@article{TEXTUAL,
      recid = {7261},
      author = {Kotovich, Dmitry and Twig, Gilad and Itsekson-Hayosh, Zeev  and Klug, Maximiliano and Simon, Asaf Ben and Yaniv, Gal  and Konen, Eli and Tau, Noam and Raskin, Daniel and Chang,  Paul J. and Orion, David},
      title = {The impact on clinical outcomes after 1 year of  implementation of an artificial intelligence solution for  the detection of intracranial hemorrhage},
      journal = {International Journal of Emergency Medicine},
      address = {2023-08-11},
      number = {TEXTUAL},
      abstract = {&lt;p&gt;Background: To assess the effect of a commercial  artificial intelligence (AI) solution implementation in the  emergency department on clinical outcomes in a single level  1 trauma center.&lt;/p&gt; &lt;p&gt;Methods: A retrospective cohort  study for two time periods-pre-AI (1.1.2017-1.1.2018) and  post-AI (1.1.2019-1.1.2020)-in a level 1 trauma center was  performed. The ICH algorithm was applied to 587 consecutive  patients with a confirmed diagnosis of ICH on head CT upon  admission to the emergency department. Study variables  included demographics, patient outcomes, and imaging data.  Participants admitted to the emergency department during  the same time periods for other acute diagnoses (ischemic  stroke (IS) and myocardial infarction (MI)) served as  control groups. Primary outcomes were 30- and 120-day  all-cause mortality. The secondary outcome was morbidity  based on Modified Rankin Scale for Neurologic Disability  (mRS) at discharge.&lt;/p&gt; &lt;p&gt;Results: Five hundred  eighty-seven participants (289 pre-AI-age 71 ± 1, 169 men;  298 post-AI-age 69 ± 1, 187 men) with ICH were eligible for  the analyzed period. Demographics, comorbidities, Emergency  Severity Score, type of ICH, and length of stay were not  significantly different between the two time periods. The  30- and 120-day all-cause mortality were significantly  reduced in the post-AI group when compared to the pre-AI  group (27.7% vs 17.5%; p = 0.004 and 31.8% vs 21.7%; p =  0.017, respectively). Modified Rankin Scale (mRS) at  discharge was significantly reduced post-AI implementation  (3.2 vs 2.8; p = 0.044).&lt;/p&gt; &lt;p&gt;Conclusion: The added value  of this study emphasizes the introduction of artificial  intelligence (AI) computer-aided triage and prioritization  software in an emergent care setting that demonstrated a  significant reduction in a 30- and 120-day all-cause  mortality and morbidity for patients diagnosed with  intracranial hemorrhage (ICH). Along with mortality rates,  the AI software was associated with a significant reduction  in the Modified Ranking Scale (mRs).&lt;/p&gt;},
      url = {http://knowledge.uchicago.edu/record/7261},
}