Problem Statement
Catheter-associated urinary tract infection (UTI) is among the common consequences of urinary catheter application in conditions of healthcare facilities all over the world. It is a proven fact that almost 70% of catheter-associated UTIs can be avoided or prevented (Saint et al., 2016). Thus, the researchers agree that there is a necessity to develop guidelines that could be implemented for the prevention of catheter-associated UTIs through specific recommendations about “appropriate use, aseptic insertion, proper maintenance, and timely removal of indwelling urinary catheters, as well as the use of established practices such as hand hygiene” (Saint et al., 2016, p. 2112).
The article under analysis presents the results of a national implementation project aimed at the prevention of catheter-associated urinary tract infection in nursing home residents (Mody et al., 2017). The problem which is studied in the research project is essential for contemporary health care. In the United States, over 1.4 million citizens live in different types of nursing homes, which are supposed to meet their short- and long-term needs (Mody et al., 2017). The statistics are that about 12% of females and 13% of male patients of nursing homes already have a urinary catheter on their admission (Mody at al., 2017).
According to the Centers for Disease Control and Prevention data (2018), about 20% of infections that develop in long-term care facilities in the United States are UTIs. Older adults who are the residents of nursing homes face more risk factors for the development of catheter-associated UTIs than other population groups, such as “age-related changes to the genitourinary tract, comorbid conditions resulting in the neurogenic bladder, and instrumentation required to manage bladder voiding” (Centers for Disease Control and Prevention, 2018, p. 1). Some previous investigations prove the existence of successful strategies that can reduce catheter-associated UTI, for example, with the application of nurse-directed catheter removal (Parry, Grant, & Sestovic, 2013). Consequently, the problem stated by Mody et al. (2017) is of great current interest in health care and a promising direction for further research.
Purpose of the Research Article
The purpose of the research article is to present the findings of the implementation project, which was conducted with the involvement of patients from the community-based nursing homes from 48 states. The major purpose of the project itself was to develop, implement into practice, and assess an intervention aimed at the reduction of catheter-associated UTI (Mody et al., 2017). Earlier research that preceded the project allowed studying the situation with catheter-associated UTI in nursing homes and prepare a research basis. The investigation conducted by the same team of researchers two years earlier outlined the principles and components of the UTI prevention initiative (Mody et al., 2015). The analyzed research article also provides answers to a question formulated by the researchers to be discovered in the course of the project implementation.
The question is “Can a multi-component initiative focusing on technical and socioadaptive interventions reduce catheter-associated urinary tract infection in nursing homes?” (Mody et al., 2017, p. 1155). These initiatives are important for advancements in older adults’ care. Rowe and Juthani-Mehta (2013) state that urinary tract infection is common for older adults in general and those residing in long-term care facilities such as nursing homes in particular.
Although the hypothesis is not clearly stated, it is evident from the context. The researchers aimed to investigate the outcomes of the interventions which constituted the project implemented during 12 months in nursing homes throughout the country. On the whole, the article is a valuable source of information that can be used by other researchers interested in the problem of catheter-associated UTI or diverse healthcare facilities including nursing homes to apply the obtained results in practice. Because UTI is a frequent cause of sepsis, admission to hospital and other negative outcomes, publication of proofs that the problem is preventable is important for healthcare. The article presents the results of the project implementation logically and thus follows its main purpose which was to implement and assess an intervention for the reduction of catheter-associated UTI.
Review of Literature
The issue of catheter-associated UTI is not new in medical research. Nicolle (2014) provides a detailed analysis of catheter-associated UTI and defines its major reasons and outcomes. The researcher states that the majority of UTI cases are the results of an indwelling urethral catheter use which is widely used in different healthcare facilities all over the world. For example, 17.5% of patients in 66 hospitals in Europe and 23.6% of patients in 183 American hospitals which were investigated, have a urethral catheter (Nicolle, 2014). Catheters can be short-term or long-term depending on the time they are used. In conditions of long-term care facilities, long-term catheters are usually applied.
Nicolle (2014) also states that bacteriuria which is acquired by many patients depends on the duration of catheterization. The author outlines such preventive strategies that can help to prevent UTI as “avoidance of catheter use, policies for catheter insertion and maintenance, catheter selection, surveillance of CA-UTI and catheter use, and recommendations for quality indicators” (Nicolle, 2014, p. 3). The researcher also provides strategies aimed at the prevention of catheter-associated UTI in long-term care facilities which include monitoring of residents with indwelling catheters to reveal infection at an early stage, minimize traumatization during catheter removal, and antimicrobial therapy for patients with bacteriuria. The article contributes to the understanding of the concept of UTI.
Prevention and treatment are the primary concerns of the researchers who investigate the issue of catheter-associated UTI. Tenke, Köves, and Johansen (2014) present the updated findings regarding prevention strategies and approaches to the treatment of catheter-associated UTI. The researchers state that catheter-associated UTI is a primary source of healthcare-acquired infections which results in significant morbidity and is cost-consuming. Tenke et al. (2014) provide the pathogenesis of catheter-associated bacteriuria and infection and present some effort that can be helpful for their prevention. For example, it is possible to apply reminder systems not to forget to take the catheter out, or “reducing biofilm formation using new catheter surface materials,” or antibiotic prophylaxis (Tenke et al., 2014, p. 103).
At the same time, catheter-associated UTIs can be prevented due to the use of catheters under antiseptic conditions, keeping the catheter system closed, avoidance of unnecessary catheterization, the introduction of programs to control infection, etc. Treatment of catheter-associated UTI usually includes antibiotics when there are evident symptoms. Tenke et al. (2014) conclude that despite the existing research and efforts to reduce and prevent catheter-associated UTI, they are still among the most frequent hospital-acquired conditions. This research stresses the necessity of implementing new strategies for the prevention of catheter-associated UTI.
Some investigations are dedicated to more specific populations. For example, D’Agata, Loeb, and Mitchell (2013) study the challenges which appear during the assessment of nursing home patients with advanced dementia for suspected UTIs. The researchers claim that diagnosing is more complicated due to the limited verbal ability of patients with dementia. This twelve-month prospective study involved 266 patients with dementia who reside in nursing homes. The authors conclude that these patients frequently do not demonstrate typical symptoms and signs which can be used to diagnose catheter-associated UTI and, as a result, they do not get the necessary treatment or, on the contrary, patients receive antimicrobial therapy without necessity (D’Agata et al., 2013). This study outlines opportunities for further research of UTI and other chronic health conditions that are likely to interfere with timely diagnosis and effective treatment.
The research by Rowe and Juthani-Mehta (2013) defines UTI as a common problem of older adults. Thus, it can be concluded that older age is a risk factor for UTI. The researchers claim that “age-associated changes in immune function, exposure to nosocomial pathogens and an increasing number of comorbidities put the elderly at an increased risk for developing infection” (Rowe & Juthani-Mehta, 2013, p. 520). Moreover, institutionalization and the presence of a urinary catheter are considered to be risk factors for UTI. Catheter-associated UTI is the third infection diagnosed in long-term care residents, and it makes up one-third of all infections that are associated with nursing homes. This investigation is another proof that catheter-associated UTI is a problem of older adults and that nursing homes as a research setting were a proper choice.
Some studies investigate the possible improvements in the reduction of catheter-associated UTI rates. Thus, Parry et al. (2013) suppose that the incidence of catheter-associated UTI can be cut down only by reducing the application of the urinary catheter. Their interventional study focused on the “nurse-directed urinary catheter removal protocol” (Parry et al., 2013, p. 1179). The evaluation of patients which lasted for 36 months showed that the use of indwelling urinary catheters decreased by 50.2%. Moreover, there were 103 infections recorded during the study compared to the expected 174 which were predicted based on the first-quarter results. However, this research lacks statistical significance due to the small number of symptomatic catheter-associated UTIs documented during the research.
A large-scale prospective implementation project is one of the recent and most detailed investigations of the prevention of catheter-associated UTIs among the residents of nursing homes. Mody et al. (2017) involved community-based nursing homes which are the participants of the Agency for Healthcare Research and Quality Safety Program for Long-Term Care. The interventions included in the project implementation comprised “catheter removal, aseptic insertion, using regular assessments, training for catheter care, and incontinence care planning, as well as a socioadaptive bundle emphasizing leadership, resident and family engagement, and effective communication” (Mody et al., 2017, p. 1154). As a result of this project implementation, the catheter-associated UTI rates were reduced by 54% after 12 months of interventions. Moreover, 75% of the participating facilities demonstrated a reduction of a minimum of 40% (Mody et al., 2017).
Also, the laboratories in nursing homes reported a decrease in the frequency of orders for urine culture tests, which proves the efficiency of stewardship in the sphere of laboratory diagnostics (Mody et al., 2017). The use of urinary catheters themselves did not decrease during the project implementation. This fact can be explained by the initial low rates of catheters used in the participating nursing homes. Although this research has a big sample, there are some limitations which do not allow generalizing its results. First of all, participation in the research was voluntary. Consequently, there is no opportunity to compare the results of the facilities included in the sample and those that were not included. Also, not all variables which could have statistical significance were evaluated.
Introduction
Power is a significant component of any research. In the context of a study, power is related to a probability of obtaining a significant result by a researcher in the conditions of the selected population. The question about this significant result comprises the use of the null hypothesis. Statistic power comprises sample size, effect size, and p-level (Murphy, Myors, & Wohach, 2014). The concepts of power, alpha, and sample size are interrelated. However, it is more likely that the sample size influences the research power. Thus, in case researchers want to increase the power of their study, they should involve a bigger sample to make it more representative. Nevertheless, the opposite effect is possible. High research power is expected to lead research to correct conclusions while power less than 0.50 has a great possibility of incorrect conclusions (Murphy et al., 2014). Thus, after researchers determine the desired power, they can define their sample. The higher is power and the lower is alpha, the bigger is the sample size.
Power Analysis
Power analysis follows a certain structure which is standard for many investigations. It can be conducted manually or with the use of the software. Some data are necessary to conduct a power analysis. The researchers define the desired confidence level (95 or 99%) and confidence interval. The sample is defined considering the selected confidence level and confidence interval. The higher is the confidence level and the smaller is a confidence interval, the bigger is the sample. Consequently, research power will increase with the growth of the sample. Statistic software allows selecting the sample size which will provide higher power and save time on calculations. Moreover, it considers both the lower and upper confidence levels.
Mody et al. (2017) do not provide power analysis in the article. Nevertheless, there is enough data to fulfill the power analysis for this research. According to the research data, the sample was selected among 16,039 nursing homes in the United States. The power analysis for this sample will be as follows. With the confidence level of 95% and confidence interval 5, the suitable sample size for the research is from 370 to 380 facilities. Consequently, it can be concluded that the sample of 404 nursing homes that provided data for analysis is representative and the obtained data are valid.
Power, Effect Size, Alpha
Effect size is defined as “quantitative reflection of the magnitude of some phenomenon that is used to address a question of interest” (Murphy et al., 2014, p. 31). It means that the researchers attempt to reveal the effect that their interventions have on the sample and evaluate this effect. Alpha usually deals with the significance level. In the context of the hypothesis test, alpha presents the possibility of Type I error occurrence.
Mody et al. (2017) do not include any specific information about power, effect size, or alpha for this study in the research article. Probably, this aspect is omitted due to the limited size of the paper and the necessity to present detailed information about the examination of the changes in caterer-associated UTI rates observed in the course of the investigation in the selected facilities. However, Mody et al. (2017) provide a sensitivity analysis, which examines “whether changes in catheter-associated UTI rates differed between nursing homes that did and those that did not complete data submission” (p. 1156). The discovered p-values are 2-sided. Also, p <.05 was considered to be statistically significant. Finally, the researcher mention that the statistical analyses in the study were performed with the help of Stata/MP software, version 13.1 (Mody et al., 2017).
Sample Planning
The national project presented in the research article under analysis was aimed at the reduction of catheter-associated UTIs in nursing homes (Mody et al., 2017). Its major purpose was to “modify the elements of the Comprehensive Unit-Based Safety Program utilized for the AHRQ Safety Program for Reducing Catheter-Associated UTI in Hospitals to launch an initiative to enhance adoption of infection prevention practices in nursing homes” (Mody et al., 2017, p. 1155). The interventions included in the project were both technical and socioadaptive. The project used a quantitative research methodology to evaluate its effectiveness.
Sample Procedure
The sample size is frequently a decisive factor for the research validity. It is directly controlled by a researcher. The sample size directly and strongly influences statistical power. It can be stated that statistical power increases with the growth of the sample. The sample for this project comprised nursing homes from 48 states, Washington, DC, and Puerto Rico. On the whole, there were five cohorts. The article presents the results obtained from the first five cohorts during the period from March 1, 2014, and August 31, 2016 (Mody et al., 2017). During the preparatory stage, 568 community-based nursing homes were recruited to participate in the implementation process. After 164 nursing homes withdrew from the project because of some reasons, 404 nursing homes managed to implement the interventions suggested by the project and provided the data which were included in the statistical analysis.
Population
Population for this project comprised the residents of nursing homes throughout the country. However, the exact number of people involved in the research is not indicated. The mean facility size in the project was 120.7 (SD 67.6), the p-value for this characteristic is <0.001 (Mody et al., 2017). There was more for-profit than nonprofit nursing homes (260 and 108 correspondently), and 19 of governmental ones.
Refusal Rate/Attrition Rate
568 community-based nursing homes were selected for the project implementation. 135 nursing homes withdrew at the initial stage. Later, 13 more nursing homes were excluded. 11 of them did not provide the outcome data and two submitted data into NHSN (Mody et al., 2017). Out of the remaining 420 nursing homes, 16 were excluded because they did not report outcome data for a minimum of two months, or had other problems with reports. Finally, data from 404 nursing homes were included in the analysis (Mody et al., 2017). Consequently, the attrition rate for this project was 33.7%.
Measurement Methods
The research used primary data which were obtained directly from the nursing homes participating in the implementation project. Quantitative methods were used for measurement. The major measurements were focused on catheter-associated UTI rates, catheter use, and urine culture orders to demonstrate the dynamics of change. A multilevel mixed-effects negative binomial regression is used for the data analysis. Statistical measurements used in the data analysis include an incidence rate ratio, confidence level, standard deviance, and p-value.
Validity of Measurement
No information about the validity of measurement is mentioned in the research article. Nevertheless, considering the careful approach to sample selection and focus on the regular character of the reports which became a basis for further statistical analysis, it can be concluded that measurement was valid. Catheter-associated UTI rates were measured per 1000 catheter days, which provides a valid picture of UTI rates changes as the result of project implementation.
Percentage Distribution
The percentage is used in the article to illustrate the sample composition and demonstrate the results of the implementation project. For example, the authors mention that 67.2% of nursing homes involved in the project were for-profit, and 56.3% of the facilities were a part of a chain (Mody et al., 2017). Describing changes in catheter-associated UTI rates and other results of the implemented interventions, the researchers claim that 75% of the participating nursing homes demonstrated at least 40% shortening of catheter-associated UTI rates (Mody et al., 2017).
Graphs
The research article under analysis uses some graphs to illustrate the analysis. There are two figures one of which demonstrates sample selection and the other presents catheter-associated UTI rates change during the project according to data provided by nursing homes. Also, two tables comprise information about the characteristics of the participating facilities and present multivariable regression estimates of changes in catheter-associated UTI rates. These graphs are useful visual tools that empower data presentation.
Central Tendency
The mean (also known as average) is used to measure the central tendency in this research project. It is a suitable measure for this study because it provides average data about the characteristics of the facilities involved in the project. Due to the big sample size, it is impossible to present profiles of all nursing homes in the article, and the mean allows for evaluating general characteristics.
Standard Deviation
The standard deviation (SD) was calculated for every characteristic of the participating facilities. For example, for the facility size, SD was estimated at 67.7 (Mody et al., 2017). For facility ownership type, SD was 67.2 in for-profit, 27.9 in nonprofit, and 4.9 in government facilities. Other characteristics with the estimated standard deviation are belonging to a chain of healthcare facilities, case-mix index, and a 5-star rating. However, these data are not very informative and overloads the article making it more complicated.
Implications for Future Study
The authors do not directly identify the implications for further research in the research article. Nevertheless, they believe that a similar approach grounded on the evidence-based framework can be applied in other investigations related to safety issues in community-based nursing homes. Moreover, further studies can address some of the study limitations. For example, another research involving a bigger sample could be conducted because the current analysis involved only the nursing homes which voluntarily agreed to participate and submitted the necessary data. Moreover, a comparative study dedicated to catheter-associated UTI in nursing homes and hospital units can be conducted. Still, it would be more valid in the case it is conducted in the form of randomized control trial.
References
Centers for Disease Control and Prevention. (2018). Urinary tract infection (UTI) event for long-term care facilities. Web.
D’Agata, E., Loeb, M., & Mitchell, S. (2013). Challenges in assessing nursing home residents with advanced dementia for suspected urinary tract infections. Journal of the American Geriatrics Society, 61(1), 62-66. Web.
Mody, L., Greene, M., Meddings, J., Krein, S., McNamara, S., Trautner, B., … Saint, S. (2017). A national implementation project to prevent catheter-associated urinary tract infection in nursing home residents. JAMA Internal Medicine, 177(8), 1154-1162. Web.
Mody, L., Meddings, J., Edson, B., McNamara, S., Trautner, B., Stone, N., … Saint, S. (2015). Enhancing resident safety by preventing healthcare-associated infection: A national initiative to reduce catheter-associated urinary tract infections in nursing homes. Clinical Infectious Diseases, 61(1), 86-94. Web.
Murphy, K.R., Myors, B., & Wohach, A. (2014). Statistical power analysis: A simple and general model for traditional and modern hypothesis tests (4th ed.). New York, NY: Routledge.
Nicolle, L. (2014). Catheter associated urinary tract infections. Antimicrobial Resistance and Infection Control, 3(1), 1-8. Web.
Parry, M., Grant, B., & Sestovic, M. (2013). Successful reduction in catheter-associated urinary tract infections: Focus on nurse-directed catheter removal. American Journal of Infection Control, 41(12), 1178-1181. Web.
Rowe, T., & Juthani-Mehta, M. (2013). Urinary tract infection in older adults. Aging Health, 9(5), 519-528. Web.
Saint, S., Greene, M., Krein, S., Rogers, M., Ratz, D., Fowler, K., … Fakih, M.G. (2016). A program to prevent catheter-associated urinary tract infection in acute care. New England Journal of Medicine, 374(22), 2111-2119. Web.
Tenke, P., Köves, B., & Johansen, T. (2014). An update on prevention and treatment of catheter-associated urinary tract infections. Current Opinion in Infectious Diseases, 27(1), 102-107. Web.