PDF(Sci-hub)
Abstract：
OBJECTIVE: 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.
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.
摘要：
目的：为了审查支持计费有效性的证据，程序,或诊断代码，或用于在管理和索赔数据库中识别类风湿关节炎（RA）患者的基于药房索赔的算法。
方法：我们从1991年至2012年9月使用与RA相关的对照词汇和关键术语检索了MEDLINE数据库，并检索了纳入研究的参考文献列表。两名研究人员根据预先确定的纳入标准独立评估了研究的全文，并提取了数据。收集的数据包括参与者和算法特征。
结果：九项研究报告了基于国际疾病分类（ICD）代码的计算机算法的验证，无论有无自由文本，药物使用,实验室数据和风湿病学家诊断的需要。这些研究产生了34％至97％的阳性预测值（PPV），以识别RA患者。使用至少两个ICD和/或程序代码（ICD-9代码714和其他代码）获得了更高的PPV，用于治疗RA的药物处方的要求，或风湿病学家参与患者护理的要求。例如,当需要使用改善疾病的抗风湿药和类风湿因子阳性时,PPV从66%增加至97%.
结论：已经在自动数据库中提出和验证识别RA患者的算法方面进行了大量努力。包括多于一个代码并且结合药物或实验室数据和/或需要风湿病学家诊断的算法可以增加PPV。
方法：我们从1991年至2012年9月使用与RA相关的对照词汇和关键术语检索了MEDLINE数据库，并检索了纳入研究的参考文献列表。两名研究人员根据预先确定的纳入标准独立评估了研究的全文，并提取了数据。收集的数据包括参与者和算法特征。
结果：九项研究报告了基于国际疾病分类（ICD）代码的计算机算法的验证，无论有无自由文本，药物使用,实验室数据和风湿病学家诊断的需要。这些研究产生了34％至97％的阳性预测值（PPV），以识别RA患者。使用至少两个ICD和/或程序代码（ICD-9代码714和其他代码）获得了更高的PPV，用于治疗RA的药物处方的要求，或风湿病学家参与患者护理的要求。例如,当需要使用改善疾病的抗风湿药和类风湿因子阳性时,PPV从66%增加至97%.
结论：已经在自动数据库中提出和验证识别RA患者的算法方面进行了大量努力。包括多于一个代码并且结合药物或实验室数据和/或需要风湿病学家诊断的算法可以增加PPV。
