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Optimizing Neurology Inpatient Documentation: A Pilot Study of a Novel Discharge Documentation EHR Tool.
Fu, Katherine A; Kerbel, Russell; Obrien, Rylan J; Li, Joshua S; Jackson, Nicholas J; Keselman, Inna; Reider-Demer, Melissa.
Afiliación
  • Fu KA; Department of Neurology, University of California, Los Angeles, CA, USA.
  • Kerbel R; Department of Medicine, University of California, Los Angeles, CA, USA.
  • Obrien RJ; Quality Informatics & Analytics, University of California, Los Angeles, CA, USA.
  • Li JS; Department of Medicine Statistics Core, University of California, Los Angeles, CA, USA.
  • Jackson NJ; Department of Medicine Statistics Core, University of California, Los Angeles, CA, USA.
  • Keselman I; Department of Neurology, University of California, Los Angeles, CA, USA.
  • Reider-Demer M; Department of Neurology, University of California, Los Angeles, CA, USA.
Neurohospitalist ; 14(1): 5-12, 2024 Jan.
Article en En | MEDLINE | ID: mdl-38235019
ABSTRACT
Background and

Purpose:

Clinical documentation of patient acuity is a major determinant of payer reimbursement. This project aimed to improve case mix index (CMI) by incorporating a novel electronic health record (EHR) discharge documentation tool into the inpatient general neurology service at the University of California, Los Angeles (UCLA) Medical Center.

Methods:

We used data from Vizient AMC Hospital Risk Model Summary for Clinical Data Base (CBD) 2017 to create a discharge diagnosis documentation tool consisting of dropdown menus to better capture relevant secondary diagnoses and comorbidities. After implementation of this tool, we compared pre- (July 2017-June 2019) and post-intervention (July 2019-June 2021) time periods on mean expected length of stay (LOS) and mean CMI with two sample T-tests and the percentage of encounters classified as having Major Complications/Comorbidities (MCC), with Complication/Comorbidity (CC), and without CC/MCC with tests of proportions.

Results:

Mean CMI increased significantly from 1.2 pre-intervention to 1.4 post-intervention implementation (P < .01). There was a pattern of increased MCC percentages for "Bacterial infections," "Other Disorders of Nervous System", "Multiple Sclerosis," and "Nervous System Neoplasms" diagnosis related groups post-intervention.

Conclusions:

This pilot study describes the creation of an innovative EHR discharge diagnosis documentation tool in collaboration with neurology healthcare providers, the clinical documentation improvement team, and neuro-informaticists. This novel discharge diagnosis documentation tool demonstrates promise in increasing CMI, shifting diagnosis related groups to a greater proportion of those with MCC, and improving the quality of clinical documentation.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Neurohospitalist Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Neurohospitalist Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos