Objective Our objective was to phenotype periodontal disease (PD) diagnoses from three different sections (diagnosis codes, clinical notes, and periodontal charting) of the electronic dental records (EDR) by developing two automated computer algorithms. Methods We conducted a retrospective study using EDR data of patients (n = 27,138) who received care at Temple University Maurice H. Kornberg School of Dentistry from January 1, 2017 to August 31, 2021. We determined the completeness of patient demographics, periodontal charting, and PD diagnoses information in the EDR. Next, we developed two automated computer algorithms to automatically diagnose patients' PD statuses from clinical notes and periodontal charting data. Last, we phenotyped PD diagnoses using automated computer algorithms and reported the improved completeness of diagnosis. Results The completeness of PD diagnosis from the EDR was as follows: periodontal diagnosis codes 36% (n = 9,834), diagnoses in clinical notes 18% (n = 4,867), and charting information 80% (n = 21,710). After phenotyping, the completeness of PD diagnoses improved to 100%. Eleven percent of patients had healthy periodontium, 43% were with gingivitis, 3% with stage I, 36% with stage II, and 7% with stage III/IV periodontitis. Conclusions We successfully developed, tested, and deployed two automated algorithms on big EDR datasets to improve the completeness of PD diagnoses. After phenotyping, EDR provided 100% completeness of PD diagnoses of 27,138 unique patients for research purposes. This approach is recommended for use in other large databases for the evaluation of their EDR data quality and for phenotyping PD diagnoses and other relevant variables.

中文翻译：

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开发自动化计算机算法以对电子牙科记录中的牙周病诊断进行表型分析

目的 我们的目标是通过开发两种自动计算机算法，从电子牙科记录 (EDR) 的三个不同部分（诊断代码、临床记录和牙周图表）对牙周病 (PD) 诊断进行表型分析。方法 我们使用 2017 年 1 月 1 日至 2021 年 8 月 31 日期间在天普大学莫里斯 H.科恩伯格牙科学院接受护理的患者 (n = 27,138) 的 EDR 数据进行了一项回顾性研究。我们确定了患者人口统计、牙周图表的完整性, PD诊断EDR中的信息。接下来，我们开发了两种自动化计算机算法，根据临床记录和牙周图表数据自动诊断患者的 PD 状态。最后，我们使用自动化计算机算法对 PD 诊断进行了表型分析，并报告了诊断完整性的改进。结果 EDR 诊断 PD 的完整性如下：牙周诊断代码 36% (n = 9,834)，临床记录诊断 18% (n = 4,867)，图表信息 80% (n = 21,710)。表型分析后，PD 诊断的完整性提高到 100%。11% 的患者牙周健康，43% 患有牙龈炎，3% 为 I 期，36% 为 II 期，7% 为 III/IV 期牙周炎。结论 我们在大型 EDR 数据集上成功开发、测试和部署了两种自动化算法，以提高 PD 诊断的完整性。表型分析后，EDR 为 27,138 名独特患者提供了 100% 完整的 PD 诊断，用于研究目的。