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Nutrición Hospitalaria

On-line version ISSN 1699-5198Print version ISSN 0212-1611


VILLALOBOS GAMEZ, Juan Luis et al. INFORNUT® Process: improves accessibility to diagnosis and nutritional support for the malnourished hospitalized patient; impact on management indicators; two-year assessment. Nutr. Hosp. [online]. 2014, vol.29, n.6, pp.1210-1223. ISSN 1699-5198.

Introduction: The high prevalence of disease-related hospital malnutrition justifies the need for screening tools and early detection in patients at risk for malnutrition, followed by an assessment targeted towards diagnosis and treatment. At the same time there is clear undercoding of malnutrition diagnoses and the procedures to correct it. Objectives: To describe the INFORNUT program/ process and its development as an information system. To quantify performance in its different phases. To cite other tools used as a coding source. To calculate the coding rates for malnutrition diagnoses and related procedures. To show the relationship to Mean Stay, Mortality Rate and Urgent Readmission; as well as to quantify its impact on the hospital Complexity Index and its effect on the justification of Hospitalization Costs. Material and methods: The INFORNUT® process is based on an automated screening program of systematic detection and early identification of malnourished patients on hospital admission, as well as their assessment, diagnoses, documentation and reporting. Of total readmissions with stays longer than three days incurred in 2008 and 2010, we recorded patients who underwent analytical screening with an alert for a medium or high risk of malnutrition, as well as the subgroup of patients in whom we were able to administer the complete INFORNUT® process, generating a report for each. Other documentary coding sources are cited. From the Minimum Basic Data Set, codes defined in the SEDOM-SENPE consensus were analyzed. The data were processed with the Alcor-DRG program. Rates in ‰ of discharges for 2009 and 2010 of diagnoses of malnutrition, procedure and procedures-related diagnoses were calculated. These rates were compared with the mean rates in Andalusia. The contribution of these codes to the Complexity Index was estimated and, from the cost accounting data, the fraction of the hospitalization cost seen as justified by this activity was estimated. Results: Results are summarized for both study years. With respect to process performance, more than 3,600 patients per year (30‰ of admissions with a stay > 3 days) underwent analytical screening. Half of these patients were at medium or high risk and a nutritional assessment using INFORNUT® was completed for 55‰ of them, generating approximately 1,000 reports/year. Our coding rates exceeded the mean rates in Andalusia, being 3.5 times higher for diagnoses (35‰); 2.5 times higher for procedures (50‰) and five times the rate of procedure-related diagnoses in the same patient (25‰). The Mean Stay of patients coded with malnutrition at discharge was 31.7 days, compared to 9.5 for the overall hospital stay. The Mortality Rate for the same patients (21.8%) was almost five times higher than the mean and Urgent Readmissions (5.5%) were 1.9 times higher. The impact of this coding on the hospital Complexity Index was four hundredths (from 2.08 to 2.12 in 2009 and 2.15 to 2.19 in 2010). This translates into a hospitalization cost justification of 2,000,000€; five to six times the cost of artificial nutrition. Conclusions: The process facilitated access to the diagnosis of malnutrition and to understanding the risk of developing it, as well as to the prescription of procedures and/or supplements to correct it. The interdisciplinary team coordination, the participatory process and the tools used improved coding rates to give results far above the Andalusian mean. These results help to upwardly adjust the hospital Complexity Index or Case Mix-, as well as to explain hospitalization costs.

Keywords : Disease-related malnutrition; Nutritional screening; Hospital costs; Diagnostic-related group; Mean Complexity or Complexity Index.

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