Proposing a model for auditing data quality of long-term periodontal outcome studies

Abstract

Objective

The assessment of the success of conventional periodontal therapy is based on retrospective studies from private practice and university clinics. Due to their marked heterogeneity, it is difficult to assess the data quality and rate these studies. The aim is to test a model for auditing and rating the data quality of periodontal outcome studies.

Methods

The method was adapted from the NIH Health Care Systems Collaboratory model, which uses three data quality dimensions: completeness (including all the relevant variables), consistency (ensuring that the same variables are compared) and accuracy (proportion of data in error with a gold standard). The model was applied to studies from a Norwegian specialist practice and data from the Norwegian Health database to test if the auditing process was workable using real world data.

Results

Forty-seven risk and prognostic factors were included for completeness. Seven variables were specified for consistency: tooth loss, smoking, systemic conditions, oral hygiene, individual tooth prognosis, maintenance profiles and timing of extractions. The factors tested showed a 95.7% completeness and an average accuracy deviation from the gold standard of −2.3% for each of the risk/prognostic factors and an overall study score of 93.3%.

Conclusions

It was possible to develop a method for auditing and rating the quality of periodontal outcome studies. The model was tested using both real world data including risk and prognostic factors from individual outcome studies and national big data. The application of the model to these sets of data showed a high accuracy of the risk/prognostic factors and a close relationship with national big data.