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- ... 1 2 The Implementation of Mock Code Simulations Ellen M. Wray Adult-Gerontology Acute Care Nurse Practitioner Track Department of Nursing Science, Saint Marys College Doctor of Nursing Practice Program Faculty Team Leader: Dr. Annette Peacock Johnson 3 Acknowledgment This paper and the research behind it would not have been possible without the exceptional support of my advisor, Professor Annette Peackock-Johnson. Her support, knowledge, and attention to detail have helped carry me through all of the stages of my project. I would also like to thank the key stakeholders involved in this project, Janet Haw, Joe Canino, Megan Gross, and Jackie Corbett for their eagerness and willingness to assist me in this project. I would also like to thank my classmates for the peer reviews along with brilliant suggestions and comments allowing me to complete this project and my research to the best of my ability. As well as Saint Marys College as without their support, this project would not have been possible. Finally, I would like to my husband Evan and my family for their continuous support and understanding when completing my research and writing this paper. Their love, patience, and belief in me kept my spirits and motivation high during this project. 4 Abstract Medical emergencies are high-risk situations that occur infrequently. The patients outcome largely depends on the ability of the first responders and the effectiveness with which they provide emergency care. When healthcare providers are not confident in their ability to provide emergency care, this often leads to a delay in recognition of a deteriorating patient as well as action taken. Simulation-based learning can be utilized to improve healthcare workers confidence levels, thus improving their efficiency and effectiveness when responding to an emergency. The aim of this study was to improve the self-confidence levels of healthcare providers by implementing mock code simulations at routine 3-month intervals. The PICOT question for this project was: Do healthcare providers in the hospital have improved confidence from the implementation of mock code simulations at routine 3-month intervals? Simulation training allows participants to integrate knowledge learned while practicing skills without fear of patient harm. This practice innovation project was performed at Rush University Medical Center in the Interventional Services (IS) Department. It was implemented in three phases with the assistance of key stakeholders. The target population for this project was the healthcare providers participating in the mock code simulation scenarios. Sixteen participants completed two mock code simulation scenarios specific to the IS Department. Data collected by the DNP student shows an increase in self-confidence levels after mock code simulations. A paired t-test was used to analyze the pre-test and post-test simulation 1 data and showed a statistically significant increase (t = -10.894, n = 16, p = <0.001) in self-confidence as well as the pre-test and post-test simulation 2 data (t = -4.478, n = 16, p = 0.003) as scored by the participants using the VAS. Keywords: mock code simulation, confidence levels, healthcare providers 5 Contents Introduction .......................................................................................................................... 6 Background ........................................................................................................................... 7 Problem Statement ............................................................................................................... 8 PICOT Question..............................................................................................................................9 Objectives......................................................................................................................................9 Literature Review .................................................................................................................. 9 Concept Map ............................................................................................................................... 12 Scholarly Project and the Novice to Expert Theory ................................................................ 12 Implementation Model ........................................................................................................ 14 Social Entrepreneurship, Innovation, and Sustainability ....................................................... 15 Ethical considerations .......................................................................................................... 16 Risks and Benefits to Participants ................................................................................................. 16 Informed Consent and Confidentiality .......................................................................................... 17 Discussion of Methods ......................................................................................................... 18 Key Stakeholders ......................................................................................................................... 18 Participants Criteria and Recruitment ........................................................................................... 18 Interventional Plan ...................................................................................................................... 19 Demographic Qualitative & Quantitative Data .............................................................................. 19 Budget ......................................................................................................................................... 20 Data analysis....................................................................................................................... 21 Conclusion ........................................................................................................................... 26 Appendix A .......................................................................................................................... 27 Appendix B .......................................................................................................................... 29 Appendix C .......................................................................................................................... 30 Appendix D.......................................................................................................................... 31 Appendix E .......................................................................................................................... 32 Appendix F .......................................................................................................................... 33 References........................................................................................................................... 34 6 DNP Practice Innovation Project Proposal Paper Introduction Nurses are expected to have the ability to quickly and accurately notice when a patient is deteriorating and to intervene appropriately. Medical emergencies such as cardiac arrest are high-risk situations that occur infrequently. The patients outcomes are largely dependent on the ability of the first responders (most often nurses) to provide the emergency care required within the first few minutes of a cardiac arrest. In-hospital cardiac arrests (IHCA) in the U.S. have a 21% survival-to-hospital discharge rate (Adcock et al., 2020, p. 50). This outcome is often related to nurses hesitant and inadequate responses, leading to a delay in cardiopulmonary resuscitation (CPR). Not only do recent graduates respond with anxiety during a code situation, but experienced nurses respond with anxiety resulting in a delay in CPR initiation (Williams et al., 2016). It is vital to ensure that nurses are confident in their ability to provide high-quality CPR in emergency situations. Simulation-based education can improve nurses knowledge and communication skills when focusing on a deteriorating patient (Crowe et al., 2018). All nurses are required to be CPR certified, as CPR during a cardiac arrest is essential to restore blood flow to vital organs. Chu and Robilotto (2018) found that approximately 3 months after CPR training, nurses CPR skills decrease dramatically due to infrequent practice. Implementing simulation-based mock codes at routine intervals can improve nurses performance and self-confidence during code situations. Frequent practice opportunities for mock codes improved teamwork, response time, and confidence (McPhee, 2018). First responders must have the confidence and skill to take action during a cardiac arrest. In order to improve patient outcomes by increasing the self-confidence of healthcare providers, this Innovation Practice Project focused on the implementation of mock 7 code simulations in the Interventional Services (IS) Department at Rush University Medical Center (RUMC). Background An estimated 209,000 adult in-hospital cardiac arrests occur annually in the United States (Morton et al., 2019, p. 177). It is imperative for the patients survival that the nurses providing care to the patient react efficiently and effectively when performing lifesaving techniques such as CPR. Hospitals with active mock code programs and education achieved a higher percentage of defibrillation in less than two minutes (Josey et al., 2018). The American Heart Association (AHA) has added Booster Training to their updated 2020 CPR guidelines. These are frequent, brief sessions focused on the repetition of prior content (Merchant et al., 2020). Booster Training has been associated with improved CPR skill retention between certification classes (Merchant et al., 2020). The AHA has also encouraged the addition of in situ simulation training. In situ training occurs in actual patient-care areas and provides learners with a more realistic training environment. This DNP practice innovation project meets these two guidelines proposed by the AHA by providing in situ mock code training sessions at more frequent intervals. The target population for this project was the healthcare providers participating in the mock code simulation scenarios. The healthcare providers most likely to be involved in a code blue situation are registered nurses, health technicians, physicians and medical students, respiratory therapists, pharmacists, and nursing management (Dillion et al., 2018). When healthcare providers participate in mock code simulations, studies have demonstrated decreased fears and anxiety related to resuscitation, improved communication, and increased knowledge and familiarity with resuscitation guidelines (Hutcheson et al., 2020). More specifically, the 8 target population for implementation of this project was healthcare workers who provide direct patient care in the IS Department at RUMC who hold a current CPR certification. The implementation of mock code simulations is within the scope of the DNP-prepared APRN as the APRN, especially in critical care areas, will be leading and giving orders during a code and other emergency situations. The APRN should participate in all mock code simulations to ensure that all participants are on the same page and to provide education when necessary. It is imperative that the APRN work as a team with all participants to help increase participant knowledge and skills, thus increasing participants self-confidence levels. Debriefing should be performed during mock code simulations to review what participants believe went well and what did not during the simulation. The APRN should be well versed in debriefing as it is an essential aspect of providing education after medical emergencies. The doctorally prepared APRN plays a vital role during mock code simulations and has the ability to offer unique insights during training. Problem Statement When patients experience a medical emergency in the hospital, it is imperative for the healthcare provider to effectively and efficiently identify the deteriorating patient to provide the best possible outcome for the patient. This can be accomplished by increasing the confidence levels of healthcare providers through the implementation of mock code simulations. Simulation training provides clinical practice challenges while developing knowledge and skills in an open and trusting environment without the fear of harming patients, thus, reducing fear and anxiety (Ahmad et al., 2017). Through mock code simulation training, healthcare providers can develop an increase in confidence in their resuscitation skills, creating improved patient outcomes. 9 There is a need for increased research on the benefit of mock code simulations, as this is a relatively new phenomenon. With improved technology and the development of simulation labs with incredibly realistic simulation manikins, mock code simulations can create life-like emergency scenarios. The DNP project aims to explore the relationship between mock code simulations and participant self-confidence levels. Not only do mock code simulations improve participants self-confidence, but they contribute to nursing knowledge by providing education to all participants and reinforcing participant skills in emergency situations. Increasing awareness of patient safety and recent advances in technology are the main incentives to use simulation to teach and evaluate clinical competencies (Ahmad et al., 2017, p. 1). PICOT Question: Do healthcare providers in the hospital have improved confidence levels from the implementation of mock code simulations at routine three-month intervals? Objectives Implement mock code simulation scenarios in the IS department at RUMC to improve participant self-confidence levels. Increase awareness of the importance of mock code simulations at routine intervals to improve patient outcomes by deliberate practice, booster learning, and in situ education. Collaborate with key stakeholders at RUMC to identify the importance of mock code simulations and the need for evidence that can be translated into clinical practice. Literature Review During the last 20 years, simulations have become an essential part of education and training in healthcare (Al Gharibi & Arulappan, 2020). Simulation has evolved due to the increased demand of healthcare providers to deliver high-quality care to increasingly complex patients. Simulation training allows participants to integrate the knowledge learned while 10 practicing the skills. In situ mock code simulations significantly increase staff confidence levels (Herbers & Heaser, 2016). In their literature review of 11 articles, Al Gharibi & Arupallan (2020) examined the outcomes of repeated simulation experiences on self-confidence. The literature review results revealed a statically significant increase in the perceived level of participant self-confidence from baseline (63% increase). Lubbers & Rossman (2017) performed a quasi-experimental study using 61 undergraduate nursing students at a Midwestern college to evaluate the use of simulation by measuring novice learners' self-confidence and satisfaction levels. When implementing mock code simulations, Lubbers & Rossman (2017) suggest that the scenarios utilized be standardized, reproducible, clinically accurate, and mimic real-life situations. The students rated their selfconfidence and satisfaction levels using a 12-item Likert scale with scores ranging from 1 (strongly disagree) to 5 (strongly agree). The study reported that the students experience yielded a high level of self-confidence with the simulation experience, thus suggesting that simulationbased learning can be utilized to improve participant self-confidence levels in emergency situations. A study performed by Kiernan (2018) was designed to demonstrate the use of simulation technology to improve clinical competency and confidence in nurses, thus improving patient outcomes. The sample group in this study consisted of 40 adult nursing students. The students were separated into three groups to complete the simulation scenarios. Each student was asked to complete a pre- and post-test comprised of a Likert scale to rate their confidence levels. It was found that most students underestimated their ability to perform basic clinical skills. The students expressed increased confidence once the skills were reinforced in a safe and judgment-free 11 environment. Nursing students exposed to deliberate practice utilizing simulation are highly likely to be competent and confident in safely performing skills when caring for patients. Crowe et al. (2018) implemented a quality improvement program at a large tertiary hospital in Canada. No patient identifiers were included in the data provided for the study. This study focused on the impact of simulation education on post-licensure nurses working in a general medicine unit. The Adult Learning Theory was utilized in this study as Crowe et al. (2018) states that adult education is most impactful when engaging learners in activities related to their own experience. A 12-item self-confidence scale was created and validated for the purpose of this study. The simulation education sessions were performed over a three-week period where participants attended seven sessions in groups of six. Three hundred thirty-one nurses participated in the simulation sessions. An overall improvement in confidence was measured immediately after completion of the simulation education and at a three-month followup. Due to the scenarios provided for the simulations, it is reasonable to conclude that simulation-based learning can increase nurses confidence related to the deteriorating patient. Hossino et al. (2018) performed a study to assess the effects of simulation scenarios focused on resuscitation to improve confidence in medical residents. The authors argue that in order to become proficient in resuscitation, it is essential for healthcare providers to participate in real-life events routinely. Simulation scenarios allow for the practice of real-life events without the fear or possibility of harming a patient. Twenty-six residents participated in the simulation scenarios, each taking turns in all of the designated roles. After the simulations were completed, the residents completed a Likert scale questionnaire to assess their self-reported confidence levels. The study results revealed that simulation training has significant positive improvements in the self-reported confidence of residents. 12 Concept Map Scholarly Project and the Novice to Expert Theory Patricia Benners Novice to Expert Model was the theoretical framework used for this study. The phenomena of interest for the DNP Practice Innovation Project was the implementation of mock code simulations to improve participant confidence levels. Tiitinen et al. (2020, p. 234) defines theory as a set of interrelated concepts, definitions, and propositions that explain events or situations by specifying relationships among variables. Theories such as Patricia Benners Novice to Expert Model are helpful when implementing a quality improvement project as all participants will begin in the novice stage with the goal to advance to the expert stage. This theoretical framework helped the facilitator to understand the goal and guide participants through the learning process. Theories play a crucial role in developing quality improvement interventions. 13 The Novice to Expert Theory served as the foundational building block for the DNP project as mock code simulations have been shown to increase nursing skills, knowledge, and confidence. The use of simulation allows students clinical reasoning skills to evolve as they are able to perform skills in a real-world problem-solving context. Studies have revealed that many new graduate nurses lack professional confidence upon entry into professional practice (Ortiz, 2016). As nurses go through the phases of Benners Novice to Expert Theory, they gained confidence as their knowledge increased. Once a nurse has reached the expert phase, they `have the ability to confidently assess and react to the patients needs without losing time. The use of simulation can help to advance the nurses through these phases without the worry of harming patients in the learning process. Previous research supports that with better quality practice environments, the greater the outcomes for nurses and patients (Papastavrou et al., 2015). By improving the practice environment, nurses can learn to facilitate care according to the individualized needs of the patient. Individualized nursing care is a significant indicator of quality nursing care and should be integrated into nursing practice. Benners Novice to Expert Model helps guide nurses in their care practices by providing the theoretical framework (Ozdemir, 2019). The APRN plays a significant role in applying theory to the mock code simulation education sessions. The APRN helps to facilitate the learning environment to effectively educate participants and guide them through the phases of Benners Novice to Expert Model. The utilization of theory-based design is key to conducting research so it can, in turn, guide development efforts and improve professional practice (Hill et al., 2020). 14 Implementation Model The implementation model was split into three phases, pre-implementation, implementation, and post-implementation. The focus of the pre-implementation phase was the development of the simulation program. This included the planning and designing of the simulation scenarios specific to the Interventional Services (IS) Department patient population. Four simulation scenarios were developed in collaboration with the key stakeholders utilizing the most commonly occurring emergency situations in the IS Department. The 4 simulation scenarios were determined by reviewing the safety reports within the IS Department. The most commonly occurring safety events were adapted for the mock code simulation scenarios. This objective was completed with advice and collaboration from the CNS in the IS department. This phase also included gaining support from key stakeholders such as the unit leadership, nurses, physicians, pharmacists, and advanced practice providers. During the pre-implementation phase, the participants were divided into groups for each simulation and assigned a specific role according to their job title. The Visual Analog Scale (VAS) was selected during the preimplementation phase as the assessment tool for measuring confidence levels. VAS allows more variability in measurements as participants are not limited to only a few responses in order to express how they feel. The VAS allows for fine-grained measurements thus preventing measurement errors (Sung & Wu, 2018). Once the aforementioned tasks and a timeline were completed, the implementation phase began. This project was implemented in multiple phases through two mock code simulations approximately 2 months apart. The 2-month time period as opposed to a 3-month time period was chosen by the key stakeholders involved due to time constraints within the institution. The Interventional Services Department has approximately sixty employees. It was projected that it 15 would take 2 months for each member to participate in the first mock code simulation. At the end of this 2-month period, the second round of mock code simulations began, starting with the first group of participants trained. At the completion of the mock code simulation training, participants were assessed for a change in their knowledge and confidence level during code blue situations. The post-implementation phase of this project included data collection and analysis. The DNP student met with a statistician to receive advice regarding the data analysis. The data collected using the VAS assessment tool was analyzed to determine an improvement in the selfconfidence levels of each of the participants. The data was measured before and after each simulation experience resulting in 4 different data points. Data for only the participants who completed two mock code simulations were included in the quantitative data analysis. The final goal of this quality improvement project was to increase participants self-confidence levels through the implementation of mock code simulations, potentially increasing response time and patient outcomes. Social Entrepreneurship, Innovation, and Sustainability Sustainable health systems have adequate resources to meet their objectives and are able to adapt and evolve in a continuously changing environment. One way to achieve sustainability is by implementing improvements, interventions, and change strategies (Braithwaite et al., 2017). This DNP project fits with sustainability as the implementation of simulation-based mock codes can be a sustainable project through continual utilization of mock code scenarios to provide education and keep providers aware of the most up-to-date guidelines. Successful innovations often possess two essential qualities: usability and desirability (Kelly & Young, 2017). The DNP project fits into this description of innovation; it is desirable since it can be used to improve 16 patient outcomes by improving staff confidence and knowledge in emergency situations. It is usable and can be easily implemented with routine education. Social entrepreneurs act as change agents by improving systems and creating sustainable solutions (Altman & Brinker 2016). Engaged nurses on the frontlines are central to achieving and sustaining change. The concept of social entrepreneurship can help support nurses leading change initiatives. Healthcare social entrepreneurs seek creative solutions to problems, utilize insights to identify and mitigate problems, and tackle challenges in the context of scarce resources (Altman & Brinker, 2016, p. 30). The implementation of mock code simulations aligns with social entrepreneurship as it is a creative solution in helping to identify and mitigate issues that occur when there is an emergency situation. This helps to improve patient outcomes by delivering high-quality care. In healthcare, a social entrepreneur provides high-quality care with positive patient outcomes. This is done by the implementation of innovative ideas. Ethical considerations Risks and Benefits to Participants The participants in this study can benefit in many ways. Hospital staff who are inexperienced in emergency situations may have anxiety and are hesitant to begin resuscitation for fear they may perform a wrong action, cause harm to the patient, or are unsure of their roles and responsibilities (Lee et al., 2021). Lee et al. (2020) showed that participants self-confidence and knowledge are improved through simulation-based training. Repeated mock code training may be an effective strategy in providing increased confidence in the healthcare providers when delivering chest compressions, assessing for a pulse and breathing, identifying dysrhythmias, and using a cardiac monitor/defibrillator. Not only will this project benefit the participants, but the patients who are receiving care during emergency situations. When those providing care can 17 effectively and efficiently deliver care in an emergency situation, patients have improved outcomes. Mock code simulations are a helpful way to enhance team performance and enhance the quality of cardiac resuscitation (Hazwani et al., 2020). There are minimal risks to the participants, such as anxiety during the mock code simulations or mild discomfort related to the assessment of the individuals performance during the simulation experiences. Informed Consent and Confidentiality Informed consent (Appendix A) was obtained from each of the participants in this study. The participants were provided with adequate information concerning the study and were provided a sufficient opportunity to consider all risks and benefits of the study. It is imperative to ensure the participants have comprehended all information regarding the study in order to make an informed decision before agreeing to participate. The documented consent serves as a guide for the verbal explanation of the study. Issues relating to understanding, comprehension, competence, and voluntariness of clinical trial participants may adversely affect the informed consent process (Kadam, 2017, p. 107). Respecting participants confidentiality and privacy is considered as the participants rights (Noroozi et al., 2017). Inappropriate disclosure of information relating to the participants may threaten the participants reputation, opportunities, and human dignity. The DNP student was the only person who had access to the participants personal information needed for the study. The data collected throughout the course of the project was seen by the key stakeholders as well as the faculty involved in the project. Participants should not be identified by individuals who are not involved in the data collection process. Data was placed in a secure file cabinet that only this investigator and the CNS could access. The file cabinet was kept in the office of the CNS and remained locked when the CNS was not present. All electronic data was 18 held on the investigators personal laptop, which was password protected. If the data needed to be transferred electronically, it was encrypted through the Rush email system. The data will be stored for three years per the request of the CNS. Discussion of Methods Key Stakeholders The key stakeholders for this performance improvement project were those involved directly in the projects development. At Rush University Medical Center (RUMC), where the project was implemented, the key stakeholders were Megan Gross, the Interventional Services (IS) CNS, Janet Haw, the Unit Director (UD) of the IS department who was responsible for approving and overseeing the budget for the project, and Joe Canino, the Assistant Unit Director (AUD) who helped to assign each participant to a group. Together with the key stakeholders and the IS education committee at RUMC, mock code simulations were implemented in order to improve participant confidence levels during emergency situations. Participants Criteria and Recruitment Healthcare providers who work at Rush University Medical Center (RUMC) in the Interventional Services (IS) Department were the main focus of the practice innovation project. A sample of convenience was used to select the participants. The healthcare providers most likely to be involved in a code blue situation are registered nurses, health technicians, physicians and medical students, respiratory therapists, and nursing management (Dillion et al., 2018). When healthcare providers participate in mock code simulations, studies have demonstrated decreased fears and anxiety related to resuscitation, improved communication, and increased knowledge and familiarity with resuscitation guidelines (Hutcheson et al., 2020). More specifically, the target population for the implementation of this project was healthcare workers 19 who provide direct patient care in the IS Department at RUMC. Inclusion criteria for this study were those who have undergone basic life support (BLS) and/or advanced care life support (ACLS) training and who hold an active certification. In the IS Department, there are approximately 40 staff members who provide direct patient care, including nurses, radiology technicians, residents, attending physicians, and respiratory therapists. No recruitment techniques were necessary as the key stakeholders involved have provided their full support for this project and required all eligible staff members in the IS Department to participate. Interventional Plan This quality improvement project was implemented using three phases: preimplementation, implementation, and post-implementation. The tasks in the pre-implementation phase have been completed. Tasks in the pre-implementation phase included collecting literature, collaborating with key stakeholders, developing the program, and research focused on data collection methods. Once IRB approval was obtained from RUMC, the implementation phase began. The implementation phase has been provided in detail using a Gantt chart in Appendix C. Once the implementation phase was completed, the post-implementation phase began. During this phase, data analysis utilized the data collected during the implementation phase to perform a statistical analysis. Demographic Qualitative & Quantitative Data Demographic data was collected from participants including their job title, any certifications they hold related to their job title, and if they are BLS or ACLS certified. If the participant holds a current certification related to their role, data will be collected on the date of their last certification. Each participant will be asked how long they have worked in their current job position in the IS department This may help to provide additional feedback into their pre- 20 simulation confidence level. An example of the demographic questionnaire can be found in Appendix E. Qualitative data was examined throughout the research process. This form of data that was collected through participant observation and interviews was described as nonnumerical, qualitative data. An interview was performed at the end of each simulation experience. The first and second rounds of simulations were held 2 months apart at the request of the key stakeholders in the IS department. The participants were asked questions such as what went well and what did not go well. They were also asked what they learned from the experience and how the experience can be improved utilizing a post simulation survey. Mock code simulation scenarios can effectively increase skill compliance and staff confidence (Hutcheson et al., 2020). The quantitative data collected for this study was any change in the confidence of the participants ability to provide effective and efficient care during an emergency situation. The quantitative data utilized in this study was measured using the VAS at the completion of the mock code simulations. Once all participants completed the VAS provided, a statistical analysis was performed in order to assess the outcome of the quality improvement project. Only those participants who completed 2 mock code simulations were included in the quantitative and qualitative data. Budget The costs related to this project were costs associated with the hourly wage of participants. Since the UD had approved this project in the IS Department, the mock code simulations were performed during scheduled work hours. The second Wednesday of each month was reserved for educational purposes. This was when the mock code simulations were performed, thus not creating any additional costs for the department. A grant was received that 21 was utilized to access the simulation lab when necessary. An operational budget was created and is listed in Appendix D. Data analysis The statistical analysis for this project was performed by analyzing the VAS completed by participants and comparing their responses before and after each mock code simulation. A ttest can be used to determine if there is a significant difference between the means of the groups. The dependent variable measured in this study was improved participant self-confidence levels. The independent variable in this study was the implementation of mock code simulation scenarios at two-month intervals. It was determined by conducting a power analysis that 16 participants were needed for the appropriate sample size for this project. For this power analysis, an error probability of 0.05 and a power of 0.95 was used. An effect size of 0.70 was calculated resulting in a sample size needed of 16 for this study. A trend analysis measures the changes in the self-confidence levels of participants over time. Due to the small sample size required for the project, a statistician was who provided insight and advice on data organization was consulted but not needed for this project. Demographic Data A total of 16 participants completed two consecutive rounds of the mock code simulation scenarios in the IS Department. Each participant completed a demographic questionnaire. The mean age of the 16 participants who completed 2 mock code simulations was 37.8 years of age with the average length in the participants current role as 11.2 years. This study included a wide range of healthcare professionals with ages from 27-58 and experience ranging from 4 months to 17 years in the current job title. A total of 27 participants completed one mock code simulation. Those who were unable to complete two simulations were not included in this study. Additional 22 participants were unable to complete two mock code simulations due to scheduling conflicts and a high turnover rate during the course of the simulations. Over half of the participants held a certification related to their job title and all individuals were BLS and/or ACLS certified. The participants included seven Registered Nurses (RN) and nine Radiology Technicians (RT). No Physicians or Respiratory Therapists completed two mock code simulations and therefore were not included in the data. Out of the seven RNs, four held a certification (three Critical Care Registered Nurse, one Emergency Certified Registered Nurse) and five of the nine RTs held a VI (Vascular Interventional) certification. A VI certification formally prepares the RT to work in a Vascular Interventional Radiology setting such as the IS department at RUMC. Certification signifies a commitment to lifelong learning and the expectation of staying up to date and implementing evidence-based practice in daily care. Results The quantitative data were analyzed by this DNP student utilizing SPSS (Statistical Package for the Social Sciences). This DNP project used a pretest/posttest design in order to evaluate the self-confidence levels of participants after completing two mock codes simulations approximately 2 months apart. The post-test scores from the VAS scale were compared to the pretest scores of the VAS rating participants self-confidence levels for the 16 individuals who completed two mock code simulations. A paired t-test was used for this data analysis to compare the pre-test and post-test scores of participants' self-confidence levels in the first simulation utilizing the VAS. There was a statistically significant increase in self-confidence levels from the pre-test (M = 7.41, SD = 0.88), t (16) = -10.89, p < 0.001. The mean increase in self-confidence levels was 1.56 with a 95% confidence interval ranging from 7.40 to 8.97. The eta squared statistic ( -2.72) indicated a small effect size. A paired t-test was used for this data analysis to 23 compare the pre-test and post-test scores of participants self-confidence levels in the second simulation utilizing the VAS. There was a statistically significant increase in self-confidence levels from the pre-test (M = 7.40, SD = 1.20), t (16) = -4.48, p < 0.001. The mean increase in self-confidence levels was .97 with a 95% confidence interval ranging from 7.41 to 8.97. The eta squared statistic ( -1.12) indicated a small effect size. A total of 16 participants completed two rounds of mock code simulations and each completed a pre-and post-test questionnaire rating confidence levels. The mean pretest score for simulation 1 was 7.01 compared to the post-test mean of 8.97. The pretest mean for simulation 2 was 7.41, compared to the mean post-test score of 8.37. A paired t-test was used to analyze simulation 1 data and showed a statistically significant increase (t = -10.894, n = 16, p = <0.001) in self-confidence levels as scored by the participants on using the VAS. A paired t-test was also used to analyze simulation 2 data and showed a statistically significant increase (t = -4.48, n = 16, p = 0.003) in self-confidence levels as scored by the participants using the VAS. Statistical data from SPSS can be found in Tables 1-3. Table 1: Paired Samples Statistics Table 2: Paired Samples Correlations 24 Table 3: Paired Samples Test Discussion The results of this study show that with the implementation of mock code simulations at routine intervals, there is an increase in healthcare providers self-confidence levels. Thus, the null hypothesis is accepted. The pretest scores were 7.40 and 7.41 with the post-test scores averaging 8.97 and 8.38. Appendix B depicts the VAS scale utilized by participants when rating their self-confidence levels. While there was an increase in self-confidence levels from each pretest to post-test, simulation 2 showed a lower overall scoring in self-confidence levels. The decrease is accounted for in the difficulty level of the scenarios presented during the mock code simulations. Four scenarios were created in collaboration with the key stakeholders related to the most common emergency situations in IS. Two scenarios were presented during each simulation, starting with the least difficult. The scenarios created for the second round of simulations were deemed to be more difficult and complex by the key stakeholders. The scenarios were created in collaboration with the key stakeholders and the IS education committee chair. A study by Chu & 25 Robilotto (2018) showed that participants CPR skills and knowledge decrease significantly within 10 weeks after training. The decrease in the participants confidence level from the completion of the first simulation to the start of the second simulation is attributed to the knowledge lost during the time between simulations when the participants did not experience emergency situations. Qualitative data was collected during post-simulation debriefing where the participants provided feedback. After completion of the first simulation, participants requested a visual aid showing the patients heart rhythm which was not provided for the first simulation but was added for the second round of simulations. It was also noted that participants were more likely to engage when roles were assigned ahead of the simulation as opposed to asking for volunteers. Finally, participants stated the mock code simulations were very helpful. The participants stated they were looking forward to completing the simulations at routine intervals. Overall, this study has shown the importance of routine mock code simulations to improve participant selfconfidence levels. When healthcare providers have increased confidence in their skills, the literature suggests that providers are able to react quickly and effectively in emergency situations thus creating improved outcomes for patients. The strengths of this study include an adequate sample size of 16 participants as indicated by the power analysis performed. Another strength of this study is the use of a valid and reliable tool, the VAS, that was used by participants to rate their self-confidence levels. The study was not without limitations. One limitation was the high turnover rate in the IS department making it difficult for all participants to complete two simulations thus excluding many participants from the data analysis. Another limitation is that this project was started during the COVID-19 pandemic thus delaying the start time of the simulations. Due to this, only two rounds of 26 simulations were able to be performed before the completion of this project. With the help of the key stakeholders and the education committee at RUMC, this project will continue with mock code simulations at routine intervals and further data will be collected and analyzed. Conclusion This DNP performance improvement project aimed to improve the confidence levels of healthcare workers such as nurses, physicians, and radiology technicians during emergency situations, thus increasing patient outcomes. This project was implemented in multiple phases, including two mock code simulation scenarios specific to the IS department. Improving selfconfidence during emergency situations provides value to the hospital or facility where the project is implemented. This value is created when providers self-confidence increases, allowing them to react appropriately and efficiently when patients are deteriorating, thus improving patient outcomes. This project received support from the internal resources provided by the IS department and RUMC. The key stakeholders in this department were excited and willing to implement this project. A study performed by Herbers and Heaser (2016) found that after participating in mock code simulations, nursing staff reported an increase in confidence when initiating first-responder interventions. The results from this performance improvement project show an improvement in staff self-confidence resulting in improved efficiency and effectiveness in staff response during emergency situations. 27 Appendix A Informed Consent The Implementation of Mock Code Simulations to Improve Participant Confidence Levels in Emergency Situations: A Quality Improvement Study Researcher: Ellen Wray: BSN, RN, DNP-FNP Student Supported By: Saint Marys College & Rush University Medical Center What is the purpose of this study? This study aims to improve healthcare provider self-confidence levels in emergency situations through the implementation of mock code simulations. What will I do if I choose to be in this study? If you join this study, you will be asked to participate in two mock code simulation educational sessions approximately two months apart with other healthcare providers. You will also be asked to complete a brief demographic survey before the simulation and a self-confidence assessment before and after each simulation. After completing the mock code simulations, you will complete a short survey assessing your confidence levels. After completion of the study, the data you have provided will be analyzed for quality improvement purposes. You will not have to share any private information with other providers. You can leave the group at any time. There will be no penalty if you leave the group. What are the possible risks or discomforts? Perceived risks to this study are anxiety and discomfort to the participant related to the pre and post-assessment required for each simulation experience. What are the possible benefits for me or others? You will increase your knowledge of actions to be performed during emergency situations. In turn, you will possibly have improved self-confidence levels resulting in increased efficiency and effectiveness during emergency situations. This will lead to improved patient outcomes. What alternatives are available? You may choose not to join this study. What happens if I dont want to participate anymore? 28 If you join this study, you may leave any time. There will be no penalty if you leave the study. Will it cost me anything to participate? It is free to join this study. Will I get paid anything if I participate? You will be paid your hourly wage during the time you participate in the study. What are my rights? You have the right to be treated with respect. You have the right to leave the study at any time. You have the right to answer or not answer our questions. You do not have to join this study. What about my confidentiality and privacy rights? You will not be asked to share private information with the other participants. Any information you write about yourself will be confidential. Your name will never be used in the study report. For additional questions or concerns, please contact Ellen Wray at ellen_wray@rush.edu. Consent I have read this form about the study or had it read to me. Any questions I have about this study have been answered. I understand the information about the study. I agree to join this study but can leave this study at any time. I will receive a copy of this form. ___________________________ Signature of Subject ___________________________ Date 29 Appendix B Visual Analog Scale 30 Appendix C Gantt Chart 31 Appendix D Program Budget Interventional Services Mock Code Simulation Program Budget Direct Fringe Costs Cost Category Units Rate Costs (22%) Facilities Simulation Lab 1 hour $29.36/hr $29.36 $0.00 IS Procedure Room 1 hour $0.00/hr $0.00 $0.00 Total Cost $29.36 $0.00 Personnel Radiology Techs (RT) 1 hour (RN x 20) 1 hour (RT x 20) Equipment Crash Cart Respiratory Supplies Documentation 1 cart 1 bag 1 computer $300 rental $25.00 per bag $0.00 $300.00 $25.00 $0.00 Educational Program Development 1 DNP Student 1 CNS in IS Department 30 hours 15 hours $40.00 $52.00 $1,200.00 $264.00 $780.00 $171.60 $1,464.00 $951.60 RN - $40.00/hr $1,200.00 $264.00 $1,464.00 RT - $30.00/hr DNP Student $40.00/hr CNS - $52.00/hr $780.00 $171.60 $951.60 $40.00 $52.00 $8.80 $11.44 $48.80 $63.44 Nurses (RN) $40.00/hr $800.00 $176.00 $976.00 $30.00/hr $600.00 $132.00 $732.00 $0.00 $0.00 $0.00 $300.00 $25.00 $0.00 Program Maintenance Routine 6-month intervals 1 hour (RN x 20) 1 hour (RT x 20) 1 hour 1 hour Total Cost $7,005.80 32 Appendix E Demographic Questionnaire 1. Age _____ 2. Job title: RN RT PHYSICIAN RESPIRATORY PHARMACY OTHER _______ 3. Do you hold any certifications? YES NO 4. What are they? _________ 5. Date you received your most recent certification ________ 6. Are you CPR or ACLS certified? YES NO 7. How long have you worked in your current role? _______ 8. How many years of experience do you have in your job title? _______ 33 Appendix F CITI Certificate 34 References Adcock, S., Kuszajewski, M. L., Dangerfield, C., & Muckler, V. C. (2020). Optimizing nursing response to in-hospital cardiac arrest events using in situ simulation. Clinical Simulation in Nursing, (2020). https://doi.org/10.1016/j.ecns.2020.05.006 Ahmad, A. A., Nannette, N., & Sheila, T. (2017). The use of simulation training to improve knowledge, skills, and confidence among healthcare students: a systematic review. Internet Journal of Allied Health Sciences and Practice, 15(3), 22. Al Gharibi, K. A., & Arulappan, S. J. (2020). Repeated simulation experience on selfconfidence, critical thinking, and competence of nurses and nursing studentsan integrative review. Sage Open Nursing, 6, 237796082092737237796082092737. https://doi.org/10.1177/2377960820927377 Altman, M., & Brinker, D. (2016). Nursing social entrepreneurship leads to positive change. Nursing Management, 47(7), 2832. https://doi.org/10.1097/01.NUMA.0000484476.21855.50 Braithwaite, J., Testa, L., Lamprell, G., Herkes, J., Ludlow, K., McPherson, E., Campbell, M., Holt, J. (2017). Built to last? the sustainability of health system improvements, interventions and change strategies: a study protocol for a systematic review. Bmj Open, 7(11). https://doi.org/10.1136/bmjopen-2017-018568 Chu, R., & Robilotto, T. (2018). Mock code training to enhance cpr skills. Nursing Made Incredibly Easy, 16(2), 1115. https://doi.org/10.1097/01.NME.0000529957.11904.8d Crowe, S., Ewart, L., & Derman, S. (2018). The impact of simulation-based education on nursing confidence, knowledge and patient outcomes on general medicine units. Nurse Education in Practice. 35 Dillon, P., Moriarty, H., & Lipschik, G. (2018). Using simulation with interprofessional team training to improve code performance. Journal of Interprofessional Education & Practice, 11, 6772. https://doi.org/10.1016/j.xjep.2018.01.002 Hazwani, T. R., Alosaimi, A., Almutairi, M., Shaheen, N., Al, H. Z., & Antar, M. (2020). The impact of mock code simulation on the resuscitation practice and patient outcome for children with cardiopulmonary arrest. Cureus, 12(7), 9197. https://doi.org/10.7759/cureus.9197 Herbers, M. D., & Heaser, J. A. (2016). Implementing an in situ mock code quality improvement program. American Journal of Critical Care : An Official Publication, American Association of Critical-Care Nurses, 25(5), 3939. https://doi.org/10.4037/ajcc2016583 Hill, J., Cuthel, A. M., Lin, P., & Grudzen, C. R. (2020). Primary palliative care for emergency medicine (prim-er): applying form and function to a theory-based complex intervention. Contemporary Clinical Trials Communications, 18. https://doi.org/10.1016/j.conctc.2020.100570 Hossino, D., Hensley, C., Lewis, K., Frazier, M., Domanico, R., Burley, M., Harris, J., Miller, B., & Flesher, S. L. (2018). Evaluating the use of high-fidelity simulators during mock neonatal resuscitation scenarios in trying to improve confidence in residents. Sage Open Medicine, 6, 205031211878195205031211878195. https://doi.org/10.1177/2050312118781954 Hutcheson, J., Waggoner, B., Gephart, B., Case, L. A., Pearcy, A., & Zehner, S. (2020). The implementation of pediatric quarterly mock codes and its impact on resuscitation skills compliance. Journal of Pediatric Nursing, 55, 266269. https://doi.org/10.1016/j.pedn.2020.09.005 36 Josey, K., Smith, M. L., Kayani, A. S., Young, G., Kasperski, M. D., Farrer, P., Raschke, R. A. (2018). Hospitals with more-active participation in conducting standardized in-situ mock codes have improved survival after in-hospital cardiopulmonary arrest. Resuscitation, 133, 4752. https://doi.org/10.1016/j.resuscitation.2018.09.020 Kadam, R. A. (2017). Informed consent process: A step further towards making it meaningful! Perspectives in Clinical Research, 8(3), 107112. https://doi.org/10.4103/picr.PICR_147_16 Kelly, C. J., & Young, A. J. (2017). Promoting innovation in healthcare. Future Healthcare Journal, 4(2), 121125. https://doi.org/10.7861/futurehosp.4-2-121 Kiernan, L. C. (2018). Evaluating competence and confidence using simulation technology. Nursing, 48(10), 4552. https://doi.org/10.1097/01.NURSE.0000545022.36908.f3 Lee, S. J., Johnson, W., & Liddell, T. (2021). Quality improvement for self-confidence, criticalthinking, and psychomotor skills in basic life support of nursing health professionals through case-scenario simulation training. Journal of Nursing Education and Practice, 11(8), 2323. https://doi.org/10.5430/jnep.v11n8p23 Lubbers, J., & Rossman, C. (2017). Satisfaction and self-confidence with nursing clinical simulation: novice learners, medium-fidelity, and community settings. Nurse Education Today, 48, 140144. https://doi.org/10.1016/j.nedt.2016.10.010 McPhee, K. (2018). Deliberate practice mock codes for new graduate nurses. Journal for Nurses in Professional Development, 34(6), 348351. https://doi.org/10.1097/NND.0000000000000494 Merchant, R. M., Topjian, A. A., Panchal, A. R., Cheng, A., Aziz, K., Berg, K. M., Lavonas, E. J., Magid, D. J., & Adult Basic and Advanced Life Support, Pediatric Basic and 37 Advanced Life Support, Neonatal Life Support, Resuscitation Education Science, and Systems of Care Writing Groups. (2020). Part 1: executive summary: 2020 american heart association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Circulation, 142(16_suppl_2), 357. https://doi.org/10.1161/CIR.0000000000000918 Morton, S. B., Powers, K., Jordan, K., & Hatley. A. (2019). The effect of high-fidelity simulation on medical-surgical nurses' mock code performance and self-confidence. Medsurg Nursing, 28(2). Noroozi, M., Zahedi, L., Bathaei, F. S., & Salari, P. (2018). Challenges of confidentiality in clinical settings: Compilation of an ethical guideline. Iranian Journal of Public Health, 47(6), 875883. Ortiz, J. (2016). New graduate nurses' experiences about lack of professional confidence. Nurse Education in practice, 19, 19-24. Ozdemir, N. G. (2019). The Development of Nurses Individualized Care Perceptions and Practices: Benner's Novice to Expert Model Perspective . International Journal of Caring Sciences, 12(2), 12791285. Papastavrou, E., Acaroglu, R., Sendir, M., Berg, A., Efstathiou, G., Idvall, E., Kalafati, M., Katajisto, J., Leino-Kilpi, H., Lemonidou, C., Deolinda Antunes da Luz, M., Suhonen, R. (2015). The relationship between individualized care and the practice environment: An international study. International Journal of Nursing Studies, 52(1), 121133. https://doi.org/10.1016/j.ijnurstu.2014.05.008 38 Sung, Y.-T., & Wu, J.-S. (2018). The visual analogue scale for rating, ranking and pairedcomparison (vas-rrp): a new technique for psychological measurement. Behavior Research Methods, 50(4), 16941715. https://doi.org/10.3758/s13428-018-1041-8 Tiitinen, S., Ilomki, S., Laitinen, J., Korkiakangas, E. E., Hannonen, H., & Ruusuvuori, J. (2020). Developing theory- and evidence-based counseling for a health promotion intervention: A discussion paper. Patient Education and Counseling, 103(1), 234239. https://doi.org/10.1016/j.pec.2019.08.015 Williams, K. L., Rideout, J., Pritchett-Kelly, S., McDonald, M., Mullins-Richards, P., & Dubrowski, A. (2016). Mock code: A code blue scenario requested by and developed for registered nurses. Cureus, 8(12), 938. https://doi.org/10.7759/cureus.938 ...
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- ... 1 The Cubbin and Jackson Scale: Accurately Assessing at Risk Patients for Pressure Ulcers Yumi Otsuka Family Nurse Practitioner Track Department of Nursing, Doctor of Nursing Practice Program Faculty Team Leader: Dr. Patricia Keresztes 2 Table of Contents Introduction 4 Background 5 Problem Statement 6 PICOT Question 8 Development of Pressure Injuries: Pathophysiology 8 Definitions of Key Terms Immobility Malnutrition Reduced Blood Flow Sensory Loss Chronic Illnesses 9 9 10 10 11 11 Literature Review Article 1 Article 2 Article 3 Article 4 Strengths, Weaknesses, and Gaps in Knowledge 11 DNP Practice Innovation Project 14 Nursing Theory: Betty Neumans Systems Model 14 Broad Overview of the Theory 15 Central Assumptions of the Model Nursing Person Health Environment 15 Key Concepts of the Model 17 Defining a Role of Nurse Utilizing Systems Model 17 Systems Model as a Foundation for Scholarly Project 17 Implementation Plan: Retrospective Data Analysis 18 Implementation Model: The John Hopkins Nursing Evidence-Based Practice Model 19 11 12 12 13 13 15 16 16 16 3 Project Sustainability 20 Ethical Considerations Human Protection through the IRB Benefits and Risks of the Project Anonymity and Confidentiality 21 Methods Stakeholders Participant Criteria 23 Operating Budget Details Tech Support and Software Equipment Clinical Project Support Team 26 Data Analysis Quantitative Data Qualitative Data 27 Conclusion 34 References 35 Appendices 41 21 22 22 23 23 26 26 26 27 27 Abstract 4 Incidence of hospital acquired pressure injuries continues to be problematic across the nation. Critically ill adults are some of the most vulnerable populations in acute care settings. When they develop pressure injuries during hospitalization, they suffer physically, emotionally, and financially. Preventive interventions of such devastating incidents should be implemented to avoid the events. Continuous improvement of such protocol should be in place to keep improving the tools to protect some of the most vulnerable individuals. At the Critical Care Center of Elkhart General Hospital, retrospective data analysis was conducted to compare the risk when utilizing the Braden scale and the Cubbin and Jackson scale. Data was gathered on four different individuals who met the criteria for participation with a total ICU days of 81-84. Both assessment tools predicted risk accurately as evidenced by statistical significance, however the Cubbin and Jackson scale predicted better than the Braden scale explained by their strengths of correlation. This important finding should not be ignored as it could influence the future practice of pressure ulcer risk assessment in critically ill adults. Keywords: pressure ulcer prevention, critically ill, the Braden scale, the Cubbin and Jackson scale Introduction The National Pressure Ulcer Advisory Panel updated the definition of pressure injuries as a localized destruction of the skin and underlying tissue over a bony area or related medical or other equipment (n.d.). Pressure ulcers (PUs) are a major health issue both nationally and 5 internationally. Berlowitz (2019) shares in UpToDate that approximately 2.5 million pressure injuries are treated annually in acute care settings in the United States alone (as cited in Reddy, 2006; Lyder, 2003). Patients in the Intensive Care Unit (ICU) are at an increased risk for acquiring pressure ulcers due to the extent of illness, injury, and intensive treatment. Pressure related skin injury occurrence in critical care settings varies from 8.8 to 23% (Krupp & Monfre, 2015). Pressure ulcers can be prevented by taking appropriate preventative measures. Institutions across the world have been implementing preventative measures; however, statistics indicate that current interventions may not be fully effective in preventing these unfortunate events. Not only are patients affected physically with the development of a pressure injury, they are also affected financially and emotionally. Increased healthcare costs can occur with extended hospital stays due to pressure ulcer accumulation, which are an unnecessary and avoidable financial burden. According to a systematic review conducted by Demarre et al. (2015), the cost of treating hospital acquired pressure ulcers (HAPUs) was substantially higher than the prevention of pressure ulcers. Individuals living with pressure ulcers may experience depression, social isolation, pain, or discomfort (Mayo Clinic, 2018). Prevention is necessary to protect at risk individuals from hospital acquired pressure ulcers. Background The development of pressure injuries is multifactorial. Berlowitz (2019) explains that external forces and their interaction with the host environment is what ultimately results in tissue damage. Pressure applied to the skin leads to tissue damage thus preventing oxygenation and delivery of nutrients which results in tissue hypoxia, accumulation of waste products and free radical generation (Berlowitz 2019). Pressure is not the only factor associated with development of pressure injuries. Friction results in an abrasion with damage to the most superficial layer of 6 skin (Berlowitz, 2019). Compression of the skin results in damage to muscle (Berlowitz, 2019). Local blood vessels and lymphatics are stretched by shear forces and experience angulation and trauma (Berlowitz, 2019). Shear forces act as an additive component in that in the presence of pressure, worsened tissue damage will occur (Berlowitz, 2019). Understanding the etiology of pressure related skin injuries, minimizing shear forces, friction, and compression is critical in order to avoid pressure injuries in acute care settings. Ebi et al. (2019) revealed that many nurses have insufficient knowledge regarding pressure ulcer prevention measures. Nurses who read academic journals and attend training were revealed to have more knowledge regarding the topic (Ebi et al., 2019). Knowledge can be enhanced through education and awareness, ultimately enhancing patient outcomes. Shortage of pressure relieving devices, lack of staff/heavy workload and inadequate training were the most frequently reported barriers to practice (Ebi et al., 2019). Staff should have all the required items to perform at their best to properly implement appropriate pressure injury prevention measures. Through this scholarly DNP Project, nurses will gain knowledge on accurate assessment of pressure ulcer risk. This phenomenon is within the scope of practice of Advanced Practice Registered Nurse (APRN). American Nurses Association (ANA) points out that APRNs engage in continuous education to stay updated on any methodological, technological, or other developments in the field (n.d.). The role of APRN encourages preventative nursing measures to confront the problem of pressure ulcers instead of utilizing a medical approach. Problem Statement Critically ill patients are some of the most vulnerable individuals to develop PUs. Their increased risk for acquiring PUs relates to the etiology of PUs. Shear forces, friction, and 7 compression can all be affected by the way patients are transferred and repositioned. Often, critically ill individuals heavily rely on bedside staff for transfers and repositioning. Adequate training in the technique of transferring and repositioning patients, proper use of body mechanics, and adequate staffing are some of the key factors influencing patient outcomes with pressure ulcer development. The DNP Practice Innovation Project allows future APRNs to be innovative in finding solutions to the many issues linked to pressure related skin injury in critical care. This scholarly DNP project addressed one of the ways to identify at-risk populations within a critical care setting to place appropriate and specific preventative interventions to critically ill patients. Predictability of the Cubbin and Jackson scale was assessed utilizing retrospective data retrieved from electronic medical records (EMRs). The Cubbin and Jackson scale, an ICU specific pressure ulcer risk assessment developed by Cubbin and Jackson consisting of age, weight, general skin condition, mentation, hemodynamics, respiratory function, nutritional status, mobility, incontinence, and hygiene was utilized in this project (1991). Risk assessed utilizing the Cubbin and Jackson scale was compared to already existing data of the Braden scale. The Braden scale composes the following six areas, including sensory perception, moisture, activity, mobility, nutrition, and friction/shearing (Bergstrom et al., 1987). Through statistical analysis determining Cronbachs alpha coefficient, both the Cubbin and Jackson scale and the Braden scale have been found to be reliable in measuring pressure ulcer risk (Abidelli & Korkmaz, 2019). Furthermore, the predictive validity of the scales confirmed validity (Abidelli & Korkmaz, 2019). A retrospective data analysis of the Cubbin and Jackson scale and the Braden scale can lead to additional supportive data to appreciate the values of these tools. Nursing knowledge will be expanded with the success of this project. 8 PICOT Question PICOT Question: Do critically ill adult patients experience less pressure related skin injuries when risk is assessed utilizing ICU specific risk assessment tools? Population (P) is critically ill adult patients. Intervention (I) is ICU specific pressure ulcer risk assessment tool, the Cubbin and Jackson scale. Comparison (C), data analyzed utilizing retrospective data will be compared to already existing scores of the Braden scale. Outcome (O) will be measured by the development of PUs in the ICU setting. Time (T) will be June of 2020 to December of 2020. Objectives The following objectives clearly reflect the background and problem of HAPUs in a critical care setting. The objectives for this project were: (1) To reduce the incidence of HAPUs in a critical care setting. (2) To improve patient outcomes related to HAPUs by accurately identifying at risk patients, placing appropriate prevention measures, and reducing healthcare costs. Development of Pressure Injuries: Pathophysiology Development of pressure injuries is multifactorial. Berlowitz (2020) explains that external forces and their interaction with the host environment is what ultimately results in tissue damage. Traditionally, it has been taught that moisture, friction, and shear are associated with development of pressure injuries, but other factors may contribute as well (Berlowitz, 2020). Pressure applied to the skin leads to tissue damage thus preventing oxygenation and delivery of nutrients which results in tissue hypoxia, accumulation of waste products and free radical generation (Berlowitz, 2020). It has been shown that pressure higher than 70mmHg for longer than two hours leads to irreversible tissue damage (Berlowitz, 2020). A patient lying on a traditional hospital mattress may experience pressures of 150 mmHg (Berlowitz, 2020). This 9 warrants the importance of turning and repositioning every two hours to off load the pressure affected areas. Pressure is not the only factor associated with development of pressure injuries. Friction results in an abrasion with damage to the most superficial layer of skin (Berlowitz, 2020). Compression of the skin results in damage to muscle (Berlowitz, 2020). Local blood vessels and lymphatics are stretched by shear forces which also experience angulation and trauma (Berlowitz, 2020). Shear forces act as an additive component in that in the presence of pressure, worsened tissue damage will occur (Berlowitz, 2020). In addition to repositioning and turning every two hours, technique to do so while minimizing shear forces, friction, and compression is critical to avoid pressure injuries in acute care settings. Definitions of Key Terms Berlowitz (2020) lists immobility, malnutrition, reduced blood flow, and sensory loss as risk factors for developing pressure injuries. Immobility As the patient is sedentary, one would experience more compression and pressures added to the body surfaces as well as friction and shear while getting repositioned and turned. Through multiple regression analyses, Lindgren et al. (2004) determined that immobility served as a significant risk factor in acquiring pressure injuries. Additionally, increased age, prolonged hospitalization, lower body weight, and undergoing surgical treatment were strongly correlated with the incidence of pressure injuries (Lindgren et al., 2004). Patients in the ICU often experience prolonged hospitalization and surgical treatment due to the complexity of their illnesses and injuries. These risk factors are relevant to critically ill adult patients. 10 Malnutrition A malnutrition universal screening tool (MUST) served to assess nutritional deficiencies in participants in the study conducted by Tsaousi et al. (2015). Poor nutritional status was found to be a significant determinant for the development of pressure injuries (Tsaousi et al., 2015). Advanced age, low Body Mass Index (BMI), poor health status by self-report, serious mood disorders, abnormal appetite status, less than normal amount of food intake in quantity, an artificial diet, limited to no autonomy in Activities of Daily Living (ADLs) were determined to be statistically significant risk factors with P value of less than 0.001 (Tsaousi et al., 2015). In critical care settings, malnourished older adults are seen. Artificial diets such as tube feeding and total parenteral nutrition (TPN) are utilized when patients are unable to consume nutrients orally. Practitioners can be more aware of patients pressure related skin injuries through nutritional assessment. Reduced Blood Flow Vasopressors are often required in critically ill individuals to restore mean arterial pressure (MAP) when experiencing a shock. Cox and Roche (2015) concluded that norepinephrine and vasopressin were significantly linked to pressure injuries. Additionally, MAP less than 60 mmHg in individuals requiring vasopressors, mechanical ventilation longer than 72 hours, and cardiac arrest were anticipating factors to develop pressure injuries (Cox & Roche, 2015). As these vasopressors are often utilized in critical care, special consideration needs to be included when delivering care. Minimizing the use of vasopressors should be practiced, limiting the exposure to vasopressors in critically ill adults. Analyzing retrospective data, Ahtiala et al. (2018) concluded that long length of stay (LOS) of three or more days and low hemoglobin concentration (less than 100 g/l) were 11 predictive factors for developing pressure injuries in the ICU setting. Patients in the ICU are often hemodynamically unstable. Restoring hemoglobin through blood transfusion when indicated should be considered as low hemoglobin concentration has been found to be linked to manifestation of pressure injuries. Sensory Loss When one has limited sensation, chances are that the person may not understand the amount of pressure and/or compression that is being applied to body surfaces. Chronic Illnesses Jaul et al. (2018) determined that chronic illnesses compromising mobility, tissue perfusion, and malnutrition are associated with the manifestation of pressure injuries. This finding is significant to the population of adult ICU patients as they are often chronically ill experiencing comorbidities. Literature Review Literature review was conducted through Google Scholar, PubMed, and the Cumulative Index of Nursing and Allied Health (CINAHL) utilizing key terms Pressure Ulcer Intervention, the Braden Scale, the Cubbin and Jackson scale. The chosen articles were issued within the last five years to stay current on the topic. The literature was carefully examined to serve as the foundation for the DNP Practice Innovation Project. Article 1 Adibelli and Korkmaz (2019) evaluated and compared the reliability and predictive validity of the Cubbin and Jackson scale and the Braden scale. Pressure Injury (PI) risk was assessed utilizing the Braden scale which was followed using the Cubbin and Jackson scale (Adibelli & Korkmaz, 2019). The study population was ICU patients in a tertiary level university 12 hospital in Turkey consisting of 176 individuals (Adibelli & Korkmaz, 2019). Both scales are reliable and valid, but the Cubbin and Jackson scale demonstrated more accurate ability to assess both patients at risk and patients not at risk than the Braden scale (Adibelli & Korkmaz, 2019). Article 2 Ahtiala, Soppi, and Kivimaki (2016) evaluated predictability of each category of the modified Cubbin and Jackson scale. Data from the ICU databases was analyzed retrospectively utilizing logistic regression and analysis of linearity and weight (Ahtiala et al., 2016). The seven out of 12 main categories (incontinence, mobility, medical history, oxygen requirement, need for assistance with hygiene, and hemodynamics, and general skin condition) were found to be significantly associated with the development of pressure injury or to the total score of the scale (Ahtiala et al., 2016). Article 3 Through retrospective data, Ahtiala, Laitio, and Soppi (2018) assessed if therapeutic hypothermia (TH) patients are at an increased risk for acquiring pressure ulcers compared to non-TH patients. Following successful resuscitation, a survivor of cardiac arrest is at increased risk for additional cardiac arrhythmia and brain damage due to lack of oxygen which occurred during cardiac arrest. John Hopkins Medicine explains that by lowering body temperature through TH, damage to the brain can be reduced (n.d.). TH patients experienced more pressure ulcers than non-TH patients (Ahtiala et al., 2018). Defined by the modified Jackson and Cubbin scale, more patients in the TH group were identified as high risk for pressure ulcers (Ahtiala et al., 2018). 13 Article 4 Another scholarly article evaluated multiple risk assessment tools including Braden, Norton, Waterlow, and Cubbin and Jackson Scale. Pattanshetty et al. (2015) concluded that the Cubbin and Jackson had the best predictive value among the rest of the scales making this scale the best scale to predict pressure ulcer risk in critically ill patients. The setting of the study was medical and surgical ICU in India (Pattanshetty et al., 2015). The finding was reassuring that Cubbin and Jackson scale has the potential to positively influence patient outcome in the ICU setting. Strengths, Weaknesses, and Gaps in Knowledge There was obvious favoritism to the Braden scale for predicting pressure injuries risk assessment. Compared to Cubin and Jackson, Braden scale had a significantly higher yield of articles when researching pressure ulcer risk assessment tools via search engines. Limited selection of articles was due to the narrowing of search results by only showing articles published within the last five years. Overall lack of research on the Cubbin and Jackson scale warranted for more investigation to assess predictability of the scale. Having a focused participant group of ICU patients was identified as a strength of the studies as unique needs and vulnerabilities of this group were addressed. Critically ill patients are at increased risk for developing pressure related skin injuries not to mention the recovery from these injuries would be extremely challenging considering their state of illness or injury. Having a variety of practice settings and countries helped in generalizing the findings. Limited repositioning capability due to patient condition and treatment and potential additional pressure caused by equipment were limitations that negatively affected the outcome of 14 intervention. Understanding these potential barriers help to better prepare for these challenges and maximize the effect of intervention by formulating a plan. DNP Practice Innovation Project Many institutions including the Critical Care Center of Elkhart General Hospital in Elkhart, Indiana utilize the Braden scale to assess pressure injury risk, however incidence of pressure related skin injuries continue to be problematic in clinical settings. Literature review on the Cubbin and Jackson scale revealed that such a scale has been found to be effective in accurately predicting risk. By predicting risk accurately, clinicians have the opportunity to maximize the available resources of pressure injury prevention devices and equipment. Retrospective data analysis allowed the Cubbin and Jackson scale to be applied without interrupting patient care and changing the course of treatment. Comparing statistical findings of the Braden and the Cubbin and Jackson scale allowed for evaluation on the predictability of each scale. By raising awareness on the issue of pressure injury in critically ill patients and empowering bedside staff through this scholarly project, patient outcomes can be positively improved. Growth in clinical knowledge is attained by staying current in practice. This scholarly project promoted both expansion of clinical knowledge and improved patient outcomes. Nursing Theory: Betty Neumans Systems Model Consideration of nursing theory is imperative when translating scholarly findings into practice through a DNP project. Nursing theory served as the foundation of the project and ideas implemented. The pressure-related skin injury prevention project focuses on avoiding harmful events as a result of pressure-related skin injuries in critically ill adult patients. As the project focused on taking proactive measures in pressure-related skin injuries, it should be considered 15 that primary prevention was set in place. Primary prevention refers to actions intended to avert from the manifestation of a disease/injury (World Health Organization, 2019). Additionally, secondary, and tertiary prevention are in place to lessen the burden of disease and injury. Betty Neuman, a nursing theorist focused on systematic prevention measures to promote health. Broad Overview of the Theory Systems Model reflects on the nature of living organisms in interaction with each other and with the environment. When balance/stability of an organism is disrupted and the stabilizing process fails or when the organism remains in a state of disharmony for too long, illness and injury may develop. Neuman utilizes the concept of levels of prevention from Caplans conceptual model (1964) and applies it to nursing practice. Utilizing primary prevention, secondary prevention, and tertiary prevention, illness and injury are preventable. Neuman also incorporated Gestalt Theory and the philosophical views of de Chardin and Marx to formulate The Systems Model (Lawson, 2014). Central Assumptions of the Model Lawson identified nursing, person, health, and environment as central assumptions of Systems Model. In the following sections, each assumption is discussed. Nursing Neuman identifies nursing as a unique profession in that it is concerned with all of the variables affecting an individuals response to stress (Lawson, 2014, p. 285). Care is influenced by the nurses perception; therefore, the perceptual field of the caregiver and the patient needs to be assessed (Lawson, 2014). 16 Person The concept of person is presented as an open client system in reciprocal interaction with the environment. The client may be the following: an individual, family, group, community, or social issue. Interrelationships among physiological, psychological, sociocultural, developmental, and spiritual factors composite of the client system (Lawson, 2014). Health Considering health as a continuum of wellness to illness that is dynamic in nature and is constantly changing, Neuman states that, Optimal wellness or stability indicates that total system needs are being met. A reduced state of wellness is the result of unmet systemic needs (Lawson, 2014, p. 287). Environment Neuman identifies the environment as all the internal and external factors that affect the client system. Intrapersonal, interpersonal, and extrapersonal stressors are expressed as environmental factors that interact with and potentially change client system stability (Lawson, 2014). Neuman classifies three relevant environments: internal, external, and created. The internal environment: intrapersonal, with all interactions contained within the client. The external environment: interpersonal or extra personal, with all factors arising from outside the client. The created environment is unconsciously established and is utilized by the client to support protective coping. It is primarily intrapersonal (Lawson, 2014). 17 Key Concepts of the Model Taking a holistic approach, clients are viewed as a whole person whose parts are in dynamic interaction (Lawson, 2014). Stressors interfere with ones stability which results in illness and injury. Systems Model aims to minimize the risk of instability through prevention implementation. Primary Prevention Decrease the chance of an encounter with stressors. Build stronger and a more flexible line of defense. Secondary Prevention Early detection to minimize the damage of injury and illness Treatment of symptoms to prevent illness and injury from getting worse Tertiary Prevention Readaptation after the illness/injury Reeducation to avoid future occurrences Maintenance of stability to strengthen the system (Lawson, 2014). Defining a Role of Nurse Utilizing Systems Model Utilizing Systems Model, a nurse should consider various levels of prevention. A nurse needs to understand that injury and illness are results of instability of ones system. Therefore, maintaining stability through prevention is critical in ones wellbeing. Being proactive in prevention may improve ones quality of life. Systems Model as a Foundation for Scholarly Project Neumans Systems Model was utilized as a foundation for the proposed practice innovation project. This theory assumes that illness and injury occur when the line of defense is 18 broken by the stressors causing instability within the system. That disruption of the system can be prevented by primary, secondary, and tertiary prevention. Primary prevention measures include turning and repositioning every two hours, adequate hydration, and nutrition. Secondary preventions include the use of a risk assessment scale and skin checks done by a preassigned nurse. Tertiary prevention includes preventing further damage by various means or treatment approaches such as with a wound vacutainer, dressing usage, and Venelex Ointment. This scholarly project fell into the category of secondary prevention. Implementation Plan: Retrospective Data Analysis The DNP project of pressure ulcer prevention intervention was an Evidence-to-Practice Translation project. Curtis et al. (2016) share that knowledge translation occurs as research knowledge is produced, circulated, and adopted into practice settings. Through the DNP Project, the aim was to apply the best evidence of pressure ulcer prevention in critically ill adult patients and assess the effectiveness of interventions to analyze the value of these tools. The retrospective study examines subjects based on their exposure status and compares their incidence of status in which their data was collected retrospectively (LaMorte, 2016). This method was found to be more suitable in this proposed DNP project as it required minimal support from staff nurses and solely relied on previously obtained data which can be in electronic medical records (EMRs). LaMorte (2016) notes the efficiency of retrospective study as such studies require less time and less financial resources than prospective studies. The Cubbin and Jackson scale was the instrument used in the project. Through statistical analysis, Abidelli and Korkmaz (2019) determined that both the Braden and the Cubbin and Jackson scales are valid tools in assessing pressure ulcer risk in critical care patients. Therefore, Abidelli and Korkmaz (2019) indicate the assessment tools accurately measure pressure ulcer 19 risk. Interrater reliability which is consistent results from the observers is measured using Cronbach's alpha (Phelan & Wren, n.d.). The Cronbach's alpha coefficient of the Braden and Jackson/Cubbin scales was 0.85 and 0.78, respectively (Abidelli & Korkmaz, 2019). As Cronbachs alpha of 0.8 and above is generally indicated as Good reliability, the results of Abidelli and Korkmaz (2019) were found to be reliable (Phelan & Wren, n.d.). Not much literature has been found on the reliability and validity of the Cubbin and Jackson scale, the lack of evidence yielded the need for more investigation. Retrospective statistical analysis on the Cubbin and Jackson scale included determination of statistical significance through appropriate power analysis and significance and correlation coefficient. Data analysis was done on patients that were admitted to CCC of Elkhart General from September of 2020 to February of 2021. This included the influx of Covid-19 patients. Including these individuals to this project was extremely important to assess the accuracy of the two pressure injury risk assessment tools, as skin issues were often observed on these patients. Utilizing existing patient data, daily retrospective risk assessment was done. This was done utilizing both the Braden scale and the Cubbin and Jackson scale while participants had critical care admission status. Once participants were transferred out of the Critical Care Center, data analysis was concluded. For the statistical findings to be significant, alpha of 0.05 was used. Additionally, to determine efficacy of measurement, 95% confidence intervals (CIs) were used. Implementation Model: The John Hopkins Nursing Evidence-Based Practice Model The John Hopkins Nursing Evidence-Based Practice Model (JHNEBP) model helps clinicians to conduct Evidence-to-Practice Translation by following a three-step process known as PET: practice question, evidence, and translation (Dang & Dearbolt, 2017). This scholarly project followed that model. The practice question being addressed was, why are there pressure- 20 related skin injuries still developing although many prevention interventions are in place? Evidence has shown that there are multiple valid risk assessment tools. One of the most widely used ones in clinical institutions is the Braden Scale, however, depending on the setting, the Cubbin and Jackson scale may be more appropriate when working closely with critically ill adult patients. The goal of this project was to translate the evidence of retrospective statistical data analysis upon project success. Project Sustainability Project sustainability is an important piece of project management that is accomplished through the identification of feasibility studies, formulation, design, appraisal, funding, implementation, monitoring, and evaluation (Morfaw, 2014). Studies on pressure ulcer prevention tools have been evaluated and appraised to formulate an implementation plan. Morfaw (2014) mentions that failure to have an appropriate sustainability plan leads to project failure. Project failure can be prevented through a comprehensive analysis of the social, economic, legal, cultural, educational, and political environments for project implementation (Morfaw, 2014). Additionally, the analysis needed to be an ongoing process to promote continuous growth of the subject matter and organizational changes that occur almost daily. Social entrepreneurship and Innovation Social entrepreneurship is the new and innovative approach to solve social issues (Schwab & Milligan, 2015). Social entrepreneurship allows one to be innovative in finding solutions to social problems. This was applicable to students pursuing their DNP degree as well. Through their innovation project, DNP students identify clinical issues and apply the best practice from literature with the hopes to solve the issues. This project of pressure ulcer prevention fitted with the model of social entrepreneurship as it was aimed to solve the issue of 21 hospital-acquired pressure-related skin injuries in critically ill adults. Pressure ulcers are very much a social issue as the development of them affect ones social capability affecting their mental, physical, and financial state. Ethical Considerations Human Protection through the IRB Any projects involving human subjects should be carried out in an ethical manner to protect human integrity and ensure safety of the participants. The Institutional Review Board (IRB) procedure was necessary to protect human subjects. IRB is an appropriately constituted group under Food and Drug Administration (FDA) in which review study design and monitor research involving human subjects in order to protect rights and welfare of human research subjects (Office of Medical Products and Tobacco, Office of Clinical Policy, Office of Good Clinical Practice, 1998). Reviewing Human Subject Regulations Decision Charts: 2018 Requirements, as the project was retrospective data analysis of already available data and application of those data to a different pressure ulcer risk assessment tool, this study was determined to be exempt from IRB review under 45 CFR46.104(d)(4) (Office for Human Research Protections, 2020). All necessary documents were submitted and approved by the IRB review committee at Beacon Health System for exemption under category 4. The University of Pittsburgh and the University of Kansas School of Medicine-Wichita mention consent waiver when conducting retrospective medical record review under Basic Exempt Criteria 45 CFR 46.101(b)(4) (n.d.). Informed consent for this project was unnecessary as personal identifiers such as full names were not used. For data tracking purposes, participant initials were used. 22 Benefits and Risks of the Project The benefits of the project to participants was limited, if anything the project was designed to benefit the overall healthcare system. The success of this project contributes to the expansion of knowledge regarding pressure ulcer prevention in critically ill adults. Nursing knowledge on this subject has heavily relied on the widely utilized scale of the Braden scale. This project helped to expand on the nursing knowledge of pressure ulcer prevention by considering another validated tool of pressure ulcer prevention. Risks for participating in this project include the following but not limited to invasion of privacy, data breach, and data mishandling. There were no physical risks for participation as the data analysis was done retrospectively and the score of the Cubbin and Jackson scale did not affect pressure ulcer prevention intervention(s). One of the potential psychological risks was that participants could feel uncomfortable after finding out they were included in the project. Some participants could feel that their privacy was invaded and violated as no consents were obtained. Other privacy and legal risks were data breach and mishandling. Data analysis was done utilizing statistical software, StatCrunch. With web and/or online base statistical software, data leak was a potential risk that needed to be considered. When third party data breach occurs, there is a huge possibility that data may be mishandled. Once the project is completed and has been analyzed, electronic data will be overwritten to prevent recovering information. Anonymity and Confidentiality To maintain anonymity, no personal identifiers such as full names were used. For data tracking reasons, participants' initials were used to associate with project results. To maintain confidentiality, no data associated with this project were shared with any individuals or organizations who were not involved with the project. The available data was solely used for the 23 project to investigate predictability of the Cubbin and Jackson scale in acutely ill critical patients. Key stakeholders such as faculty project advisor (Dr. Patricia Keresztes), statistician, and the primary investigator had the opportunity to access the data. Data was stored in a password protected computer. No public internet was used while analyzing data to prevent data breach. Methods Stakeholders Certified Wound Care Nurse shared her expertise of wound management and pressure ulcer prevention. Faculty project advisor (Dr. Patricia Keresztes) for overall management of the project and to facilitate the process of scholarly project. Unit director, unit manager, and IRB Chair granted permission for the project to be carried out and provided support. Statistician to help analyze data. Participant Criteria Inclusion criteria for the participants in this project were the following: age 18 and older, no presence of pressure ulcers at admission, and critical care admission status of at least 24 hrs. Power Analysis from the previous assignment revealed that at least 128 patients were necessary to achieve meaningful results. This meant at least 64 individuals in each category of acquired pressure ulcer during hospitalization and did not acquire pressure ulcer during hospitalization. However, with heavy reliance on the primary investigator to collect data, the number of participants were modified to four with the total number of ICU stays N ranging from 81 to 84. Selection of participants was done through convenience sampling. 24 Through literature review, Chello et al. (2019) determined that unique intrinsic risk profiles of cardiac surgery patients complicate risk assessment for pressure injuries. Due to this reason, cardiac surgery patients were excluded from the study. Similarly, neurosurgery patients undergoing time consuming extended surgery like cardiac patients, were also excluded. After the project was approved for review exemption by the IRB at Elkhart General Hospital of Beacon Health System, Saint Marys research committee was notified of the approval and the project was implemented. This started with identifying participants after reviewing EMRs. Extensive study of each participant was necessary to understand different variables involved in the development of pressure ulcers in critically ill adult individuals. Abidelli and Korkmaz (2019) determined that both the Braden and the Cubbin and Jackson scales are valid tools in assessing pressure ulcer risk in critical care patients. Therefore, Abidelli and Korkmaz (2019) indicate the assessment tools accurately measure pressure ulcer risk. In this project, the validated tool of Cubbin and Jackson scale was utilized on all participants to evaluate their risk of developing skin injuries. The Gantt chart under appendices displays the timeline of the project from the beginning to completion. Data Collection After potential participants were determined by setting exclusion and inclusion criteria, System Intelligence at Elkhart General Hospital compiled a list of candidates by identifying individuals by ICD-10 code of L89.90 pressure ulcers of unspecified site, unspecified stage along with other similar ICD-10 codes. This was made possible by the help of Revenue Cycle. Revenue Cycle is a tool to keep track of charges so that healthcare institutions are billing events appropriately to create healthier financial outcomes (Cerner, 2021). System Intelligence was able to identify 1756 individuals who met the criteria for project participation. To benefit from the 25 implementation of the Revenue Cycle, the project timeframe was shifted to September of 2020 to February of 2021. Addendum was made to request change in the project timeframe. Once the list was provided to the primary investigator of this project, data collection began. This was facilitated by the use of Duo Mobile, an application which allowed remote access to patient data by two-factor authentication for secure access to patient data (2021). Cost of Duo Mobile was assumed by the CCC and came out of the unit budget. Data was gathered on four different individuals who met the criteria for participation with a total ICU days of 81-84. The number of participants was much smaller than the initially projected number of participants however with the delay in access to patient data and volume of patient charts with extended hospital days prohibited obtaining such high volume. Each participants charts were reviewed carefully to numerically analyze their risk of developing pressure ulcers in the ICU setting. Numerical responses of eight categories within the Cubbin and Jackson scale were totaled to calculate the daily sums for each ICU stay days. Values on two of the categories (age and mentation) were determined upon admission to the ICU and stayed the same for the rest of their stay as decided by the operational definition of the Cubbin and Braden Jackson scale (see Appendix E). The category of weight considered both at admission status and continuous changes that the participants experienced. The rest of the categories including general skin condition, mobility, hemodynamics, respiration, nutrition, incontinence, and hygiene were continuously evaluated based on participant conditions during their ICU stay. In each category of the Cubbin and Jackson scale, the lower the number was the higher the risk participant was at developing pressure injuries in the ICU. Appendix E can be utilized as an aide to understand the numerical distribution of the Cubbin and Jackson scale. 26 Conversely, as the Braden scale was already completed on the participants by CCC nurses at the project site, the sum values from each ICU stay days were collected for each participant and considered for statistical analysis. Values of each category were ignored in this project as the main focus was to evaluate the effectiveness of the Cubbin and Jackson scale. The sum values from each ICU stay days were sufficient to conduct statistical analysis. Operating Budget Details Below is a detailed description of the items on the operating budget with specific meaning for this project. Tech Support and Software Such a category related to conducting data analysis through statistical analysis software such as StatCrunch, annual fees paid for software upgrades, help desks, etc. Excel and Google Doc were utilized for scholarly writing to organize and summarize statistical findings. Equipment Computers, Internet router and modem were included in this category. No additional fees were required as both the project proposer and project host site have access to above equipment already. Clinical Project Support Team Project support team consisted of a unit director and a unit manager. This team was an inkind contribution as each person is paid by the organization. Statistician Mr. Matej Marek of Statistics Help was hired to assist with data analysis. 27 Data Analysis Quantitative Data Correlation coefficients were determined to evaluate the correlation among the categories of the tool tested. The Cubbin and Jackson scale score was gathered on all inpatient Critical Care admission days of participants. Daily total values were used to compute correlation coefficient. Two of the participants experienced a long hospitalization in the CCC therefore the scores were obtained for a long period of time. Data that was pulled to calculate the Cubbin and Jackson scale were the age, weight, general skin condition, mental condition, mobility, hemodynamic status, respiratory status, nutrition status, continence level, and hygiene as previously discussed. All data points were entered and organized on an Excel worksheet. Appendix G consists of such a worksheet. All the information was already available from the EMRs. Reviewing physicians progress notes was most helpful in painting the most accurate patient presentations. Qualitative Data Although skin injuries have been known to affect patients on multitudes of levels and efforts to obtain qualitative data were beneficial to better understand the effects of hospital acquired pressure related skin injuries, the retrospective nature of this project complicated the process of gathering qualitative data. Therefore, this project solely focused on quantitative data of the Cubbin and Jackson scale. Results Data was collected on a total of 4 individuals with total ICU days (N = 84). With some data missing from the EMRs, the Braden scale had N of 81. Each ICU day had 10 data points. Correlation between the length of ICU day and sums of the Cubbin and Jackson scale was 28 compared to correlation between the length of ICU stay and sums of the Braden scale to analyze the accuracy of pressure ulcer risk assessment. First, data analysis began with tests of normality to assess for normal distribution of data samples as well as checking for outliers. The Cubbin and Jackson Scale No extreme outliers were found. However, it was not normally distributed. Tests of Normality Kolmogorov-Smirnova Statistic sum .217 Df Shapiro-Wilk Sig. 84 .000 a. Lilliefors Significance Correction The Braden Scale No extreme outliers were detected. Statistic .912 df Sig. 84 .000 29 Again, no normal distribution. Test of Normality Kolmogorov-Smirnova Statistic sum .106 Df Shapiro-Wilk Sig. 81 .026 Statistic .962 df Sig. 81 .018 a. Lilliefors Significance Correction Analysis Correlation coefficient measures the strength of linear relationship. The coefficient values range from -1 to 1. A negative sign indicates a negative correlation. The strength of the correlation is influenced by the following scale: 0 - no correlation, 0.1 to 0.3 weak correlation, 0.3 to 0.5 medium correlation, 0.5 to 1 strong correlation. Because the data were not normally distributed, Spearmans correlation coefficient was utilized instead of Pearson correlation coefficient (Laerd Statistics, 2018). Cubbin and Jackson scale correlations 30 day Spearman's rho day Correlation sum 1.000 -.871** . .000 84 84 -.871** 1.000 .000 . 84 84 Coefficient Sig. (2-tailed) N sum Correlation Coefficient Sig. (2-tailed) N **. Correlation is significant at the 0.01 level (2-tailed). Strong negative correlation between number of days in the ICU and sums of Cubbin and Jackson scale (R= -0.871, p-value = 0.000) was found. Braden scale correlations 31 day Spearman's rho day Correlation Coefficient Sig. (2-tailed) N sum Correlation Coefficient Sig. (2-tailed) N Sum 1.000 -.416** . .000 81 81 -.416** 1.000 .000 . 81 81 **. Correlation is significant at the 0.01 level (2-tailed). Medium strength negative correlation between number of days in the ICU and sums of Braden scale (R= -0.416, p-value = 0.000) was determined. Data Interpretation Statistically significant findings indicate data analysis produced meaningful results. As previously explained, the lower the sum score of scales, the higher the participant was at risk for developing pressure related skin injuries. The Cubbin and Jackson scale Negative correlation meant that the longer the ICU stay was, the lower the Cubbin and Jackson scale sum was. Strong negative correlation indicated that the longer the ICU stay was, the higher chance the patient was at acquiring skin injuries utilizing the Cubbin and Jackson scale. 32 The Braden scale Similar to the results of the Cubbin and Jackson scale/sums, with the Braden scale, negative correlation was found between the number of days in the ICU and sums of Braden scale. However, the strength differed from the one from the Cubbin and Jackson scale, making it a medium strength. Comparing the Results Correlation strength differing among the Cubbin and Jackson scale and the Braden scale meant that one scale predicted risk better than the other. Although both assessment tools predicted risk accurately as evidenced by statistical significance, the Cubbin and Jackson scale predicted better than the Braden scale explained by their strengths of correlation. This important finding should not be ignored as it could influence the future practice of pressure ulcer risk assessment in critically ill adults. Strengths The utilization of the Cubbin and Jackson scale can help providers and nurses identify and assess for the degree of pressure ulcer development risk. Objective aspects of the scale can allow accuracy in predicting risk unlike the Braden scale which consists of subjective data. Predicting risk accurately can help maximize the limited resources that healthcare organizations have, especially during the Covid-19 crisis. Overestimating or underestimating the risks not only misuse the resources, but care efficiency can be put at risk. The objective assessments of the Cubbin and Jackson scale can allow the providers to simply input patients demographics and head to toe assessment results helping the providers to treat the patient holistically. Pressure ulcer risk assessment may not be a top priority when providing patient care however the importance of assessing pressure sore risk utilizing the 33 Cubbin and Jackson scale cannot be expressed enough. It can potentially prevent the incidence of pressure ulcers as well as other burdens such as financial and emotional burdens. Protecting the vulnerable population is a duty that healthcare professionals carry. Limitations There were several limitations to this project. Small sample size posed from analyzing pressure ulcer risk across the ICU patients therefore generalization of the results is restricted. Barnes et al. (2021) reported generalizability is the extension of research results from a study conducted on a sample population to the population at large. Large sample size is required to produce generalizability (Barnes et al., 2021). This does not cancel the statistically significant results the project produced but rather generazalibality is not applicable. Another limitation of the project was that the project host site did not have a clear layout as to how to initiate a scholarly research project. Once IRB approval was granted, the primary investigator reached out to the Information Technology (IT) department at Elkhart General Hospital to inquire on how to identify potential participants. Privacy Officer reached out requesting additional information on the project and the primary investigator was later connected to the System Intelligence. This process took approximately six months to complete delaying the data collection process. Even after the participant list was provided, remote access was not granted for another month. Once remote access to patient records was granted, data collection occurred consistently and frequently. However, this is when it was determined due to the labor intensity and the presented list not being precise, that it would be best to limit to several participants to fully understand and accurately apply the Cubbin and Jackson scale and the Braden scale. Again, this limited generalizability of the results but allowed articulate analyzation of data. 34 Some data points were missing from the charts on the Braden scale. This incident made the project not as concise however very understandable since the Covid-19 pandemic was an influential event during the project implementation period. Nurses who would score the patients were allowed to do limited documentation as long as there was no change in patient condition. The Braden scale was still required to be done on each shift however when a patient decompensated, it appeared to be that the Braden scale was not on the top priority for these bedside staff. Implications for Clinical Practice The results of this project advance nursing knowledge by identifying at risk individuals and predicting risk accurately through the utilization of the Cubbin and Jackson scale. As primary investigator who is a registered nurse completed the process of assessing risk utilizing the Cubbin and Jackson scale, nurses who are trained to complete the Braden scale at the moment should be able to easily complete the Braden scale after appropriate training. Policy Recommendations The Cubbin and Jackson scale could be considered for use on adult acutely ill individuals admitted to the ICU. The Cubbin and Jackson scale should be made available on the EMRs for easy access with references to help answer the questions providers may have. By having the scale on the EMRs, providers may have the opportunity to compare his or her own score on the patient to assess the trend of pressure ulcer risk. Conclusion With hospital acquired pressure related skin injuries being a continued problem of healthcare, this project has the potential to positively affect patients outcome and reduce the incidence of pressure ulcers in critically ill adults. By accurately predicting risks, redundancy is 35 limited, and prevention measures are implemented where they are due. With the increased demand of patient conditions, allocating and utilizing available resources efficiently is extremely crucial. Pressure ulcers can produce detrimental long-term effects, therefore preventive interventions would be in patients best interest. Considering additional and unique risk factors of critically ill adults, the Cubbin and Jackson scale aids to reduce pressure injuries in clinical settings. Although the sample size was small, the results of this project are important as they could function as an aide to policy change or open doors to more studies on this specific population using the Cubbin and Jackson scale. Adult acutely ill patients deserve a detailed risk assessment tool for pressure injuries as their risk factors are unique and different from other typical adult patients. References Abidelli, S., & Korkmaz, F. (2019). Pressure injury risk assessment in intensive care units: Comparison of the reliability and predictive validity of the Braden and Jackson/Cubbin scales. Journal of Clinical Nursing, 28(23-24), 4595-4605. doi: http://smcproxy1.saintmarys.edu:2067/10.1111/jocn.15054 American Nurses Association. (n.d.). Advanced practice registered nurse (APRN). 36 https://www.nursingworld.org/practice-policy/workforce/what-is-nursing/aprn/ Ahtiala, M. H., Soppi, E. & Kivimaki, R. (2016). 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Guidelines for retrospective chart reviews. http://wichita.kumc.edu/Documents/wichita/researchcompliance/Guidelines%20for%20R etrospective%20Chart%20Reviews.pdf 41 Appendices Appendix A 42 Appendix B: Concept Map Linking the Disease Process, Participants, and Concepts of Interest 43 Chronic Illnesses (Examples of) Diabetes Mellitus Hypertension Neuropathy Cardiovascular disease Dementia or Alzheimers disease Mood disorders Patients in the ICU and Their Complicated Situations Prolonged hospitalization Malnutrition Poor blood supply Immobility Pathogenesis Friction Sensory loss Shear Surgeries Compressio Use of artificial diet n Poor health status Pressure Little to no independence in ADLs Low BMI Advanced age Abnormal appetite status Pressure injury prevention Professional Growth through academic journals and trainings Environment Staff shortage Demanding workload Outcome Avoidable or unavoidable pressure injuries Limited supply and items to effectively implement measures Resistance from staff 44 Appendix C: Gantt chart of project timeline Meet with stakeholder s in project setting to discuss plan; identify participants IRB process and submission of research proposal Data collection Statistical analysis; compare results to predictions DNP scholarly paper and presentation 8/202 0 9/2020 10/202 0 11/2020 12/2020 1/2021 2/2021 3-12/2021 Appendix D: Operating Budget Type of service unit Job title & wage Unit manager $40/hr x1h plus 22% fringe Direc t cost $40 Indirec t cost $8.8 Total cost $48.8 Non-Monetary Cost In-Kind Contribution Non-Monetary Cost In-Kind Contribution Unit director $49/hr x 1hr plus 22% fringe $49 $10.78 $59.78 Monetary cost Statistician $440 per assignment $440 NA $440 Non-Monetary Cost In-Kind Contribution Staff RN $27/hr x80 hrs plus 22% fringe $2160 $475.20 $2635.20 Total cost $440 Appendix E: The Cubbin and Jackson scale 45 Appendix F: The Braden scale 46 Appendix G: Excel worksheet for organizing data FIN Initials CCC admit date CCC d/c date Covid CRRT Proning Surgery Age Weight (kg) Height (cm) Events Date Age Weight/ BMI Skin Neuro Mobility Hemody namics Resp. Nutri Inconti nence Hygiene sum ...
- Creator:
- Otsuka, Yumi
- Type:
- Project