Magister Curationis - MCur / Infections (including healthcare-associated infections) are one of the leading causes of neonatal morbidity and mortality, yet these deaths could be prevented by cost-effective interventions. Handwashing (HW) is crucial to preventing the spread of antimicrobial resistance and reducing healthcare-associated infections (HCAIs). However, healthcare workers' compliance with optimal practices remains low in most settings.The purpose of this study was to determine the compliance with HW among nurses and midwives caring for newborn babies at Rwamagana Health Facilities, and the extent to which demographic and cognitive characteristics predict nurses' HW compliance. The study’s methodology involved a cross-sectional approach encompassing descriptive and quantitative methods. The data was collected over a period of 3 weeks from a total sample of 139 nursemidwives. An anonymous self-administered questionnaire was used to collect data; out of 139 questionnaires distributed 134 were returned back completed, giving a rate of 96.4%. The data analysis was done using SPSS software version 21.The results demonstrate that a mean self-reported HW compliance rate was 82.00% (SD= 13.60). A compliance rate of 80% or greater was confirmed by most of the participants in the study (79.1%). The highest reported rate of hand washing was HW after exposure to the newborn's body fluids (M= 89.33%; SD= 14.878),while results revealed that nurses tend to perform less HW after touching an object in the vicinity of the patient(73.43%; SD=22.81). A multiple regression analysis revealed that attitudes, subjective norms and intentions were unique independent predictors of HW compliance. However, results did not show any relationship between HW and nurses' demographic characteristics.This study recommends that, strategies aiming to improve HW compliance must be focused on concepts that predict HW. Further research ought to be conducted using observational approach.

Clostridium difficile infection (CDI) is the leading cause of bacterial infectious diarrhea in nosocomial settings and approximately 25% of patients with CDI experience disease recurrence. Prior CDI epidemiological investigations are limited though. They do not reflect the burden of CDI in federal facilities, nor do they capture recent estimates on patient health outcomes. Furthermore, few studies have integrated CDI recurrence risk factors into a tool that clinicians can use to identify patients at risk for CDI recurrence. This study 1) described the epidemiology of CDI in the national Veterans Health Administration (VHA), 2) derived and validated a clinical prediction rule for 60-day CDI first recurrence, and 3) derived and validated a clinical prediction rule for 60-day CDI second recurrence. This was a retrospective cohort study of VHA beneficiaries with CDI between October 1, 2001 and September 30, 2012. VHA clinical and pharmacy data were integrated to develop several independent variables, including patient baseline demographics, CDI characteristics, comorbidities, concomitant medications, prior medications, prior hospitalization, hospital length of stay (LOS), and CDI severity. The dependent variables included 30/60/90-day mortality, and 30/60/90-day CDI recurrence. CDI incidence and outcomes were presented descriptively and compared using generalized linear regression models. CDI recurrence prediction rules were derived using multivariable logistic regression models and validated using the area under the receiver-operating-characteristic curve (AUROC), sensitivity, specificity, positive predictive value, and negative predictive value. Our study demonstrated that CDI first episodes, recurrences, and severity increased over the study period, while mortality decreased. Our CDI first recurrence prediction rule included the following predictor variables: dyslipidemia, CDI type, renal disease, hospital LOS <7 days, principal CDI diagnosis, concomitant gastric acid suppressors, and concomitant antibiotics. This model demonstrated moderate 60-day first recurrence discrimination (AUROC=0.62). Our CDI second recurrence prediction rule was similar in predictor variables and validity. In conclusion, CDI is an important, rapidly-emerging public health problem in the VHA. A clinical prediction rule might aid clinicians in directing preventative therapies to patients at high risk for CDI recurrence. / text

Healthcare-associated infections occur commonly in hospitals and have a major impact on patient well-being. The occurrence of the healthcare-associated infection, Clostridium difficile, has been occurring more frequently among hospitalized patients due to an epidemic strain, and is an important cause of antibiotic-associated diarrhea and colitis. This study examined the impact of several organizational factors on the occurrence of C. difficile infection (CDI) in hospitals using an institutional theory perspective. Administrative claims were utilized from University HealthSystem Consortium hospitals to obtain hospital-level data for the calendar year 2011. Data were available for 89 hospitals. Hospital-level analyses, negative binomial regression models, were conducted to test eight developed hypotheses and the associations between organizational factors and the incidence of CDI in hospitals. Cases of CDI were risk-adjusted for known factors associated with CDI. After controlling for factors known to be associated with CDI, the results of the analyses showed that one study hypothesis was supported. That is, hospitals with higher Leapfrog Group Safety Scores had CDI rates that were no different than hospitals with lower Safety Scores. Further, it was found that U.S. News and World Report Best Hospital Honor Roll member hospitals had significantly higher occurrence of CDI as compared to non-Honor Roll member hospitals, though it was predicted that there would be no difference in CDI rates. The organizational factors state-led CDI prevention collaboratives, state mandatory CDI reporting, Magnet status, the rate of central line-associated bloodstream infections and catheter-associated urinary tract infections, and CDI physician champions, were not significantly associated with CDI occurrence.

Healthcare-associated infections is the most common healthcare related injury and affect almost every tenth patient. With the purpose of reducing these infections Infektionsverktyget, The Anti-Infection Tool, was developed for registration and feedback of infection data. The tool is now used in all Swedish county councils resulting in a wealth of data. The purpose of this thesis was thus to investigate how data mining can be applied to describe patterns in this data and predict patient outcomes regarding healthcare-associated infections that need to be treated with antibiotics. Data mining was performed with Microsoft SQL Server 2008 in which models based on six different data mining algorithms with different parameter settings were developed. They used the attributes gender, age and previous diagnoses and medical actions as inputs and antibiotic treated healthcare-associated infection outcome as output. The predictive performance of the models was evaluated using 5-fold cross validation and macro averaged measures of recall, precision and F-measure. Patterns generated by selected models were extracted. Models based on the Naive Bayes algorithm showed the highest predictive capabilities with respect to recall and models based on the Decision Trees algorithm with low pruning had the highest precision. Although, none were considered to perform sufficiently well and several areas of improvement were identified. The most important factor in the inadequate performance is believed to be the relatively rare occurrences of infections in the dataset. Extracted patterns based on the Association Rules algorithm were considered the easiest to interpret. Patterns included clinically valid and invalid as well as trivial relationships. Future studies should be focused on further model improvements and gathering of more patient data. The idea is that data mining in Infektionsverktyget in the future could be used both to provide ideas for further medical research and to identify risk patients and prevent healthcare-associated infections in daily clinical work. / Vårdrelaterade infektioner är den vanligaste vårdskadan och drabbar nästan var tionde patient. Med syfte att minska antalet vårdrelaterade infektioner utvecklades Infektionsverktyget för registrering och återkoppling av infektionsdata. Verktyget används nu i alla Sveriges landsting vilket resulterar i stora mängder data. Syftet med detta examensarbete var därför att undersöka hur data mining kan användas för att beskriva mönster i denna data och för att förutsäga om patienter kommer att drabbas av en vårdrelaterad infektion som behöver antibiotikabehandlas. Data mining genomfördes med Microsoft SQL Server 2008 där modeller baserade på sex olika data mining-algoritmer med olika parameterinställningar utvecklades. De hade inputattributen kön, ålder och tidigare diagnoser och medicinska åtgärder, och outputattributet utfall av antibiotikabehandlad vårdrelaterad infektion. Förutsägelseförmågan hos modellerna utvärderades med 5-delad korsvalidering och makrogenomsnitt av måtten recall, precision och F-measure. Fyra modeller användes även för att ta fram mönster ur datamängden. Modeller baserade på Naive Bayes-algoritmen hade den bästa förutsägelseförmågan med avseende på recall och modeller baserade på Decision Trees-algoritmen med en låg beskärningsnivå uppnådde bäst precision. Trots detta ansågs ingen av modellerna prestera tillräckligt bra och flera möjliga förbättringsområden hittades. Den viktigaste anledningen till den otillräckliga förutsägelseförmågan tros vara att infektioner är relativt ovanliga i datamängden. Mönster som tagits fram med Association Rules-algoritmen ansågs vara lättast att tolka. Mönstren innehöll både kliniskt relevanta och irrelevanta såväl som triviala samband. Framtida studier bör fokuseras på att förbättra modellerna ytterligare och att samla in mer patientdata. Idén är att data mining i Infektionsverktyget i framtiden skulle kunna användas för att ge uppslag till medicinsk forskning och för att identifiera riskpatienter och därmed förebygga vårdrelaterade infektioner i den dagliga kliniska verksamheten.

Bakgrund: Vårdrelaterade infektioner (VRI) ses som en av de främsta vårdskadorna i världen och beskrivs ge ett enormt lidande för patienten. Basala hygienrutiner började utvecklas redan på 1800-talet och är idag den huvudsakliga åtgärden för att minska VRI. Sjuksköterskor och övrig vårdpersonal har en skyldighet att följa lagar, författningar och riktlinjer så att omvårdnaden av patienter blir patientsäker. Syfte: Var att undersöka vårdpersonalens följsamhet till basala hygienrutiner. Metod: En kvantitativ retrospektiv longitudinell studie som byggde på observationer av vårdpersonal samt punkprevalensmätningar av VRI. Resultat: Det sågs en högre följsamhet till basala hygienrutiner hos vårdpersonalen på medicinkliniken. Medicinkliniken hade även en signifikant förbättring av följsamhet till basala hygienrutiner. Båda klinikerna hade en lägre följsamhet till desinfektion av händer före en patientkontakt än efteråt. Studerande hade högre följsamhet än sjuksköterskor och läkare. Medicinkliniken hade som mest 5 (n=43; 11,6%) patienter med en VRI och kirurgkliniken hade som mest 9 (n=63; 14,3%) patienter. Diskussion: Tidigare forskning visar att det är lägre följsamhet till desinfektion av händer före en patientkontakt än efteråt, något som även setts i resultatet. Tidigare forskning tar även upp möjliga orsaker till en låg följsamhet samt verktyg för att skapa en högre följsamhet till basala hygienrutiner / Background: Healthcare-associated infections (HAI) are one of the leading health damage in the world and described provides immense suffering to the patient. Basic hygiene began to develop early in the 1800s and is today the main arrangements for reducing HAI. Nurses and other health care workers has an obligation to comply with laws, regulations and guidelines so that the care of patients become safe. Objective: To investigate the health care workers’ adherence to basic hygiene routines. Method: A quantitative retrospective longitudinal study based on observations of health care workers and point prevalence surveys of HAI. Results: Showed a higher adherence to basic hygiene among health professionals in the medical clinic. Medical clinic had a significant improvement in adherence to basic hygiene. Both clinics had a lower adherence to hand disinfection before a patient contact than afterwards. Students had higher adherence than nurses and doctors. Medical clinic had at most 5 (n = 43, 11.6%) patients with a HAI and surgery clinic had at most 9 (n = 63, 14.3%) patients. Discussion: Past research shows that there is less adherence to hand disinfection before a patient contact then afterwards, which is also shown in the result. Previous research also mentions possible causes of a low adherence and tool to create a higher adherence to basic hygiene.

Low hand hygiene compliance among health staff is a problem globally in health care settings. Improving hand hygiene could prevent many of the health care associated infections that affects hundreds of millions of patients every year around the globe. The aim of this literature study was to describe obstacles to maintain proper hand hygiene in hospitals, seen from a global perspective. Eight articles from seven countries, all based on qualitative research have been analysed according to Friberg's five-step method that contributes to evidence-based nursing. The challenges to sustain hand hygiene found in the results were split into two main categories: Organizational factors and Individual factors. Organizational factors included five subcategories: Work environment, Inadequate education, Infrastructure, Insufficient management and Power structures. The results showed that when these factors were negatively affected so was compliance regarding proper hand hygiene. These were often issuesthat the health staff felt powerless to change and affect. Individual factors included two subcategories: Attitudes and social factors. Example of this could be healthcare workers neglected hygiene guidelines out of personal reasons or healthcare workers giving care to patients that didn’t accept how it was carried out because of social and cultural differences. The complex issues revolving these matters need to be addressed on an overall perspective. Cooperation between management and health staff is fundamental to obtain changes within healthcare organizations. Both parties need to work together to be able to improve hand hygiene compliance and to reduce healthcare associated infections.

Orientador: Carlos Magno Castelo Branco Fortaleza / Resumo: Estudos anteriores do nosso grupo reforçaram a evidência recente e inesperada de sazonalidade e determinação meteorológica na incidência das Infecções Relacionadas à Assistência à Saúde (IRAS, anteriormente chamadas “Infecções Hospitalares”. No entanto, nenhuma pesquisa até o momento associou esses agravos à temperatura e umidade nos diversos setores de um hospital. Com o objetivo de preencher esse hiato no conhecimento sobre epidemiologia das IRAS, realizamos um estudo ecológico baseado na avaliação de temperatura e umidade em áreas assistenciais. Resumidamente, oito termo-higrômetros foram afixados em diferentes unidades do Hospital das Clínicas da Faculdade de Medicina de Botucatu, e dois outros foram utilizados de forma móvel para os demais setores de internação desse mesmo hospital. Os resultados obtidos serão comparados com: (a) dados informados por estação meteorológica no município de Botucatu; (b) indicadores de incidência de IRAS; (c) Indicadores de incidência de microrganismos multidroga-resistentes. O estudo teve duração de 12 meses. A análise estatística envolveu modelos multivariados de regressão de Poisson e Regressão Logística. Os resultados demonstraram que, apesar de haver diferença significativa, temperatura e umidade no interior do hospital (mesmo em áreas climatizadas) variam em associação estatisticamente significante com os parâmetros medidos em estação meteorológica. Apesar do pouco tempo de observação, foi possível constatar associação entre temperatu... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Previous studies by our group have reinforced recent and unexpected evidence of seasonality and meteorological determination in the incidence of Healthcare-Associated Infections (HAI’s, formerly called “Nosocomial infections.") However, no research to date has associated these conditions with temperature and humidity. In order to fill this gap in the knowledge on HAI epidemiology, we carried out an ecological study based on the evaluation of temperature and humidity in care areas. In summary, eight thermohygrometers were posted in different units of the teaching hospital of Botucatu Medical School (“Hospital das Clínicas da Faculdade de Medicina de Botucatu”). The results obtained would be compared with: (a) data reported by meteorological station in the city of Botucatu, (b) incidence of HAI; (c) incidence of multidrug-resistant microorganisms. The study lasted 12 months. Statistical analysis involved multivariate Poisson regression and logistic regression models. The results showed that, although there is a significant difference, temperature and humidity inside the hospital (even in climatized areas) vary in a statistically significant association with the parameters measured in meteorological station. Despite the short observation period, it was possible to verify the association between temperature and HAI (including multidrug-resistant microorganisms) in the Intensive Care Unit (ICU), wards for non-critically ill patients and Surgical Theater. Taken together, our findin... (Complete abstract click electronic access below) / Mestre

My original contribution to knowledge is the emergence of an inductively derived conceptual framework that provides a generic account of the way in which people construct and communicate risk. Within this framework, a detailed contextual understanding of how this was applied to C.difficile is developed. Furthermore, in seeking to place responses to health risks in the wider social, cultural and political context, moving beyond a standard critique of media output, an understanding of both how and why the media report health-related risks helped identify ways in which the media can influence how people can construct and communicate about risks. The incidence and severity of C.difficile infection is increasing and it is one of the most common healthcare associated infections, posing a global threat to public health. With the occurrence of major outbreaks within the UK and elsewhere, fear, confusion and unsafe infection prevention and control practices continue to exist among the public and healthcare professionals. Consequently, C.difficile is of particular interest to the media, being the focus of much media reporting. How the public perceive and respond to a health-related risk is shaped by a range of socially and contextually structured evaluations and interpretations, based on a range of factors such as availability heuristics, direct and indirect experiences and social influences, particularly those emanating from the media. Expert risk perceptions and responses on the other hand, are sometimes supposed to be more veridical than those of the public because they are based on calculations of scientific probabilities. Risk perceptions and responses however are context dependent and therefore to be understood, need to be considered within the context that they are perceived and experienced. There is currently little risk perception empirical research to draw upon within the context of C.difficile. The aim of this study was to explore risk perceptions and responses of the public and healthcare professionals within the context of C.difficile and to examine the role of the media in health-related risk reporting. This qualitative study adopted three approaches to data collection: a media coverage analysis of a major C.difficile outbreak, focus groups with the public and healthcare professionals in two geographical areas (an outbreak versus a non-outbreak area), and in-depth, semi-structured interviews with media professionals. The media coverage analysis found that the media portrayed key individuals involved in the outbreak as victims, villains and heroes. These ‘characters’ evolved as the outbreak progressed and new information became available. Such representations were frequently used as a backdrop for the public and healthcare professionals in order to support or refute their perceptions about C.difficile. For the public and healthcare professionals, the consequence of C.difficile and why it occurred was much more salient than estimations of the probability or likelihood of it occurring. Conceptual factors that were found to be important in influencing perceptions included: feelings of vulnerability; attribution of responsibility; judgements about competence; and evaluations of risk communicators. Media professionals were seen as important risk communicators in the focus groups, however they saw themselves as predominantly story tellers and entertainers, rather than ‘educators’. They also believed themselves to be advocates for the public whereby they uncover information that officialdom would seek to keep hidden. What emerged from this study was a coherent, structured and generic account of how various stakeholders construct and communicate about risk. Within this conceptual structuring, a detailed contextual understanding of how this was applied by the public and healthcare professionals around C.difficile was gained. Findings indicate that uncertainty, fear and confusion about C.difficile exist that appear to be influenced by a range of contextual factors such as indirect and direct experiences, social interaction and the media. If risk management and communication strategies are to influence the desired and effective responses towards C.difficile and wider health-related risks, those responsible for managing and communicating risk must consider already established risk perceptions in addition to the factors that have influenced such risk perceptions.

Healthcare-associated infections (HAI) are a significant issue in healthcare facilities worldwide. Hand hygiene (HH) remains the most effective method for preventing the incidence of HAI in routine patient care. Past and current interventions focused on the overall improvement of HH compliance, but studies found that the amount of time required to achieve full HH compliance with the existing guidelines may not be practical. Improving HH compliance at critical moments during patient care may be more effective than improving HH compliance at all opportunities. However, there are little to no studies on healthcare workers’ (HCWs) behavior regarding HH during the patient care process. Secondary data analysis on a prospective dataset from the STAR-ICU trial was completed to identify HCWs’ behavior patterns regarding HH during the patient care process. Multiple logistic regression for transitions with random effects using repeated measures and transition modeling was used to identify possible associations between HH compliance and patient care tasks, the order of tasks, and workload. The models adjusted for the effects of HCW type, glove use, and isolation precautions. The study identified 28,826 task sequences and 42,349 HH opportunities. HCWs were slightly less likely to do HH before critical tasks compared with other tasks (OR: 0.97, 95% CI: 0.96-0.99), but more likely to do HH after contaminating tasks compared with other tasks (OR: 1.12, 95% CI: 1.10-1.13). HCWs are also more likely to move from task sequences that have a relatively lower risk to patients to task sequences that have a relatively higher risk to patients than vice versa (65.4% versus 34.7%). HCWs are also less likely to do HH after moving from tasks that have a relatively lower risk to patients to tasks that have a relatively higher risk to patients than vice versa (OR: 0.93, 95% CI:0.92-0.95). HCWs’ HH compliance rates decreased as the workload level increased (OR: 0.93, 95% CI: 0.89-0.98). Workload did not appear to affect HH compliance before critical tasks or after contaminating tasks and did not affect the order in which HCWs perform patient care tasks. Increase in workload was associated with an increase in the odds of critical tasks occurring (OR: 1.55, 95% CI: 1.45-1.65). In conclusion, HCWs are more likely to perform HH after contaminating tasks to prevent contaminating themselves and to reduce the risk of transmission in subsequent task sequences. However, they do not perform tasks in an order that minimizes risk to the patient; instead, it appears that they perform tasks as they come up in routine care. Furthermore, HH is not being performed at critical moments during patient care. Lastly, workload did not affect the order in which HCWs perform patient care tasks, suggesting that HCWs behavior patterns contribute significantly to how they care for patients and perform HH. Interventions targeting the order in which HCWs perform patient care tasks and improving HH compliance before critical tasks may be more effective than those designed to improve HH compliance at all HH opportunities for reducing HAI rates.

Objective: The primary objective of this study was to examine the relationship between hospital structural characteristics and penalization status (penalized or not penalized) in any given hospital acquired condition (HAC) Reduction Program year, FY 2015 through 2018. Structural characteristics included hospital type, case mix index, average daily census, bed size, ownership, disproportionate share percentage, location, and American Nurses Credentialing Center Magnet status. The secondary objective of the study was to determine whether a hospital's penalization status across one or more HAC Reduction Program years is related to quality performance (Total HAC Score) in subsequent years. These objectives were achieved through retrospective, longitudinal, multivariate regression analysis using 4 publicly available data sources. Background: The intention of pay-for-performance programs, including the Centers for Medicare and Medicaid HAC Reduction Program, is to improve the quality of care delivered; however, the theoretical and conceptual basis of pay-for-performance programs and their efficacy in improving care are widely debated. This study was designed to address the gap in knowledge related to the efficacy of value-based reimbursement as a means of motivating providers and organizations to improve healthcare quality. Results: Higher average daily census, disproportionate share percentage, and case mix index were associated with increased likelihood of receiving a penalty in the HAC Reduction Program. Approximately half (49%) of who did not experience a penalty at all improved their Total HAC Score. 51% of hospitals with 1 year of penalty improved their Total HAC Score; 54% of hospitals with 2 years of penalty improved their Total HAC Score; 73% of hospitals with 3 years of penalty improved their Total HAC Score. Conclusions: Despite the inability of some hospitals to meet the benchmark to avoid penalty, the vast majority of hospitals improved their performance over time. This finding holds promise for value-based reimbursement as a means for improving HAC incidence.