Medical Data Quality Assessment Model Based on Credibility Analysis

The current main problem of medical data is low accuracy. Although existing data quality evaluation and audit can meet the needs, network security problem will be more serious in the future. As a result, the data quality evaluation model must include data credibility. This paper proposes the medical big data quality evaluation model based on credibility analysis and Analytic Hierarchy Process(AHP). Firstly, analyze the data credibility. After eliminating the unreliable data, calculate the data quality dimensions respectively. Then obtain the data quality evaluation result by integrating all dimensions with AHP. Through simulation, the data quality evaluation model can effectively identify the data that affects the credibility. The data quality evaluation results are improved after removing the untrusted data, besides the amount of data is reduced, which is applicable to the big data scenario.