Assessing the queuing process using data envelopment analysis:an application in health centres

Queuing is one of the very important criteria for assessing the performance and efficiency of any service industry, including healthcare. Data Envelopment Analysis (DEA) is one of the most widely-used techniques for performance measurement in healthcare. However, no queue management application has been reported in the health-related DEA literature. Most of the studies regarding patient flow systems had the objective of improving an already existing Appointment System. The current study presents a novel application of DEA for assessing the queuing process at an Outpatients’ department of a large public hospital in a developing country where appointment systems do not exist. The main aim of the current study is to demonstrate the usefulness of DEA modelling in the evaluation of a queue system. The patient flow pathway considered for this study consists of two stages; consultation with a doctor and pharmacy. The DEA results indicated that waiting times and other related queuing variables included need considerable minimisation at both stages

Non-maximizing output behavior for firms with a cost-constrained technology

Indirect output distance function, Shadow cost, Shadow prices, Input preference, Allocative efficiency, C31,

Technology diffusion in hospitals: A log odds random effects regression model

This study identifies the factors that affect the diffusion of hospital innovations. We apply a log odds random effects regression model on hospital micro data. We introduce the concept of clustering innovations and the application of a log odds random effects regression model to describe the diffusion of technologies. We distinguish a number of determinants, such as service, physician, and environmental, financial and organizational characteristics of the 60 Dutch hospitals in our sample. On the basis of this data set on Dutch general hospitals over the period 1995–2002, we conclude that there is a relation between a number of determinants and the diffusion of innovations underlining conclusions fromearlier research. Positive effectswere found on the basis of the size of the hospitals, competition and a hospital’s commitment to innovation. It appears that if a policy is developed to further diffuse innovations, the external effects of demand and market competition need to be examined, which would de facto lead to an efficient use of technology. For the individual hospital, instituting an innovations office appears to be the most prudent course of action.Values Technology and InnovationTechnology, Policy and Managemen

Governance and performance: The performance of Dutch hospitals explained by governance characteristics

This paper describes the efficiency of Dutch hospitals using the Data Envelopment Analysis (DEA) method with bootstrapping. In particular, the analysis focuses on accounting for cost inefficiency measures on the part of hospital corporate governance. We use bootstrap techniques, as introduced by Simar and Wilson (J. Econom. 136(1):31–64, 2007), in order to obtain more efficient estimates of the effects of governance on the efficiency. The results show that part of the cost efficiency can be explained with governance. In particular we find that a higher remuneration of the board as well as a higher remuneration of the supervisory board does not implicate better performance.Innovation SystemsTechnology, Policy and Managemen

School size effects: review and conceptual analysis

In this chapter, a review of international review studies on school size effects is presented. Next, ingredients of a more contextualized and tentative causal mediation model of school size effects are discussed. The chapter is completed by a short overview of school size effects as found in international comparative assessment studies and by a synthesis of Dutch empirical studies that have addressed school size effects, in terms of achievement and attainment outcomes, costs, social outcomes, and good teaching practice