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Predictors of patient satisfaction with anesthesia using the Press Ganey patient satisfaction survey
Dan Drzymalski1, Evan Liu2, Miki Calderon2
1Department of Anesthesiology and Perioperative Medicine, Tufts Medical Center, Boston, MA, USA.
Background:
While patient satisfaction is a major marker of quality in healthcare, predictors of Press Ganey scores for anesthesia survey questions have not been well explored. This study aimed to explore factors associated with anesthesia-specific patient satisfaction scores.
Material And Methods:
Univariable and multivariable regression analyses were performed to identify predictors of percentile ranking on patient satisfaction questions. We conducted a retrospective analysis of the patient experiences with anesthesia at our institution. Three questions were added to the Press Ganey surveys: (1) rating of anesthesia services, (2) explanations provided by the anesthesiologists, (3) friendliness/courtesy of the anesthesiologist. A total of 3,218, 3,294, and 3,200 patients, respectively, answered the questions on a Likert scale. Covariates included attending anesthesiologist workload, number of comparator healthcare institutions, and season of year.
Results:
Lower percentile rank with rating of anesthesia services was associated with greater attending anesthesiologist workload (-13.7; 95% CI: -24.8 to -2.6; P = 0.017), season of year (-9.0; 95% CI: -16.2 to -1.8; P = 0.016), and smaller number of comparator healthcare institutions (2.4; 95% CI: 0.5 to 4.3; P = 0.015). Lower percentile rank with explanations provided by the anesthesiologists (0.7; 95% CI: 0.1 to 1.3; P = 0.021) and friendliness/courtesy of the anesthesiologist (0.9; 95% CI: 0.2 to 1.5; P = 0.008) were associated with decreasing number of comparator healthcare institutions.
Conclusions:
Improving patient satisfaction may require reduction or redistribution of anesthesiologist workload, improvement in resident communication skills, and increased supervision of junior residents. Anesthesia-specific patient satisfaction scores should be risk-adjusted for contextual factors such as seasonality, workload, and number of comparator institutions before being tied to payment.
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