Identifying potential predictable indicators for the management of tertiary hospitals

Yolima Cossio‐Gil, Francisco Javier Pérez‐Sádaba, Jaume Ribera, Emmanuel Giménez, Luís Marte, Rosa Ramos, Eva Aurin, Michael Peterlunger, Jens Steinbrink, Elena Angela Maria Bottinelli, Nina Nelson, Lynn Seveke, Noe Garin and Cesar Velasco

International Journal of Health Planning and Management, 2024, vol. 39, issue 2, 278-292

Abstract: Background The European University Hospitals Alliance (EUHA) recognises the need to move from the classical approach of measuring key performance indicators (KPIs) to an anticipative approach based on predictable indicators to take decisions (Key Decision Indicators, KDIs). It might help managers to anticipate poor results before they occur to prevent or correct them early. Objective This paper aims to identify potential KDIs and to prioritize those most relevant for high complexity hospitals. Methods A narrative review was performed to identify KPIs with the potential to become KDIs. Then, two surveys were conducted with EUHA hospital managers (n = 51) to assess potential KDIs according to their relevance for decision‐making (Value) and their availability and effort required to be predicted (Feasibility). Potential KDIs are prioritized for testing as predictable indicators and developing in the short term if they were classified as highly Value and Feasible. Results The narrative review identified 45 potential KDIs out of 153 indicators and 11 were prioritized. Of nine EUHA hospitals, 25 members from seven answered, prioritizing KDIs related to the emergency department (ED), hospitalisation and surgical processes (n = 8), infrastructure and resources (n = 2) and health outcomes and quality (n = 1). The highest scores in this group were for those related to ED. The results were homogeneous among the different hospitals. Conclusions Potential KDIs related to care processes and hospital patient flow was the most prioritized ones to test as being predictable. KDIs represent a new approach to decision‐making, whose potential to be predicted could impact the planning and management of hospital resources and, therefore, healthcare quality.

Date: 2024
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