Digital Health Interventions & Applied AI in Healthcare: Predicting Overcrowding in the Emergency Department
Thesis (MA) - Reference number 2024-253
Advisor: Cornelius Born
CONTEXT
The emergency department (ED) is a critical yet highly volatile healthcare environment with varying patient volumes and acuity levels (Croskerry & Sinclair, 2001; Kovacs & Croskerry, 1999). One of the most pressing challenges is overcrowding, where the demand for emergency services surpasses the available resources to provide timely care (Affleck et al., 2013; Bernstein et al., 2009; Javidan et al., 2021). Numerous studies have demonstrated the correlation between overcrowding and adverse clinical outcomes, including increased patient morbidity and mortality (McKenna et al., 2019; Rasouli et al., 2019).
Therefore, the ZNAflow project [1] aims to develop an AI-based assistance system that forecasts overcrowding to support clinicians in preparing for and mitigating these situations. The system accesses internal and external data sources, e.g., ambulance, weather, and event data.
At the project’s current stage, we have a running prototype and are planning an intervention study for evaluation. At the same time, we are drafting guidelines for integrating ethics and norms in AI engineering in the healthcare sector and developing a concept for transfer to other hospitals.
We offer the opportunity to write a highly relevant and practical thesis that fits your skills and interests.
TASKS
- Design and implementation of a before-and-after intervention study in a German emergency department
- Creation of a guideline on the integration of ethics and norms in AI engineering in the healthcare sector
- Creation of a roll-out concept, including a business model (taxonomy of business models of digital health applications, as well as design principles, functionalities, and individualization aspects of the application)
REQUIREMENTS
- High degree of individual responsibility
- Experience in and willingness to conduct scientific studies and analyze qualitative and quantitative data
- Structured, reliable, and self-motivated work style
- Previous experience in the healthcare sector would be advantageous, especially for the intervention studies
FURTHER INFORMATION
The topic can be adapted according to your interests. The thesis can be written in English or German. If you have any further questions, do not hesitate to contact me directly. Please send your application, including our application form, "Notenauszug" from TUMonline, and CV to cornelius.born@tum.de. Please note that we can only consider applications with complete documents.
REFERENCES
Affleck, A., Parks, P., Drummond, A., Rowe, B. H., & Ovens, H. J. (2013). Emergency department overcrowding and access block. Canadian Journal of Emergency Medicine, 15(6), 359–370. https://doi.org/10.1017/S1481803500002451
Bernstein, S. L., Aronsky, D., Duseja, R., Epstein, S., Handel, D., Hwang, U., McCarthy, M., John McConnell, K., Pines, J. M., Rathlev, N., Schafermeyer, R., Zwemer, F., Schull, M., Asplin, B. R., & Society for Academic Emergency Medicine, E. D. C. T. F. (2009). The Effect of Emergency Department Crowding on Clinically Oriented Outcomes. Academic Emergency Medicine, 16(1), 1–10. https://doi.org/10.1111/j.1553-2712.2008.00295.x
Croskerry, P., & Sinclair, D. (2001). Emergency medicine: A practice prone to error? Canadian Journal of Emergency Medicine, 3(4), 271–276. https://doi.org/10.1017/S1481803500005765
Javidan, A. P., Hansen, K., Higginson, I., Jones, P., & Lang, E. (2021). The International Federation for Emergency Medicine report on emergency department crowding and access block: A brief summary. Emergency Medicine Journal, 38(3), 245–246. https://doi.org/10.1136/emermed-2020-210716
Kovacs, G., & Croskerry, P. (1999). Clinical Decision Making: An Emergency Medicine Perspective. Academic Emergency Medicine, 6(9), 947–952. https://doi.org/10.1111/j.1553-2712.1999.tb01246.x
McKenna, P., Heslin, S. M., Viccellio, P., Mallon, W. K., Hernandez, C., & Morley, E. J. (2019). Emergency department and hospital crowding: Causes, consequences, and cures. Clinical and Experimental Emergency Medicine, 6(3), 189–195. https://doi.org/10.15441/ceem.18.022
Rasouli, H. R., Esfahani, A. A., Nobakht, M., Eskandari, M., Mahmoodi, S., Goodarzi, H., & Abbasi Farajzadeh, M. (2019). Outcomes of Crowding in Emergency Departments; a Systematic Review. Archives of Academic Emergency Medicine, 7(1), e52.
Link
[1] https://www.cs.cit.tum.de/bpm/krcmar/research/current-projects/znaflow/