ABSTRACT
BACKGROUND & AIMS: Screening for malnutrition is not often done in the management of hospitalized patients. An original computer tool was developed at the Dunkerque hospital to detect readmissions of patients with malnutrition during a previous stay and generate e-mail alerts to the nutrition department. The aim of the study was to describe and evaluate this tool and the activity of the nutrition department in connection with the alerts sent. METHODS: The number of alerts sent, dietary consultations conducted, assessments of the nutritional status and the number of malnourished patients diagnosed were collected from September 1st to November 30th 2012. The positive predictive value (PPV) of the malnutrition screening tool was estimated. The evolution of the nutritional status between the last and the current hospitalization was also evaluated. RESULTS: A total of 531 e-mail alerts were sent (mean of 8.2 per working day), leading to 205 dietary consultations but only 144 recorded assessments of the nutritional status (lack of information in medical records). Of the latter, 128 diagnoses of malnutrition were made, i.e. a PPV of 88.9%, 95% Confidence Interval = [83.8%, 94%]. Overall, only one quarter of readmitted patients had improved nutritional status. CONCLUSIONS: The automatic e-mail alert system is operational and useful to effectively detect patients at risk of malnutrition and make follow up possible. In addition, an unfavorable evolution of the nutritional status of malnourished patients was observed.
Subject(s)
Electronic Mail , Hospitalization , Malnutrition/diagnosis , Aged , Aged, 80 and over , Diet , Female , Humans , Logistic Models , Male , Mass Screening , Middle Aged , Nutrition Assessment , Nutritional Status , Patient Readmission , Risk Factors , Surveys and QuestionnairesABSTRACT
The recent development of hospital information systems in France presently makes it possible to study similarity between establishments based on an official data source, the AGHN. The AGHN is based on three types of information: medical, structural (personnel and material) and economic. Using the PCA (principal component analysis) tool, we can examine the situation of one regional and\or university hospital with regards to others of the same kind.
