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INFORNUT® PROCESS; IMPROVES ACCESSIBILITY TO DIAGNOSIS AND NUTRITIONAL SUPPORT FOR THE MALNOURISHED HOSPITALIZED PATIENT; IMPACT ON MANAGEMENT INDICATORS; TWO-YEAR ASSESSMENT.

Overview of attention for article published in Nutricion Hospitalaria, January 2014
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Title
INFORNUT® PROCESS; IMPROVES ACCESSIBILITY TO DIAGNOSIS AND NUTRITIONAL SUPPORT FOR THE MALNOURISHED HOSPITALIZED PATIENT; IMPACT ON MANAGEMENT INDICATORS; TWO-YEAR ASSESSMENT.
Published in
Nutricion Hospitalaria, January 2014
DOI 10.3305/nh.2014.29.6.7486
Pubmed ID
Authors

Juan Luis Villalobos Gámez, Cristina González Pérez, José Manuel García-Almeida, Alfonso Martínez Reina, José Del Río Mata, Efrén Márquez Fernández, Rosalía Rioja Vázquez, Joaquín Barranco Pérez, Alfredo Enguix Armada, Luis Miguel Rodríguez García, Olga Bernal Losada, Diego Osorio Fernández, Alfredo Mínguez Mañanes, Carlos Lara Ramos, Laila Dani, Antonio Vallejo Báez, Jesús Martínez Martín, José Manuel Fernández Ovies, Francisco Javier Tinahones Madueño, Joaquín Fernández-Crehuet Navajas

Abstract

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 SEDOMSENPE 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 procedurerelated 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.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 13%
Student > Bachelor 1 4%
Professor 1 4%
Student > Master 1 4%
Unknown 17 74%
Readers by discipline Count As %
Nursing and Health Professions 3 13%
Medicine and Dentistry 2 9%
Social Sciences 1 4%
Unknown 17 74%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 June 2014.
All research outputs
#2,309,929
of 4,655,155 outputs
Outputs from Nutricion Hospitalaria
#158
of 784 outputs
Outputs of similar age
#49,687
of 109,414 outputs
Outputs of similar age from Nutricion Hospitalaria
#3
of 11 outputs
Altmetric has tracked 4,655,155 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 784 research outputs from this source. They receive a mean Attention Score of 1.5. This one has gotten more attention than average, scoring higher than 72% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 109,414 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.