DeepAI AI Chat
Log In Sign Up

EHRs Connect Research and Practice: Where Predictive Modeling, Artificial Intelligence, and Clinical Decision Support Intersect

04/22/2012
by   Casey Bennett, et al.
0

Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and genetic information as well, and, as such, can be seen as repositories of increasingly valuable information about patients' health conditions and responses to treatment over time. Methods: We describe a case study of 423 patients treated by Centerstone within Tennessee and Indiana in which we utilized electronic health record data to generate predictive algorithms of individual patient treatment response. Multiple models were constructed using predictor variables derived from clinical, financial and geographic data. Results: For the 423 patients, 101 deteriorated, 223 improved and in 99 there was no change in clinical condition. Based on modeling of various clinical indicators at baseline, the highest accuracy in predicting individual patient response ranged from 70-72 terms of individual predictors, the Centerstone Assessment of Recovery Level - Adult (CARLA) baseline score was most significant in predicting outcome over time (odds ratio 4.1 + 2.27). Other variables with consistently significant impact on outcome included payer, diagnostic category, location and provision of case management services. Conclusions: This approach represents a promising avenue toward reducing the current gap between research and practice across healthcare, developing data-driven clinical decision support based on real-world populations, and serving as a component of embedded clinical artificial intelligences that "learn" over time.

READ FULL TEXT

page 9

page 15

07/23/2020

Clinical Recommender System: Predicting Medical Specialty Diagnostic Choices with Neural Network Ensembles

The growing demand for key healthcare resources such as clinical experti...
10/17/2019

Generalized Mixed Modeling in Massive Electronic Health Record Databases: what is a healthy serum potassium?

Converting electronic health record (EHR) entries to useful clinical inf...
11/02/2022

A study linking patient EHR data to external death data at Stanford Medicine

This manuscript explores linking real-world patient data with external d...
09/19/2022

A cost-based multi-layer network approach for the discovery of patient phenotypes

Clinical records frequently include assessments of the characteristics o...
11/13/2018

Embedding Electronic Health Records for Clinical Information Retrieval

Neural network representation learning frameworks have recently shown to...