Efficiency of Primary Health Services in the Greek Public Sector: Evidence from Bootstrapped DEA/FDH Estimators.

Strengthening primary healthcare (PHC) is vital for enhancing efficiency and improving access, clinical outcomes, and population well-being. The World Health Organization emphasizes the role of effective PHC in reducing healthcare costs and boosting productivity. With growing healthcare demands and limited resources, efficient management is critical.

Valuing Outpatients' Perspective on Primary Health Care Services in Greece: A Cross-Sectional Survey on Satisfaction and Personal-Centered Care.

Introduction: The aims of the study were to identify and analyze the determinants associated with outpatient satisfaction in Greek primary care. This is because there is a general consensus that primary care is the linchpin of effective person-centered care delivery.

Methods: A cross-sectional survey was conducted with 1012 patients' exit interviews; sociodemographic variables were included in the questionnaire to obtain data on the satisfaction of primary care users with 20 public primary healthcare centers in Athens between June 2019 and April 2021.

Evaluation of the Quality of Life and the Quality of Sleep of postmenopausal osteoporotic women, without evidence of an osteoporotic fracture, who attended an outpatient DXA scan service.

Objectives: The present study aimed to investigate whether impairment of health-related quality of life (HRQOL) and possibly, the quality of sleep (Sleep Quality - SQ), of osteoporotic women, may occur, even before the onset of an osteoporotic fracture.

Methods: The study included 109 women, divided (DXA) into two groups (age-matched): the Control Group (n=68; normal and osteopenic) and the Patient Group (n=41; osteoporotic). Review of medical history of the participants, was followed by evaluation of HRQOL and SQ with the EQ-5D-3L and the PSQI questionnaires, respectively.

A window-DEA based efficiency evaluation of the public hospital sector in Greece during the 5-year economic crisis.

The main objective of this study was to apply the non-parametric method of Data Envelopment Analysis (DEA) to measure the efficiency of Greek NHS hospitals between 2009-2013. Hospitals were divided into four separate groups with common characteristics which allowed comparisons to be carried out in the context of increased homogeneity. The window-DEA method was chosen since it leads to increased discrimination on the results especially when applied to small samples and it enables year-by-year comparisons of the results.

Decomposition of potential efficiency gains from hospital mergers in Greece.

This paper evaluates the technical efficiency of 71 Greek public hospitals and examines potential efficiency gains from 13 candidate mergers among them. Efficiency assessments are performed using bootstrapped Data Envelopment Analysis (DEA) whilst merger analysis is conducted by applying the Bogetoft and Wang methodology which allows the overall potential merger gains to be decomposed into three main components of inefficiency, namely technical (or learning), scope (or harmony) and scale (or size) effects. Thus, the analysis provides important insights not only on the magnitude of the potential total efficiency gains but also on their sources.

The impact of non-discretionary factors on DEA and SFA technical efficiency differences.

The purpose of this study was to examine if factors of the external operating environment can explain differences in technical efficiency derived from Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA). In a sample of 124 dialysis facilities, technical efficiency was compared according to ownership, region, years in operation and size. With second-stage Tobit regression, DEA and SFA efficiency was regressed against these environmental factors to determine their potential for predicting technical efficiency, as well as the efficiency differences between the two frontier methods.

Employing post-DEA cross-evaluation and cluster analysis in a sample of Greek NHS hospitals.

To increase Data Envelopment Analysis (DEA) discrimination of efficient Decision Making Units (DMUs), by complementing "self-evaluated" efficiencies with "peer-evaluated" cross-efficiencies and, based on these results, to classify the DMUs using cluster analysis. Healthcare, which is deprived of such studies, was chosen as the study area. The sample consisted of 27 small- to medium-sized (70-500 beds) NHS general hospitals distributed throughout Greece, in areas where they are the sole NHS representatives.