Reducing Complexity in Surgical Consents: The Role of AI in Patient Communication

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Published Jan 2, 2026
DOI: https://doi.org/10.18103/mra.v13i12.7178

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Main Article Content

Rahul Ramanathan, MD
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA ; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
Ryan J. Kelly, BS
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
Jeremy D. Shaw, MD
Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA; Intermountain Health, Salt Lake City UT, USA
Adway Gopakumar, BS
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
Michael F. Shannon, BS
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
Christopher Gonzalez, BA
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
Jacob Weinberg, BS
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
John Bonamer, MD
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
Richard A. Wawrose, MD
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
Michael J. Spitnale, MD
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
Joon Y. Lee, MD
Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh PA, USA; Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA
John Weddle, MD
Pittsburgh Orthopaedic Spine Research Group (POSR), Pittsburgh PA, USA; The Orland Bethel Family Musculoskeletal Research Center (BMRC), Pittsburgh PA, USA; Department of Orthopaedic Surgery, Geisinger Health System, Danville, PA, USA

Abstract

Introduction: Surgical consent forms often exceed recommended reading levels, limiting patient understanding and hindering truly informed decision-making. Artificial intelligence (AI)"based tools like ChatGPT offer a novel strategy to improve readability without compromising content accuracy.


Methods: Four standardized spine surgery consent forms from a tertiary academic center were simplified using ChatGPT. Readability was assessed before and after simplification using six validated metrics: Flesch-Kincaid Grade Level, Flesch Reading Ease, Coleman-Liau Index, Automated Readability Index, Gunning Fog Index, and SMOG Index. Changes were analyzed using paired t-tests. Linguistic complexity"including total word count, character count, sentence count, words per sentence, and sentences per paragraph"was evaluated using one-sample t-tests. Statistical significance was set at p<0.05.


Results: ChatGPT simplification significantly improved readability across all measures. Flesch-Kincaid Grade Level decreased from 11.37 to 6.67 (p<0.001), and Flesch Reading Ease improved from 44.51 to 68.88 (p<0.005). Similar improvements were noted in Coleman-Liau (12.00 to 8.09), Automated Readability Index (10.79 to 5.79), Gunning Fog Index (18.07 to 11.65), and SMOG Index (15.70 to 11.32), all with p<0.005. Linguistic complexity was also reduced: total words (−43%, p<0.001), characters (−43%, p<0.001), sentences (−23%, p<0.01), words per sentence (−26%, p<0.001), and sentences per paragraph (−18%, p<0.001).


Conclusions: ChatGPT significantly enhances the readability of spine surgery consent forms while preserving essential medical content. This AI-driven approach may improve patient comprehension and support more equitable, informed decision-making. These findings highlight the potential of AI tools to streamline clinical communication and enhance the informed consent process.

Keywords: Artificial intelligence (AI), surgical consent forms, patient comprehension, health literacy, ChatGPT

Article Details

How to Cite
RAMANATHAN, Rahul et al. Reducing Complexity in Surgical Consents: The Role of AI in Patient Communication. Medical Research Archives, [S.l.], v. 13, n. 12, jan. 2026. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/7178>. Date accessed: 02 jan. 2026. doi: https://doi.org/10.18103/mra.v13i12.7178.
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Issue
Vol 13 No 12 (2025): Vol.13 Issue 12 December 2025
Section
Research Articles

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