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Use of automatic SQL generation interface to enhance transparency and validity of health-data analysis.
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.
Afiliación
  • Wagholikar KB; Harvard Medical School, Boston, MA, USA.
  • Zelle D; Massachusetts General Hospital, Boston, MA, USA.
  • Ainsworth L; Brigham and Women's Hospital, Boston, MA, USA.
  • Chaney K; Mass General Brigham, Boston, MA, USA.
  • Blood AJ; Brigham and Women's Hospital, Boston, MA, USA.
  • Miller A; Harvard Medical School, Boston, MA, USA.
  • Chulyadyo R; Brigham and Women's Hospital, Boston, MA, USA.
  • Oates M; Massachusetts General Hospital, Boston, MA, USA.
  • Gordon WJ; Mass General Brigham, Boston, MA, USA.
  • Aronson SJ; Mass General Brigham, Boston, MA, USA.
  • Scirica BM; Harvard Medical School, Boston, MA, USA.
  • Murphy SN; Brigham and Women's Hospital, Boston, MA, USA.
Article en En | MEDLINE | ID: mdl-35874460
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Inform Med Unlocked Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Inform Med Unlocked Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos