BACKGROUND: Malnutrition is prevalent among patients within certain cancer types. There is lack of universal standard of care for nutrition screening and a lack of agreement on an operational definition and on validity of malnutrition indicators. OBJECTIVE: In a secondary data analysis, we investigated prevalence of malnutrition diagnosis with 3 classification methods using data from medical records of a National Cancer Institute-designated comprehensive cancer center. METHODS: Records of 227 patients hospitalized during 1998 with head and neck, gastrointestinal, or lung cancer were reviewed for malnutrition based on 3 methods: (1) physician-diagnosed malnutrition-related International Classification of Diseases, Ninth Revision codes; (2) in-hospital nutritional assessment summaries conducted by registered dietitians; and (3) body mass indexes (BMIs). For patients with multiple admissions, only data from the first hospitalization were included. RESULTS: Prevalence of malnutrition diagnosis ranged from 8.8% based on BMI to approximately 26% of all cases based on dietitian assessment. κ coefficients between any methods indicated a weak (κ = 0.23, BMI and dietitians; and κ = 0.28, dietitians and physicians)-to-fair strength of agreement (κ = 0.38, BMI and physicians). CONCLUSIONS: Available methods to identify patients with malnutrition in a National Cancer Institute-designated comprehensive cancer center resulted in varied prevalence of malnutrition diagnosis. A universal standard of care for nutrition screening that uses validated tools is needed. IMPLICATIONS FOR PRACTICE: The Joint Commission on the Accreditation of Healthcare Organizations requires nutritional screening of patients within 24 hours of admission. For this purpose, implementation of a validated tool that can be used by various healthcare practitioners, including nurses, needs to be considered.
BACKGROUND: Malnutrition is prevalent among patients within certain cancer types. There is lack of universal standard of care for nutrition screening and a lack of agreement on an operational definition and on validity of malnutrition indicators. OBJECTIVE: In a secondary data analysis, we investigated prevalence of malnutrition diagnosis with 3 classification methods using data from medical records of a National Cancer Institute-designated comprehensive cancer center. METHODS: Records of 227 patients hospitalized during 1998 with head and neck, gastrointestinal, or lung cancer were reviewed for malnutrition based on 3 methods: (1) physician-diagnosed malnutrition-related International Classification of Diseases, Ninth Revision codes; (2) in-hospital nutritional assessment summaries conducted by registered dietitians; and (3) body mass indexes (BMIs). For patients with multiple admissions, only data from the first hospitalization were included. RESULTS: Prevalence of malnutrition diagnosis ranged from 8.8% based on BMI to approximately 26% of all cases based on dietitian assessment. κ coefficients between any methods indicated a weak (κ = 0.23, BMI and dietitians; and κ = 0.28, dietitians and physicians)-to-fair strength of agreement (κ = 0.38, BMI and physicians). CONCLUSIONS: Available methods to identify patients with malnutrition in a National Cancer Institute-designated comprehensive cancer center resulted in varied prevalence of malnutrition diagnosis. A universal standard of care for nutrition screening that uses validated tools is needed. IMPLICATIONS FOR PRACTICE: The Joint Commission on the Accreditation of Healthcare Organizations requires nutritional screening of patients within 24 hours of admission. For this purpose, implementation of a validated tool that can be used by various healthcare practitioners, including nurses, needs to be considered.
Authors: Angel Segura; Josep Pardo; Carlos Jara; Luis Zugazabeitia; Joan Carulla; Ramón de Las Peñas; Encarna García-Cabrera; María Luz Azuara; Josefina Casadó; Carmen Gómez-Candela Journal: Clin Nutr Date: 2005-10 Impact factor: 7.324
Authors: W D Dewys; C Begg; P T Lavin; P R Band; J M Bennett; J R Bertino; M H Cohen; H O Douglass; P F Engstrom; E Z Ezdinli; J Horton; G J Johnson; C G Moertel; M M Oken; C Perlia; C Rosenbaum; M N Silverstein; R T Skeel; R W Sponzo; D C Tormey Journal: Am J Med Date: 1980-10 Impact factor: 4.965
Authors: Mercè Planas; Julia Álvarez-Hernández; Miguel León-Sanz; Sebastián Celaya-Pérez; Krysmarú Araujo; Abelardo García de Lorenzo Journal: Support Care Cancer Date: 2015-06-23 Impact factor: 3.603
Authors: G Perl; S Nordheimer; S Lando; C Benedict; B Brenner; S Perry; G Shmoisman; O Purim; L Amit; S M Stemmer; I Ben-Aharon Journal: BMC Cancer Date: 2016-08-12 Impact factor: 4.430
Authors: Elaine B Trujillo; Katrina Claghorn; Suzanne W Dixon; Emily B Hill; Ashlea Braun; Elizabeth Lipinski; Mary E Platek; Maxwell T Vergo; Colleen Spees Journal: J Oncol Date: 2019-11-22 Impact factor: 4.375