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探索医师助理数据源。

Exploring physician assistant data sources.

作者信息

Orcutt Venetia L

机构信息

Venetia L. Orcutt is an associate professor and associate director in the PA program at the University of Texas Southwestern Medical Center in Dallas, Tex. The author has disclosed no potential conflicts of interest, financial or otherwise.

出版信息

JAAPA. 2015 Aug;28(8):49-50, 52-6. doi: 10.1097/01.JAA.0000469443.64882.4e.

Abstract

OBJECTIVES

To assess four physician assistant (PA) proprietary datasets and inform researchers about data quality for addressing healthcare policy and workforce questions.

METHODS

The quality of datasets was assessed by experienced researchers. Descriptive analysis included overview, collection methodology, variables, and availability. Assessment included each dataset's strengths and limitations.

RESULTS

Datasets from the American Academy of Physician Assistants, National Commission on Certification of Physician Assistants, Physician Assistant Education Association, and Optum Provider360 Database include overlap in variables reflecting organizational mission and/or design. Attributes include variables for validation; limitations were lack of public use files, requirements for specific data requests or data purchase. The datasets do not have unique identifiers and cannot easily be linked.

CONCLUSIONS

The PA datasets contain variables of interest but are limited in scope. Better data collection and shared platforms could further the understanding of PA workforce characteristics and contributions to American healthcare. Researchers await more comprehensive, longitudinal, linked, and publicly available datasets.

摘要

目的

评估四个医师助理(PA)专有数据集,并向研究人员提供有关数据质量的信息,以解决医疗保健政策和劳动力问题。

方法

数据集的质量由经验丰富的研究人员进行评估。描述性分析包括概述、收集方法、变量和可用性。评估包括每个数据集的优势和局限性。

结果

来自美国医师助理学会、医师助理国家认证委员会、医师助理教育协会和Optum Provider360数据库的数据集在反映组织使命和/或设计的变量方面存在重叠。属性包括用于验证的变量;局限性在于缺乏公共使用文件、特定数据请求或数据购买的要求。这些数据集没有唯一标识符,也不容易链接。

结论

PA数据集包含感兴趣的变量,但范围有限。更好的数据收集和共享平台可以进一步加深对PA劳动力特征及其对美国医疗保健贡献的理解。研究人员期待更全面、纵向、链接且公开可用的数据集。

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