Kohut Mike, Jalbuena Tracy, Alfiero Rachel, DiPalazzo John, Anderson Eric, Bishop Jasmine
Center for Interdisciplinary Population and Health Research, MaineHealth Institute for Research, Scarborough, Maine, USA.
Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, Massachusetts, USA.
Telemed J E Health. 2025 May;31(5):634-642. doi: 10.1089/tmj.2024.0300. Epub 2024 Dec 27.
In order to assess patient experiences of telemedicine, researchers and administrators use the net promoter score (NPS), based on a likelihood to recommend (LTR) question. However, there is reason to doubt validity of this metric for this purpose. We assessed the degree to which the LTR question reflects actual patient preferences about telemedicine. Using data from a patient experience survey collected in Spring 2020, we compared LTR responses to open comments. Through content analysis, we transformed comments into categorical variables and used those variables in a multiple logistic regression model to predict LTR responses. We also thematically analyzed comments to further elucidate our results. Only about half the comments mentioned telemedicine at all. Around 6% of comments were wholly incongruent with LTR responses. In many comments, ideas about telemedicine were semantically entangled with ideas about providers. Our logistic regression found strong associations between sentiments expressed in comments and LTR responses. However, comments about telemedicine were relatively poor predictors for LTR compared to comments about the provider. NPS, which is included on many patient experience surveys used by health systems across the United States, has limitations for use as a measure of the acceptability of telemedicine for patients. Patients have more than telemedicine in mind when responding to the LTR question, and ratings conflate attitudes about providers, office policies, and staff with the telemedicine modality. More direct measures are necessary for meaningful research on the acceptability and usability of telemedicine for patients.
为了评估患者对远程医疗的体验，研究人员和管理人员使用基于推荐可能性（LTR）问题的净推荐值（NPS）。然而，有理由怀疑该指标用于此目的的有效性。我们评估了LTR问题反映患者对远程医疗实际偏好的程度。利用2020年春季收集的患者体验调查数据，我们将LTR回答与开放式评论进行了比较。通过内容分析，我们将评论转化为分类变量，并在多元逻辑回归模型中使用这些变量来预测LTR回答。我们还对评论进行了主题分析，以进一步阐明我们的结果。只有大约一半的评论提到了远程医疗。约6%的评论与LTR回答完全不一致。在许多评论中，关于远程医疗的想法在语义上与关于医疗服务提供者的想法纠缠在一起。我们的逻辑回归发现评论中表达的情绪与LTR回答之间存在强烈关联。然而，与关于医疗服务提供者的评论相比，关于远程医疗的评论对LTR的预测能力相对较差。NPS被纳入了美国各地医疗系统使用的许多患者体验调查中，但作为衡量患者对远程医疗可接受性的指标存在局限性。患者在回答LTR问题时考虑的不仅仅是远程医疗，评分将对医疗服务提供者、办公室政策和工作人员的态度与远程医疗模式混为一谈。对于有意义的患者远程医疗可接受性和可用性研究，需要更直接的测量方法。
