Sabrina Gmuca1, Duriel I Hardy2, Sona Narula3, Sharon Stoll4, Julia Harris5, Yongdong Zhao6, Rui Xiao7, Pamela F Weiss8, Amy T Waldman3, Jeffrey S Gerber9. 1. Department of Pediatrics, Division of Rheumatology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, United States; Perelman School of Medicine at University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19104, United States; Center for Pediatric Clinical Effectiveness, Children's Hospital of Philadelphia, Roberts Center for Pediatric Research, Philadelphia, PA,19146, United States; PolicyLab, Children's Hospital of Philadelphia, Roberts Center for Pediatric Research, Philadelphia, PA, 19146, United States. Electronic address: gmucas@email.chop.edu. 2. Department of Pediatric, Division of Neurology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia PA, 19104, United States. 3. Perelman School of Medicine at University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19104, United States; Department of Pediatric, Division of Neurology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia PA, 19104, United States. 4. Department of Neurology, Yale New Haven Hospital, 20 York St. New Haven, CT, 06519, United States; Yale School of Medicine, 333 Cedar St, New Haven, CT, 06510, United States. 5. University of Missouri-Kansas City School of Medicine, 2411 Holmes St, Kansas City MO, 64108, United States; Department of Pediatrics, Division of Rheumatology, Children's Mercy Kansas City, 2401 Gillham Road, Kansas City MO, 64108, United States. 6. Department of Pediatrics, Division of Rheumatology, Seattle Children's Hospital, 4800 Sand Point Way NE, Seattle, Washington, 98105, United States; University of Washington School of Medicine, 1959 NE Pacific Street, Seattle, WA 98195, United States. 7. Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA,19104, United States. 8. Department of Pediatrics, Division of Rheumatology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA, 19104, United States; Perelman School of Medicine at University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19104, United States; Center for Pediatric Clinical Effectiveness, Children's Hospital of Philadelphia, Roberts Center for Pediatric Research, Philadelphia, PA,19146, United States. 9. Perelman School of Medicine at University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19104, United States; Department of Pediatrics, Division of Infectious Disease, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia PA, 19014, United States.
Abstract
BACKGROUND: Neuromyelitis optica spectrum disorder (NMOSD) is a rare demyelinating disease in need of more studies to determine effective treatment regimens. The rarity of the disorder, however, makes large randomized-controlled trials challenging. Validation of the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code for NMO could facilitate the use of large healthcare claims data for future research. We aimed 1) to determine the positive predictive value (PPV) of the ICD-9-CM code for NMO as well as evaluate case-finding algorithms for the identification of patients with NMO/NMOSD and 2) to compare the evaluation of and treatment for pediatric versus adult patients. METHODS: This was a multicenter retrospective cohort study of patients with ≥ 1 ICD-9 code for NMO seen at 3 pediatric and 2 adult United States medical centers from 2001-2016. Using a standardized data entry form, pediatric and adult neurologists and rheumatologists reviewed patients' medical records to determine whether patients fulfilled the 2006 criteria for NMO and/or the 2015 criteria for NMOSD in order to determine the positive predictive value (PPV) for the ICD-9-CM code. Demographic and clinical information was abstracted from patient medical records to ascertain variables then evaluated in case-based finding algorithms for further identification of patients with true NMO/NMOSD. We also evaluated differences in clinical characteristics between pediatric and adult patients using chi-squared or Fisher's exact tests, as appropriate, to assess for treatment variation. RESULTS: A single code for NMO had a PPV of 47% across all sites, with significant site variation (0-77%). The best case-finding algorithm included at least 5 codes as well as a documented hospitalization (PPV = =90% for children and PPV = 92% for adults). Children were more likely to be evaluated by a rheumatologist or ophthalmologist, undergo magnetic resonance imaging of the orbits, and receive immunosuppressive and biologic agents than their adult counterparts. Rituximab was administered similarly among the two groups. CONCLUSION: The ICD-9 code for neuromyelitis optica (NMO) is inaccurate for identification of NMO/NMOSD. Using case-finding algorithms increases the PPV. The initial diagnostic evaluation and treatment of NMOSD differs significantly between children and adults. Published by Elsevier B.V.
BACKGROUND:Neuromyelitis optica spectrum disorder (NMOSD) is a rare demyelinating disease in need of more studies to determine effective treatment regimens. The rarity of the disorder, however, makes large randomized-controlled trials challenging. Validation of the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code for NMO could facilitate the use of large healthcare claims data for future research. We aimed 1) to determine the positive predictive value (PPV) of the ICD-9-CM code for NMO as well as evaluate case-finding algorithms for the identification of patients with NMO/NMOSD and 2) to compare the evaluation of and treatment for pediatric versus adult patients. METHODS: This was a multicenter retrospective cohort study of patients with ≥ 1 ICD-9 code for NMO seen at 3 pediatric and 2 adult United States medical centers from 2001-2016. Using a standardized data entry form, pediatric and adult neurologists and rheumatologists reviewed patients' medical records to determine whether patients fulfilled the 2006 criteria for NMO and/or the 2015 criteria for NMOSD in order to determine the positive predictive value (PPV) for the ICD-9-CM code. Demographic and clinical information was abstracted from patient medical records to ascertain variables then evaluated in case-based finding algorithms for further identification of patients with true NMO/NMOSD. We also evaluated differences in clinical characteristics between pediatric and adult patients using chi-squared or Fisher's exact tests, as appropriate, to assess for treatment variation. RESULTS: A single code for NMO had a PPV of 47% across all sites, with significant site variation (0-77%). The best case-finding algorithm included at least 5 codes as well as a documented hospitalization (PPV = =90% for children and PPV = 92% for adults). Children were more likely to be evaluated by a rheumatologist or ophthalmologist, undergo magnetic resonance imaging of the orbits, and receive immunosuppressive and biologic agents than their adult counterparts. Rituximab was administered similarly among the two groups. CONCLUSION: The ICD-9 code for neuromyelitis optica (NMO) is inaccurate for identification of NMO/NMOSD. Using case-finding algorithms increases the PPV. The initial diagnostic evaluation and treatment of NMOSD differs significantly between children and adults. Published by Elsevier B.V.
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