Objectives: The aim of this study was to determine how diagnosing and coding of malnutrition in an internal medicine ward setting influences potential hospital reimbursement. Methods: Patients admitted to the internal medicine ward of Centro Hospitalar do Médio Ave between April 24 and May 22, 2018 were screened by Nutritional Risk Screening 2002, and patients classified as at “risk for malnutrition” were assessed by the Patient-Generated Subjective Global Assessment (PG-SGA). For each patient, medical coders simulated coding, taking into account the malnutrition diagnosis by PG-SGA, and compared it with the real coding as retrieved from the medical records. For the coding, the Diagnosis-Related Group and Severity of Illness were determined, allowing the calculation of hospitalization cost (HC) according to Portuguese Ministerial Directive number 207/2017. The increase of HC in this subsample was extrapolated to the number of patients admitted during 2018, to obtain the estimated unreported annual HC. Results: Of the 71% (92/129) participants having malnutrition risk according to Nutritional Risk Screening 2002, 86% were malnourished. Including malnutrition diagnosis in the coding of malnourished patients increased the level of Severity of Illness in 39% of cases and increased HC for this subsample, resulting in €52 000. Extrapolating for the annual HC, total HC reached €1.3 million. Conclusions: Identifying malnourished patients and including this highly prevalent diagnosis in medical records allows malnutrition coding and consequent increase of HC. This can improve the potential hospital reimbursement, which could contribute to the quality of patient care and economic sustainability of hospitals.
Objectives: Malnutrition is associated with a twofold higher risk of dying in patients with tuberculosis (TB) and considered an important potentially reversible risk factor for failure of TB treatment. The construct of malnutrition has three domains: intake or uptake of nutrition; body composition and physical and cognitive function. The objectives of this systematic review are to identify malnutrition assessment methods, and to quantify how malnutrition assessment methods capture the international consensus definition for malnutrition, in patients with TB.Design: Different assessment methods were identified. We determined the extent of capturing of the three domains of malnutrition, that is, intake or uptake of nutrition, body composition and physical and cognitive function.Results: Seventeen malnutrition assessment methods were identified in 69 included studies. In 53/69 (77%) of studies, body mass index was used as the only malnutrition assessment method. Three out of 69 studies (4%) used a method that captured all three domains of malnutrition.Conclusions: Our study focused on published articles. Implementation of new criteria takes time, which may take longer than the period covered by this review. Most patients with TB are assessed for only one aspect of the conceptual definition of malnutrition. The use of international consensus criteria is recommended to establish uniform diagnostics and treatment of malnutrition.
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This study evaluates the concurrent validity of five malnutrition screening tools to identify older hospitalized patients against the Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria as limited evidence is available. The screening tools Short Nutritional Assessment Questionnaire (SNAQ), Malnutrition Universal Screening Tool (MUST), Malnutrition Screening Tool (MST), Mini Nutritional Assessment—Short Form (MNA-SF), and the Patient-Generated Subjective Global Assessment—Short Form (PG-SGA-SF) with cut-offs for both malnutrition (conservative) and moderate malnutrition or risk of malnutrition (liberal) were used. The concurrent validity was determined by the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the level of agreement by Cohen’s kappa. In total, 356 patients were included in the analyses (median age 70 y (IQR 63–77); 54% male). The prevalence of malnutrition according to the GLIM criteria without prior screening was 42%. The conservative cut-offs showed a low-to-moderate sensitivity (32–68%) and moderate-to-high specificity (61–98%). The PPV and NPV ranged from 59 to 94% and 67–86%, respectively. The Cohen’s kappa showed poor agreement (k = 0.21–0.59). The liberal cut-offs displayed a moderate-to-high sensitivity (66–89%) and a low-to-high specificity (46–95%). The agreement was fair to good (k = 0.33–0.75). The currently used screening tools vary in their capacity to identify hospitalized older patients with malnutrition. The screening process in the GLIM framework requires further consideration.
