疾病控制区域卫生信息平台中高血压数据质量控制指标研究

Quality control index of hypertension data based on regional health information platform

【目的】基于大数据分析,建立适宜的、有效的、稳定的、可靠的高血压数据质量控制指标。【方法】通过文献研究法和专家咨询法研究制定高血压数据质量控制指标,利用高血压、糖尿病、死亡三个条线的历史数据对指标进行验证。【结果】通过对高血压业务和数据特点的研究,得出四个数据质量控制指标,分别为BMI纵向波动、BMI横向波动、死后随访、血压无波动。通过验证,这四个指标均能找出异常数据,BMI纵向波动(异常率0.29%,t=4.70,P<0.000 1)、BMI横向波动(异常率1.9%,t=-7.72,P<0.000 1)、死后随访(异常率33.76%)、血压无波动(异常率20.03%)。【结论】通过对高血压历年数据及与其他条线关联数据的研究,制定的四个质量控制指标,能够准确找出存在的异常数据。运用大数据分析,不仅可以提高业务工作效率,还有助于提高业务数据的真实性。

[Objective]Based on the big data analysis,to establish appropriate,effective,stable and reliable data quality control indicators for hypertension.[Methods]The data quality control index of hypertension was established through literature research and expert consultation.Then was tested and verified the index by the historical data on three lines of hypertension,diabetes and death.[Results]Four data quality control indexes were obtained through the study of hypertension business and data characteristics,including the longitudinal fluctuation of BMI,transverse fluctuation of BMI,postmortem follow-up and no fluctuation blood pressure.Through the verification,these four indexes can find abnormal data with longitudinal fluctuation of BMI(abnormal rate 0.29%,t=4.70,P<0.000 1),transverse fluctuation of BMI(abnormal rate 1.9%,t=-7.72,P<0.000 1),postmortem follow-up(abnormal rate 33.76%),no fluctuation blood pressure(abnormal rate 20.03%).[Conclusion]Through the study of the data on hypertension and other lines of related data,four quality control indexes developed here are able to find out the abnormal data.Using big data analysis can not only improve the efficiency of business work,but also raise the authenticity of business data.