Partial least squares path modelling for the evaluation of patients’ satisfaction after thoracic surgical procedures☆

Abstract

Patient satisfaction can be measured by criteria inspired by currently available marketing research methods. Among the latter, qualitative methods can be performed on limited population samples and be based on latent variables, i.e., variables that are not directly observed but deducted from mathematical analysis (i.e., quality of life). Qualitative research methods include the partial least squares (PLS) path modelling aimed at defining optimal linear relations among latent variables in order to assemble the best set of predictions. In the February-May 2007 period, 73 patients (41 males and 32 females) consecutively discharged from the Division of Thoracic Surgery of the National Cancer Institute at Naples underwent an adaptation of the PLS path modelling by accepting to file an itemized questionnaire on 29 different aspects of hospitalization. The sampled population represented about 32% of all patients operated by a single surgeon and about 21% of all patients admitted to a 12-bed thoracic surgical ward in 2007. Five categories of performance were identified, i.e., quality of the facilities, quality and clarity of provided Information, quality of relationship with surgeons and nurses, quality of the received care, overall patient satisfaction. During the analyzed period, the overall patient satisfaction reached 91% (+/-15). The mean scores were 62% (+/-33), 80% (+/-28), 84% (+/-21), 81% (+/-19), 88% (+/-15) for ward facilities, information provided, relationship with personnel, clinical services, and, perceived quality, respectively. In addition, overall perceived quality, relationship with personnel and the provision of information were the variables with greatest positive impact on patient satisfaction. Conversely, waiting times for radiological procedures, quality of meals and duration of visiting hours adversely affected the level of satisfaction. In the setting of a thorough audit of current clinical practice, PLS path modelling may represent another valuable tool to measure quality in the setting of managed health care since it allows for the identification of areas where the service can be improved.