Wagholikar Kavishwar B, Zelle David, Ainsworth Layne, Chaney Kira, Blood Alexander J, Miller Angela, Chulyadyo Rupendra, Oates Michael, Gordon William J, Aronson Samuel J, Scirica Benjamin M, Murphy Shawn N
Harvard Medical School, Boston, MA, USA.
Massachusetts General Hospital, Boston, MA, USA.
Inform Med Unlocked. 2022;31. doi: 10.1016/j.imu.2022.100996. Epub 2022 Jun 25.
Analysis of health data typically requires development of queries using structured query language (SQL) by a data-analyst. As the SQL queries are manually created, they are prone to errors. In addition, accurate implementation of the queries depends on effective communication with clinical experts, that further makes the analysis error prone. As a potential resolution, we explore an alternative approach wherein a graphical interface that automatically generates the SQL queries is used to perform the analysis. The latter allows clinical experts to directly perform complex queries on the data, despite their unfamiliarity with SQL syntax. The interface provides an intuitive understanding of the query logic which makes the analysis transparent and comprehensible to the clinical study-staff, thereby enhancing the transparency and validity of the analysis. This study demonstrates the feasibility of using a user-friendly interface that automatically generate SQL for analysis of health data. It outlines challenges that will be useful for designing user-friendly tools to improve transparency and reproducibility of data analysis.
健康数据的分析通常需要数据分析人员使用结构化查询语言（SQL）来编写查询语句。由于SQL查询是手动创建的，因此容易出错。此外，查询的准确执行依赖于与临床专家的有效沟通，这进一步增加了分析出错的可能性。作为一种潜在的解决方案，我们探索了一种替代方法，即使用自动生成SQL查询的图形界面来进行分析。后者使临床专家能够直接对数据执行复杂查询，尽管他们不熟悉SQL语法。该界面提供了对查询逻辑的直观理解，使临床研究人员能够理解分析过程，从而提高了分析的透明度和有效性。本研究证明了使用自动生成SQL的用户友好界面来分析健康数据的可行性。它概述了一些挑战，这些挑战对于设计用户友好的工具以提高数据分析的透明度和可重复性将是有用的。
