Leveraging electronic health record documentation for Failure Mode and Effects Analysis team identification

Area of Science:

• Healthcare Quality Improvement
• Health Informatics
• Clinical Process Analysis

Background:

• Process maps are crucial for quality improvement but may not accurately reflect real-world clinical workflows.
• Electronic health records (EHRs) contain rich data on daily clinical practice that can be leveraged for analysis.

Purpose of the Study:

• To evaluate if secondary use of EHR data can enhance the accuracy of process maps for quality improvement.
• To examine discrepancies between expected and observed activities and personnel in a high-risk clinical process.

Main Methods:

• A process map for inpatient cardiology unit discharge was created by staff.
• Activities and providers on the process map were matched against electronic health record (EHR) data.
• Four diagnostic measures were used to analyze discrepancies between the process map and EHR observations.

Main Results:

• EHR data indicated 35% of activities were performed by unexpected providers from 12 unmapped categories.
• EHR data revealed process sub-components not present on the initial process map.
• The process map was revised using EHR data, highlighting expectation-observation differences.

Conclusions:

• Electronic health record (EHR) data can identify gaps in process maps and reveal workflow characteristics for quality improvement.
• Organizations can use clinical documentation within EHRs to improve process maps for initiatives like Failure Mode and Effects Analysis (FMEA).
• Findings are applicable to various quality improvement activities requiring accurate process mapping.