Optimizing Documentation Integrity of Ophthalmic Diagnostic Test Interpretation through Electronic Health Record Clinical Decision Support

Abstract

Background

Electronic health records (EHRs) have revolutionized clinical practice, but clinicians and institutions have not yet fully optimized their use. Inconsistent documentation of ophthalmic test results can increase potential medicolegal risks if providers bill for tests without properly documenting clinical interpretations.

Objectives

To address this, we developed and implemented a logic tool in Epic (Epic Systems, Verona, Wisconsin, United States) that prompts clinicians to document diagnostic test interpretations as discrete data before closing the patient chart.

Methods

We implemented a “Close Encounter Warning” using logic rules to redirect clinicians to the Imaging and Procedures section of the Epic chart for documenting test interpretations. The implementation only allows clinicians to finalize each outpatient encounter's charting as closed if the logic rules confirm that no unsigned test results remain. The logic rules were revised many times to accommodate the unique workflow of the Ophthalmology department and to consider the roles of fellows, residents, and staff who also work with encounter charting. We implemented the initial logic rule on October 23, 21 and the final iteration on February8, 22. To evaluate the impact, we compared the number of closed charts containing unresulted diagnostic tests from October 2017 to December 2024.

Results

Before we implemented the logic rules, clinicians closed an average of 897.1 charts per month with unresulted diagnostic images (median: 916, interquartile range [IQR]: 170, 5.78% of all outpatient encounters). After implementation, this number dropped to 8.3 per month (median: 8, IQR: 5.75, 0.05% of all outpatient encounters), a 108% reduction (p < 0.001).

Conclusion

The Close Encounter Warning logic rules significantly reduced the number of Imaging and Procedure-type diagnostic tests lacking final attending signatures in the Ophthalmology department. By implementing this EHR change, we successfully minimized potential medicolegal liability for our clinicians and institution.

Keywords

electronic health record - health information management - discrete data - ophthalmology - clinical informatics - clinical operations

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 did not involve human subjects, thus, Institutional Review Board (IRB) approval was not indicated.

Publication History

Received: 02 September 2024

Accepted: 10 April 2025

Article published online:
14 August 2025

• References

• 1 Kemp T, Butler-Henderson K, Allen P, Ayton J. The impact of health information management professionals on patient safety: a systematic review. Health Info Libr J 2021; 38 (04) 248-258
• 2 Klappe ES, Cornet R, Dongelmans DA, de Keizer NF. Inaccurate recording of routinely collected data items influences identification of COVID-19 patients. Int J Med Inform 2022; 165: 104808
• 3 Poulos J, Zhu L, Shah AD. Data gaps in electronic health record (EHR) systems: an audit of problem list completeness during the COVID-19 pandemic. Int J Med Inform 2021; 150: 104452
• 4 Chiang MF, Read-Brown S, Tu DC. et al. Evaluation of electronic health record implementation in ophthalmology at an academic medical center (an American Ophthalmological Society thesis). Trans Am Ophthalmol Soc 2013; 111: 70-92
• 5 Huang C, Koppel R, McGreevey III JD, Craven CK, Schreiber R. Transitions from one electronic health record to another: challenges, pitfalls, and recommendations. Appl Clin Inform 2020; 11 (05) 742-754
• 6 Miake-Lye IM, Cogan AM, Mak S. et al. Transitioning from one electronic health record to another: a systematic review. J Gen Intern Med 2023; 38 (4, suppl 4): 956-964
• 7 Bowman S. Impact of electronic health record systems on information integrity: quality and safety implications. Perspect Health Inf Manag 2013; 10 (Fall): 1c
• 8 Vukmir RB. Medicolegal aspects of documentation and the electronic health record. Med Clin (Barc) 2024; 162 (08) e9-e14
• 9 Kuhn T, Basch P, Barr M, Yackel T. Medical Informatics Committee of the American College of Physicians. Clinical documentation in the 21st century: executive summary of a policy position paper from the American College of Physicians. Ann Intern Med 2015; 162 (04) 301-303
• 10 Coding Trends of Medicare Evaluation and Management Services. Office of Inspector General | Government Oversight | U.S. Department of Health and Human Services. May 8, 2012. Accessed December 21, 2024 at: https://oig.hhs.gov/reports/all/2012/coding-trends-of-medicare-evaluation-and-management-services/
• 11 Beasley JW, Wetterneck TB, Temte J. et al. Information chaos in primary care: implications for physician performance and patient safety. J Am Board Fam Med 2011; 24 (06) 745-751
• 12 Patterson ES, Sillars DM, Staggers N. et al. Safe practice recommendations for the use of copy-forward with nursing flow sheets in hospital settings. Jt Comm J Qual Patient Saf 2017; 43 (08) 375-385
• 13 Hultman GM, Marquard JL, Lindemann E, Arsoniadis E, Pakhomov S, Melton GB. Challenges and opportunities to improve the clinician experience reviewing electronic progress notes. Appl Clin Inform 2019; 10 (03) 446-453
• 14 Goldstein IH, Hwang T, Gowrisankaran S, Bales R, Chiang MF, Hribar MR. Changes in electronic health record use time and documentation over the course of a decade. Ophthalmology 2019; 126 (06) 783-791
• 15 Overhage JM, Perkins S, Tierney WM, McDonald CJ. Controlled trial of direct physician order entry: effects on physicians' time utilization in ambulatory primary care internal medicine practices. J Am Med Inform Assoc 2001; 8 (04) 361-371
• 16 Chiang MF, Boland MV, Margolis JW, Lum F, Abramoff MD, Hildebrand PL. American Academy of Ophthalmology Medical Information Technology Committee. Adoption and perceptions of electronic health record systems by ophthalmologists: an American Academy of Ophthalmology survey. Ophthalmology 2008; 115 (09) 1591-1597 , quiz 1597.e1–1597.e5
• 17 Mattison JE, Dolin RH, Laberge D. Managing the tensions between national standardization vs. regional localization of clinical content and templates. Stud Health Technol Inform 2004; 107 (Pt 2): 1081-1085
• 18 DesRoches CM, Campbell EG, Rao SR. et al. Electronic health records in ambulatory care–a national survey of physicians. N Engl J Med 2008; 359 (01) 50-60
• 19 Powers EM, Shiffman RN, Melnick ER, Hickner A, Sharifi M. Efficacy and unintended consequences of hard-stop alerts in electronic health record systems: a systematic review. J Am Med Inform Assoc 2018; 25 (11) 1556-1566
• 20 Institute of Medicine (US) Committee on Quality of Health Care in America. To Err Is Human: Building a Safer Health System. Kohn LT, Corrigan JM, Donaldson MS. eds. National Academies Press (United States); 2000. . Accessed June 5, 2024 at: http://www.ncbi.nlm.nih.gov/books/NBK225182/
• 21 Nijor S, Rallis G, Lad N, Gokcen E. patient safety issues from information overload in electronic medical records. J Patient Saf 2022; 18 (06) e999-e1003
• 22 Kwan JL, Lo L, Ferguson J. et al. Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials. BMJ 2020; 370: m3216
• 23 USCGA. Medicare Program Integrity Manual. December 12, 2024
• 24 Ranum D. Electronic Health Records Continue to Lead to Medical Malpractice Suits. Accessed March 31, 2025 at: https://www.thedoctors.com/articles/electronic-health-records-continue-to-lead-to-medical-malpractice-suits/
• 25 Evans CS, Bunn B, Reeder T, Patterson L, Gertsch D, Medford RJ. Standardization of emergency department clinical note templates: a retrospective analysis across an integrated health system. Appl Clin Inform 2024; 15 (02) 397-403
• 26 Thornton JD, Schold JD, Venkateshaiah L, Lander B. Prevalence of copied information by attendings and residents in critical care progress notes. Crit Care Med 2013; 41 (02) 382-388
• 27 Sittig DF, Wright A. Identifying a clinical informatics or electronic health record expert witness for medical professional liability cases. Appl Clin Inform 2023; 14 (02) 290-295
• 28 Ryan ML, Mutore KT, DeLeon J, Gillory L, Chung DH, Pandya S. Improving billing and collections in a high-volume pediatric surgery practice: denials-based approach. J Am Coll Surg 2023; 236 (04) 630-635
• 29 Lin CT, McKenzie M, Pell J, Caplan L. Health care provider satisfaction with a new electronic progress note format: SOAP vs APSO format. JAMA Intern Med 2013; 173 (02) 160-162