scholarly journals Reducing the risk of healthcare-associated infections through Lean Six Sigma: The case of the medicine areas at the Federico II University Hospital in Naples (Italy)

2017 ◽  
Vol 24 (2) ◽  
pp. 338-346 ◽  
Author(s):  
Giovanni Improta ◽  
Mario Cesarelli ◽  
Paolo Montuori ◽  
Liberatina Carmela Santillo ◽  
Maria Triassi
2016 ◽  
Vol 23 (3) ◽  
pp. 530-539 ◽  
Author(s):  
Emma Montella ◽  
Maria Vincenza Di Cicco ◽  
Anna Ferraro ◽  
Piera Centobelli ◽  
Eliana Raiola ◽  
...  

Healthcare ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1667
Author(s):  
Giuseppe Cesarelli ◽  
Rita Petrelli ◽  
Carlo Ricciardi ◽  
Giovanni D’Addio ◽  
Orjela Monce ◽  
...  

The reduction of healthcare-associated infections (HAIs) is one of the most important issues in the healthcare context for every type of hospital. In three operational units of the Scientific Clinical Institutes Maugeri SpA SB, a rehabilitation hospital in Cassano delle Murge (Italy), some corrective measures were introduced in 2017 to reduce the occurrence of HAIs. Lean Six Sigma was used together with the Define, Measure, Analyze, Improve, Control (DMAIC) roadmap to analyze both the impact of such measures on HAIs and the length of hospital stay (LOS) in the Rehabilitative Cardiology, Rehabilitative Neurology, Functional Recovery and Rehabilitation units in the Medical Center for Intensive Rehabilitation. The data of 2415 patients were analyzed, considering the phases both before and after the introduction of the measures. The hospital experienced a LOS reduction in both patients with and without HAIs; in particular, Cardiology had the greatest reduction for patients with infections (−7 days). The overall decrease in HAIs in the hospital was 3.44%, going from 169 to 121 cases of infections. The noteworthy decrease in LOS implies an increase in admissions and in the turnover indicator of the hospital, which has a positive impact on the hospital management as well as on costs.


2021 ◽  
pp. 175717742110358
Author(s):  
Sailesh Kumar Shrestha ◽  
Swarup Shrestha ◽  
Sisham Ingnam

Information on the burden of healthcare-associated infections (HAIs) and patterns of antibiotic use are prerequisites for infection prevention and control (IPC) and antibiotics stewardship programmes. However, a few studies have been reported from resource-limited settings and many of them have not used standard definitions to diagnose HAI precluding benchmarking with regional or international data. This study aims to estimate the prevalence of HAIs and antibiotic use in our centre. We conducted a point prevalence survey in a 350-bed university hospital in Kathmandu, Nepal in April 2019. We reviewed all patients aged ⩾ 18 years admitted to the hospital for at least two calendar days and evaluated for the three common HAIs—pneumonia, urinary tract infection and surgical site infection. We used the clinical criteria by the European Center for Disease Prevention and Control to diagnose the HAIs. We also collected information on the antibiotics used. Of 160 eligible patients, 18 (11.25%) had HAIs and 114 (87.5%) were on antibiotics, with more than half of them (61/114 patients, 53.5%) receiving two or more antibiotics. This highlights the need for effective implementation of IPC as well as antibiotics stewardship programmes in our centre.


2019 ◽  
Vol 19 (1) ◽  
Author(s):  
F. Cyr Doscoph Afle ◽  
Alidéhou Jerrold Agbankpe ◽  
Roch Christian Johnson ◽  
Olivia Houngbégnon ◽  
Sègbè Christophe Houssou ◽  
...  

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
H Hannachi ◽  
A Ben Cheikh ◽  
S Bhiri ◽  
H Ghali ◽  
S Khefacha ◽  
...  

Abstract Introduction Healthcare -associated infections has become a worldwide public health problem. The aim of this study was to estimate the incidence of healthcare- associated infections in a university hospital of Tunisia. Methods This was a cohort study conducted in six intensive care units in a university hospital of Tunisia during three months (from august to October 2018). Data was provided from patients’ files. Data entry and analysis was done using SPSS version 22. Multivariate analysis was used in order to identify independent risk factors for healthcare associated infection. Results A total of 202 patients were enrolled in this study. The incidence rate of healthcare-associated infections was 53,96%(109/202). The ratio infection/infected was estimated to 1.65(109/66). The incidence of multi-drug resistant pathogens was 21,28% (43/202). The most common resistant pathogens included pseudomonas aeruginosa resistant to cefdazidime in 13,76%(15/109) followed by those resistant to extended spectrum cephalosporin 11.92% (13/109), followed by carbapenem-resistant acinetobcater baumanii 6,42%(7/109) then by carbapenem resistant pathogens and enterococcus resistant to vancomycin 2.75%(3/109) and finally staphylococcus aureus resistant to methicillin 2.1%(2/1.83). The multivariate analysis showed that long duration of central line catheterisation (RR = 7.44; 95%CI[2.79-19.82]), tracheotomy(RR = 8.61;95%CI[2.09-35,39]) and length of stay (RR = 1.08; 95%CI[1.04-1.13]) were found as independent risk factors for healthcare -associated infection. Conclusions The emergence of mutli-drug resistant pathogens needs to be deeply studied and effective measures have to be taken in order to detect and prevent transmission of resistant strains and/or their resistance determinants, especially those with phenotypes having the fewest viable treatment options. Key messages The incidence of healthcare associated infection in the intensive care unit was high. Effective measures have to be taken in the intensive care unit to detect and prevent transmission of resistant pathogens.


2020 ◽  
Vol 2020 ◽  
pp. 1-7 ◽  
Author(s):  
Moti Tolera ◽  
Dadi Marami ◽  
Degu Abate ◽  
Merga Dheresa

Background. Healthcare-associated infection is a major public health problem, in terms of mortality, morbidity, and costs. Majorities of the cause of these infections were preventable. Understanding the potential risk factors is important to reduce the impact of these avoidable infections. The study was aimed to identify factors associated with healthcare-associated infections among patients admitted at Hiwot Fana Specialized University Hospital, Harar, Eastern Ethiopia. Methods. A cross-sectional study was carried out among 433 patients over a period of five months at Hiwot Fana Specialized University Hospital. Sociodemographic and clinical data were obtained from a patient admitted for 48 hours and above in the four wards (surgical, medical, obstetrics/gynecology, and pediatrics) using a structured questionnaire. A multivariate logistic regression model was applied to identify predictors of healthcare-associated infections. A p value <0.05 was considered statistically significant. Results. Fifty-four (13.7%) patients had a history of a previous admission. The median length of hospital stay was 6.1 days. Forty-six (11.7%) participants reported comorbid conditions. Ninety-six (24.4%) participants underwent surgical procedures. The overall prevalence of healthcare-associated infection was 29 (7.4%, 95% CI: 5.2–10.6). Cigarette smoking (AOR: 5.18, 95% CI: 2.15–20.47), staying in the hospital for more than 4 days (AOR: 4.29, 95% CI: 2.31–6.15), and undergoing invasive procedures (AOR: 3.58, 95% CI: 1.11–7.52) increase the odds of acquiring healthcare-associated infections. Conclusion. The cumulative prevalence of healthcare-associated infections in this study was comparable with similar studies conducted in developing countries. Cigarette smoking, staying in the hospital for more than 4 days, and undergoing invasive procedures increase the odds of healthcare-associated infections. These factors should be considered in the infection prevention and control program of the hospital.


2016 ◽  
Vol 10 (11) ◽  
pp. 1250-1257 ◽  
Author(s):  
Elham AM El-Feky ◽  
Doa’a A Saleh ◽  
Jehan El-Kholy ◽  
Ahmed Mahmoud Sayed ◽  
Yasmeen Mansi ◽  
...  

Introduction: Personal digital assistants (PDAs) used in electronic laboratory-based surveillance are a promising alternative to conventional surveillance to detect healthcare-associated infections (HAIs). The aim of the study was to monitor, detect, and analyze HAIs using PDAs in a neonatal intensive care unit (NICU). Methodology: In this descriptive study, 1,053 neonates admitted to the NICU in the obstetrics and gynecology ward at the Cairo University hospital were included and evaluated for HAIs by collecting data using PDAs programmed by Naval Medical Research Unit 3, Cairo, with the definitions for HAIs provided by the National Healthcare Safety Network of the Centers for Disease Control and Prevention. Case records were reviewed three times a week over 19 months, from March 2012 to September 2013. Results: Of 124 suspected episodes of infection recorded in PDAs, 89 confirmed episodes of infection were identified. HAI and NICU infection rates were 7.4 and 2.72/1,000 patient-days, respectively. Primary bloodstream infection was detected in 81 episodes and pneumonia in 8 episodes. The majority of infections (62%) were acquired in the ward before NICU admission. Klebsiella spp. was isolated most frequently (42%), followed by coagulase-negative Staphylococci (31%). Conclusions: This study is the first to report the use of PDAs in surveillance to detect HAIs in the NICU in our hospital. The majority of infections were acquired at the obstetric care department, indicating the importance of implementing rigorous prevention and control programs and a more detailed surveillance to identify other risk factors for infections.


2006 ◽  
Vol 11 (1) ◽  
pp. 13-14 ◽  
Author(s):  
C Cuny ◽  
J Kuemmerle ◽  
C Stanek ◽  
B Willey ◽  
B Strommenger ◽  
...  

Methicillin-resistant Staphylococcus aureus has become an emerging public health problem worldwide, no longer only associated with healthcare-associated infections. With the exception of some recent reports concerning infections in cats, dogs and horses, infections with MRSA in companion animals have been infrequently reported. Here we submit findings for MRSA infections in horses in a central European university hospital.


Author(s):  
Mohamed Mahjoub ◽  
Nebiha Bouafia ◽  
Waadia Bannour ◽  
Tasnim Masmoudi ◽  
Rym Bouriga ◽  
...  

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