Quality evaluation of registration data of Shenzhen Type 1 Diabetes Alliance: based on the collaborative research platform network of China Type 1 Diabetes Alliance
10.3760/cma.j.cn431274-20210920-01002
- VernacularTitle:深圳1型糖尿病联盟登记数据质量评价研究：基于中国1型糖尿病联盟协作研究平台网
- Author:
Xueting LIU
1
;
Haiyan LI
;
Lingbo LYU
;
Mingzheng LI
;
Yan HUANG
;
Shu LI
;
Hongmei WU
;
Qin ZHANG
;
Chuanqi CHEN
;
Liao SUN
;
Zhiguang ZHOU
;
Xia LI
;
Dewen YAN
Author Information
1. 深圳市第二人民医院（深圳大学第一附属医院）内分泌科 深圳市代谢性疾病临床医学研究中心，深圳 518035
- Keywords:
Diabetes mellitus, type 1;
Specific disease database;
Data quality evaluation;
Big data
- From:
Journal of Chinese Physician
2022;24(7):1060-1066
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate the data quality of Shenzhen Type 1 Diabetes Alliance (SZT1D), and to provide a basis for evaluation and improvement for the continuous improvement of data quality.Methods:From December 2018 to July 2021, 697 first-visit type 1 diabetes (T1DM) patients (including 501 in Shenzhen and 196 out-of-Shenzhen) and 120 re-visited T1DM patients (including 113 in Shenzhen and 7 out-of-Shenzhen) who were registered by SZT1D in collaborative research platform network of China Type 1 Diabetes Alliance (hereinafter referred to as China T1D). The data quality was evaluated from three dimensions: data completion, accuracy and revisit. The data completion degree was evaluated by the overall data completion degree and the key indicator completion degree; the data accuracy was evaluated by the probability of abnormal blood glucose value; the patient′s return visit was evaluated by the return visit rate.Results:The main characteristics of T1DM in SZT1D were young and middle-aged adults [age: (34.4±17.1)years] with thin body [BMI: (19.80±3.52)kg/m 2)], half of male and female patients [proportion of male: 52.4%(365/697)]; the main types of diagnosis were classical T1DM [65.22%(150/230)] and latent autoimmune diabetes in adults(LADA) [26.08%(60/230)], and the fasting blood glucose (FPG) [(10.93±6.98)mmol/L] and glycosylated hemoglobin (HbA 1c) [(10.63±3.01)%] were high. The average completion rate of the overall data of the first diagnosed patients in SZT1D was only 60% [(62.9±31.5)%]: the number of patients with overall data completion ≥80% in SZT1D was only 50.2%(350/697); the number of patients with overall data completion ≥80% in Shenzhen was less than that outside Shenzhen [44.3%(222/501) vs 65.3%(128/196), P<0.001]. The key indicators with better completion rate of first-visit were disease course [76.2%(531/697)], age of onset [75.8%(528/697)], family history of diabetes [74.9%(522/697)], etc., but none of them had a completion rate of more than 80%, and the diabetes self-management behavior assessment questionnaire and scale score were completely missing; the frequency of daily blood glucose monitoring [46.1%(231/501) vs 64.3%(126/196), P<0.001], current insulin regimen [44.3%(222/501) vs 63.3%(124/196), P<0.001], number of diabetic ketoacidosis (DKA) since the onset of the disease [45.7%(229/501) vs 64.8%(127/196), P<0.001] and the number of symptomatic hypoglycemia in the past 1 month [39.3%(197/501) vs 63.8%(125/196), P<0.001] were higher in Shenzhen than those reported outside Shenzhen. In addition, the probability of abnormal FPG and postprandial glucose (PPG) [5.2%(24/466); 3.8%(19/236)] were low. The revisit rate was not high [17.2%(120/697)], and the revisit rate in Shenzhen was higher than that outside Shenzhen [22.6%(113/501) vs 3.6%(7/196), P<0.001]. The first revisit rate was 16.2%(113/697) and the second revisit rate was seriously insufficient [1.0%(7/697)]. Conclusions:The data quality of T1DM patients recorded by SZT1D needs to be further improved. Improving the information interconnection between China-T1D and SZT1D, employing quality control personnel and building a systematic data quality evaluation analysis and feedback mechanism are methods to promote the comprehensive, accurate and efficient input of T1DM data and continuously improve the evaluation methods to improve the overall data quality.
