A Comprehensive Key Performance Indicators Dashboard for Emergency Medical Services
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32807
A Comprehensive Key Performance Indicators Dashboard for Emergency Medical Services

Authors: G. Feletti, D. Tedesco, P. Trucco

Abstract:

The present study aims to develop a dashboard of Key Performance Indicators (KPI) to enhance information and predictive capabilities in Emergency Medical Services (EMS) systems, supporting both operational and strategic decisions of different actors. The employed research methodology consists of a first phase of revision of the technical-scientific literature concerning the indicators currently in use for the performance measurement of EMS. It emerges that current studies focus on two distinct areas and independent objectives: the ambulance service, a fundamental component of pre-hospital health treatment, and the patient care in the Emergency Department (ED). Conversely, the perspective proposed by this study is to consider an integrated view of the ambulance service process and the ED process, both essential to ensure high quality of care and patient safety. Thus, the proposal covers the end-to-end healthcare service process and, as such, allows considering the interconnection between the two EMS processes, the pre-hospital and hospital ones, connected by the assignment of the patient to a specific ED. In this way, it is possible to optimize the entire patient management. Therefore, attention is paid even to EMS aspects that in current literature tend to be neglected or underestimated. In particular, the integration of the two processes enables to evaluate the advantage of an ED selection decision having visibility on EDs’ saturation status and therefore considering, besides the distance, the available resources and the expected waiting times. Starting from a critical review of the KPIs proposed in extant literature, the design of the dashboard was carried out: the high number of analyzed KPIs was reduced by eliminating firstly the ones not in line with the aim of the study and then the ones supporting a similar functionality. The KPIs finally selected were tested on a realistic dataset, which draw us to exclude additional indicators due to unavailability of data required for their computation. The final dashboard, that was discussed and validated by experts in the field, includes a variety of KPIs able to support operational and planning decisions, early warning, and citizens’ awareness on EDs accessibility in real time. The association of each KPI to the EMS phase it refers to enabled the design of a well-balanced dashboard, covering both efficiency and effectiveness performance objectives of the entire EMS process. Indeed, just the initial phases related to the interconnection between ambulance service and patient care are covered by traditional KPIs. Future developments could be directed to building a hierarchical dashboard, composed by a high-level minimal set of KPIs for measuring the basic performance of the EMS system, at an aggregate level, and lower levels of KPIs that bring additional and more detailed information on specific performance dimensions or EMS phases.

Keywords: Emergency Medical Services, Key Performance Indicators, Dashboard, Decision Support.

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References:


[1] El Sayed, Mazen J. 2012. “Measuring Quality in Emergency Medical Services: A Review of Clinical Performance Indicators.” Emergency Medicine International 2012: 1–7.
[2] Rahman, Nik Hisamuddin, Hideharu Tanaka, Sang Do Shin, Yih Yng Ng, Thammapad Piyasuwankul, Chih Hao Lin, and Marcus Eng Hock Ong. 2015. “Emergency Medical Services Key Performance Measurement in Asian Cities.” International Journal of Emergency Medicine 8 (1): 4–9.
[3] Krafft, Thomas, Luis García Castrillo-Riesgo, Steve Edwards, Matthias Fischer, Jerry Overton, Iain Robertson-Steel, and Anke König. 2003. “European Emergency Data Project (EED Project): EMS Data-Based Health Surveillance System.” European Journal of Public Health 13 (3 SUPPL.): 85–90.
[4] Ministero della Salute. 2019. “Linee Di Indirizzo Nazionali Sul Triage Intraospedaliero,” no. 2: 1–135.
[5] Almasi, Sohrab, Reza Rabiei, Hamid Moghaddasi, and Mojtaba Vahidi-Asl. 2021. “Emergency Department Quality Dashboard; a Systematic Review of Performance Indicators, Functionalities, and Challenges.” Archives of Academic Emergency Medicine.
[6] Wiler, Jennifer L., Shari Welch, Jesse Pines, Jeremiah Schuur, Nick Jouriles, and Suzanne Stone-Griffith. 2015. “Emergency Department Performance Measures Updates: Proceedings of the 2014 Emergency Department Benchmarking Alliance Consensus Summit.” Academic Emergency Medicine 22 (5): 542–53.
[7] Khalifa, Mohamed, and Ibrahim Zabani. 2016. “Developing Emergency Room Key Performance Indicators: What to Measure and Why Should We Measure It?” Studies in Health Technology and Informatics 226 (October 2017): 179–82.
[8] Núñez, Alicia, Liliana Neriz, Ricardo Mateo, Francisco Ramis, and Arkalgud Ramaprasad. 2018. “Emergency Departments Key Performance Indicators: A Unified Framework and Its Practice.” International Journal of Health Planning and Management 33 (4): 915–33.
[9] Ospina, Maria B., Kenneth Bond, Michael Schull, Grant Innes, Sandra Blitz, and Brian H. Rowe. 2007. “Key Indicators of Overcrowding in Canadian Emergency Departments: A Delphi Study.” Canadian Journal of Emergency Medicine 9 (5): 339–46.
[10] Abo-Hamad, Waleed, and Amr Arisha. 2013. “Simulation-Based Framework to Improve Patient Experience in an Emergency Department.” European Journal of Operational Research 224 (1): 154–66.
[11] Kadri, Farid, Sondès Chaabane, and Christian Tahon. 2016. “Reactive Control System to Manage Strain Situations in Emergency Departments.” ICINCO 2016 - Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics 2 (January): 576–83.
[12] Castanheira-Pinto, Alexandre, Bruno S. Gonçalves, Rui M. Lima, and José Dinis-Carvalho. 2021. “Modeling, Assessment and Design of an Emergency Department of a Public Hospital through Discrete-Event Simulation.” Applied Sciences (Switzerland) 11 (2): 1–25.
[13] Duarte, Diego, Chris Walshaw, and Nadarajah Ramesh. 2021. “A Comparison of Time-Series Predictions for Healthcare Emergency Department Indicators and the Impact of COVID-19.” Applied Sciences (Switzerland).
[14] Welch, Shari, James Augustine, Carlos A. Camargo, and Charles Reese. 2006. “Emergency Department Performance Measures and Benchmarking Summit.” Academic Emergency Medicine 13 (10): 1074–80.
[15] Di Somma, Salvatore, Lorenzo Paladino, Louella Vaughan, Irene Lalle, Laura Magrini, and Massimo Magnanti. 2015. “Overcrowding in Emergency Department: An International Issue.” Internal and Emergency Medicine 10 (2): 171–75.
[16] Postma, Jeroen, and Teun Zuiderent-Jerak. 2017. “Beyond Volume Indicators and Centralization: Toward a Broad Perspective on Policy for Improving Quality of Emergency Care.” Annals of Emergency Medicine 69 (6): 689-697.e1.
[17] Stefanini, Alessandro, Davide Aloini, Elisabetta Benevento, Riccardo Dulmin, and Valeria Mininno. 2018. “Performance Analysis in Emergency Departments: A Data-Driven Approach.” Measuring Business Excellence 22 (2): 130–45.
[18] Ismail, Khaled, Waleed Abo-Hamad, and Amr Arisha. 2010. “Integrating Balanced Scorecard and Simulation Modeling to Improve Emergency Department Performance in Irish Hospitals.” Proceedings - Winter Simulation Conference 2007 (Hse 2007): 2340–51.
[19] Vittadini, Giorgio, Paolo Berta, Michele Castelli, Gianmaria Martini, Luca Giuseppe Merlino, and Carlo Zocchetti. 2012. “Manuale Del Sistema Di Valutazione Della Performance Degli Ospedali Lombardi.”
[20] Lin, Chih Hao, Chung Yao Kao, and Chong Ye Huang. 2015. “Managing Emergency Department Overcrowding via Ambulance Diversion: A Discrete Event Simulation Model.” Journal of the Formosan Medical Association 114 (1): 64–71.
[21] Schull, Michael J., Astrid Guttmann, Chad A. Leaver, Marian Vermeulen, Caroline M. Hatcher, Brian H. Rowe, Merrick Zwarenstein, and Geoffrey M. Anderson. 2011. “Prioritizing Performance Measurement for Emergency Department Care: Consensus on Evidencebased Quality of Care Indicators.” Canadian Journal of Emergency Medicine.
[22] Di Bella, Enrico, Luca Gandullia, Lucia Leporatti, Marcello Montefiori, and Patrizia Orcamo. 2018. “Ranking and Prioritization of Emergency Departments Based on Multi-Indicator Systems.” Social Indicators Research.
[23] Tregunno, Deborah, G. Ross Baker, Jan Barnsley, and Michael Murray. 2004. “Competing Values of Emergency Department Performance: Balancing Multiple Stakeholder Perspectives.” Health Services Research 39 (4 I): 771–92.
[24] ACSS Regione Lombardia. 2020. “Analisi Finalizzate Alla Valutazione Delle Performance Di Pronto Soccorso - Area Di Azione L.R. 33/2009 s.m.i. Art.11 c.4 Lett. d) e G),” 7/8.
[25] Ministero della Salute. 2020. “Specifiche Funzionali Dei Tracciati 118 e Pronto Soccorso.”
[26] Emergency Urgency OnLine (EUOL). https://www.astir.com/soluzioni/euol-emergenza-urgenza-online/