Dataset Information

Use of animation video in surgical decision-making for treatment of early breast cancer in Indian women.

ABSTRACT: Introduction:Surgical decision-making in early breast cancer is difficult for the patient and also for the treating clinician, especially when the patient is not completely aware of the available options. Adjuncts such as animation video with case scenarios can be helpful in this regard. We used an animation video to help in decision-making and evaluated the effect of such adjunct in Indian women with early breast cancer. Materials and Methods:An animation video of running time of 4 min and 11 s was shown to forty patients with early breast cancer, who filled in a patient satisfaction multimedia questionnaire at the end of the animation. Results:Seventeen (42.5%) patients underwent breast-conserving surgery (BCS) while the rest 23 (57.5%) patients underwent the mastectomy. All forty patients were satisfied with the animation video. The mean score of the utility of the video to improve understanding of the disorder, better organization of treatment, stimulated interest in the relations, and saved unnecessary discussion was 88.50, 88.50,88.3, and 90.3, respectively. Age and literacy status did not significantly affect the scores. Discussion:All the patients found the video useful and most patients made the decision on the first attempt. Patients' perspective about BCS is influenced by the fear of recurrence, fear of multiple surgeries, complications, and also the counseling provided by the surgeon. Conclusion:In this situation, such animation videos provide an unbiased view on the operative procedure and help in decision-making.

SUBMITTER: Bothra S

PROVIDER: S-EPMC6699233 | biostudies-literature | 2019 Jul-Sep

REPOSITORIES: biostudies-literature

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Use of animation video in surgical decision-making for treatment of early breast cancer in Indian women.

Bothra Sapana S Mayilvaganan Sabaretnam S Mishra Prabhaker P Mishra Anjali A Agarwal Amit A Agarwal Gaurav G

South Asian journal of cancer 20190701 3

<h4>Introduction</h4>Surgical decision-making in early breast cancer is difficult for the patient and also for the treating clinician, especially when the patient is not completely aware of the available options. Adjuncts such as animation video with case scenarios can be helpful in this regard. We used an animation video to help in decision-making and evaluated the effect of such adjunct in Indian women with early breast cancer.<h4>Materials and methods</h4>An animation video of running time of ...[more]

PMID: 31489281

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Project description:Purpose This study was conducted to determine the effect of iCanDecide, an interactive and tailored breast cancer treatment decision tool, on the rate of high-quality patient decisions-both informed and values concordant-regarding locoregional breast cancer treatment and on patient appraisal of decision making. Methods We conducted a randomized clinical trial of newly diagnosed patients with early-stage breast cancer making locoregional treatment decisions. From 22 surgical practices, 537 patients were recruited and randomly assigned online to the iCanDecide interactive and tailored Web site (intervention) or the iCanDecide static Web site (control). Participants completed a baseline survey and were mailed a follow-up survey 4 to 5 weeks after enrollment to assess the primary outcome of a high-quality decision, which consisted of two components, high knowledge and values-concordant treatment, and secondary outcomes (decision preparation, deliberation, and subjective decision quality). Results Patients in the intervention arm had higher odds of making a high-quality decision than did those in the control arm (odds ratio, 2.00; 95% CI, 1.37 to 2.92; P = .0004), which was driven primarily by differences in the rates of high knowledge between groups. The majority of patients in both arms made values-concordant treatment decisions (78.6% in the intervention arm and 81.4% in the control arm). More patients in the intervention arm had high decision preparation (estimate, 0.18; 95% CI, 0.02 to 0.34; P = .027), but there were no significant differences in the other decision appraisal outcomes. The effect of the intervention was similar for women who were leaning strongly toward a treatment option at enrollment compared with those who were not. Conclusion The tailored and interactive iCanDecide Web site, which focused on knowledge building and values clarification, positively affected high-quality decisions largely by improving knowledge compared with static online information. To be effective, future patient-facing decision tools should be integrated into the clinical workflow to improve decision making.

Project description:BackgroundSurgical patients incur preventable harm from cognitive and judgment errors made under time constraints and uncertainty regarding patients' diagnoses and predicted response to treatment. Decision analysis and techniques of reinforcement learning theoretically can mitigate these challenges but are poorly understood and rarely used clinically. This review seeks to promote an understanding of decision analysis and reinforcement learning by describing their use in the context of surgical decision-making.MethodsCochrane, EMBASE, and PubMed databases were searched from their inception to June 2019. Included were 41 articles about cognitive and diagnostic errors, decision-making, decision analysis, and machine-learning. The articles were assimilated into relevant categories according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.ResultsRequirements for time-consuming manual data entry and crude representations of individual patients and clinical context compromise many traditional decision-support tools. Decision analysis methods for calculating probability thresholds can inform population-based recommendations that jointly consider risks, benefits, costs, and patient values but lack precision for individual patient-centered decisions. Reinforcement learning, a machine-learning method that mimics human learning, can use a large set of patient-specific input data to identify actions yielding the greatest probability of achieving a goal. This methodology follows a sequence of events with uncertain conditions, offering potential advantages for personalized, patient-centered decision-making. Clinical application would require secure integration of multiple data sources and attention to ethical considerations regarding liability for errors and individual patient preferences.ConclusionTraditional decision-support tools are ill-equipped to accommodate time constraints and uncertainty regarding diagnoses and the predicted response to treatment, both of which often impair surgical decision-making. Decision analysis and reinforcement learning have the potential to play complementary roles in delivering high-value surgical care through sound judgment and optimal decision-making.

Dataset Information

Use of animation video in surgical decision-making for treatment of early breast cancer in Indian women.

Publications

Use of animation video in surgical decision-making for treatment of early breast cancer in Indian women.

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