications have widespread interest. We found that a hierarchical coding approach correctly classified more than 90% of spine patients into their respective SPORT cohorts. Therefore, claims data seem to be a reasonably valid approach to classifying patients by surgical indication. LEVEL OF EVIDENCE: 3.
Authors: James N Weinstein; Tor D Tosteson; Jon D Lurie; Anna N A Tosteson; Brett Hanscom; Jonathan S Skinner; William A Abdu; Alan S Hilibrand; Scott D Boden; Richard A Deyo Journal: JAMA Date: 2006-11-22 Impact factor: 56.272
Authors: Richard A Deyo; Darryl T Gray; William Kreuter; Sohail Mirza; Brook I Martin Journal: Spine (Phila Pa 1976) Date: 2005-06-15 Impact factor: 3.468
Authors: James N Weinstein; Tor D Tosteson; Jon D Lurie; Anna N A Tosteson; Emily Blood; Brett Hanscom; Harry Herkowitz; Frank Cammisa; Todd Albert; Scott D Boden; Alan Hilibrand; Harley Goldberg; Sigurd Berven; Howard An Journal: N Engl J Med Date: 2008-02-21 Impact factor: 91.245
Authors: Brook I Martin; Richard A Deyo; Sohail K Mirza; Judith A Turner; Bryan A Comstock; William Hollingworth; Sean D Sullivan Journal: JAMA Date: 2008-02-13 Impact factor: 56.272
Authors: James N Weinstein; Jon D Lurie; Tor D Tosteson; Wenyan Zhao; Emily A Blood; Anna N A Tosteson; Nancy Birkmeyer; Harry Herkowitz; Michael Longley; Lawrence Lenke; Sanford Emery; Serena S Hu Journal: J Bone Joint Surg Am Date: 2009-06 Impact factor: 5.284
Authors: Anna Ialynytchev; Alan M Sear; Arthur R Williams; Barbara Langland-Orban; Nanhua Zhang Journal: Eur Spine J Date: 2016-05-06 Impact factor: 3.134
Authors: Brook I Martin; Jon D Lurie; Anna N A Tosteson; Richard A Deyo; Farrokh R Farrokhi; Sohail K Mirza Journal: Spine J Date: 2014-12-15 Impact factor: 4.166
Authors: Christopher J Lucasti; Myles Dworkin; Kris E Radcliff; Kristen Nicholson; Christopher J Lucasti; Barrett I Woods Journal: Int J Spine Surg Date: 2019-06-30
Authors: Neel K Patel; Rachel A Moses; Brook I Martin; Jon D Lurie; Sohail K Mirza Journal: Spine (Phila Pa 1976) Date: 2017-05-01 Impact factor: 3.241
Authors: Brook I Martin; Richard A Deyo; Jon D Lurie; Timothy S Carey; Anna N A Tosteson; Sohail K Mirza Journal: Spine (Phila Pa 1976) Date: 2016-06 Impact factor: 3.241
Authors: Brook I Martin; Jon D Lurie; Farrokh R Farrokhi; Kevin J McGuire; Sohail K Mirza Journal: Spine (Phila Pa 1976) Date: 2018-05-15 Impact factor: 3.241