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Evaluating the efficacy of NoteAid on EHR note comprehension among US Veterans through Amazon Mechanical Turk.
Lalor, John P; Wu, Hao; Mazor, Kathleen M; Yu, Hong.
Afiliación
  • Lalor JP; Department of Information Technology, Analytics, and Operations, Mendoza College of Business, University of Notre Dame, Notre Dame, IN, US.
  • Wu H; Department of Psychology and Human Development, Peabody College, Vanderbilt University, Nashville, TN, US.
  • Mazor KM; Department of Medicine, University of Massachusetts Medical School, Worcester, MA, US; Meyers Primary Care Institute, University of Massachusetts Medical School/Reliant Medical Group/Fallon Health, Worcester, MA, US.
  • Yu H; Department of Computer Science, University of Massachusetts Lowell, Lowell, MA, US; College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA, US; Center for Healthcare Organization and Implementation Research, Bedford Veterans Affairs Medical Center, Bedford, MA
Int J Med Inform ; 172: 105006, 2023 04.
Article en En | MEDLINE | ID: mdl-36780789
ABSTRACT

OBJECTIVE:

Low health literacy is a concern among US Veterans. In this study, we evaluated NoteAid, a system that provides lay definitions to medical jargon terms in EHR notes to help Veterans comprehend EHR notes. We expected that low initial scores for Veterans would be improved by using NoteAid. MATERIALS AND

METHODS:

We recruited Veterans from the Amazon Mechanical Turk crowd work platform (MTurk). We also recruited non-Veterans from MTurk as a control group for comparison. We randomly split recruited MTurk Veteran participants into control and intervention groups. We recruited non-Veteran participants into mutually exclusive control or intervention tasks on the MTurk platform. We showed participants de-identified EHR notes and asked them to answer comprehension questions related to the notes. We provided participants in the intervention group with EHR note content processed with NoteAid, while NoteAid was not available for participants in the control group.

RESULTS:

We recruited 94 Veterans and 181 non-Veterans. NoteAid leads to a significant improvement for non-Veterans but not for Veterans. Comparing Veterans recruited via MTurk with non-Veterans recruited via MTurk, we found that without NoteAid, Veterans have significantly higher raw scores than non-Veterans. This difference is not significant with NoteAid.

DISCUSSION:

That Veterans outperform a comparable population of non-Veterans is a surprising outcome. Without NoteAid, scores on the test are already high for Veterans, therefore, minimizing the ability of an intervention such as NoteAid to improve performance. With regards to Veterans, understanding the health literacy of Veterans has been an open question. We show here that Veterans score higher than a comparable, non-Veteran population.

CONCLUSION:

Veterans on MTurk do not see improved scores when using NoteAid, but they already score high on the test, significantly higher than non-Veterans. When evaluating NoteAid, population specifics need to be considered, as performance may vary across groups. Future work investigating the effectiveness of NoteAid on improving comprehension with local Veterans and developing a more difficult test to assess groups with higher health literacy is needed.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Alfabetización en Salud / Colaboración de las Masas Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Humans Idioma: En Revista: Int J Med Inform Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Alfabetización en Salud / Colaboración de las Masas Tipo de estudio: Clinical_trials / Prognostic_studies Límite: Humans Idioma: En Revista: Int J Med Inform Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos