Electronic health record systems for large, integrated healthcare delivery networks today are often viewed as monolithic, inflexible, difficult to use and costly to configure. They are almost always obtained from commercial vendors and require considerable time, money, and consulting assistance to implement, support and optimize.
Using AI to Improve Electronic Health Records
Electronic health record systems for large, integrated healthcare delivery networks today are often viewed as monolithic, inflexible, difficult to use and costly to configure. As delivery networks grow and deploy broad enterprise EHR platforms, the challenge of making them help rather than hinder clinicians is increasing. A promising approach is to use AI to make existing EHR systems more flexible and intelligent. Some delivery networks are making strides in this direction, using AI to assist with data extraction from free text, clinical documentation and data entry, and clinical decision support. Ultimately, AI should help doctors tailor EHRs to their specific needs and work styles making them easier to use and more valuable in the care process. That could help reduce clinician burnout and improve patient outcomes.