Data Omission by Physician Trainees on ICU Rounds

Abstract

Objectives: Incomplete patient data, either due to difficulty gathering and synthesizing or inappropriate data filtering, can lead clinicians to misdiagnosis and medical error. How completely ICU interprofessional rounding teams appraise the patient data set that informs clinical decision-making is unknown. This study measures how frequently physician trainees omit data from prerounding notes ("artifacts") and verbal presentations during daily rounds.

Design: Observational study.

Setting: Tertiary academic medical ICU with an established electronic health record and where physician trainees are the primary presenters during daily rounds.

Subjects: Presenters (medical student or resident physician), interprofessional rounding team.

Interventions: None.

Measurements and main results: We quantified the amount and types of patient data omitted from photocopies of physician trainees' artifacts and audio recordings of oral ICU rounds presentations when compared with source electronic health record data. An audit of 157 patient presentations including 6,055 data elements across nine domains revealed 100% of presentations contained omissions. Overall, 22.9% of data were missing from artifacts and 42.4% from presentations. The interprofessional team supplemented only 4.1% of additional available data. Frequency of trainee data omission varied by data type and sociotechnical factors. The strongest predictor of trainee verbal omissions was a preceding failure to include the data on the artifact. Passive data gathering via electronic health record macros resulted in extremely complete artifacts but paradoxically predicted greater likelihood of verbal omission when compared with manual notation. Interns verbally omitted the most data, whereas medical students omitted the least.

Conclusions: In an academic rounding model reliant on trainees to preview and select data for presentation during ICU rounds, verbal appraisal of patient data was highly incomplete. Additional trainee oversight and education, improved electronic health record tools, and novel academic rounding paradigms are needed to address this potential source of medical error.

Figure 1.

Success and method of data extraction to presenter artifacts by data domain. “Manual” method of extraction indicates free-typed or handwritten data on the artifact, whereas “macros” refers to using electronic health record (EHR)-specific commands to electronically import data from the EHR in a prespecified format. MD Consult = physician consultant recommendations, non-MD Consult = non-physician consultant recommendations.

Figure 2.

Histogram of prevalence of per patient data omissions at artifact creation (“artifact omission”) and rounds presentation (“trainee verbal omission”) steps.

Figure 3.

Frequency of omitted data on artifacts (“artifact omission”) and during rounds presentations (“trainee verbal omission”) stratified by physician trainee presenter training level. *Fourth year medical student (MS-4) group had fewer artifact and verbal omissions when compared with postgraduate year (PGY)-1 (p < 0.00001, p < 0.00001) and combined PGY-2/3 groups (p < 0.00015, p < 0.00001), respectively. #PGY-1 group had more verbal omissions compared with combined PGY-2/3 group (p < 0.00001).