SurveillanceMapper: a simple method for creating an overview of quality data

Area of Science:

• Healthcare Management
• Health Informatics
• Quality Improvement

Background:

• Increasing volumes of quality data present challenges for healthcare managers.
• Traditional data presentation methods (reports, tables, graphs) are time-consuming and lack comprehensive overviews.
• Prioritizing quality improvement resources requires efficient data analysis tools.

Purpose of the Study:

• To present an empirically tested tool for simplifying complex quality data.
• To enable managers to create a simple overview of quality indicators.
• To facilitate the prioritization of resources for quality improvement initiatives.

Main Methods:

• Utilized data from a patient satisfaction survey (13,129 patients) and staff survey (1,589 staff) at Ribe County Hospital.
• Developed a color-coding method to present results for 16 indicators across 28 departments and 46 ambulatories on a single page.
• Measured patient satisfaction and evaluations from three staff groups.

Main Results:

• Mean satisfaction scores for patients and staff were mapped for each department and ambulatory.
• Aggregated departmental and hospital-wide mean satisfaction scores were calculated.
• Identified that most quality issues were localized to a minority of departments, suggesting targeted interventions.

Conclusions:

• The SurveillanceMapper tool effectively handles the complexity of quality measures.
• The tool simplifies hundreds of graphs and tables into an easily digestible format.
• Facilitates the identification of areas for quality improvement and evaluation of intervention outcomes.