Harnessing Natural Language Processing to Assess Quality of End-of-Life Care for Children With Cancer
Lindsay M, de Oliveira S, Sciacca K, Lindvall C, Ananth P. Harnessing Natural Language Processing to Assess Quality of End-of-Life Care for Children With Cancer. JCO Clinical Cancer Informatics 2024, 8: e2400134. PMID: 39265122, PMCID: PMC11407740, DOI: 10.1200/cci.24.00134.Peer-Reviewed Original ResearchConceptsEnd-of-life carePalliative care consultationGoals of careLocation of deathProportion of decedentsDocumented discussionCare consultationEvidence-based quality measuresMeasure quality of careGold standard manual chart reviewQuality measuresQuality of careEnd of lifeContent of clinical notesLife-sustaining treatmentEnd-of-lifeManual chart reviewCancer decedentsEfficient quality measureCohort of childrenAssess qualityMulti-center researchQuality improvementMeasure qualityCareDefining the Denominator for Measuring Quality of End-of-Life Care in Children with Cancer: Results of a Nominal Group Technique
Johnston E, Tefera R, Ananth P, Martinez I, Porter A, Snaman J, Thienprayoon R, Asch S, Bhatia S, O'Beirne R. Defining the Denominator for Measuring Quality of End-of-Life Care in Children with Cancer: Results of a Nominal Group Technique. The Journal Of Pediatrics 2024, 271: 114038. PMID: 38554745, DOI: 10.1016/j.jpeds.2024.114038.Peer-Reviewed Original ResearchEnd-of-lifePoor-prognosis cancerEnd-of-life quality measuresQuality of EOL careQuality measuresPediatric oncologyPediatric palliative carePediatric quality measuresPrognosis cancersNon-Hispanic whitesNominal groupsSpecific treatment scenarioNominal group techniqueEOL carePalliative careSeventy-nine percentBereaved parentsMeasure qualityClinical programsEnhance qualityGroup techniqueGroup of childrenCareParticipantsClinician-scientists