Predicting patient complaints in hospital settings.
BACKGROUND
The prediction of patient complaints is not clearly understood. This is important in so far as patient complaints have been shown to correlate with other adverse outcomes of interest in acute care facilities.


OBJECTIVE
To evaluate the complexity of the patient case and patient safety culture as predictors of patient complaints.


METHODS
A matched case-control analysis of data from patients filing complaints (cases) and matched patients who did not file complaints (controls) in 2005. Staff surveys were used to measure the Patient Safety Culture on individual units.


METHODS
45 inpatient acute care units from four general hospitals in a large metropolitan centre in western Canada.


METHODS
586 patients registering complaints in 2005.


METHODS
The primary outcome was patient complaints (number and type). Predictors included unit-level measures of patient safety culture based on a survey and patient admission characteristics (including age, gender, treatment unit, primary diagnosis, case resource intensity).


RESULTS
The probability of a patient complaint was positively associated with cases of higher complexity (beta = 0.145, p = 0.032; odds ratio = 1.16; CI 0.994 to 1.344). The culture of patient safety within hospital units was not related to the probability of complaints within a given unit.


CONCLUSIONS
Patient complaints are associated with higher clinical complexity. However, the confidence interval around the odds ratio for this association just crosses 1.0 and is thus not "significant" in a traditional framework of dichotomously judging statistical significance at the 95% confidence level. The lack of association with a unit's safety culture, meanwhile, implies that the non-modifiable clinical complexity factor is a more important determinant of patient complaints.
Department of Psychology, University of Calgary, Calgary, Alberta, Canada. babbitt@ucalgary.ca
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Kline
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Willness
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Ghali
D000328:Adult; D000368:Aged; D002170:Canada; D016022:Case-Control Studies; D005260:Female; D005544:Forecasting; D006302:Health Services Research; D006757:Hospital Units / Q000458:organization & administration; D015285:Hospital-Patient Relations; D006769:Hospitals, General / Q000706:statistics & numerical data; D006786:Hospitals, Urban / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D015279:Organizational Culture; D010043:Outcome and Process Assessment, Health Care; D017060:Patient Satisfaction / Q000706:statistics & numerical data*; D011787:Quality of Health Care; D012044:Regression Analysis; D011795:Surveys and Questionnaires