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Datos de Historias Clínicas Electrónicas frente a Datos de Historias Clínicas Electrónicas para la Mejora de la
James L Galloway1, Vivi W Chen2, Jennifer Kramer3
1Veterans Affairs Quality Scholars Program, Atlanta VA Health Care System, Decatur, Georgia; Department of Surgery, Emory University School of Medicine, Atlanta, Georgia.
The Journal of surgical research
|January 10, 2026
Resumen
La automatización de la recopilación de datos para el Programa de Mejora de la Calidad Quirúrgica de Asuntos de Veteranos (VASQIP) utilizando historias clínicas electrónicas (HCE) muestra una alta precisión para la mayoría de las variables. Esta automatización puede mejorar los programas de mejora de la calidad (CQ) quirúrgica al ahorrar recursos y mejorar la puntualidad de los datos.
Área de la Ciencia:
- Informática de la Salud
- Mejora de la Calidad Quirúrgica
- Ciencia de Datos en Atención Médica
Sus antecedentes:
- La extracción manual de datos es el punto de referencia para los programas de mejora de la calidad (CQ) quirúrgica.
- La automatización de la recopilación de datos puede beneficiar significativamente las iniciativas de CQ al reducir las demandas de recursos.
- El Programa de Mejora de la Calidad Quirúrgica de Asuntos de Veteranos (VASQIP) se basa en la extracción manual.
Objetivo del estudio:
- Evaluar la precisión y concordancia de las variables derivadas de historias clínicas electrónicas (HCE) en comparación con las variables de VASQIP extraídas manualmente.
- Determinar la viabilidad de automatizar la recopilación de datos para VASQIP.
- Evaluar el potencial de los datos de HCE para mejorar la CQ quirúrgica.
Principales métodos:
- Un análisis transversal nacional que compara los correlatos de variables de VASQIP derivados de HCE con las variables de VASQIP extraídas manualmente (2016-2020).
- Se utilizó el índice Kappa de Cohen, la sensibilidad, la especificidad y los valores predictivos para medir la concordancia.
- Se definió una fuerte concordancia como kappa ≥80%.
Principales resultados:
- Se evaluaron 533,164 casos en 113 hospitales.
- Alta concordancia (mediana kappa 98.1%) para raza y etnia.
- Concordancia variable para factores de riesgo preoperatorios (mediana 28.6%) y complicaciones postoperatorias (mediana 15.1%).
- Fuerte concordancia para laboratorios preoperatorios (mediana 91.9%) y factores intraoperatorios (mediana 93.9%).
Conclusiones:
- Los correlatos derivados de HCE demuestran una alta precisión para automatizar la recopilación de datos para muchas variables de VASQIP, excluyendo las complicaciones postoperatorias.
- La automatización puede reducir los recursos de extracción manual de datos.
- Se puede lograr una mayor puntualidad y solidez de los programas de CQ quirúrgica a través de la utilización de datos de HCE.
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