Abstract
Purpose
Primary immunodeficiency diseases (PID) are a rare group of disorders with a wide array of clinical presentations. The absence of validated methods to identify these diseases in electronic databases has limited understanding of their epidemiology and the impact of drug therapies on outcomes. We measured the positive predictive values (PPVs) of ICD-9 diagnoses for identifying PID within US Medicaid.
Methods
We identified Medicaid patients from California, Florida, New York, Ohio, and Pennsylvania with PID ICD-9 diagnoses (common variable immunodeficiency [279.06], X-linked agammaglobulinemia [279.04], hyper-immunoglobulin M syndrome [279.05], Wiskott Aldrich Syndrome [279.12]) recorded at least twice from 1999 to 2007. Outpatient records were reviewed by a clinical immunologist to adjudicate diagnoses. PPVs with 95 % confidence intervals (CIs) for confirmed outcomes were determined for individual ICD-9 diagnoses and combinations of diagnoses and Current Procedural Terminology codes for a quantitative immunoglobulin test (82784) or immunoglobulin infusion (96365).
Results
Among 83 patients with PID ICD-9 diagnoses, 16 were adjudicated as having the condition (PPV, 19.3 %; 95 % CI, 11.4–29.4 %). Individual ICD-9 diagnoses had low PPVs (range, 16.7–33.3 %). Requiring procedural codes for quantitative immunoglobulins or intravenous immunoglobulin did not increase PPVs of these diagnoses (range, 11.1–41.7 %). An X-linked agammaglobulinemia diagnosis plus intravenous immunoglobulin had the highest PPV among the algorithms evaluated (PPV, 41.7 %; 95 % CI, 15.1–72.3 %).
Conclusions
Algorithms comprising PID ICD-9 diagnoses and procedures for quantitative immunoglobulin tests and immunoglobulin infusion had low PPVs for adjudicated diagnoses in Medicaid. Alternative data sources should be evaluated to study the epidemiology of these diseases.
Similar content being viewed by others
References
Al-Herz W, Bousfiha A, Casanova JL, Chatila T, Conley ME, Cunningham-Rundles C, et al. Primary immunodeficiency diseases: an update on the classification from the international union of immunological societies expert committee for primary immunodeficiency. Front Immunol. 2014;5:162.
Lim MS, Elenitoba-Johnson KS. The molecular pathology of primary immunodeficiencies. J Mol Diagn. 2004;6(2):59–83.
Boyle JM, Buckley RH. Population prevalence of diagnosed primary immunodeficiency diseases in the United States. J Clin Immunol. 2007;27(5):497–502.
Kobrynski L, Powell RW, Bowen S. Prevalence and morbidity of primary immunodeficiency diseases, United States 2001–2007. J Clin Immunol. 2014;34(8):954–61.
Resnick ES, Bhatt P, Sidi P, Cunningham-Rundles C. Examining the use of ICD-9 diagnosis codes for primary immune deficiency diseases in New York State. J Clin Immunol. 2013;33(1):40–8.
Hennessy S, Bilker WB, Weber A, Strom BL. Descriptive analyses of the integrity of a US Medicaid claims database. Pharmacoepidemiol Drug Saf. 2003;12(2):103–11.
Hennessy S, Leonard CE, Palumbo CM, Newcomb C, Bilker WB. Quality of medicaid and medicare data obtained through Centers for Medicare and Medicaid Services (CMS). Med Care. 2007;45(12):1216–20.
Centers for Medicare & Medicaid Services. Medicaid Analytic eXtract (MAX) Validation Reports. http://www.cms.gov/MedicaidDataSourcesGenInfo/MVR/list.asp. Accessed 10 Mar 2015.
Centers for Medicare & Medicaid Services. Medicaid Statistical Information System (MSIS) Tables. http://www.cms.gov/MedicaidDataSourcesGenInfo/MSIS/list.asp. Accessed 10 Mar 10, 2015.
Walkup J, Sambamoorthi U, Crystal S. Incidence and consistency of antiretroviral use among HIV-infected medicaid beneficiaries with schizophrenia. J Clin Psychiatry. 2001;62(3):174–8.
Geha RS, Notarangelo LD, Casanova JL, Chapel H, Conley ME, Fischer A, et al. Primary immunodeficiency diseases: an update from the International Union of Immunological Societies Primary Immunodeficiency Diseases Classification Committee. J Allergy Clin Immunol. 2007;120(4):776–94.
Hennessy S, Leonard CE, Bilker WB. Researchers and HIPAA. Epidemiology. 2007;18(4):518.
Hennessy S, Leonard CE, Freeman CP, Deo R, Newcomb C, Kimmel SE, et al. Validation of diagnostic codes for outpatient-originating sudden cardiac death and ventricular arrhythmia in Medicaid and Medicare claims data. Pharmacoepidemiol Drug Saf. 2010;19(6):555–62.
Walkup JT, Wei W, Sambamoorthi U, Crystal S. Sensitivity of an AIDS case-finding algorithm: who are we missing? Med Care. 2004;42(8):756–63.
Fultz SL, Skanderson M, Mole LA, Gandhi N, Bryant K, Crystal S, et al. Development and verification of a “virtual” cohort using the National VA Health Information System. Med Care. 2006;44(8 Suppl 2):S25–30.
Local Coverage Article: Intravenous Immune Globulin - Policy Article - Effective January 2011 (A46341).
Funding
Support from the University of Pennsylvania’s Center for Pharmacoepidemiology Research & Training and Penn’s CTSA grant # 3UL1TR000003. Additional support from K01 AI070001 awarded to V. Lo Re.
Conflicts of Interest
Author Jordan S. Orange is a paid consultant for Baxter, CSL Behring, ASD Healthcare, and Walgreens and has a research grant from CSL Behring.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Supplementary Table 1
(PDF 18 kb)
Rights and permissions
About this article
Cite this article
Hernandez-Trujillo, H., Orange, J.S., Roy, J.A. et al. Validity of Primary Immunodeficiency Disease Diagnoses in United States Medicaid Data. J Clin Immunol 35, 566–572 (2015). https://doi.org/10.1007/s10875-015-0185-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10875-015-0185-x