Patient Complaints in Image-Guided Interventions: Evaluation of Multifactorial Issues Using a Coding Taxonomy.

Area of Science:

• Medical Imaging
• Patient Safety
• Healthcare Quality

Background:

• Image-guided interventions are complex procedures.
• Patient feedback is crucial for improving healthcare services.
• A systematic approach to classifying patient complaints is needed.

Purpose of the Study:

• To classify patient complaints from image-guided interventions using a coding taxonomy.
• To compare the resolution rates of single-coded versus multifactorial complaints.

Main Methods:

• Retrospective review of patient complaint narratives (April 1999-December 2012).
• Categorization of complaints using a three-level taxonomy into domains and codes.
• Classification of resolutions as satisfactory or unsatisfactory.
• Statistical analysis using the Fisher test.

Main Results:

• 146 codes were extracted from 71 narratives, with clinical issues being most common (52%).
• Quality of care, safety, and communication breakdown were frequent complaint codes.
• No statistically significant difference in satisfactory resolution between single-coded (81%) and multifactorial (86%) complaints.
• Over 50% of complaints were resolved by providing clarification.

Conclusions:

• Patient complaints in image-guided interventions do not differ significantly based on single vs. multifactorial coding.
• Clinical issues and communication breakdowns are primary drivers of patient complaints.
• Clarification is an effective method for resolving most patient complaints.