Meeting
Abstract Number: 267
SHM Converge 2024
Background: There is growing interest in the use of artificial intelligence (AI) predictive models in hospital medicine. However, real-world implementation and evaluation of AI models lags the development of such models, with many such models being developed but never used in live practice. (1) Therefore, relatively less is known about the performance of these models […]
Abstract Number: 280
SHM Converge 2024
Background: Inadequate assessment and recognition of barriers to discharge at time of admission leads to delays in the discharge process and prolongation of hospital admissions. These delays are associated with multiple negative outcomes such as increased length of stay, decreased patient satisfaction, strain on hospital bed capacity, and higher readmission rates. Prior studies have shown […]
Abstract Number: 371
SHM Converge 2024
Background: In-hospital patient deterioration, often unpredictable and multifaceted, presents a significant challenge in hospital medicine. Despite existing measures like illness severity scoring systems and rapid response teams (RRT), patient outcomes remain suboptimal. Delays in recognizing and treating worsening conditions lead to adverse effects and increased healthcare costs. Purpose: In our large healthcare system, covering two […]
Abstract Number: 372
SHM Converge 2024
Background: To address the risk of missed or delayed diagnoses, organizations need to identify and learn from their diagnostic opportunities. However, current approaches to identifying diagnostic opportunities are insensitive, resource intensive and often have low yield.(1,2) Evaluation of diagnostic trajectories can highlight diagnostic opportunities. For example, a patient may re-present to the healthcare system with […]