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

The amount of quality data continues to increase. To help prioritise resources for quality improvement, managers need thorough reviews to help them decide which indicators are most important to improve. The reality is that data is presented in piles of reports and hundreds of tables and graphs that are very time-consuming to go through and that rarely result in a simple comprehensive overview. This paper presents an empirically tested tool to create a simple overview of complex quality data.

Data comes from a questionnaire-based patient satisfaction survey of 13,129 patients and 1,589 staff members at Ribe County Hospital. A method is described: how to use colour coding in order to present the results for 16 indicators, measured both by patients and three staff member groups, for 28 departments and 46 ambulatories, in one page.

Data for mean satisfaction scores on all questions are shown for each department in a core map. Aggregated departmental mean satisfaction scores are then calculated, as are hospital mean scores for each question. The same is done for staff members' evaluation and for outpatient care. Few problems are universal and most of the problematic scores are related to a minority of departments, calling for local activities to improve quality. Diversity seems to be the rule.

The SurveillanceMapper-tool proved effective for handling the complexity of quality measures. It is easy to translate hundreds of graphs and tables into the SurveillanceMapper-tool format. The method facilitates easy spotting areas for quality improvements and evaluating the results of intervention.