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BACKGROUND Early warning scores based on simple physiological variables were originally derived to recognize the impending patients’ clinical deterioration and to prevent in-hospital deaths. However, they can also be used to allocate patients on admission. The hypothesis of a previously validated model, the Modified Early Warning Score (MEWS) was tested. It could be used as a stratifying tool to identify medical patients whose baseline physiological measures predict a worse outcome, in order to assign them to an appropriate care level (e.g., High Dependence Units, special areas etc.).  METHODS We considered all patients admitted to Internal Medicine wards over a week period, without any exclusion criteria. On admission, we calculated the MEWS and a 28-variables original Dependence Index (DI). The main outcomes of the study were: in-hospital mortality and a composite of mortality and admission to a higher care level (namely, transfer to ICU, Coronary Care Unit, CCU, or Emergency Medicine). A secondary end-point was the length of stay for discharged patients.  RESULTS 22 Internal Medicine wards participated in the study. 597 patients were admitted, 329 females (55.4%; 95% CI 51.3-59.4) and 265 males (44.6%; 95% CI 40.6-48.7; female to male ratio was 1.24; p < 0.05). Women were older (mean age 76.2 years) than men (73.3 years); a large proportion of patients (509/597 or the 85.2%) were 65 or older. 522 patients were discharged, 44 died and 31 were transferred. The MEWS on admission predicted both death (Chi2 for trend 59.391, p < 0.00001) and the death and transfer composite end-point (Chi2 for trend 55.339; p < 0.00001); the DI worked well, too (risk of death, Chi2 for trend 53.052; p < 0.00001; risk of death or transfer, Chi2 for trend 66.030; p < 0.00001). These results were not influenced by either the wards dimensions or the hospitals complexity.  CONCLUSIONS In this multicentric study we have confirmed that the MEWS, even when calculated once on admission, is a simple but highly useful tool to predict a worse in-hospital outcome

The allocation of patients in an intensity-of-care based Internal Medicine ward: the ADOIT Tri-Co (Triage in the Corridor) study