Copy-and-Paste in Medical Student Notes: Extent, Temporal Trends, and Relationship to Scholastic Performance

Abstract

Background Medical students may observe and subsequently perpetuate redundancy in clinical documentation, but the degree of redundancy in student notes and whether there is an association with scholastic performance are unknown.

Objectives This study sought to quantify redundancy, defined generally as the proportion of similar text between two strings, in medical student notes and evaluate the relationship between note redundancy and objective indicators of student performance.

Methods Notes generated by medical students rotating through their medicine clerkship during a single academic year at our institution were analyzed. A student–patient interaction (SPI) was defined as a history and physical and at least two contiguous progress notes authored by the same student during a single patient's hospitalization. For some students, SPI pairs were available from early and late in the clerkship. Redundancy between analogous sections of consecutive notes was calculated on a 0 to 100% scale and was derived from edit distance, the number of changes needed to transform one text string into another. Indicators of student performance included United States Medical Licensing Exam (USMLE) scores.

Results Ninety-four single SPIs and 58 SPI pairs were analyzed. Redundancy in the assessment/plan section was high (40%) and increased within individual SPIs (to 60%; p < 0.001) and between SPI pairs over the course of the clerkship (by 30–40%; p < 0.001). Students in the lowest tertile of USMLE step II clinical knowledge scores had higher redundancy in the assessment/plan section than their classmates (67 ± 24% vs. 38 ± 22%; p = 0.002).

Conclusion During the medicine clerkship, the assessment/plan section of medical student notes became more redundant over a patient's hospital course and as students gained clinical experience. These trends may be indicative of deficiencies in clinical knowledge or reasoning, as evidenced by performance on some standardized evaluations.

Keywords

Undergraduate Medical Education - clinical clerkship - documentation

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by the Vanderbilt Medical Center Institutional Review Board.

• References

• 1 Hirschtick RE. A piece of my mind. Copy-and-paste. JAMA 2006; 295 (20) 2335-2336
• 2 Siegler EL, Adelman R. Copy and paste: a remediable hazard of electronic health records. Am J Med 2009; 122 (06) 495-496
• 3 Bowman S. Impact of electronic health record systems on information integrity: quality and safety implications. Perspect Health Inf Manag 2013; 10: 1c
• 4 Weir CR, Hurdle JF, Felgar MA, Hoffman JM, Roth B, Nebeker JR. Direct text entry in electronic progress notes. An evaluation of input errors. Methods Inf Med 2003; 42 (01) 61-67
• 5 Hammond KW, Helbig ST, Benson CC, Brathwaite-Sketoe BM. Are electronic medical records trustworthy? Observations on copying, pasting and duplication. AMIA Annu Symp Proc 2003; 2003: 269-273
• 6 Heiman HL, Rasminsky S, Bierman JA. , et al. Medical students' observations, practices, and attitudes regarding electronic health record documentation. Teach Learn Med 2014; 26 (01) 49-55
• 7 Weed LL. Medical records that guide and teach. N Engl J Med 1968; 278 (11) 593-600
• 8 Singh H, Giardina TD, Meyer AN, Forjuoh SN, Reis MD, Thomas EJ. Types and origins of diagnostic errors in primary care settings. JAMA Intern Med 2013; 173 (06) 418-425
• 9 Turchin A, Goldberg SI, Breydo E, Shubina M, Einbinder JS. Copy/paste documentation of lifestyle counseling and glycemic control in patients with diabetes: true to form?. Arch Intern Med 2011; 171 (15) 1393-1394
• 10 Wrenn JO, Stein DM, Bakken S, Stetson PD. Quantifying clinical narrative redundancy in an electronic health record. J Am Med Inform Assoc 2010; 17 (01) 49-53
• 11 Spickard III A, Ridinger H, Wrenn J. , et al. Automatic scoring of medical students' clinical notes to monitor learning in the workplace. Med Teach 2014; 36 (01) 68-72
• 12 Ye C, Coco J, Epishova A. , et al. A crowdsourcing framework for medical data sets. AMIA Jt Summits Transl Sci Proc 2018; 2017: 273-280
• 13 Levenshtein VI. Binary codes capable of correcting deletions, insertions, and reversal. Sov Phys Dokl 1966; 10: 707-710
• 14 Zhang R, Pakhomov SV, Lee JT, Melton GB. Using language models to identify relevant new information in inpatient clinical notes. AMIA Annu Symp Proc 2014; 2014: 1268-1276
• 15 Zhang R, Pakhomov SVS, Arsoniadis EG, Lee JT, Wang Y, Melton GB. Detecting clinically relevant new information in clinical notes across specialties and settings. BMC Med Inform Decis Mak 2017; 17 (Suppl. 02) 68
• 16 Rizvi RF, Harder KA, Hultman GM. , et al. A comparative observational study of inpatient clinical note-entry and reading/retrieval styles adopted by physicians. Int J Med Inform 2016; 90: 1-11
• 17 Swary JH, Stratman EJ. Practice gaps in patient safety among dermatology residents and their teachers: a survey study of dermatology residents. JAMA Dermatol 2014; 150 (07) 738-742
• 18 Colicchio TK, Cimino JJ. Clinicians' reasoning as reflected in electronic clinical note-entry and reading/retrieval: a systematic review and qualitative synthesis. J Am Med Inform Assoc 2019; 26 (02) 172-184