The €œNEW SETTLERS”: RESULTS OF a BACTERIOLOGICAL SURVEY DURING THE FIRST 6-Months OPERATION PERIOD OF AN INTERNAL MEDICINE WARD IN a TERTIARY HOSPITAL

Abstract

During the first six months of operating a new Internal-medicine ward in a tertiary hospital, a prospective survey, tracking both patient and environment bacteriological samples taken, was conducted. The motive behind the study was to establish the pattern in which environmental colonization is transmitted to the hospitalized patients and vice versa, thus defining the nosocomial pathogens that are typical to the ward. That information can be used to guide empirical antibiotic treatment. Patient sampling was done on clinical grounds whereas environmental cultures were systematically acquired from different surfaces around the ward. 6-months' results analysis suggest that clinically guided culture rates were tightly associated with volume of patients admitted, with no such association demonstrated between volume of cultures taken and rate of positive results, except for urine cultures. Regarding environmental sampling, we demonstrated no benefit in taking empirical, surface samples for common nosocomial pathogens. Our findings could further improve future resources allocation with regard to infection control and clinical bacteriology routines in newly established internal medicine wards.

Infectious disease during hospitalization is the major causative factor for prolonged hospitalization: multivariate analysis of diagnosis procedure combination (DPC) data of 20,876 cases in Japan

“…Aging and diabetes mellitus, which might exacerbate infectious diseases, were also risk factors for prolongation of hospitalization. Regulation and control of infectious diseases during hospitalization has been enforced by the infectious diseases control division in the hospital, ( 13 , 15 , 16 ) and the present study clearly demonstrated the importance of infectious disease control during hospitalization.…”

Selecting Perfect Interestingness Measures by Coefficient of Variation Based Ranking Algorithm

“…In statistical aspect, there are many association measures available to measure the dependency between the variables. Segal et al (2013) applied the association measures on their work. But all the association measures are not going to produce interestingness rules due to the over whelming of data and by existence of the redundant rules on mined patterns.…”