Comparison of clinical note quality between an automated digital intake tool and the standard note in the emergency department.

BACKGROUND

Medical encounters require an efficient and focused history of present illness (HPI) to create differential diagnoses and guide diagnostic testing and treatment. Our aim was to compare the HPI of notes created by an automated digital intake tool versus standard medical notes created by clinicians.

METHODS

Prospective trial in a quaternary academic Emergency Department (ED). Notes were compared using the 5-point Physician Documentation Quality Instrument (PDQI-9) scale and the Centers for Medicare & Medicaid Services (CMS) level of complexity index. Reviewers were board certified emergency medicine physicians blinded to note origin. Reviewers received training and calibration prior to note assessments. A difference of 1 point was considered clinically significant. Analysis included McNemar's (binary), Wilcoxon-rank (Likert), and agreement with Cohen's Kappa.

RESULTS

A total of 148 ED medical encounters were charted by both digital note and standard clinical note. The ability to capture patient information was assessed through comparison of note content across paired charts (digital-standard note on the same patient), as well as scores given by the reviewers. Reviewer agreement was kappa 0.56 (CI 0.49-0.64), indicating moderate level of agreement between reviewers scoring the same patient chart. Considering all 18 questions across PDQI-9 and CMS scales, the average agreement between standard clinical note and digital note was 54.3% (IQR 44.4-66.7%). There was a moderate level of agreement between content of standard and digital notes (kappa 0.54, 95%CI 0.49-0.60). The quality of the digital note was within the 1 point clinically significant difference for all of the attributes, except for conciseness. Digital notes had a higher frequency of CMS severity elements identified.

CONCLUSION

Digitally generated clinical notes had moderate agreement compared to standard clinical notes and within the one point clinically significant difference except for the conciseness attribute. Digital notes more reliably documented billing components of severity. The use of automated notes should be further explored to evaluate its utility in facilitating documentation of patient encounters.

Informations de copyright

Copyright © 2022 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest This study was funded by a sponsored research collaboration between Diagnostic Robotics and Mayo Clinic. Data collection and analysis were done independently by study coordinators and a biostatistician at Mayo Clinic. Methodological strategies were used to mitigate the potential conflict of interest of some of the authors. None of the reviewers or the statistician have potential conflict of interests to disclose. The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the official view of Diagnostic Robotics. Daniel Cabrera, MD has intellectual property associated to the product described in this manuscript. Fernanda Bellolio, MD has intellectual property associated to the product described in this manuscript. Andy Boggust, MD has intellectual property associated to the product described in this manuscript. Ron Eshel, MD was an employee of Diagnostic Robotics. Nathan Shapiro, MD is a paid consultant and small shareholder of Diagnostic Robotics.