A Network-DEA model to evaluate the impact of quality and access on hospital performance.

The relationship between efficiency, quality, and access in healthcare is far from being well defined. In particular, there is no consensus on whether there is a trade-off between hospital performance and its social dimensions, such as the care appropriateness, safety, and access to proper health care. This study proposes a new approach based on the Network Data Envelopment Analysis (NDEA) to evaluate the existence of potential trade-offs between efficiency, quality, and access. The aim is to contribute for the heated debate around this topic with a novel approach. The suggested methodology combines a NDEA model with the weak disposability of outputs to handle with undesirable outputs related to the poor quality of care or the lack of access to appropriate and safe care. This combination results in a more realistic approach that has not yet been used to investigate this topic. We utilised data of the Portuguese National Health Service from 2016 to 2019, with four models and nineteen variables selected to quantify the efficiency, quality, and access to public hospital care in Portugal. A baseline efficiency score was calculated and compared with the performance scores obtained under two hypothetical scenarios to quantify the impact of each quality/access-related dimension on efficiency. The first scenario considers that each variable, individually, is at its best situation (for example, absence of septicaemia cases), and the second one, at its worst (e.g., all seen inpatients had a septicaemia case). The findings suggest that there might exist meaningful trade-offs between efficiency, quality, and access. Most variables exhibited a considerable and negative impact on the overall hospital efficiency. That is, we may expect a trade-off between efficiency and quality/access.

Electre Tri-C, a multiple criteria decision aiding sorting model applied to assisted reproduction.

OBJECTIVE: The aim of this paper is to apply an informatics tool for dealing with a medical decision aiding problem to help infertile couples to become parents, when using assisted reproduction. METHODS: A multiple criteria decision aiding method for sorting or ordinal classification problems, called Electre Tri-C, was chosen in order to assign each couple to an embryo-transfer category. The set of categories puts in evidence a way for increasing the single pregnancy rate, while minimizing multiple pregnancies. The decision aiding sorting model was co-constructed through an interaction process between the decision aiding analysts and the medical experts. RESULTS: According to the sample used in this study, the Electre Tri-C method provides a unique category in 86% of the cases and it achieves a sorting accuracy of 61%. Retrospectively, the medical experts do agree that some of their judgments concerning the number of embryos to transfer back to the uterus of the woman could be different according to these results. The current ART methodology achieves a single pregnancy rate of 47% and a twin pregnancy rate of 14%. Thus, this informatics tools may play an important role for supporting ART medical decisions, aiming to increase the single pregnancy rate, while minimizing multiple pregnancies. LIMITATIONS: Building the set of criteria comprises a part of arbitrariness and imperfect knowledge, which require time and expertise to be refined. Among them, three criteria are modeled by means of a holistic classification procedure by the medical experts.