Modern psychometric methods for estimating physician performance on the Clinician and Group CAHPS® survey
Modern psychometric methods for estimating physician performance on the Clinician and Group CAHPS® survey
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DOI：
10.1007/s10742-013-0111-8
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发表时间：
2013-12-01
影响因子：
1.5
通讯作者：
Crane, Paul K.
中科院分区：
文献类型：
--
作者：
Mukherjee, Shubhabrata;Rodriguez, Hector P.;Crane, Paul K.
采用现代心理测量学方法对医疗保健提供者和系统的临床医师和群体消费者评估（CG-CAHPS (R)）进行评分，可以提高患者评分的精度。然而，这些方法能在多大程度上提高对医生个人表现的可靠评估和比较，目前仍不清楚。利用南加州448名初级保健医生的12244例独特患者的CG-CAHPS (R)数据，采用四种方法计算综合评分：(1)标准评分，(2)单因素验证性因素分析模型，(3)双因素模型，(4)相关因素模型。我们从每个模型中提取了医生的因素得分，并根据受访者的特征调整了得分，包括年龄、教育程度、自评身体健康状况和种族/民族。通过四种方法检验了医生水平的可靠性和医生排名。双因子和相关因子模型对三个核心复合测度的核心CG-CAHPS (R)问题的拟合效果最佳。与标准调整评分相比，双因素模型评分导致每位医生所需样本量减少25%。不同评分方法间医师排名的相关系数为0.58 ~ 0.86。不同评分方法的医师排名的不一致性在绩效分布的中间表现最为明显。使用现代心理测量方法在核心CG-CAHPS (R)问题上对医生的表现进行评分，可以提高医生对患者体验措施的绩效评估的可靠性，从而减少与标准评分相比，每位医生所需的受访者样本量。为了评估现代心理测量方法生成的CG-CAHPS (R)评分的预测效度，未来的研究应检验不同评分方法与重要的以患者为中心的护理结果之间的相对关联。
Modern psychometric methods for scoring the Clinician & Group Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS (R)) instrument can improve the precision of patient scores. The extent to which these methods can improve the reliable estimation and comparison of individual physician performance, however, remains unclear. Using CG-CAHPS (R) data from 12,244 unique patients of 448 primary care physicians in southern California, four methods were used to calculate composite scores: (1) standard scoring, (2) a single factor confirmatory factor analysis model, (3) a bifactor model, and (4) a correlated factor model. We extracted factor scores for physicians from each model and adjusted the scores for respondent characteristics, including age, education, self-rated physical health, and race/ethnicity. Physician-level reliability and physician rankings were examined across the four methods. The bifactor and correlated factor models achieved the best fit for the core CG-CAHPS (R) questions from the three core composite measures. Compared to standard adjusted scoring, the bifactor model scores resulted in a 25 % reduction in required sample sizes per physician. The correlation of physician rankings between scoring methods ranged from 0.58 to 0.86. The discordance of physician rankings across scoring methods was most pronounced in the middle of the performance distribution. Using modern psychometric methods to score physician performance on the core CG-CAHPS (R) questions may improve the reliability of physician performance estimates on patient experience measures, thereby reducing the required respondent sample sizes per physician compared to standard scoring. To assess the predictive validity of the CG-CAHPS (R) scores generated by modern psychometric methods, future research should examine the relative association of different scoring methods and important patient-centered outcomes of care.