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利用结构化电子数据进行带状疱疹和疱疹后神经痛监测。

Herpes zoster and postherpetic neuralgia surveillance using structured electronic data.

机构信息

Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA.

出版信息

Mayo Clin Proc. 2011 Dec;86(12):1146-53. doi: 10.4065/mcp.2011.0305. Epub 2011 Oct 13.

Abstract

OBJECTIVE

To develop electronic algorithms for rapid, automated surveillance for herpes zoster and postherpetic neuralgia (PHN) using codified electronic health data.

PATIENTS AND METHODS

We attempted to identify every case of herpes zoster and PHN arising between January 1 and December 31, 2008, within the electronic medical record of a 560,000-patient ambulatory practice using an array of diagnosis codes; intervals between herpes zoster encounters; and prescriptions for analgesics, anticonvulsants, and antidepressants. We assessed the sensitivity and positive predictive value (PPV) of each screening criterion by medical record review and then integrated multiple criteria into combination algorithms to optimize sensitivity and PPV. We applied the optimized algorithms to the practice's historical data spanning January 1, 1996, to December 31, 2008, to assess for changes in the annual incidence of PHN.

RESULTS

The International Classification of Diseases, Ninth Revision, code 053 detected herpes zoster with 98% sensitivity and 93% PPV. A combination algorithm including diagnosis codes, visit intervals, and prescriptions detected PHN with 86% sensitivity and 78% PPV. Between 1996 and 2008, the age- and sex-adjusted annual incidence of PHN rose from 0.18 to 0.47 cases per 1000 patients, and the proportion of herpes zoster patients progressing to PHN rose from 5.4% to 17.6%.

CONCLUSION

Novel algorithms incorporating multiple streams of electronic health data can reasonably detect herpes zoster and PHN. These algorithms could facilitate meaningful public health surveillance using electronic health data. The incidence of PHN may be increasing.

摘要

目的

利用编码电子健康数据开发用于带状疱疹和带状疱疹后神经痛(PHN)快速自动监测的电子算法。

患者和方法

我们试图使用一系列诊断代码、带状疱疹就诊间隔以及镇痛药、抗惊厥药和抗抑郁药处方,在一个拥有 560000 名患者的门诊实践的电子病历中,确定 2008 年 1 月 1 日至 12 月 31 日期间出现的每一例带状疱疹和 PHN。我们通过病历回顾评估了每种筛选标准的敏感性和阳性预测值(PPV),然后将多个标准整合到组合算法中,以优化敏感性和 PPV。我们将优化的算法应用于该实践的历史数据,涵盖 1996 年 1 月 1 日至 2008 年 12 月 31 日,以评估 PHN 的年发病率变化。

结果

国际疾病分类,第九修订版 053 代码检测带状疱疹的敏感性为 98%,PPV 为 93%。包括诊断代码、就诊间隔和处方的组合算法检测 PHN 的敏感性为 86%,PPV 为 78%。1996 年至 2008 年间,年龄和性别调整后的 PHN 年发病率从 0.18 例/1000 人上升至 0.47 例/1000 人,发展为 PHN 的带状疱疹患者比例从 5.4%上升至 17.6%。

结论

纳入多种电子健康数据流的新型算法可以合理地检测带状疱疹和 PHN。这些算法可以使用电子健康数据进行有意义的公共卫生监测。PHN 的发病率可能在上升。

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