Hearing the patient's voice? Factors affecting the use of patient survey data in quality improvement.

OBJECTIVE: To develop a framework for understanding factors affecting the use of patient survey data in quality improvement.
DESIGN: Qualitative interviews with senior health professionals and managers and a review of the literature.
SETTING: A quality improvement collaborative in Minnesota, USA involving teams from eight medical groups, focusing on how to use patient survey data to improve patient centred care. PARTICIPANTS: Eight team leaders (medical, clinical improvement or service quality directors) and six team members (clinical improvement coordinators and managers).
RESULTS: Respondents reported three types of barriers before the collaborative: organisational, professional and data related. Organisational barriers included lack of supporting values for patient centred care, competing priorities, and lack of an effective quality improvement infrastructure. Professional barriers included clinicians and staff not being used to focusing on patient interaction as a quality issue, individuals not necessarily having been selected, trained or supported to provide patient centred care, and scepticism, defensiveness or resistance to change following feedback. Data related barriers included lack of expertise with survey data, lack of timely and specific results, uncertainty over the effective interventions or time frames for improvement, and consequent risk of perceived low cost effectiveness of data collection. Factors that appeared to have promoted data use included board led strategies to change culture and create quality improvement forums, leadership from senior physicians and managers, and the persistence of quality improvement staff over several years in demonstrating change in other areas.
CONCLUSION: Using patient survey data may require a more concerted effort than for other clinical data. Organisations may need to develop cultures that support patient centred care, quality improvement capacity, and to align professional receptiveness and leadership with technical expertise with the data.