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利用行政数据验证慢性肾脏病的病例定义。

Validating a case definition for chronic kidney disease using administrative data.

机构信息

Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada.

出版信息

Nephrol Dial Transplant. 2012 May;27(5):1826-31. doi: 10.1093/ndt/gfr598. Epub 2011 Oct 19.

Abstract

BACKGROUND

Administrative data are commonly used for surveillance of chronic medical conditions. The purpose of this study was to determine the validity of an algorithm derived from administrative data for identifying chronic kidney disease (CKD) compared to the reference standard of estimated glomerular filtration rate (eGFR).

METHODS

We identified adults from the province of Alberta with at least two outpatient serum creatinine measurements within a 1-year time period. Validity indices were estimated for CKD using up to 3 years of administrative data (physician billing claims and hospital discharge abstracts) for various case-definition combinations. For each algorithm, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated against two reference standard definitions of CKD (two eGFR measurements <60 mL/min/1.73m(2) or mean eGFR < 30 mL/min/1.73m(2)).

RESULTS

A total of 321 293 eligible subjects were identified. Irrespective of the algorithm, sensitivities for defining CKD (eGFR < 60 mL/min/1.73m(2)) using administrative codes were low. A case-definition algorithm employing two physician claims or one hospitalization within a 2-year period had sensitivity of 19.4%, specificity of 97.2%, PPV of 60.1% and NPV of 84.8% for detecting CKD. Estimates of sensitivity were higher when <30 mL/min/1.73m(2) was used as the reference standard, although PPVs were lower and consistently less than 50%.

CONCLUSION

These results, using eGFR as a reference standard, suggest that administrative data have insufficient sensitivity and PPV for CKD surveillance, although they may be useful when highly specific algorithms are required for research purposes.

摘要

背景

行政数据通常用于监测慢性疾病。本研究的目的是确定一种从行政数据中提取的算法在识别慢性肾脏病(CKD)方面的有效性,与估计肾小球滤过率(eGFR)的参考标准进行比较。

方法

我们从艾伯塔省中确定了至少有两次在 1 年内门诊血清肌酐测量值的成年人。使用长达 3 年的行政数据(医生计费和医院出院摘要)对各种病例定义组合的 CKD 进行有效性指标评估。对于每个算法,根据两个 CKD 的参考标准定义(两次 eGFR 测量值<60 mL/min/1.73m(2)或平均 eGFR < 30 mL/min/1.73m(2))计算敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)。

结果

共确定了 321293 名符合条件的受试者。无论算法如何,使用行政代码定义 CKD(eGFR < 60 mL/min/1.73m(2))的敏感性都很低。一个使用两年内两次医生就诊或一次住院的病例定义算法,其敏感性为 19.4%,特异性为 97.2%,PPV 为 60.1%,NPV 为 84.8%,用于检测 CKD。当使用<30 mL/min/1.73m(2)作为参考标准时,敏感性的估计值更高,尽管 PPV 较低,且始终低于 50%。

结论

使用 eGFR 作为参考标准,这些结果表明行政数据在 CKD 监测方面的敏感性和 PPV 不足,尽管当需要高度特异性算法进行研究时,它们可能有用。

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