A Natural Language Processing Study to Assess Quality of End-of-Life Care for Children with Cancer (RP215)
Lindsay M, De Oliveira S, Ward D, Sciacca K, Lindvall C, Ananth P. A Natural Language Processing Study to Assess Quality of End-of-Life Care for Children with Cancer (RP215). Journal Of Pain And Symptom Management 2024, 67: e763. DOI: 10.1016/j.jpainsymman.2024.02.425.Peer-Reviewed Original ResearchEnd-of-life careGoals of care discussionsEnd-of-lifePalliative care consultationLocation of deathProportion of decedentsNatural language processingCode status limitationsCancer decedentsHospice discussionCare discussionsCare consultationDocumented goals of care discussionsEnd-of-life care qualityEvidence-based process measuresKeyword libraryLanguage processingElectronic health recordsManual chart abstractionMonths of lifeQuality measuresRule-based natural language processingCare qualityNatural language processing technologyNatural language processing studiesTransforming Written and Spoken Words into Quantitative Data for Palliative Care Research Using Natural Language Processing (ME301)
Lindvall C, Walling A, Ananth P. Transforming Written and Spoken Words into Quantitative Data for Palliative Care Research Using Natural Language Processing (ME301). Journal Of Pain And Symptom Management 2024, 67: e847-e848. DOI: 10.1016/j.jpainsymman.2024.02.491.Peer-Reviewed Original ResearchGoals of care conversationsPay-for-performance programsPay-for-performanceChart abstractionCare conversationsElectronic health record dataQuality improvementPalliative care deliveryAssess care qualityCare process measuresAdvanced cancerHealth record dataElectronic health recordsManual chart abstractionEnd-of-lifeManual chart reviewUS healthcare systemIllness careCare qualityNatural language processingCare deliveryAudio-recorded conversationsHealth recordsSocial supportIllness research