Consistency of priorities for quality improvement for nursing homes in Italy and Canada: A comparison of optimization models of resident satisfaction. Issue 8 (August 2017)

• Record Type: Journal Article
• Authors: Barsanti, Sara; Walker, Kevin; Seghieri, Chiara; Rosa, Antonella; Wodchis, Walter P.
• Is Part Of: Health policy. Volume 121:Issue 8(2017)
• Page Start: 862
• Page End: 869
• Publication Date: 2017-08
• Subjects: Quality improvement -- Processes -- Willingness to recommend -- Nursing homes -- Long-term care -- Patient experience -- Optimization technique; Medical education -- Periodicals; Medical policy -- Periodicals; Delivery of Health Care -- Periodicals; Education, Medical -- Periodicals; Health Education -- Periodicals; Health Planning -- Periodicals; Public Policy -- Periodicals; Enseignement médical -- Périodiques; Politique sanitaire -- Périodiques; Medical education; Medical policy; Periodicals; Electronic journals; Electronic journals; 362.1
• DOI: 10.1016/j.healthpol.2017.06.004
• Languages: English
• ISSNs: 0168-8510

Abstract

Highlights: The research analyzes residents' satisfaction with nursing homes across Canada and Italy. It is based on optimization model for quality improvement in nursing homes. Different aspects of nursing homes were prioritized in each jurisdiction. Staff-related aspects of care is a shared quality phenomenon. Context matters when prioritizing areas for quality improvement activities. Abstract: The paper seeks to identify aspects of care that may be easily modified to yield a desired level of improvement in residents' overall satisfaction with nursing homes, comparing data across Canada and Italy. Using a structured questionnaire, 681 and 1116 nursing home residents were surveyed in Ontario in 2009 and in Tuscany in 2012, respectively. Fourteen items were common to the surveys, including willingness to recommend (WTR), which was used as the dependent variable and measure of global satisfaction. The other analogous items were entered as covariates in ordinal logistic regression models predicting residents' WTR in each jurisdiction separately. Regression coefficients were then incorporated into a constrained nonlinear optimization problem selecting the most efficient combination of predictors necessary to increase WTR by as much as 15%. Staff-related aspects of care were selected first in the optimization models of each jurisdiction. In Ontario, to improve WTR the primary focus should be on staff relationships with residents, while in Tuscany it was the technical skill and knowledge of staff that was selected first by the optimization model. Different optimization solutions might mean that the strategies required to improve global satisfaction in one jurisdiction could be different than those for the other jurisdictions. The optimization model employed provides a novel solution for prioritizing areas of focus for quality improvement for nursing homes.