How a tiny hospital used AI to lower costs and improve patient outcomes
As a physician who does lots of bioinformatics, this seems like a very optimistic article which is likely just overfitting the existing data.<p>Patients don&#x27;t come to the hospital saying &quot;I have pneumonia&quot;. The come for a cough or a fever and it takes these tests to figure out the diagnosis. A small hospital like this probably doesn&#x27;t have the data to really build a robust model that will help all its patients. Even major academic centers have relatively limited data for the number of permutations of health possibilities. Sure they have lots of pneumonia data, but how many cases of pneumonia do they have in cystic fibrosis patients who also have COPD?<p>I certainly think AI can help cut costs, reduce over-testing and reduce length of stay, but decreasing length of stay by 2 days would be a shocking advance. (The average simple pneumonia LOS of stay for a medicare patient without co-morbidities* was 3.3 days and with major co-morbidities* was 5.7 days in 2017). [0]<p>*as defined by medicare.<p>[0] <a href="https:&#x2F;&#x2F;www.cms.gov&#x2F;Medicare&#x2F;Medicare-Fee-for-Service-Payment&#x2F;AcuteInpatientPPS&#x2F;FY2017-IPPS-Final-Rule-Home-Page-Items&#x2F;FY2017-IPPS-Final-Rule-Tables.html" rel="nofollow">https:&#x2F;&#x2F;www.cms.gov&#x2F;Medicare&#x2F;Medicare-Fee-for-Service-Paymen...</a>