Use of the Flugelman index for identifying patients who are difficult to discharge from the hospital

• Published in: Italian journal of medicine Vol. 5; no. 2; pp. 103 - 108
• Main Authors: Bozzano, Chiara, Lancini, Ilario, Mei, Elena, Lucarini, Maida, Mastriforti, Roberta, Zuccone, Nunzia, Vanni, Dino, Pedace, Claudio
• Format: Journal Article
• Language: English
• Published: PAGEPress Publications 07.03.2013
• Subjects: Difficult hospital discharge; Flugelman index; Multidimensional assessment
• ISSN: 1877-9344; 1877-9352
• DOI: 10.4081/itjm.2011.103

Introduction: To evaluate the use of multidimensional assessment based on the Fluegelman Index (FI) to identify internal medicine patients who are likely to be difficult to discharge from the hospital. Materials and methods: Have been evaluated all patients admitted to the medical wards of the District General Hospital of Arezzo from September 1 to October 31, 2007. We collected data on age, sex, socioeconomic condition, cause of admission, comorbidity score preadmission functional status (Barthel Index), incontinence, feeding problems, length of hospitalization, condition at discharge, and type of discharge. The FI cut off for difficult discharge was > 17. Results: Of the 413 patients (mean age 80 + 11.37 years; percentage of women, 56.1%) included in the study, 109 (26.39%) had Flugelman Index > 17. These patients were significantly older than the patients with lower FIs (85 + 9.35 vs 78 + 11.58 years, p < 0.001), more likely to be admitted for pneumonia (22% vs. 4.9% of those with lower FIs; p < 0,001). They also had more comorbidity, loss of autonomy, cognitive impairment, social frailty, and nursing care needs. The subgroup with FIs>17 had significantly higher in-hospital mortality (30.28% vs 6.25%, p < 0.001), longer hospital stay (13 vs. 10 days, p < 0.05), and higher rates of discharge to nursing homes. Conclusions: Evaluation of internal medicine patients with the Flugelman Index may be helpful for identifying more critical patients likely to require longer hospitalization and to detect factors affecting the hospital stay. This information can be useful for more effective discharge planning.