Abstract Details

Title Optimizing Neurology Inpatient Documentation: A Pilot Study of a Novel Discharge Documentation EMR Tool

Topic Practice, Policy, and Ethics

Presentation(s) Practice, Policy, and Ethics Posters (7:00 AM-5:00 PM)

Poster/Presentation
Number 022

Objective To create a discharge documentation tool in the electronic medical record (EMR) that better captures the complexity and severity of illness of neurology patients at an academic medical center.

Background

The goal was to create an EMR tool to improve documentation of discharge diagnoses of the inpatient general neurology service at UCLA. With more robust documentation capturing patient complexity and associated comorbidities, we aimed to improve the percentage of diagnosis-related group (DRG) with major complication or comorbidity (MCC) and complement the work of a clinical documentation improvement (CDI) team by decreasing hospital queries.

Design/Methods We employed the Academic Medical Center Hospital Risk Model Summary for Clinical Database 2017 to identify the top ten neurology DRG triplets for General Neurology. We reviewed the MS-DRG (Medicare Severity-Diagnosis Related Group), MCC, and CC (complication or comorbidity) list for each condition, and corresponding variables across mortality, length of stay (LOS), and direct cost models. This information was used to create a general neurology discharge documentation tool, comprising a “SmartList” for discharge diagnoses in the Epic EMR. When a provider selected one of the 10 diagnoses from the DRG Smartlist, a drop-down menu prompted the selection of relevant explanatory variables, or associated diagnoses. This tool was standardized into a discharge note template for use by all neurology residents starting July 2019.

Results We compared Neurology service line data for average CDI queries from before and after implementation, which improved from a 12-month average of 3.62 to 2.58, a decrease of 1.04. Although not statistically significant, there was a trend towards improvement of the DRG Seizures with MCC from 3.28% pre-intervention to 4.08% post-intervention.

Conclusions The use of this innovative tool yielded improvement in hospital queries and showed promise in improving the percentage of DRG with MCC, thereby demonstrating potential to improve Case Mix Index (CMI).

Authors/Disclosures
Katherine Fu, MD (University of California, Los Angeles) PRESENTER	Dr. Fu has received personal compensation in the range of $10,000-$49,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for ��ɫ��: Neurology Journal . Dr. Fu has received research support from ��ɫ��. Dr. Fu has received personal compensation in the range of $0-$499 for serving as a Edmond J. Safra Fellowship Reviewer with The Michael J. Fox Foundation.
	No disclosure on file
	No disclosure on file
Melissa Reider-Demer, DNP, MN, CNP (UCLA Medical Group)	Dr. Reider-Demer has nothing to disclose.

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