Performance of Tunisian Public Hospitals: A Comparative Assessment Using the Pabón Lasso Model

Document Type : Research Paper


Unit of Research in Development Economics (URDE), Faculty of Economics and Management of Sfax, Tunisia


Background and Objectives: Constant monitoring of healthcare organizations’ performance is an integral part of informed health policy-making. Several hospital performance assessment methods have been proposed in the literature. Pabon Lasso Model offers a fast and convenient method for comparative evaluation of hospital performance. This study aimed to evaluate the relative performance of hospitals in Tunisia, using Pabon Lasso Model.   Methods: A cross-sectional descriptive study was conducted during 2011-2012 to measure the hospitals performance in Tunisia. A sample of 40 public hospitals was surveyed. The assessed hospital performance indicators included Bed Occupation Rate (BOR), Bed Turnover Ratio (BTR), Average Length of Stay (ASL). The relevant data were collected using a standard forms approved by the Tunisian Ministry of Health. For each hospital the data were extracted from the Hospital Information Systems. The data were plotted on Pabon Lasso diagram and the performance of each hospital was analyzed by visual inspection. The data were summarized using descriptive statistical methods.   Findings: Average values of 62.3, 58.1% and 3.8 days, was observed for the BTR, BOR, and ALS, respectively. While nineteen hospitals (47.5%) were located in zone 1 of the Pabón Lasso diagram, three (7.5%) were located in zone 2, eleven (27.5%) in zone 3, and seven (17.5%) in zone 4. In addition, 50% of the studied hospitals had low performance in terms of either bed occupancy rate or bed turnover ratio or both.   Conclusions: This study ranked the surveyed hospitals of Tunisia with respect to their overall performance and reveals the relative strength and weakness of each hospital. The speed and convenience of Pabon Lasso measurement method facilitate constant monitoring of overall hospital performance. Moreover, large-scale application of this method, can offer an overall view of the health system performance, which could be used by policy-makers in future plantings.