Dodson Crystal, Layman Lucas
School of Nursing, University of North Carolina Wilmington, Wilmington, NC, USA.
Department of Computer Science, University of North Carolina Wilmington, Wilmington, NC, USA.
Ann Transl Med. 2022 Dec;10(23):1261. doi: 10.21037/atm-2022-68.
This study extended a precision medicine clinical decision support mobile application (app) for use with oncology medications. Two gene variants ( and ) associated with pharmacogenomic dosing algorithms in oncology was added to a prototype app. Usability of the app was evaluated. The use of smartphones and mobile apps for prescribing medications has exponentially increased since the introduction of physician order entry. Decision support apps have improved provider performance and studies have shown broader adoption is crucial for the success of these tools. Therefore, successful use of mobile apps will depend on perceptions of users. Rogers' Diffusion of Innovation theory will be the guiding framework for this study.
The main research variable is usability as measured by effectiveness, efficiency, and satisfaction. A mixed method design was used. The setting was inpatient and outpatient oncology practices within North Carolina. The sample included registered nurses and nurse practitioners within the oncology field. A functioning mobile app was extended based on the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines to address the most common gene variants seen in oncology patients. Usability testing is divided into two main categories, inspection and testing methods. Prior to the field study, a heuristic evaluation was conducted. This evaluation inspected the user interface, comparing the elements and aspects of it to a set of principles, heuristics, as a guideline to evaluate the usability of the mobile app.
The testing evaluation was conducted with a sample of 51 health care providers to evaluate usability, measured by the System Usability Scale and open-ended questions. Descriptive statistics was used to summarize usefulness and end-user perceived ease of use. In addition, a thematic analysis of the open-ended questions was conducted.
The development of this mobile app is relevant to nurses who have prescriptive privileges, as well as an educational tool for nurses to understand the rationale behind prescribing certain medications and alternate dosages by providing specific recommendations. Translation of precision medicine into practice will benefit patients by improving care, reducing adverse reactions, and lowering costs.
本研究扩展了一款用于肿瘤药物的精准医学临床决策支持移动应用程序（应用）。与肿瘤学中药物基因组剂量算法相关的两个基因变体（和）被添加到一个原型应用中。对该应用的可用性进行了评估。自引入医生医嘱录入以来，使用智能手机和移动应用程序开药的情况呈指数级增长。决策支持应用提高了医疗服务提供者的绩效，研究表明更广泛的采用对这些工具的成功至关重要。因此，移动应用的成功使用将取决于用户的认知。罗杰斯的创新扩散理论将作为本研究的指导框架。
主要研究变量是通过有效性、效率和满意度衡量的可用性。采用了混合方法设计。研究地点是北卡罗来纳州的住院和门诊肿瘤学实践。样本包括肿瘤学领域的注册护士和执业护士。根据临床药物基因组学实施联盟（CPIC）指南扩展了一个功能正常的移动应用，以处理肿瘤患者中最常见的基因变体。可用性测试分为两大类，检查和测试方法。在实地研究之前，进行了启发式评估。该评估检查了用户界面，将其元素和方面与一组原则（启发式）进行比较，作为评估移动应用可用性的指南。
对51名医疗保健提供者的样本进行了测试评估，以通过系统可用性量表和开放式问题评估可用性。使用描述性统计来总结有用性和最终用户感知的易用性。此外，对开放式问题进行了主题分析。
这款移动应用的开发与拥有处方权的护士相关，也是护士了解通过提供特定建议开具某些药物和替代剂量背后原理的教育工具。将精准医学转化为实践将通过改善护理、减少不良反应和降低成本使患者受益。
