BACKGROUND Patient-reported experience measures (PREMs), such as the Jefferson Scale of Patient Perceptions of Physician Empathy (JSPPPE) or the Wake Forest Trust in Physician Scale (WTPS), have notable intercorrelation and ceiling effects (the proportion of observations with the highest possible score). Information is lost when high ceiling effects occur as there almost certainly is at least some variation among the patients with the highest score that the measurement tool was unable to measure. Efforts to identify and quantify factors associated with diminished patient experience can benefit from a PREM with more variability and a smaller proportion of highest possible scores (that is, a more limited ceiling effect) than occurs with currently available PREMs. QUESTIONS/PURPOSES In the first stage of a two-stage process, using a cohort of patients seeking musculoskeletal specialty care, we asked: (1) What groupings of items that address a similar aspect of patient experience are present among binary items directed at patient experience and derived from commonly used PREMs? (2) Can a small number of representative items provide a measure with potential for less of a ceiling effect (high item difficulty parameters)? In a second, independent cohort enrolled to assess whether the identified items perform consistently among different cohorts, we asked: (3) Does the new PREM perform differently in terms of item groupings (factor structure), and would different subsets of the included items provide the same measurement results (internal consistency) when items are measured using a 5-point rating scale instead of a binary scale? (4) What are the differences in survey properties (for example, ceiling effects) and correlation between the new PREM and commonly used PREMs? METHODS In two cross-sectional studies among patients seeking musculoskeletal specialty care conducted in 2022 and 2023, all English-speaking and English-reading adults (ages 18 to 89 years) without cognitive deficiency were invited to participate in two consecutive, separate cohorts to help develop (the initial, learning cohort) and internally validate (the second, validation cohort) a provisional new PREM. We identified 218 eligible patients for the initial learning cohort, of whom all completed all measures. Participants had a mean ± SD age of 55 ± 16 years, 60% (130) were women, 45% (99) had private insurance, and most sought care for lower extremity (56% [121]) and nontraumatic conditions (63% [137]). We measured 25 items derived from other commonly used PREMs that address aspects of patient experience in which patients reported whether they agreed or disagreed (binary) with certain statements about their clinician. We performed an exploratory factor analysis and confirmatory factor analysis (CFA) to identify groups of items that measure the same underlying construct related to patient experience. We then applied a two-parameter logistic model based on item response theory to identify the most discriminating items with the most variability (item difficulty) with the aim of reducing the ceiling effect. We also conducted a differential item functioning analysis to assess whether specific items are rated discordantly by specific subgroups of patients, which can introduce bias. We then enrolled 154 eligible patients, of whom 99% (153) completed all required measures, into a validation cohort with similar demographic characteristics. We changed the binary items to 5-point Likert scales to increase the potential for variation in an attempt to further reduce ceiling effects and repeated the CFA. We also measured internal consistency (using Cronbach alpha) and the correlation of the new PREM with other commonly used PREMs using bivariate analyses. RESULTS We identified three groupings of items in the learning cohort representing "trust in clinician" (13 items), "relationship with clinician" (7 items), and "participation in shared decision-making" (4 items). The "trust in clinician" factor performed best of all three factors and therefore was selected for subsequent analyses. We selected the best-performing items in terms of item difficulty to generate a 7-item short form. We found excellent CFA model fit (the 13-item and 7-item versions both had a root mean square error of approximation [RMSEA] of < 0.001), excellent internal consistency (Cronbach α was 0.94 for the 13-item version and 0.91 for the 7-item version), good item response theory parameters (item difficulty ranging between -0.37 and 0.16 for the 7-item version, with higher values indicating lower ceiling effect), no local dependencies, and no differential item functioning among any of the items. The other two factors were excluded from measure development due to low item response theory parameters (item difficulty ranging between -1.3 and -0.69, indicating higher ceiling effect), multiple local dependencies, and exhausting the number of items without being able to address these issues. The validation cohort confirmed adequate item selection and performance of both the 13-item and 7-item version of the Trust and Experience with Clinicians Scale (TRECS), with good to excellent CFA model fit (RMSEA 0.058 [TRECS-13]; RMSEA 0.016 [TRECS-7]), excellent internal consistency (Cronbach α = 0.96 [TRECS-13]; Cronbach α = 0.92 [TRECS-7]), no differential item functioning and limited ceiling effects (11% [TRECS-13]; 14% [TRECS-7]), and notable correlation with other PREMs such as the JSPPPE (ρ = 0.77) and WTPS (ρ = 0.74). CONCLUSION A relatively brief 7-item measure of patient experience focused on trust can eliminate most of the ceiling effects common to PREMs with good psychometric properties. Future studies may externally validate the TRECS in other populations as well as provide population-based T-score conversion tables based on a larger sample size more representative of the population seeking musculoskeletal care. CLINICAL RELEVANCE A PREM anchored in trust that reduces loss of information at the higher end of the scale can help individuals and institutions to assess experience more accurately, gauge the impact of interventions, and generate effective ways to learn and improve within a health system.

中文翻译：

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是否有可能开发具有较低上限效应的患者报告体验测量？


背景患者报告的经验测量 （PREM），例如患者对医生同理心的杰斐逊感知量表 （JSPPPE） 或维克森林信任医师量表 （WTPS），具有显着的相互相关性和天花板效应（得分最高的观察比例）。当高天花板效应发生时，信息会丢失，因为几乎可以肯定，得分最高的患者之间至少存在一些差异，而测量工具无法测量。与目前可用的 PREM 相比，PREM 具有更大的可变性和更小的最高分数比例（即更有限的上限效应），因此识别和量化与患者体验减少相关的因素的努力可以从中受益。问题/目的 在两阶段过程的第一阶段，使用一组寻求肌肉骨骼专业护理的患者，我们询问： （1） 在针对患者体验并源自常用 PREM 的二元项目中，存在哪些涉及患者体验相似方面的项目分组？（2） 少量代表性项目能否提供可能降低上限效应（高项目难度参数）的度量？在第二个独立队列中，为了评估已识别的项目在不同队列中的表现是否一致，我们询问：（3） 新的 PREM 在项目分组（因子结构）方面的表现是否不同，当使用 5 分制评分量表而不是二进制量表测量项目时，纳入项目的不同子集是否会提供相同的测量结果（内部一致性）？（4） 新 PREM 与常用 PREM 在测量特性（例如天花板效应）和相关性方面有什么区别？ 方法 在 2022 年和 2023 年对寻求肌肉骨骼专业护理的患者进行的两项横断面研究中，所有没有认知缺陷的英语口语和英语阅读成年人（年龄 18 至 89 岁）被邀请参加两个连续的、独立的队列，以帮助开发（初始学习队列）和内部验证（第二个验证队列）临时的新 PREM。我们为初始学习队列确定了 218 名符合条件的患者，其中所有患者都完成了所有测量。参与者的平均 ±SD 年龄为 55 ± 16 岁，其中 60% （130） 为女性，45% （99） 拥有私人保险，大多数人寻求下肢 （56% [121]）和非创伤性疾病 （63% [137]）的护理。我们测量了来自其他常用 PREM 的 25 个项目，这些项目涉及患者体验的各个方面，其中患者报告他们是否同意或不同意 （二元） 关于其临床医生的某些陈述。我们进行了探索性因子分析和验证性因子分析 （CFA） 以确定测量与患者体验相关的相同基本结构的项目组。然后，我们应用了一个基于项目反应理论的双参数 logistic 模型来识别最具辨别力和最大可变性（项目难度）的项目，以减少天花板效应。我们还进行了差异项目功能分析，以评估特定项目是否被特定患者亚组不一致地评级，这可能会引入偏倚。然后，我们将 154 名符合条件的患者纳入具有相似人口学特征的验证队列，其中 99% （153） 完成了所有必需的措施。 我们将二进制项目更改为 5 点李克特量表以增加变化的可能性，以试图进一步减少天花板效应并重复 CFA。我们还使用双变量分析测量了内部一致性（使用 Cronbach alpha）以及新 PREM 与其他常用 PREM 的相关性。结果 我们在学习队列中确定了三组项目，分别代表 “对临床医生的信任” （13 个项目）、 “与临床医生的关系” （7 个项目） 和 “参与共同决策” （4 个项目）。“信任临床医生”因素在所有三个因素中表现最好，因此被选中进行后续分析。我们选择了在项目难度方面表现最好的项目来生成一个 7 项目的简短表格。我们发现了出色的 CFA 模型拟合（13 项和 7 项版本的近似均方根误差 [RMSEA] 均为 < 0.001），出色的内部一致性（13 项版本的克朗巴赫α为 0.94,7 项版本的克朗巴赫为 0.91），良好的项目响应理论参数（7 项版本的项目难度在 -0.37 和 0.16 之间， 值越高表示上限效果越低），没有本地依赖关系，并且任何项目之间没有不同的项目功能。由于项目响应理论参数较低（项目难度在 -1.3 和 -0.69 之间，表明更高的上限效应）、多个局部依赖关系以及耗尽项目数量而无法解决这些问题，其他两个因素被排除在测量开发之外。验证队列证实了临床医生信任和经验量表 （TRECS） 的 13 项和 7 项版本的适当项目选择和性能，具有良好到优秀的 CFA 模型拟合 （RMSEA 0.058 [TRECS-13];RMSEA 0.016 [TRECS-7]），出色的内部一致性 （Cronbach α = 0.96 [TRECS-13];Cronbach α = 0.92 [TRECS-7]），无差异项目功能和有限的上限效应 （11% [TRECS-13];14% [TRECS-7]），并且与其他 PREM 有显著相关性，例如 JSPPPE （ρ = 0.77） 和 WTPS （ρ = 0.74）。结论 以信任为重点的相对简短的 7 项患者体验测量可以消除具有良好心理测量特性的 PREM 常见的大部分天花板效应。未来的研究可能会从外部验证其他人群的 TRECS，并根据更能代表寻求肌肉骨骼护理的人群的更大样本量提供基于人群的 T 分数转换表。临床相关性 以信任为基础的 PREM 可以减少规模高端的信息损失，可以帮助个人和机构更准确地评估体验，衡量干预措施的影响，并产生在卫生系统内学习和改进的有效方法。