A Novel Schema to Enhance Data Quality of Patient Safety Event Reports

Abstract

The most important knowledge in the field of patient safety is regarding the prevention and reduction of patient safety events (PSEs). It is believed that PSE reporting systems could be a good resource to share and to learn from previous cases. However, the success of such systems in healthcare is yet to be seen. One reason is that the qualities of most PSE reports are unsatisfactory due to the lack of knowledge output from reporting systems which makes reporters report halfheartedly. In this study, we designed a PSE similarity searching model based on semantic similarity measures, and proposed a novel schema of PSE reporting system which can effectively learn from previous experiences and timely inform the subsequent actions. This system will not only help promote the report qualities but also serve as a knowledge base and education tool to guide healthcare providers in terms of preventing the recurrence of PSEs.

Figure 1.

Performance evaluation for the similarity searching model. 1) A 4-point Likert Scale measure which contains 1-irrelevant, 2-somewhat irrelevant, 3-relevant, and 4-highly relevant was adopted; 2) Three experts labeled every case with one of the four scales according to the degree of similarity between this case and the given query case, meanwhile the model ranked the sample cases according to the similarity scores and labeled them with the four scales; 3) The sample agreement ratio was calculated by dividing the numbers of agreement cases by the number of total cases. 4) The performance of the model was evaluated by comparing the sample agreement ratio to the random agreement ratios.

Figure 2.

Similar cases of the query case “Ebola: Are We Ready?” calculated by the PSE similarity searching model (Vector Space method)

Figure 3.

Solution recommendation for a fall event reported in AHRQ Common Formats. The specific solutions are recommended dynamically according to the report options. E.g., the solution entry “Re-evaluate types of assistive devices used by the facility to prevent falls” was presented because the reporter chose “b. Ambulating with assistance and/or with an assistive device or medical equipment” to answer the Question 6.

Figure 4.

The workflow to improve the data quality of PSE reporting system. Data collection and management, algorithm implementation based on semantic similarity measures, expert review, agreement analysis, statistical test, user interface, and user feedback mechanism are the key modules to improve the data quality of the proposed PSE reporting system.