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

Background and Purpose Clinical documentation of patient acuity is a major determinant payer reimbursement. This project aimed to improve case mix index (CMI) by incorporating novel electronic health record (EHR) discharge tool into the inpatient general neurology service at University California, Los Angeles (UCLA) Medical Center. Methods We used data from Vizient AMC Hospital: Risk Model Summary for Data Base (CBD) 2017 create diagnosis consisting dropdown menus better capture relevant secondary diagnoses comorbidities. After implementation this tool, we compared pre- (July 2017-June 2019) post-intervention 2019-June 2021) time periods on mean expected length stay (LOS) CMI with two sample T-tests percentage encounters classified as having Major Complications/Comorbidities (MCC), Complication/Comorbidity (CC), without CC/MCC tests proportions. Results Mean increased significantly 1.2 pre-intervention 1.4 ( P < .01). There was pattern MCC percentages “Bacterial infections,” “Other Disorders Nervous System”, “Multiple Sclerosis,” “Nervous System Neoplasms” related groups post-intervention. Conclusions pilot study describes creation an innovative EHR in collaboration healthcare providers, clinical improvement team, neuro-informaticists. demonstrates promise increasing CMI, shifting greater proportion those MCC, improving quality documentation.