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Tia Albright

How 3 Leading Health Systems Improved Hospital Length of Stay with Aidoc 

Length of Stay
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Looking to move patients from diagnosis to treatment — and, ultimately, discharge — faster? An effective and beneficial way to do that is by reducing bottlenecks in the patient journey with clinical AI. 

The benefits: fewer complications, smarter resource allocation and better financial outcomes. 

Aidoc’s Impact on Length of Stay (LoS)

Here are some examples of how Aidoc helps hospitals deliver faster, safer care by reducing LoS. 

Yale New Haven Health

Yale New Haven Health experienced the LoS impacts: 

  •  36-minute reduction in Emergency Department (ED) LoS for intracranial hemorrhage (ICH) patients1
  • 2.3-day reduction in inpatient LoS (18.1 days to 15.8 days) for ICH patients1
  • 2.6-day reduction in inpatient LoS for all other patients1

Cedars-Sinai Medical Center

At Cedars-Sinai Medical Center, the team saw these LoS results: 

  • 3-day reduction in intensive care unit (ICU) LoS for Pulmonary Embolism (PE) patients2
  • 3-day reduction in ICU LoS for ICH patients2
  • 1.3-day reduction in inpatient LoS for ICH patients3
  • 2.07-day reduction in inpatient LoS for PE patients3

HCA Healthcare

HCA Healthcare saw the following benefits: 

  • 44.4-minute reduction in mean ICU LoS (80.2 hours to 35.8 hours) for thrombectomy patients4 
  • 55-minute reduction in mean ICU LoS for ultrasound-assisted thrombolysis (USAT) patients4

Interested in learning more about Aidoc’s research?

Download the compendium.

Citations

  1. Davis, Melissa A., et al. “Machine Learning and Improved Quality Metrics in Acute Intracranial Hemorrhage by Noncontrast Computed Tomography.” Current Problems in Diagnostic Radiology, vol. 51, no. 4, July–August 2022, pp. 556-561, Elsevier, https://doi.org/10.1067/j.cpradiol.2020.10.007.
  2. Gupta, Kavish, MD, et al. “Mechanical Thrombectomy, Artificial Intelligence and the Activation of a Pulmonary Embolism Response Team.” PERT Consortium 2022, abstract presentation.
  3. Petry, Michael et al. “Decreased Hospital Length of Stay for ICH and PE after Adoption of an Artificial Intelligence-Augmented Radiological Worklist Triage System.” Radiology research and practice vol. 2022 2141839. 18 Aug. 2022, doi:10.1155/2022/2141840
  4. Burch, Charles, Craig Ainsworth, Jairo Melo, Paige Castaneda, Anne Scheid, Odai Alhasanat, Chandra Kunavarapu, and Eric Nelson. “Improving Patient Outcomes with an AI-Enhanced Pulmonary Embolism Response Team in a Large Healthcare Network.” PERT Consortium, 2024, Methodist Healthcare, San Antonio, TX. Abstract presentation

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Tia Albright
Tia Albright
Manager, Radiology and ED Marketing Communications

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