ANTIBIOTIC USE IN SLOVENIAN HOSPITALS

Abstract: Motivation/Background: Antibiotics are commonly overused and misused what increase the emergence of resistant organisms, sideeffects and costs. To assess the appropriate use of antibiotics many methods are available. The aim of the present study is to find correlation between antibiotic use and case mix index (CMI) in Slovenian hospitals. Method: In retrospective study (in the years between 2004 and 2013) we correlated the total consumption of antibiotics for systemic use and CMI. Weighted linear regression test analysis was performed to determine correlation between defined daily dose (DDD) / 100 admissions and DDD / 100 bed-days and CMI. Results: The total antibiotic consumption in all included hospitals was in mean 317.69 DDD / 100 admissions and 58.88 DDD / 100 bed days, respectively. CMI range were from 1.25 to 3.55. A significant correlation between consumption expressed in DDD / 100 admissions and CMI (p = 0.028) and DDD / 100 bed days and CMI (p =0.008) was found. Conclusions: Thus, detailed analysis of correlations between DDD of antibiotics and CMI may constitutes a proper use of antibiotics. Motivation/Background: Antibiotics are commonly overused and misused what increase the emergence of resistant organisms, sideeffects and costs. To assess the appropriate use of antibiotics many methods are available. The aim of the present study is to find correlation between antibiotic use and case mix index (CMI) in Slovenian hospitals. Method: In retrospective study (in the years between 2004 and 2013) we correlated the total consumption of antibiotics for systemic use and CMI. Weighted linear regression test analysis was performed to determine correlation between defined daily dose (DDD) / 100 admissions and DDD / 100 bed-days and CMI. Results: The total antibiotic consumption in all included hospitals was in mean 317.69 DDD / 100 admissions and 58.88 DDD / 100 bed days, respectively. CMI range were from 1.25 to 3.55. A significant correlation between consumption expressed in DDD / 100 admissions and CMI (p = 0.028) and DDD / 100 bed days and CMI (p =0.008) was found. Conclusions: Thus, detailed analysis of correlations between DDD of antibiotics and CMI may constitutes a proper use of antibiotics.


Introduction
Antibiotics are commonly used in hospitalized patients (range 19-59%) (1). Large variations in total and pattern of use have been found between countries and between hospitals in the country (2,3). The most common infection types are respiratory tract (24 %), skin bone, and joint (18 %), intra-abdominal organs (16 %), urinary tract (11 %) (1,(4)(5)(6). Antibiotics are commonly overused and misused what increase the emergence of resistant organisms, side-effects and costs. To assess the appropriate use of antibiotics many methods are available. The most accurate is patient-level surveillance what is time consuming and limited to a small number of patients (7). Point prevalence study survey is useful tool to judge the appropriateness of antibiotic use (8). The case mix index (CMI) is an economic surrogate marker (i.e. the total cost weights of all inpatients per a defined time period divided by the number of admissions) to describe the average patients' morbidity of individual hospitals (9). In the first study in 2008, Kuster et al. proved methodology and strong significant correlation between defined daily dose (DDD) of antibiotics / 100 admissions and DDD / 100 bed-days and CMI in Canton Zurich, Switzerland hospitals (9). Our study is the first such survey in Slovenia. The aim of the present study is to find correlation between antibiotic use and CMI in 12 Slovenian hospitals including two University hospitals and ten general hospitals.

Participants
We performed a retrospective observational study of antibiotic use and CMI in two University Medical Centres, Ljubljana and Maribor and another 10 acute care hospitals, a state in Slovenia, during the study period between 2004 to 2013.
The study included all patients hospitalized in 12 Slovenian hospitals from 2003 to 2014 illnesses by infectious diseases. Patients have been registered in the national statistical collections, which will be presented below, patient information is anonymous.

Methods
Number of admissions and number of bed-days of infectious diseases were calculated from electronic health information system of hospital care (ZISBO) of the National Institute of Public Health (NIPH) (13) of each patient hospitalized for ≥ 24 hours in the same hospital unit counting the days of admission and discharge together as one bed-day. For the all studied hospitals, aggregate hospital antibiotic consumption data defined daily dose (DDD) were collected from the hospital pharmacies and entered into a Microsoft Office Excel 2010 database. The 2014 version (group J01 (Antibacterial for system use*)) of the ATC Index with DDDs was used. DDD per 100 admissions and DDD per 100 bed-days were calculated for each hospital. CMIs for patient hospitalized in these defined patient care areas were calculated for the studied years (between 2004 and 2013), using data provided by the Database of hospital treatments of the same type based on cost weights for each patient (14,15). Diagnoses were coded with ICD-10 WHO version 1.3. Table  1 presents the list of infectious diseases that we have included in the analysis. Chosen diagnoses were recommended by the Center for Disease Control and Prevention, Atlanta, USA (16).
The University Medical Centre Ljubljana and University Medical Centre Maribor are tertiary and secondary care hospitals. Other ten hospitals (GH Nova Gorica, GH Brežice, GH Novo mesto, GH Celje, GH Izola, GH Jesenice, GH Ptuj, GH Murska Sobota, GH Trbovlje and GH Slovenj Gradec) are secondary type hospitals The CMI equals the sum of the total cost weights of all inpatients per a defined time period divided by a number of admissions (9). In Slovenia cost weight are regularly recalculated in the databases Groups of applicable cases (in Slovenian language short (skupine primerljivih primerov SPP). IBM SPSS Statistics for Windows, Version 21.0 was used for analysis. Weighted linear regression test analysis was performed to determine correlation between antibiotic use and CMI. A p value ≤ 0.05 was considered statistically significant.

Antibiotic Consumption
Antibiotic consumption data are listed in Table 2 Table 3

Correlation Between CMI and Antibiotic Use at The Hospitals
The correlation between antibiotic use and CMI is shown in Figure 1 and Figure 2. Weighted linear regression test analysis was performed to determine correlation between DDD/ 100 admissions and DDD / 100 bed-days and CMI in 10 GHs and two University hospitals from 2004 to 2013. A significant correlation between consumption expressed in DDD / 100 admissions and CMI (R 2 =0,018, R = 0.135, p = 0.028) and DDD / 100 bed days and CMI (R 2 = 0,027, R = 0.163, p =0.008) was found.

DDD / 100 Admissions and DDD / 100 Bed-Days and CMI For Certain Antibiotics Most Commonly Prescribed in Slovenian Hospitals for Each Year from The Years 2004 To 2013
DDD / 100 admissions and DDD / 100 bed-days were calculated for certain antibiotics, such as amoxiclav, moxifloxacin, azithromycin, cefuroxim, cefotaxim, antistaphylococcal penicillies, ciprofloxacin, aminoglycoside antibacterials and metronidayole i.v. for each year from 2004 to 2013. Results are shown in Table 5 and 6.     (19). Total consumption of antibiotics in Slovenia in GHs in comparison with other countries with more rational prescribing of antibiotics is higher than in Denmark and Sweden and a surprisingly lower than in the Netherlands in 2007 (20). In second Slovenian national healthcare-associated infections (HAIs) prevalence survey (SNHPS) was conducted in acute-care hospitals in 2011. The objective was to assess the sensitivity and specificity of the method used for the ascertainment of six types of HAIs (bloodstream infections, catheter-associated infections, lower respiratory tract infections, and urinary tract infections) in the University Medical Centre Ljubljana. The overall sensitivity of SNPHS collection method for ascertaining HAIs overall was high and the specificity was very high (21). In the second Slovenian national HAIs prevalence survey, conducted within European point prevalence survey of HAIs and antimicrobial use in acute care hospitals, they estimated the prevalence of all types of HAIs and identified risk factors. They found that the prevalence of HAIs in Slovenian acute care hospitals in 2011 was substantial, especially in ICUs. HAIs prevention and control is an important public health priority (22).
Data on the correlation of cost indicators and antibiotic use are limited in the current literature. Our study is the first such survey in Slovenia. We found a statistical significant correlation between antibiotic use and CMI when analysing data of Slovenian hospitals from 2004 to 2013. Correlation was strong significant (p = 0.028 and p = 0.008, respectively). We demonstrate differences between CMI and antibiotic use in 12 studied hospitals and results are comparable with the studies. Kuster at all. presented the first study to evaluate such a correlation between CMI and antibiotic use within a single institution and across various acute care hospitals. Antibiotic use varied substantially between different departments of the University hospital and between primary and secondary care hospitals. Kunster et all. recommended antibiotic use within and across hospitals, adjustment for CMI as a useful tool in order to take into account the differences in hospital category and patients' morbidities (9). Polk et all. shows of 1 791 180 discharged adults, 63.7% received antibacterial drugs. Mean ± SD hospital-wide use was 839 ± 106 days of therapy's (DOTs) (range, 594-1109) and 536 ± 53.0 length of therapy (LOT) (range, 427-684) per 1000 patient-days. Differences between expected and observed use reflect usage patterns that were benchmarked and are targets for evaluation and intervention (23). In 2008, the Slovenian hospitals most commonly