Cargando…
Effective Communication of Personalized Risks and Patient Preferences During Surgical Informed Consent Using Data Visualization: Qualitative Semistructured Interview Study With Patients After Surgery
BACKGROUND: There is no consensus on which risks to communicate to a prospective surgical patient during informed consent or how. Complicating the process, patient preferences may diverge from clinical assumptions and are often not considered for discussion. Such discrepancies can lead to confusion...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107059/ https://www.ncbi.nlm.nih.gov/pubmed/35486432 http://dx.doi.org/10.2196/29118 |
_version_ | 1784708409354878976 |
---|---|
author | Gisladottir, Undina Nakikj, Drashko Jhunjhunwala, Rashi Panton, Jasmine Brat, Gabriel Gehlenborg, Nils |
author_facet | Gisladottir, Undina Nakikj, Drashko Jhunjhunwala, Rashi Panton, Jasmine Brat, Gabriel Gehlenborg, Nils |
author_sort | Gisladottir, Undina |
collection | PubMed |
description | BACKGROUND: There is no consensus on which risks to communicate to a prospective surgical patient during informed consent or how. Complicating the process, patient preferences may diverge from clinical assumptions and are often not considered for discussion. Such discrepancies can lead to confusion and resentment, raising the potential for legal action. To overcome these issues, we propose a visual consent tool that incorporates patient preferences and communicates personalized risks to patients using data visualization. We used this platform to identify key effective visual elements to communicate personalized surgical risks. OBJECTIVE: Our main focus is to understand how to best communicate personalized risks using data visualization. To contextualize patient responses to the main question, we examine how patients perceive risks before surgery (research question 1), how suitably the visual consent tool is able to present personalized surgical risks (research question 2), how well our visualizations convey those personalized surgical risks (research question 3), and how the visual consent tool could improve the informed consent process and how it can be used (research question 4). METHODS: We designed a visual consent tool to meet the objectives of our study. To calculate and list personalized surgical risks, we used the American College of Surgeons risk calculator. We created multiple visualization mock-ups using visual elements previously determined to be well-received for risk communication. Semistructured interviews were conducted with patients after surgery, and each of the mock-ups was presented and evaluated independently and in the context of our visual consent tool design. The interviews were transcribed, and thematic analysis was performed to identify major themes. We also applied a quantitative approach to the analysis to assess the prevalence of different perceptions of the visualizations presented in our tool. RESULTS: In total, 20 patients were interviewed, with a median age of 59 (range 29-87) years. Thematic analysis revealed factors that influenced the perception of risk (the surgical procedure, the cognitive capacity of the patient, and the timing of consent; research question 1); factors that influenced the perceived value of risk visualizations (preference for rare event communication, preference for risk visualization, and usefulness of comparison with the average; research question 3); and perceived usefulness and use cases of the visual consent tool (research questions 2 and 4). Most importantly, we found that patients preferred the visual consent tool to current text-based documents and had no unified preferences for risk visualization. Furthermore, our findings suggest that patient concerns were not often represented in existing risk calculators. CONCLUSIONS: We identified key elements that influence effective visual risk communication in the perioperative setting and pointed out the limitations of the existing calculators in addressing patient concerns. Patient preference is highly variable and should influence choices regarding risk presentation and visualization. |
format | Online Article Text |
id | pubmed-9107059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-91070592022-05-15 Effective Communication of Personalized Risks and Patient Preferences During Surgical Informed Consent Using Data Visualization: Qualitative Semistructured Interview Study With Patients After Surgery Gisladottir, Undina Nakikj, Drashko Jhunjhunwala, Rashi Panton, Jasmine Brat, Gabriel Gehlenborg, Nils JMIR Hum Factors Original Paper BACKGROUND: There is no consensus on which risks to communicate to a prospective surgical patient during informed consent or how. Complicating the process, patient preferences may diverge from clinical assumptions and are often not considered for discussion. Such discrepancies can lead to confusion and resentment, raising the potential for legal action. To overcome these issues, we propose a visual consent tool that incorporates patient preferences and communicates personalized risks to patients using data visualization. We used this platform to identify key effective visual elements to communicate personalized surgical risks. OBJECTIVE: Our main focus is to understand how to best communicate personalized risks using data visualization. To contextualize patient responses to the main question, we examine how patients perceive risks before surgery (research question 1), how suitably the visual consent tool is able to present personalized surgical risks (research question 2), how well our visualizations convey those personalized surgical risks (research question 3), and how the visual consent tool could improve the informed consent process and how it can be used (research question 4). METHODS: We designed a visual consent tool to meet the objectives of our study. To calculate and list personalized surgical risks, we used the American College of Surgeons risk calculator. We created multiple visualization mock-ups using visual elements previously determined to be well-received for risk communication. Semistructured interviews were conducted with patients after surgery, and each of the mock-ups was presented and evaluated independently and in the context of our visual consent tool design. The interviews were transcribed, and thematic analysis was performed to identify major themes. We also applied a quantitative approach to the analysis to assess the prevalence of different perceptions of the visualizations presented in our tool. RESULTS: In total, 20 patients were interviewed, with a median age of 59 (range 29-87) years. Thematic analysis revealed factors that influenced the perception of risk (the surgical procedure, the cognitive capacity of the patient, and the timing of consent; research question 1); factors that influenced the perceived value of risk visualizations (preference for rare event communication, preference for risk visualization, and usefulness of comparison with the average; research question 3); and perceived usefulness and use cases of the visual consent tool (research questions 2 and 4). Most importantly, we found that patients preferred the visual consent tool to current text-based documents and had no unified preferences for risk visualization. Furthermore, our findings suggest that patient concerns were not often represented in existing risk calculators. CONCLUSIONS: We identified key elements that influence effective visual risk communication in the perioperative setting and pointed out the limitations of the existing calculators in addressing patient concerns. Patient preference is highly variable and should influence choices regarding risk presentation and visualization. JMIR Publications 2022-04-29 /pmc/articles/PMC9107059/ /pubmed/35486432 http://dx.doi.org/10.2196/29118 Text en ©Undina Gisladottir, Drashko Nakikj, Rashi Jhunjhunwala, Jasmine Panton, Gabriel Brat, Nils Gehlenborg. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 29.04.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Human Factors, is properly cited. The complete bibliographic information, a link to the original publication on https://humanfactors.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Gisladottir, Undina Nakikj, Drashko Jhunjhunwala, Rashi Panton, Jasmine Brat, Gabriel Gehlenborg, Nils Effective Communication of Personalized Risks and Patient Preferences During Surgical Informed Consent Using Data Visualization: Qualitative Semistructured Interview Study With Patients After Surgery |
title | Effective Communication of Personalized Risks and Patient Preferences During Surgical Informed Consent Using Data Visualization: Qualitative Semistructured Interview Study With Patients After Surgery |
title_full | Effective Communication of Personalized Risks and Patient Preferences During Surgical Informed Consent Using Data Visualization: Qualitative Semistructured Interview Study With Patients After Surgery |
title_fullStr | Effective Communication of Personalized Risks and Patient Preferences During Surgical Informed Consent Using Data Visualization: Qualitative Semistructured Interview Study With Patients After Surgery |
title_full_unstemmed | Effective Communication of Personalized Risks and Patient Preferences During Surgical Informed Consent Using Data Visualization: Qualitative Semistructured Interview Study With Patients After Surgery |
title_short | Effective Communication of Personalized Risks and Patient Preferences During Surgical Informed Consent Using Data Visualization: Qualitative Semistructured Interview Study With Patients After Surgery |
title_sort | effective communication of personalized risks and patient preferences during surgical informed consent using data visualization: qualitative semistructured interview study with patients after surgery |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107059/ https://www.ncbi.nlm.nih.gov/pubmed/35486432 http://dx.doi.org/10.2196/29118 |
work_keys_str_mv | AT gisladottirundina effectivecommunicationofpersonalizedrisksandpatientpreferencesduringsurgicalinformedconsentusingdatavisualizationqualitativesemistructuredinterviewstudywithpatientsaftersurgery AT nakikjdrashko effectivecommunicationofpersonalizedrisksandpatientpreferencesduringsurgicalinformedconsentusingdatavisualizationqualitativesemistructuredinterviewstudywithpatientsaftersurgery AT jhunjhunwalarashi effectivecommunicationofpersonalizedrisksandpatientpreferencesduringsurgicalinformedconsentusingdatavisualizationqualitativesemistructuredinterviewstudywithpatientsaftersurgery AT pantonjasmine effectivecommunicationofpersonalizedrisksandpatientpreferencesduringsurgicalinformedconsentusingdatavisualizationqualitativesemistructuredinterviewstudywithpatientsaftersurgery AT bratgabriel effectivecommunicationofpersonalizedrisksandpatientpreferencesduringsurgicalinformedconsentusingdatavisualizationqualitativesemistructuredinterviewstudywithpatientsaftersurgery AT gehlenborgnils effectivecommunicationofpersonalizedrisksandpatientpreferencesduringsurgicalinformedconsentusingdatavisualizationqualitativesemistructuredinterviewstudywithpatientsaftersurgery |