Abstract
Background Clinical documentation improvement programs are utilized by most health care systems
to enhance provider documentation. Suggestions are sent to providers in a variety
of ways, and are commonly referred to as coding queries. Responding to these coding
queries can require significant provider time and do not often align with workflows.
To enhance provider documentation in a more consistent manner without creating undue
burden, alternative strategies are required.
Objectives The aim of this study is to evaluate the impact of a real-time documentation assistance
tool, named AutoDx, on the volume of coding queries and encounter-level outcome metrics,
including case-mix index (CMI).
Methods The AutoDx tool was developed utilizing tools existing within the electronic health
record, and is based on the generation of messages when clinical conditions are met.
These messages appear within provider notes and required little to no interaction.
Initial diagnoses included in the tool were electrolyte deficiencies, obesity, and
malnutrition. The tool was piloted in a cohort of Hospital Medicine providers, then
expanded to the Neuro Intensive Care Unit (NICU), with addition diagnoses being added.
Results The initial Hospital Medicine implementation evaluation included 590 encounters pre-
and 531 post-implementation. The volume of coding queries decreased 57% (p < 0.0001) for the targeted diagnoses compared with 6% (p = 0.77) in other high-volume diagnoses. In the NICU cohort, 829 encounters pre-implementation
were compared with 680 post. The proportion of AutoDx coding queries compared with
all other coding queries decreased from 54.9 to 37.1% (p < 0.0001). During the same period, CMI demonstrated a significant increase post-implementation
(4.00 vs. 4.55, p = 0.02).
Conclusion The real-time documentation assistance tool led to a significant decrease in coding
queries for targeted diagnoses in two unique provider cohorts. This improvement was
also associated with a significant increase in CMI during the implementation time
period.
Keywords
clinical documentation - automated - AutoDx
