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Vaccine. 2013 Dec 30;31 Suppl 10:K41-61. doi: 10.1016/j.vaccine.2013.03.075.

A systematic review of validated methods for identifying patients with rheumatoid arthritis using administrative or claims data.

Author information

1
Division of Rheumatology, Vanderbilt University School of Medicine, 1161 21st Avenue South, D-3100, Medical Center North, Nashville, TN 37232-2358, USA. Electronic address: c.chung@vanderbilt.edu.
2
Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, Food and Drug Administration, WOC1 Building, Room 454S, 1401 Rockville Pike, Rockville, MD 20852-1428, USA.
3
Vanderbilt Evidence-based Practice Center, Vanderbilt University Medical Center, Suite 600, 2525 West End Avenue, Nashville, TN 37203-1738, USA. Electronic address: shanthi.krishnaswami@vanderbilt.edu.
4
Vanderbilt Evidence-based Practice Center and Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Suite 600, 2525 West End Avenue, Nashville, TN 37203-1738, USA. Electronic address: melissa.mcpheeters@vanderbilt.edu.

Abstract

PURPOSE:

To review the evidence supporting the validity of billing, procedural, or diagnosis code, or pharmacy claim-based algorithms used to identify patients with rheumatoid arthritis (RA) in administrative and claim databases.

METHODS:

We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to RA and reference lists of included studies were searched. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria and extracted the data. Data collected included participant and algorithm characteristics.

RESULTS:

Nine studies reported validation of computer algorithms based on International Classification of Diseases (ICD) codes with or without free-text, medication use, laboratory data and the need for a diagnosis by a rheumatologist. These studies yielded positive predictive values (PPV) ranging from 34 to 97% to identify patients with RA. Higher PPVs were obtained with the use of at least two ICD and/or procedure codes (ICD-9 code 714 and others), the requirement of a prescription of a medication used to treat RA, or requirement of participation of a rheumatologist in patient care. For example, the PPV increased from 66 to 97% when the use of disease-modifying antirheumatic drugs and the presence of a positive rheumatoid factor were required.

CONCLUSIONS:

There have been substantial efforts to propose and validate algorithms to identify patients with RA in automated databases. Algorithms that include more than one code and incorporate medications or laboratory data and/or required a diagnosis by a rheumatologist may increase the PPV.

KEYWORDS:

A; ACR; AMI; ANA; Administrative database; Algorithm; American College of Rheumatology; CD; CI; CPT; Crohn's disease; DB; DMARD; DMBA; Deseret Mutual Benefits Administration; EDC; EMR; GHS; Geisinger health system; HCPCS; HZ; Health Care Financing Administration Common Procedure Coding System; IBD; ICD; ICD-9; International Classification of Diseases; JRA; KPNC; Kaiser Permanente Northern California; MEDECHO; MTX; Maintenance et Exploitation des Donnees pour l’Etude de la Clientele Hospitaliere; NDC; NJ; NMSC; NPV; NSAID; National Drug Code; New Jersey; OSHPD; Office of Statewide Health Planning and Development; PA; PACE; PPV; Pennsylvania; Pennsylvania Assistance Contract for the Elderly; Positive predictive value; PsA; RA; RAMQ; RF; ROC; RX; Regie de l’assurance maladie du Quebec; Rheumatoid arthritis; SLE; THR; VA; VAMC; VISN; Validation; Veterans Affairs Medical Center; Veterans Affairs/Administration; Veterans Integrated Services Network; acute myocardial infarction; algorithm; anti-CCP; anti-TNF; anti-cyclic citrullinated peptide; anti-tumor necrosis factor; antinuclear antibody; confidence interval; current procedural terminology; database; disease-modifying antirheumatic drug; electronic medical records; estimated date of conception; herpes zoster; inflammatory bowel disease; juvenile-onset rheumatoid arthritis; methotrexate; negative predictive value; non-melanoma skin cancer; non-steroidal anti-inflammatory drug; positive predictive value; prescription; psoriatic arthritis; receiver operating characteristic (curve area); rheumatoid arthritis; rheumatoid factor; systemic lupus erythematosus; total hip replacement

PMID:
24331074
DOI:
10.1016/j.vaccine.2013.03.075
[Indexed for MEDLINE]

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