NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY

Walden University NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY– Step-By-Step Guide

This guide will demonstrate how to complete the Walden University NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.

How to Research and Prepare for NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY

Whether one passes or fails an academic assignment such as the Walden University NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.

After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.

How to Write the Introduction for NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY

The introduction for the Walden University NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.

How to Write the Body for NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY

After the introduction, move into the main part of the NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.

Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.

How to Write the Conclusion for NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY

After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.

How to Format the References List for NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY

The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.

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Sample Answer for NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY

Healthcare facilities aim to deliver high-quality medical services to patients. The demand for high-quality patient services is motivated by adjusting to upcoming organizational structures, healthcare system changes, and available procedures. Recently, there has been an increased focus on delivering high-quality medical treatment, as recognized by the government, medical experts, and patients (Palese et al., 2020). Assessing the probability and frequency of encountering quality issues is crucial to determining the provision of high-quality services. This paper identifies three rate-based measures of patient care.

Rate-based Measurements

Rate-based measurements effectively assess healthcare service quality by utilizing data from events at a specific frequency. Different forms can express these measures, including rates and proportions, means, and ratios (Dart & Cunningham, 2023). Using rate-based measurements to assess the quality of care for three patients, focusing on patient safety, timeliness, and patient-centeredness, is recommended. This approach facilitates comparisons of trends over time or among providers, aiding in identifying areas requiring improvement.

Patient Safety Measure

Definition of the Measure

A patient safety measure assesses the quality of care provided in a healthcare setting. This tool evaluates the safety of healthcare settings by analyzing adverse events, including medical errors, infections, and other such incidents. Patient safety measures assess various aspects of care quality, including the proficiency of healthcare professionals, the precision of medication orders, and the safety of the healthcare setting (Elliott et al., 2020). Patient safety measures assess compliance with regulatory standards and guidelines in healthcare settings.

Numerical Description

Quantifying a patient safety measure in a healthcare setting involves calculating the frequency of adverse events within a specific timeframe. The number is divided by the total number of patients seen during the specified period and multiplied by 100 to obtain a percentage. The given study by Palese et al. (2020) found that a hospital with a monthly occurrence of ten adverse events out of 500 treated patients had a safety measure of 2%.

Data Collection

Incident reports, surveillance systems, and patient records are typically used to gather data for patient safety measures. A thorough summary of a patient’s treatment may be found in their medical records, which can also be utilized to spot any possible negative outcomes. To further evaluate the safety of the treatment given, incident reports include comprehensive details about any unfavorable incidents. By recording and observing unfavorable occurrences, surveillance systems provide a more thorough understanding of the safety of the care given (Uddin et al., 2021). Surveys, focus groups, and other data sources, including test results and electronic medical records, may also be used to gather data. The safety of the care being given may then be evaluated, and possible areas for improvement can be found using the data that has been gathered.

Comparison to Other Settings

The effectiveness of a healthcare setting may be assessed by comparing its patient safety measures to those of other environments. The proportion of settings that perform better or worse than the measured setting might be shown in a percentile ranking as part of this comparison (Elliott et al., 2020). Regulatory agencies’ benchmarks for patient safety measures may also be compared to ascertain if the environment is according to norms and requirements.

Risk Adjustment

Any possible variations in patient populations that can impact the outcomes of a patient safety measure can be considered using risk adjustment. The process of risk adjustment involves estimating the seriousness of a negative occurrence. The outcomes of the patient safety measure are then modified using this weight. For instance, the risk-adjusted patient safety measure would be 4% if a hospital had ten adverse occurrences in a month, five of which were deemed serious (Braun & Clarke, 2020).

Goals for Aggressive Organization

An ambitious company looking to dominate its industry would aim higher than the regulatory authorities’ standards for patient safety measures. For example, the company may aim for a 2 percent patient safety measure higher than the 3 percent guideline (Braun & Clarke, 2020). The company can also aim to enhance the standard of treatment and lessen the severity of unfavorable situations.

Importance to a Clinical Organization

A clinical organization prioritizes patient safety measures since they provide valuable information on the quality of care in a medical setting. Furthermore, patient safety metrics may pinpoint improvement areas and establish objectives for better quality standards (Reddy et al., 2019). Furthermore, patient safety precautions may lower the total cost of healthcare delivery and the cost of subpar treatment. Healthcare businesses may save money by minimizing adverse occurrences and enhancing quality by lowering expenditures related to malpractice, medical mistakes, and other adverse events.

Relation to Patient Safety, Cost of Poor Quality, and Cost of Healthcare Delivery

Because they provide light on the safety of a medical environment, patient safety measures are intimately tied to patient safety. Patient safety measures may assist healthcare organizations in lowering the cost of subpar treatment by lowering the frequency of adverse occurrences, which can be measured to identify areas for improvement (Uddin et al., 2021). Furthermore, by enhancing the standard of care given and lowering the expense of malpractice and medical mistakes, patient safety measures may assist healthcare companies in lowering the total cost of healthcare delivery.

Timeliness Measures

Definition

Timeliness in healthcare refers to the speed at which healthcare services are delivered to patients, encompassing the period from identifying the need for care to the actual provision of care. This measure evaluates the time patients need to access necessary healthcare services, encompassing clinical and administrative aspects. This measure encompasses various time intervals in the healthcare system, such as the duration between a patient’s request for an appointment with a physician, the time taken for a patient to undergo a diagnostic test or procedure, and the time required for a patient to receive a referral to a specialist (Elliott et al., 2020).

Numerical Description

The numerical representation of the timeliness measure is typically based on the designated service timeframe and the actual timeframe in which the service was delivered. The timeliness measure for a physician appointment can be determined by subtracting the actual appointment duration from the expected appointment duration (Elliott et al., 2020).

Data Collection

The timeliness measure data is obtained from patient surveys and medical and administrative records. Patient surveys are commonly employed to evaluate patients’ time to obtain appointments with healthcare providers and access related services. Haraldstad et al. (2019) utilize medical and administrative records to evaluate the duration of time required for patients to undergo diagnostic tests or procedures, as well as the duration of time needed to obtain a referral to a specialist.

External Comparison

The timeliness indicator may be externally compared to other contexts by quantifying the duration it takes for patients to get treatment at different healthcare institutions. This comparison may be used to discern disparities in the duration it takes for patients to acquire medical attention at various establishments. The external comparison may also assess the real timeliness rate about a percentile rating, quantifying the duration a specific hospital takes to provide care compared to comparable facilities (Haraldstad et al., 2019).

Risk Adjustment

Risk-adjusted timeliness metrics are often adjusted to account for patient characteristics and differences in healthcare needs. Risk adjustment is often used to account for the complexity of the patient’s condition and the possible length of time that treatment may be needed. Giving patients prompt medical attention indicates the staff’s responsiveness and responsibility (Elliott et al., 2020). Patients are more likely to seek further medical care when they and their healthcare practitioner have built trust.

Setting Goals

In an assertive organization, the objectives for a timeliness metric may be established by assessing the duration it takes for a patient to obtain medical attention at various facilities. The aim would be to decrease the duration it takes for a patient to receive treatment at a certain facility. For example, a proactive organization may establish an objective to decrease the duration of a patient’s appointment with a physician by 10% (Agarwal et al., 2019). This objective may be monitored over time to verify that the organization is achieving its target. One of the objectives that might be set to ensure the application of timeliness measures is to reduce the number of in-patient stays by enhancing the dependability and effectiveness of patient treatment. The second objective is to enhance hospital infrastructure to enable healthcare professionals to provide high-quality treatment. The third objective is to alleviate the psychological distress of waiting for medical attention.

Importance to a Clinical Setting

The timeliness metric is of significant value in a clinical environment for two main reasons. Timely access to care is crucial to ensure patients get treatment promptly. This is particularly crucial for individuals requiring immediate medical attention or in danger of a medical crisis. Moreover, prompt access to healthcare might enhance the patient’s experience by decreasing waiting periods and mitigating patient dissatisfaction (Elliott et al., 2020). Furthermore, prompt access to healthcare might enhance patient safety by reducing the likelihood of medical mistakes. This is because prompt access to healthcare may decrease the duration of a patient’s stay in a medical facility, reducing the likelihood of medication errors and other medical mistakes. Moreover, prompt access to healthcare might mitigate the likelihood of nosocomial infections by minimizing the duration of a patient’s hospital stay.

Relationship to Patient Safety, Cost of Poor Quality, and Cost of Healthcare Delivery

The timeliness indicator is closely correlated with patient safety, the financial implications of subpar quality, and the total expenses associated with healthcare provision. Timely access to treatment is crucial for patient safety since it minimizes the duration of a patient’s stay in a healthcare facility, minimizing the likelihood of medical mistakes. Moreover, prompt access to healthcare might mitigate the likelihood of nosocomial infections by minimizing the duration of a patient’s hospital stay. Timely access to treatment may mitigate the cost of poor quality by minimizing a patient’s duration in a healthcare facility, hence decreasing the expenses linked to medical mistakes (Dart & Cunningham, 2023). Additionally, timely access to medical treatment may shorten a patient’s hospital stay, saving costs associated with nosocomial infections. In the end, early access to medical care may reduce healthcare costs by shortening the length of time a patient stays in a hospital. This might result in less time spent providing care and less use of available resources. Additionally, early access to healthcare may shorten a patient’s hospital stay, saving hospital treatment costs somewhat.

Patient-Centeredness Measure

Definition

The patient-centeredness metric quantifies the extent to which a healthcare facility, institution, or organization prioritizes the patient’s preferences and requirements in providing treatment. This metric is predicated on the notion that healthcare organizations prioritizing patient-centric treatment, customized to meet each person’s specific requirements, desires, and preferences, are the most efficacious (Al-Fraihat et al., 2020). This care method considers the patient’s unique requirements, beliefs, and choices and utilizes this data to direct the supplied treatment. This encompasses educating patients and encouraging them to actively engage in their treatment, using patient-centered communication, and delivering care customized to each person’s unique requirements.

Numerical Definition

The percentage of patients rated their overall care experience as “excellent” or “very good” on a five-point scale is used to calculate this score. The number of patients who rated their care experience as “excellent” or “very good” is represented by the numerator. In addition, the total number of patients who took part in the survey is represented by the denominator. The following formula is used to compute the rate: Patient-centeredness measure is calculated by dividing the total number of patients who responded to the survey by the number of patients who rated their treatment as “excellent” or “very good,” then multiplying the result by 100. (Al-Fraihat et al., 2020).

Data Collection

Patient and healthcare provider feedback is gathered on this statistic via surveys, focus groups, and interviews. Surveys of patients may be used to learn more about their experiences receiving care from the medical facility and the quality of that care. In order to learn more about healthcare professionals’ direct experiences with the organization’s patient-centered practices, interviews may be conducted (Elliott et al., 2020). In contrast, focus groups may be used by medical professionals and patients to discuss their experiences with the organization’s patient-centered procedures.

Measurement Comparison

By comparing a percentile rating to the actual patient satisfaction rate with the patient-centeredness of their treatment, the Patient-Centeredness metric is compared to different settings. For instance, if a healthcare institution has a Patient-Centeredness rate of 75%, it indicates that 75% of the polled patients expressed satisfaction with the patient-centeredness of their treatment (Enticott et al., 2021). Subsequently, this rate may be juxtaposed with a percentile rating to assess the healthcare facility’s relative performance compared to other settings.

Risk-Adjusted or Not

The Patient-Centeredness Measure lacks risk adjustment. Risk adjustment is a technique used to factor in variations in patient attributes while evaluating healthcare quality. Risk adjustment incorporates variables such as age, gender, and other attributes that may influence the result of healthcare. As the Patient-Centeredness Measure does not evaluate healthcare results, there is no need for risk adjustment (Enticott et al., 2021).

Goals

The objective for this metric in a proactive organization would be to surpass the mean rate of patient-centric practices across comparable organizations. This objective might be accomplished by including supplementary patient-centric measures, such as offering more patient instruction and engaging patients in decision-making. The organization should adopt additional patient-centered practices that surpass the current provision of basic care. This could involve offering resources and support systems to patients with chronic conditions or those requiring assistance managing their health (Agarwal et al., 2019). In addition, the organization should aim to enhance patient-centered communication by offering explicit guidelines to patients on medication adherence, maintaining regular contact with their care team, and diligently adhering to their treatment plans.

Importance of the Measure

The Patient-Centeredness Measure is crucial for a healthcare organization as it offers valuable insights into the quality of patient care they provide. The metric may facilitate the identification of deficient regions in healthcare and can be used to monitor advancements over some time (Enticott et al., 2021). Furthermore, the measure may provide valuable information on patient engagement in their healthcare and the extent of autonomy they are granted. This may be advantageous for both the organization and the patient since it can assist in guaranteeing that the patient is getting optimal treatment.

This measure may also aid in the identification of possible issues related to patient participation or autonomy. If the measure indicates that patients lack sufficient autonomy or have poor participation in their treatment, the organization may take steps to remedy this issue. This may include allocating more resources to enhance patient involvement in their healthcare or additional resources to promote autonomy (Enticott et al., 2021). Ultimately, the metric may be used to monitor the efficacy of patient-centered treatment as time progresses. This facilitates the organization’s identification of areas that need improvement in care and enables the measurement of the effects of implemented changes aimed at enhancing patient-centered care. Implementing this may enable the organization to guarantee optimal patient care and reduce medical mistakes and readmission expenses.

Relation to Patient Safety, Cost of Poor Quality, and Cost of Healthcare Delivery

Since it measures the organization’s capacity to meet patients’ needs and provide all-encompassing care, the patient-centeredness metric has a significant correlation with patient safety. Low patient-centeredness rates in hospitals may indicate that patients are not receiving enough patient-centered care, which might lead to negative outcomes and an overall reduction in patient safety (Agarwal et al., 2019). Because it measures how well an organization can meet patient needs and provide all-encompassing care, the patient-centeredness metric is highly correlated with the price of subpar quality. Inadequate patient-centered care has negative effects and may increase costs for the organization since more treatments or services are required.

The patient-centeredness metric correlates with the overall healthcare cost because it measures how effectively an organization meets patients’ needs and provides a thorough treatment plan. Unfavorable results from inadequate patient-centered care may increase healthcare costs by necessitating more treatments and services (Enticott et al., 2021). Patients who get subpar patient-centered treatment are more likely to be dissatisfied, which lowers patient satisfaction and increases patient turnover rates. As a result, the company may experience increased costs.

Conclusion

The quality of healthcare that is provided is objectively evaluated using quality metrics. To improve patient care, they support the creation of standardized medical care procedures. The active involvement of patients, regulatory agencies, and healthcare professionals is necessary for continuous quality improvement. Patient safety, timeliness measures, and patient preparedness are the three most effective quality measures. To protect patients, all healthcare facilities must implement patient safety procedures. Metrics that measure timeliness are essential for reducing the number of people who die or suffer negative outcomes as a result of receiving subpar medical treatment. It is crucial to prioritize patient-centeredness by considering patient preferences and including family members. Consequently, the main priority should be to evaluate and ensure the quality of care, allocating resources to enhance its quality while minimizing potential damage and expenses.

References

Agarwal, S., Sripad, P., Johnson, C., Kirk, K., Bellows, B., Ana, J., Blaser, V., Kumar, M. B., Buchholz, K., Casseus, A., Chen, N., Dini, H. S., Deussom, R., Jacobstein, D., Kintu, R., Kureshy, N., Meoli, L., Otiso, L., Pakenham-Walsh, N., . . . Warren, C. E. (2019). A conceptual framework for measuring community health workforce performance within primary health care systems. Human Resources for Health, 17(1). https://doi.org/10.1186/s12960-019-0422-0

Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, pp. 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004

Braun, V., & Clarke, V. (2020). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 18(3), 328–352. https://doi.org/10.1080/14780887.2020.1769238

Dart, S., & Cunningham, S. (2023). Using institutional data to drive quality, improvement, and innovation. In University development and administration (pp. 1–24). https://doi.org/10.1007/978-981-19-9438-8_29-1

Elliott, R. A., Camacho, E., Janković, D., Sculpher, M., & Faria, R. (2020). Economic analysis of the prevalence and clinical and economic burden of medication error in England. BMJ Quality & Safety, 30(2), 96–105. https://doi.org/10.1136/bmjqs-2019-010206

Enticott, J., Johnson, A., & Teede, H. (2021). Learning health systems using data to drive healthcare improvement and impact: a systematic review. BMC Health Services Research, 21(1). https://doi.org/10.1186/s12913-021-06215-8

Haraldstad, K., Wahl, A. K., Andenæs, R., Andersen, J. R., Andersen, M. H., Beisland, E. G., Borge, C. R., Engebretsen, E., Eisemann, M., Halvorsrud, L., Hanssen, T. A., Haugstvedt, A., Haugland, T., Johansen, V. A., Larsen, M. H., Løvereide, L., Løyland, B., Kvarme, L. G., Moons, P., . . . Helseth, S. (2019). A systematic review of quality of life research in medicine and health sciences. Quality of Life Research, 28(10), 2641–2650. https://doi.org/10.1007/s11136-019-02214-9

Palese, A., Navone, E., Danielis, M., Vryonides, S., Sermeus, W., & Papastavrou, E. (2020). Measurement tools used to assess unfinished nursing care: A systematic review of psychometric properties. Journal of Advanced Nursing, 77(2), 565–582. https://doi.org/10.1111/jan.14603

Reddy, S., Allan, S., Coghlan, S., & Cooper, P. (2019). A governance model for the application of AI in health care. Journal of the American Medical Informatics Association, 27(3), 491–497. https://doi.org/10.1093/jamia/ocz192

Uddin, M. G., Nash, S., & Olbert, A. I. (2021). A review of water quality index models and their use for assessing surface water quality. Ecological Indicators, p. 122, 107218. https://doi.org/10.1016/j.ecolind.2020.107218

Sample Answer 2 for NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY

Irrespective of their health conditions, all patients require timely, effective, and quality health care services. Overall, achieving the desired state of health care quality remains a leading goal of health care organizations. Processes, procedures, and routine interactions should ensure that patients are excellently served. Satisfaction should be a guiding principle. In health practice, quality of care represents the degree to which health services meet the desired outcomes. To examine whether they are providing quality care, organizations should regularly evaluate their performance using rate-based quality measures. Evaluating performance guided by rate-based quality measures is a practical way of improving care delivery and patient outcomes. This paper describes rate-based measures of quality in health care organizations. It further deconstructs each measure, describes the importance, and explains how each measure relates to patient safety and the cost of healthcare delivery.

Rate-Based Measures: Description

Quality measures are reliable indicators of a healthcare organization’s capacity to deliver optimal care. Rates show the difference between performance and expectations. Appropriate rate-based quality measures for in-depth exploration include readmission rates, complication rates, and post-procedure death rates. These measures have been selected since they directly relate to the type of care that patients receive in health care settings. Their rates are inversely proportional to the quality of care. For instance, high readmission rates indicate that the quality of care does not meet the desired performance levels. The same case applies to complication rates and post-procedure death rates.

The other reason for selecting these measures is their significance in the overall health care provision in the United States. The Centers for Medicare & Medicaid Services (CMS) reports that quality health care is a priority for the President of the United States, Department of Health and Human Services, and CMS (Centers for Medicare & Medicaid, 2020). Due to the significance and interest of quality health care, CMS uses quality initiatives for health improvement in many instances and spends considerable resources in quality enhancement programs. As a result, the rate-based quality measures indicate the extent to which health care organizations align with the President’s and CMS’ expectations as far as quality is concerned.

Health care organizations require tools for quantifying healthcare processes. The selected rate-based measures are used for quantifying outcomes. Quantifying the processes and outcomes shows an organization’s ability to provide high-quality care. Quantifying outcomes by rating them also indicates the areas requiring more attention as the organization adopts new quality improvement mechanisms.

Deconstructing Each Measure

When a patient visits a healthcare organization for medical assistance, the general desire is to get an accurate diagnosis and proper treatment. Such assistance promotes healing and helps the patient to recover within the healthcare facility or at home. Unfortunately, health complications may necessitate readmission. Upadhyay et al. (2019) described readmission rate as hospital admission occurring within a specified time frame after discharge from the first admission. As a result, the readmission rate denotes the percentage of patients readmitted after discharge. Readmission rates may be calculated in terms of weeks, months, or annual readmission.

With hospital-acquired infections (HAIs) a sincere concern in health care delivery, the complication rate should guide health care providers in preventing HAIs. Lim (2019) described the complication rate as the percentage of patients developing complications resulting from care. In most instances, complication rates are high in complex procedures such as surgeries. For instance, the complication rate associated with heart surgeries is often higher than treatment for malaria. Routinely, many health care organizations track the complication rate by a specific timeframe or division. In this case, all complications can be calculated together or segmented according to the type of disease. The extent of complication rate indicates the quality of care that patients receive in a particular health care setting.

After the treatment, patients always look forward to a full and speedy recovery. Healthcare organizations also implement the necessary measures to prevent deaths to ensure that the mortality rates for all illnesses are as low as possible. Despite these efforts, deaths still occur after procedures. According to Lim (2019), the post-procedure death rate is the number of deaths occurring after treatment. The death rate usually varies depending on the procedure. Like readmissions and complication rates, a high post-procedure death rate may be an indicator of low-quality health services.

To construct the readmission rate, the number of readmitted patients (numerator) is divided by the number of patients served during a given period (denominator). The figure is given in percentage. For instance, if five patients were readmitted after 200 discharges, the readmission rate would be (5/200) x 100, giving 2.5%.  The complication rate is constructed by dividing the number of patients who develop complications by the number who received care in a given timeframe. The post-procedure death rate is calculated by dividing the number of deaths by the number of patients who received treatment. The post-procedure death rate is provided for each procedure. Like complication rates, post-procedure death rates differ depending on the type of procedure.

In each case, comparative data analysis occurs to develop the measure and get the necessary meaning to guide decision-making. For readmission rates, health care organizations may opt to record readmission cases for all illnesses after discharge. Alternatively, they may collect data for specific illnesses, which helps to determine illnesses associated with the highest readmission rates. The same approach can be used for collecting data for complication rates. Data may be case-specific or combine all complications over a given timeframe.  Post-procedure death rates’ data can be tracked hospital-wide or for specific divisions and health care teams.

To determine whether a healthcare organization’s performance is within the expected performance levels, data comparison is necessary. According to the Centers for Medicare & Medicaid Services (2020), quality measures should be publicly reported. As a result, health care organizations make their data public when required, implying that their performance is visible to other settings in the same state or different regions. Shah et al. (2019) noted that the availability of such performance data, including readmission rates, allows the Readmissions Reduction Program (HRRP) to incentivize decreased readmissions. A healthcare organization can do comparative performance analysis to reflect on its performance versus other organizations through the publicly reported data.

The rates can be provided as actual figures or percentile ranking. Like illustrated in readmission, complication, and post-procedure death rate calculations, actual rates represent the figures of each measure calculated using historical operating functions and adjustment factors. For instance, the actual readmission rate is the number of readmissions divided by the number of discharges in a given time. Mostly, actual rates are given in percentage. On the other hand, percentile ranking is the percentage of scores in the frequency distribution equal or lower than the score. For instance, if the readmission rate is 65% of a hospital, 65 is the percentile rank. Since readmissions illustrate poor performance, the facility would have performed worse than 65% of other facilities included in the frequency distribution.

Some measures of quality are usually risk-adjusted. For accurate calculations of post-procedure death rate, the measurement must factor the risk level into calculations (Ng-Kamstra et al., 2018). The risk level varies for each procedure. Risk adjustment also applies to complication and readmission rates. Risk adjustment includes risk factors associated with a measure score, allowing fair and accurate healthcare outcomes comparison. A typical risk factor is the health status of a patient.

Healthcare organizations set different goals based on their missions, visions, and performance objectives. For an aggressive organization seeking to excel in the marketplace, a reasonable goal for readmission rate as a measure of quality is to reduce the rates to below the state and nationally minimum allowable levels. As a result, the organization would adopt the necessary measures to reduce the rates, such as bedside patient education and technology adoption in healthcare processes for better communication and patient monitoring.  For complication rate, an aggressive organization would set quality improvement goals focusing on reducing the complication rate. As a result, the organization would initiate measures to prevent complications after a medical procedure. Similar goals apply to the post-procedure death rate. The organization should be motivated to have no death case after a medical procedure. The reference point should always be the state and national performance benchmarks.

Importance of Each Rate-Based Measure to a Chosen Clinical Organization and Setting

All healthcare organizations have a moral and legal obligation to promote healthy living in the populace. Besides the usual diagnosis and treatment of illnesses, it is crucial to build lasting patient-provider relationships and adopt mechanisms for enhancing the quality, safety, and timeliness of care. Saint Joseph Hospital, Denver, is among clinical organizations providing primary and specialized care. In primary care, Saint Joseph Hospital’s fundamental principle is that the organization’s primary care providers are the first people that patients visit for their health questions and concerns (SLC Health Saint Joseph, 2021). Advanced care in Saint Joseph Hospital includes heart and vascular care, orthopedics, and emergency.

As a rate-based measure, the readmission rate is crucial at Saint Joseph Hospital as an indicator of the quality of care that patients receive. Gupta et al. (2019) described hospital readmission within 30 days as a significant quality measure since it represents a potentially preventable adverse outcome. With Saint Joseph Hospital engaging in complex procedures such as heart surgery, cardiac rehabilitation, and heart arrhythmia treatment, the chances of readmissions might be high in such settings. Brunner-La Rocca et al. (2020) observed that the readmission rate is high in advanced care such as cardiovascular health procedures. As a result, Saint Joseph’s management should use the readmission rate as a motivation to improve quality outcomes. The rates indicate the magnitude of effort required to achieve the desired level of patient satisfaction.

Like other clinical settings, Saint Joseph Hospital should apply evidence-based practice strategies to improve clinical outcomes. Its primary, emergency and acute care outcomes should match the required performance benchmarks at local, state, and national levels. Achieving this critical goal requires Saint Joseph Hospital to collect data and measure performance on significant outcome areas. Accordingly, complication rates indicate areas that need more intervention as far as the quality of care is concerned. For instance, shock, hemorrhage, urinary retention, and pulmonary embolism are common complications after surgeries. Since they are costly to manage and extend hospital stays, measuring their rates is crucial always. The rate indicates the extent and type of responses required to ensure that Saint Joseph Hospital provides care that meets all the quality standards.

As a measure of care quality, the post-procedure death rate is also crucial to Saint Joseph’s Hospital in decision making and resource allocation. From a general operation viewpoint, healthcare organizations must reduce mortality rates as low as possible. The goal should be conducting procedures associated with zero deaths. Like in readmission and complication rates, post-procedure death rates indicate the areas of attention requiring improvement to reduce mortality rates. For instance, deaths associated with health complications can be prevented by increasing or improving interventions that reduce complications. Deaths associated with home-based care after surgeries can be prevented by improving home-based care.

Relationship with Patient Safety, Cost of Poor Quality, and the Overall Cost of Healthcare Delivery

It is an unfortunate scenario for patients to receive unsatisfactory care. According to Upadhyay et al. (2019), readmissions indicate unsafe transitions between points of care (hospital to home). As a result, readmission rates indicate the extent to which the patient received care that guarantees safety. As an indicator of low-quality services, readmission rates show that the patient receives care in unsafe settings. Health complications, emotional and financial burdens associated with increased readmissions are costly to manage. Patients are forced to travel more to get care, involve family members, and utilize more resources. The entire process is costly and increases the illness burden. Regarding the overall cost of care, the annual cost of readmissions to the US healthcare system is as high as $17.4 billion annually (Warcho et al., 2019). Such resources could be used for illness prevention and promotion programs if there were no readmissions.

Complications have similarly profound effects on safety concerns and cost implications. Health complications risk patient safety due to extended hospital stays and frequent visits. Health complications also increase the mortality rate. Postoperative complications, including atelectasis, wound infection, and deep vein thrombosis, are costly to treat and manage. In a review of postoperative complications cost of 6,387 patients, prolonged ventilation management was found to consume approximately $48,168 and renal failure $18,528 (Merkow et al., 2020). Such costs can be minimized by a proportional reduction in complication rates.

The post-procedure death rate not only indicates patient safety concerns but is a threat to their lives. Unlike readmissions and complications, death rates show a health care facility’s incapacity to guarantee patient safety. Deaths are costly since the patient and the family does not get the value for their money. Hospitals also incur huge costs associated with litigation if the family is not satisfied with how the patient was handled.

In conclusion, rate-based quality measures indicate the extent to which a healthcare organization provides quality healthcare services. In this paper, readmission, complication, and post-procedure death rates have been discussed as rate-based quality measures.  The three measures were selected since they directly relate to the type of care that patients receive in healthcare settings. The case of Saint Joseph Hospital has been provided to illustrate the importance of each rate-based measure. In terms of safety, the magnitude of each rate is inversely proportional to patient safety. Poor quality care is costly to manage from a patient’s and healthcare delivery’s dimensions. As a result, healthcare organizations should heavily invest in strategies that reduce readmissions, complications, and post-procedure rates to acceptable levels.

References

Brunner-La Rocca, H. P., Peden, C. J., Soong, J., Holman, P. A., Bogdanovskaya, M., & Barclay, L. (2020). Reasons for readmission after hospital discharge in patients with chronic diseases—Information from an international dataset. PloS One, 15(6), e0233457. https://doi.org/10.1371/journal.pone.0233457

Centers for Medicare & Medicaid Services. (2020, Feb 11). Quality measures. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures

Gupta, S., Zengul, F. D., Davlyatov, G. K., & Weech-Maldonado, R. (2019). Reduction in hospitals’ readmission rates: Role of hospital-based skilled nursing facilities. Inquiry : A Journal of Medical Care Organization, Provision and Financing, 56, 46958018817994. https://doi.org/10.1177/0046958018817994

Lim, R. (2019). Multidisciplinary approaches to common surgical problems. Springer Nature.

Merkow, R. P., Shan, Y., Gupta, A. R., Yang, A. D., Sama, P., Schumacher, M., … & Bilimoria, K. Y. (2020). A comprehensive estimation of the costs of 30-day postoperative complications using actual costs from multiple, diverse hospitals. The Joint Commission Journal on Quality and Patient Safety, 46(10), 558-564. https://doi.org/10.1016/j.jcjq.2020.06.011

Ng-Kamstra, J. S., Arya, S., Greenberg, S. L., Kotagal, M., Arsenault, C., Ljungman, D., … & Shrime, M. G. (2018). Perioperative mortality rates in low-income and middle-income countries: a systematic review and meta-analysis. BMJ Global Health, 3(3), e000810. http://dx.doi.org/10.1136/bmjgh-2018-000810

Shah, R. M., Zhang, Q., Chatterjee, S., Cheema, F., Loor, G., Lemaire, S. A., … & Ghanta, R. K. (2019). Incidence, cost, and risk factors for readmission after coronary artery bypass grafting. The Annals of Thoracic Surgery, 107(6), 1782-1789. https://doi.org/10.1016/j.athoracsur.2018.10.077

SLC Health Saint Joseph. (2021). Our services. https://www.sclhealth.org/locations/saint-joseph-hospital/

Upadhyay, S., Stephenson, A. L., & Smith, D. G. (2019). Readmission Rates and Their Impact on Hospital Financial Performance: A Study of Washington Hospitals. Inquiry : A Journal Of Medical Care Organization, Provision and Financing, 56, 46958019860386. https://doi.org/10.1177/0046958019860386

Warchol, S. J., Monestime, J. P., Mayer, R. W., & Chien, W. W. (2019). Strategies to Reduce Hospital Readmission Rates in a Non-Medicaid-Expansion State. Perspectives in Health Information Management, 16(Summer), 1a. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6669363/

Sample Answer 3 for NURS 8302 Week 2: TOOLS FOR MEASURING QUALITY

Nosocomial infections, also known as healthcare-associated infections, are a significant issue in healthcare institutions globally. These infections result in extended hospitalization and heightened expenses and may even lead to mortality. Annually, 1.7 million individuals in the United States have these illnesses, resulting in more than 98,000 fatalities (Omar et al., 2020). Quality assessment instruments may assist with tackling these concerns by monitoring advancement, pinpointing places for enhancement, and directing forthcoming choices. Rate-based metrics, characterized by a numerator and denominator, are a specific category of quality measures. Utilizing these techniques may improve the overall quality of treatment in healthcare settings and help combat nosocomial infections. The paper will analyze three rate-based quality measures chosen to tackle the clinical quality problem of nosocomial infections. It will explain each measure, including its creation, data collection, and external comparison.

Three Rate-Based Measures of Quality

The rate of nosocomial infections is an important health measure that shows how often infections happen in hospitals. This quality measure based on rates helps hospitals determine what they need to work on and keep track of their growth over time. It is correct and detailed, giving hospitals helpful knowledge to improve patient care. The type of patients accepted, the length of stay, the tools and methods used, and the level of care given to patients are all things that can change the rate of nosocomial diseases. Electronic Health Records and hospital exit records can determine the rate of nosocomial infections (Rosenthal et al., 2021). This lets us measure the number of nosocomial illnesses and keep track of the hospital’s progress. So, the rate of nosocomial infections is an excellent way to judge how well a hospital is doing.

Another crucial clinical quality indicator is the rate of complications, which shows how often patients with nosocomial illnesses have significant health problems. Nosocomial infections can happen at any time while you are in the hospital and can cause considerable difficulties like acute respiratory distress syndrome, pancreatitis, sepsis, endocarditis, or even death. The complication rate represents the frequency of problems encountered by hospital patients, measured as the number of issues per 100 individuals. Understanding this figure can assist individuals in identifying strategies to enhance patient care (Rosenthal et al., 2021). The quality of care can be improved by reducing the number of problems with nosocomial illnesses and finding patients most likely to have significant complications. This knowledge can be used by healthcare management to change the rules and processes of the hospital.

The third way to judge quality is by how happy the patients are with their care. This number shows how pleased hospital patients are with their care. In healthcare, patient happiness is a crucial quality measure that shows how well an organization meets the wants and desires of its patients. Rate-based quality measures, like how happy patients are with their healthcare, let you see how well your organization is doing compared to others in the same field. One way to measure patient happiness is to ask them how happy they are with their care. However, this method needs to be more accurate (Alvim et al., 2020). one can also use polls and reviews from doctors or nurses to get feedback. Overall, these tests help show how well a healthcare organization ensures and stops infections.

Deconstructing Each Measure

Quality Measure 1: Rate of Nosocomial Infections

The nosocomial infection rate is calculated by dividing the number of infections in hospitalized patients by the total number of days patients spend there. Precise measurements are essential for enhancing clinical quality and ensuring optimal patient care. Nosocomial infection rates are determined by using the relevant numerators and denominators. The numerators consist of the count of infections occurring within a specific time frame and the count of patients who have been infected. On the other hand, the denominators include the number of patients admitted or released, the total number of days patients have spent in the hospital, and the number of days medical devices have been used. The rate derived from the division of the number of infections by patient days or infected patients by admitted patients provides valuable insights into the quality of treatment or the success of Quality Improvement Initiatives that target clinical concerns (Tchouaket et al., 2021).

The rate of nosocomial infections is determined by dividing the number of infections inside a hospital by the total number of patient days. The rate is multiplied by a factor of 1000 to represent a ratio of thousand cases per 100,000 patient days (Omar et al., 2020). Surveillance of hospital patients who get infections may be used to obtain data on the rate of nosocomial infections. Data may be gathered on the nature of the infection, the location of the illness, the organism responsible, the time of infection acquisition, and the administration of antibiotics to the patient.

A practical method of conveying this metric to internal stakeholders is illustrating the fluctuations in nosocomial infection rates. One way to do this is by using a graph or chart visually representing the trajectory of nosocomial infection rates. This information should be shared with department heads, managers, and nurses to ensure they are informed about the success achieved and the necessary steps to sustain and enhance these advances (Tchouaket et al., 2021). Internal stakeholders may be informed about this step by providing them with tailored training on various forms of nosocomial infections and the necessary preventive measures. This will help ensure the hospital takes the necessary safety measures to protect its patients from infection. In order to increase awareness of the issue and encourage other hospitals to steer clear of nosocomial infections, targeted communications may also be employed to alert external stakeholders about this strategy.

Nosocomial infection rates may be assessed in other hospital settings using percentile rankings. This implies that the prevalence of nosocomial infections in a particular group is distributed evenly among 100 identical segments. The incidence of nosocomial infections in that population is compared to the predicted incidence in that population, considering the population’s characteristics. For instance, if the prevalence of nosocomial infections in a community is 10%, then the anticipated number of nosocomial infections in that population, considering the population’s characteristics, would be 9.9% (Omar et al., 2020). This metric is risk-adjusted since it specifically quantifies infections occurring inside the hospital environment. This is accomplished by considering the different patient types treated in the hospital and the illnesses these people are more likely to get. This may be done by altering the percentage of hospital admissions for that particular sickness based on data on the frequency of infections among patients admitted to the hospital in the previous year.

In a proactive institution, setting goals to reduce the frequency of nosocomial infections may be beneficial. Hospitals could aim to lower the number of nosocomial infections per 100,000 patient days or the incidence of nosocomial infections by a certain percentage. Furthermore, this strategy can aim to reduce the frequency of nosocomial infections by 50% or 75% in the next year. Every organization member must work together on this project, from the top executives to the front-line employees (Omar et al., 2020). Potential approaches for attaining this objective include enhancing awareness about preventing nosocomial infections, refining infection control protocols, and establishing incentives to encourage personnel to report suspicious illnesses.

Quality Measure 2: Rate of Complications Arising from Nosocomial Infections

The rate of complications resulting from nosocomial infections quantifies the frequency of problems caused by nosocomial infections in patients admitted to hospitals. Typically, it is quantified as the rate of complications per 1000 patients. The incidence of issues resulting from nosocomial infections is a crucial measure of the quality of care given to hospitalized patients (Lemiech-Mirowska et al., 2021). Additionally, it may assist hospitals in identifying specific areas where they can enhance the quality of their treatment. The incidence of problems resulting from nosocomial infections is also a significant measure of the overall health status of a hospital.

The rate of complications from nosocomial infections is calculated by dividing the number of affected patients by the total number of patients. The rate can be determined using the following formula: The rate is calculated by dividing the number of complications by the total number of patients. The rate is expressed as a percentage. For example, a study by Lemiech-Mirowska et al. (2021) found that out of 10,000 patients, 1,000 experienced difficulties due to nosocomial infections. This translates to an incidence rate of 10%. This metric is valuable for assessing the frequency of problems resulting from nosocomial infections.

Several methods may be used to gather data on the frequency of problems arising from nosocomial infections. An approach may include surveying hospitalized or released patients to see if they encountered any issues arising from their nosocomial infections. An alternative approach would consist of monitoring the frequency of hospital admissions due to nosocomial infections within a specific timeframe and examining if there exists a relationship between the number of hospitalizations and the incidence of problems arising from nosocomial infections (Tchouaket et al., 2021). Furthermore, it is possible to gather data about the extent of the issues arising from nosocomial infections. Researchers would be able to ascertain the most prevalent issues and assess any variations in the severity of consequences across various kinds of nosocomial infections.

This quality assessment compares the incidence of problems resulting from nosocomial infections with other healthcare settings. The rate refers to the precise frequency of the issues, but the percentile score compares this rate to comparable institutions. The percentile rating quantifies the extent to which the hospital’s rate is lower than the median. In this scenario, the value would be reduced by 50% (Lemiech-Mirowska et al., 2021). The healthcare quality assessment is assessed by determining the incidence rate of problems resulting from nosocomial infections and comparing it to other hospitals.

Individual risk variables are not considered when estimating the prevalence of problems arising from nosocomial infections. This suggests that it does not consider the different risks patients could have of experiencing problems from nosocomial infections. This may mean that the measure has to have a more excellent representation of particular patients. This would be taken into consideration by risk-adjusted measures, which examine the occurrence of nosocomial infection consequences across different risk groups. Medicare patients of all ages, with and without chronic health conditions, would be included in an illustrative risk-adjusted measure for nosocomial infection complication rates (Lemiech-Mirowska et al., 2021).

According to Tchouaket et al. (2021), an aggressive organization may set goals to perform at a level that equals or exceeds that of the highest-performing company in the market, reduce the frequency of problems by half, or reduce the frequency of issues by three quarters. Establishing and carrying out standardized protocols for preventative care, such as diagnosing and treating nosocomial infections, is possible for an organization to achieve these goals. The goals would be achieved partly by offering staff training on recognizing and handling issues resulting from nosocomial infections via evidence-based treatment approaches.

Quality Measure 3: Patient Satisfaction

Patient satisfaction measures how well a healthcare facility meets the needs and expectations of its clients. The number of patients who reported being satisfied with their care is the numerator of this metric. On the other hand, the denominator is the total number of patients treated during the designated reporting period. Dividing the numerator by the denominator yields the rate for this measure. This metric’s percentile rating is used to compare it to other settings outside. This metric lacks risk adjustment since it does not consider patient-specific risk variables (Tchouaket et al., 2021). Possible objectives for this metric include augmenting or diminishing the rate by a certain magnitude.

Importance of Each Measure

An essential healthcare indicator for a healthcare organization dealing with an increase in nosocomial infections is the incidence of these illnesses. This statistic provides a way to track the frequency of infections inside the hospital and evaluate it compared to the expected infection rate based on population. The data above might aid healthcare establishments in pinpointing aspects of their infection control procedures that need improvement. For healthcare organizations, the incidence of complications from nosocomial infections is an essential indicator since it provides essential insights into the organization’s infection control practices. This metric may facilitate the identification of regions requiring enhancements in infection control and contribute to enhancing patient safety (Izadi et al., 2020). Furthermore, by identifying areas for improvement, healthcare organizations may guarantee that their patients get the utmost secure and efficient treatment feasible. Patient satisfaction is a crucial metric for assessing a healthcare organization’s overall quality of service. Patients pleased with their treatment are more inclined to seek further services and endorse the organization to others.

Relation of Each Measure to Patient Safety, Cost of Poor Quality, Overall Cost

The prevalence of nosocomial infections is directly linked to patient safety as it seeks to minimize the number of illnesses patients get while in the hospital. This decreases patient safety problems and, thus, may lower the expenses associated with inadequate patient care. Insufficient patient care may also result in a rise in the total expenditure of healthcare provision since it can cause extended hospital admissions and heightened costs related to treating infections such as MRSA (Alvim et al., 2020). An instance of how this healthcare quality indicator is connected to cost is that decreasing nosocomial infections may reduce the expenses associated with prescription medications. This is because several nosocomial illnesses are managed with pharmaceuticals such as antibiotics, and diminishing the incidence of these infections might lead to decreased expenditure on the medicines required.

Improving the treatment methods for nosocomial infections will enhance patient safety and decrease the occurrence of problems. Reducing nosocomial infections enhances patient safety by decreasing the likelihood of poor outcomes associated with their hospitalization. The expense associated with substandard quality rises as the number of hospital-acquired illnesses grows, resulting in higher spending on healthcare. The total expenditure on healthcare delivery is likewise elevated, resulting in more extraordinary healthcare expenses for patients, their families, and the broader society (Izadi et al., 2020). Consequently, hospitals must implement measures to prevent and decrease the incidence of nosocomial infections. It is essential to thoroughly evaluate patients for nosocomial infections and quickly provide appropriate treatment and isolation. Hospitals should also promote adherence to preventive measures among personnel, including frequent handwashing, use of personal protective equipment, and implementation of other precautionary measures.

Patient satisfaction is a metric used to assess the quality of healthcare. It is closely linked to patient safety since it indicates if patients are getting appropriate treatment and are content with it. Poor quality is directly related to patient dissatisfaction since dissatisfied patients tend to deviate from treatment regimens or lodge complaints or lawsuits. In general, there is a correlation between reasonable patient satisfaction and reduced healthcare expenses. Moreover, patients who are content are more inclined to endorse their treatment to others, which leads to a rise in demand for services and a decrease in healthcare expenses for the overall system (Rosenthal et al., 2021).

Conclusion

Nosocomial infections are a significant healthcare concern, resulting in extended hospital stays, heightened expenses, and sometimes fatal outcomes. Rate-based quality measurements are practical tools for monitoring progress and pinpointing improvement areas. Examining nosocomial infection rates, complication rates, and patient satisfaction might help identify areas that need improvement. Lowering nosocomial infection rates may lead to decreased healthcare expenses and increased service demand, eventually benefitting the healthcare system.

References

Alvim, A. L. S., Couto, B. R. G. M., & Gazzinelli, A. (2020). Quality of the hospital infection control programs: an integrative review. Revista Gaúcha De Enfermagem, 41. https://doi.org/10.1590/1983-1447.2020.20190360

Izadi, N., Eshrati, B., Etemad, K., Mehrabi, Y., & Hashemi-Nazari, S. (2020). The rate of the incidence of hospital-acquired infections in Iran is based on the data from the national nosocomial infections surveillance. New Microbes and New Infections, 38, 100768. https://doi.org/10.1016/j.nmni.2020.100768

Lemiech-Mirowska, E., Kiersnowska, Z. M., Michałkiewicz, M., Depta, A., & Marczak, M. (2021). Nosocomial infections are one of the most important problems in the healthcare system. AAEM. Annals of Agricultural and Environmental Medicine/Annals of Agricultural and Environmental Medicine, 28(3), 361–366. https://doi.org/10.26444/aaem/122629

Omar, I., Shirazy, M., Omar, M., & Chaari, A. (2020). Controlling nosocomial infection in adult intensive treatment unit: A quality improvement project. International Journal of Risk & Safety in Medicine, 1–7. https://doi.org/10.3233/jrs-190028

Rosenthal, V. D., Duszynska, W., Ider, B., Gurskis, V., Al-Ruzzieh, M. A., Myatra, S. N., Gupta, D., Belkebir, S., Upadhyay, N., Zand, F., Todi, S. K., Kharbanda, M., Nair, P. K., Mishra, S., Chaparro, G., Mehta, Y., Zala, D., Janc, J., Aguirre-Avalos, G., . . . Erben, N. (2021). International Nosocomial Infection Control Consortium (INICC) report, data summary of 45 countries for 2013-2018, Adult and Pediatric Units, Device-associated Module. American Journal of Infection Control, 49(10), 1267–1274. https://doi.org/10.1016/j.ajic.2021.04.077

Tchouaket, E. N., Sia, D., Brousseau, S., Kilpatrick, K., Boivin, S., Dubreuil, B., Larouche, C., Parisien, N., Dubois, C., Brousselle, A., & Da Silva, R. B. (2021). Economic Analysis of the Prevention and Control of Nosocomial Infections: Research Protocol. Frontiers in Public Health, 9. https://doi.org/10.3389/fpubh.2021.531624