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

ObjectiveBased on the big data analysis, to establish appropriate, effective, stable and reliable data quality control indicators for hypertension.

MethodsThe data quality control index of hypertension was established through literature research and expert consultation.Then was tested and verifiedthe index by the historical data onthree lines of hypertension, diabetes and death.

ResultsFour data quality control indexes wereobtainedthrough the study of hypertension business and data characteristics, includingthe longitudinal fluctuation of BMI, transverse fluctuation of BMI, postmortem follow-up and no fluctuationblood 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 fluctuationblood pressure(abnormal rate 20.03%).

ConclusionThrough the study of the data onhypertension 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 raisethe authenticity of business data.