Name
Capella University
NURS-FPX8012: Nursing Technology and Health Care Information Systems
Prof Name
September 2024
Quality Improvement Project Plan
A Quality Improvement (QI) Project Plan is designed to solve a significant issue in the environment of healthcare with the use of technology and informatics by improving the outcomes for the patient and efficiency of an organization (Whiteman et al., 2021). This plan identifies a specific problem supported with facts from reliable sources, such as Leapfrog and Medicare Compare, and offers technology-driven solutions for a healthcare setting. Any solutions that have been found need to carefully contemplate the potential challenges that might come ahead, including resource allocation, preparedness of staff, and other logistics. There is a careful examination of a detailed workflow, and before-and-after implementation processes are visually represented to highlight the expected improvements. Guidance of the change management comes from the leadership as it helps facilitate communication and ensures a smooth adoption of the proposed plan.
Problem Statement and its Significance
This quality improvement project identified the problem: high rates of hospital-acquired infections in the chosen healthcare facility in such a manner that seriously impacted patient safety, the quality of care, and overall performance in the hospitals. HAIs contribute to extended hospital stays, increased readmissions, and higher mortality rates, which escalate healthcare costs and strain resources (Stewart et al., 2021). The Leapfrog data scored the facility below average in the infection control measures, particularly those attributed to CLABSIs and CAUTIs, an indicator of urgent intervention. Medicare Compare sheds another significant light on financial penalties for poor infection control, which goes directly into the facility’s rate of reimbursement as well as public perception. By applying focused technological solutions, this problem will help decrease HAI, enhance patient outcomes, and improve the facility’s position in quality care metrics.
This calls for attention due to their profound effect not just on the outcome of patient care but on operational efficiency in a healthcare environment. Apart from being responsible for increased morbidity and mortality, HAIs also raise monetary burdens by way of penalties and loss of reimbursement for preventable infections as part of Medicare’s Hospital-Acquired Condition Reduction Program. Data released by the CDC indicates that on a given day, one of the hospital patients experiences an HAI; this contributes to thousands of deaths that could have otherwise been avoided annually. Implementing evidence-based practices and state-of-the-art informatics solutions, including real-time infection tracking and electronic health record integration, should significantly decrease rates of infection, enhance patient safety, and improve resource utilization to ultimately drive overall improvements in quality of care (Scardoni et al., 2020).
Proposed Solution and Implementation Plan
This is a proposed technology solution for the problem of hospital-acquired infections: Implementing a real-time infection surveillance system, aligned with the EHR platform of the facility (Seibert et al., 2021). It continuously monitors infection data so that healthcare providers can receive automated alerts when their patients are at risk of infection, providing early signals of central line-associated bloodstream infections or catheter-associated urinary tract infections. Reporting to infection control teams will also be streamlined and made more efficient, meaning interventions can happen promptly. Since data analytics is utilized through the surveillance system, it is feasible to detect any patterns or trends in the rates of infections, thus allowing targeted improvement in hygiene practices and patient care protocols in addition to resource allocation. This real-time view of infection data really promotes the ability to be proactive concerning HAIs before they become widespread problems within the facility.
The solution is relevant because it directly approaches the identified problem of high HAI rates. For a facility in such difficulties, as seen by the Leapfrog and Medicare Compare data, this technology represents a concentrated and efficient route toward the improvement of infection control practices. Infections could be recognized through real-time capability in the system, and action could be taken on these earlier infections to further reduce periods of patient care brought about by adverse patient complications. Moreover, the interface with the EHR offers communication between interdisciplinary teams as opposed to the obsolete, laborious process of reporting errors on pen and paper. The solution eradicates the immediate problem of infection control but also fosters long-term quality of care and regulation compliance through a reduction in the occurrence of preventable HAIs (Bakerjian, 2022).
Potential Implementation Challenges
Developing an effective real-time infection surveillance system could be quite a challenge from a logistical, financial, and personnel point of view. The most obvious one is the acquisition and integration into the existing electronic health record because of the high cost of such a system. Most healthcare facilities work on relatively tight budgets, and finding funds for such a sophisticated system would be challenging (Spoon et al., 2020). The staff may also resist the system due to unfamiliarity with the new technology as well as excessive added workload resulting from learning and using a new system. Training health care personnel effectively in the use of an infection surveillance system can be difficult as such exercise requires time and resources that momentarily interfere with routine operations. For its part, the facility may consider applying for grant support and government incentives targeting patient safety and quality-care initiatives to help it overcome some of these challenges.
Make sure early in the process that stakeholders like infection control specialists, IT personnel, and leadership are included so that the advantages of the system can be well presented to get more people on board with the initiative from the staff side. In-depth training programs, perhaps gradually phased in over time, could furnish some overload in resistance as employees would be best able to absorb the system with some gradual process. Ensuring technical support throughout the implementation process will help assuage anxiety and apprehension about learning the new technology. In this manner, by addressing these potential barriers early on, the facility may ensure that the infection surveillance system will eventually be well accepted and sustainably implemented (Lowe et al., 2021).
Role of Leaders in Change Management
Leaders should lead and facilitate change management in managing the implementation of the real-time infection surveillance system (Advani & Vaughn, 2021). They will provide the vision, create an innovative culture, and ensure that all staff understand and respect the importance of this new technology to reduce HAIs in a hospital setting. Champions of the proposed plan should be effective leaders who act in a way that communicates to all levels and benefits of the system to both patient safety and operational efficiency. They have to engage and incorporate their interdisciplinary teams, encouraging collaboration with infection control specialists, IT personnel, and frontline healthcare workers. The transparent management of goals of implementation, coupled with proactive handling of concerns, would reduce resistance during an easier transition process.
Structures of communications need to accompany the implementation and performance-tracking process for change management to be successful. First, leaders must adopt usual open updates by many channels town hall meetings, e-newsletters, and one-to-one discussions to let all employees know the purpose, timeline, and expected outcomes of the installation of the surveillance system. This approach would complement this by including active listening sessions where leaders will listen to the staff and identify concerns or problems early. Clear, concise messaging should reveal how the new system benefits the patients, in which data reductions on HAIs are very obvious (Beville et al., 2021). Rewards to accepters, as well as additional support during the change process, will be taken over by the staff and become ownership. Open, consistent communication will enable leaders to show all the different aspects, which they need to maintain changing their behavior; this will enhance long-term success in reducing infections.
Workflow Analysis
The current workflow, with respect to infection control at the healthcare facility, traditionally has been based on manual data collection, delayed reporting, and variable flows of communication between departments (Streefkerk et al., 2020). Infection control specialists rely on nurses and other clinical staff to report possible hospital-acquired infections, and through this mechanism, the maximum number of efficiencies such as missing cases or delayed interventions may be lost. Manual tracking would expose the possibility of errors in data entry, which would make it a challenge to track infection trends in real time. Probably, most clinicians lack effective communication with infection control teams because there is no central control mechanism for notifying people of infections. This compartmental approach leads to delays in response by putting patients at risk and making it challenging to contain outbreaks early.
After the establishment of the real-time infection surveillance system, there should be a more streamlined and efficient workflow. It will automatically monitor patient data regarding possible early signs of HAIs and give instant alerts to the clinical teams and to the infection control specialists (Fregonese et al., 2023). Thus, it prevents multiple manual reports by infection specialists and allows for instant initiation of interventions after identification of potential infections. The system will facilitate automation of direct notification to all persons concerned hence minimizing the likelihood of missed or late information. The real-time data analysis capabilities of the system shall enable infection control teams to identify trends, respond to inefficiencies, and inform decisions designed to prevent similar outbreaks in the future. Coordination, error reduction, and patient results improvement in the new workflow would also come from centralization.
NURS FPX 8012 Assessment 5 Conclusion
In a nutshell, the real-time surveillance of infections in the healthcare environment provides far greater benefits for patient safety and operational efficiency. Since it can automate data collection and provide real-time alerts, this technology addresses the inefficiencies and delays of manual reporting processes (Essink et al., 2020). Furthermore, it allows the infection control team to intervene at the right time, reducing hospital-acquired infections and improving better outcomes for patients. The workflow changes help improve responsiveness and provide constant monitoring, which shows exactly how critical this technological solution is for the problem in question, namely, infection management. Proper leadership and a properly structured communication plan will ensure the adoption of this system, transforming infection control practices toward better healthcare quality.
NURS FPX 8012 Assessment 5 References
Advani, S., & Vaughn, V. M. (2021). Quality improvement interventions and implementation strategies for urine culture stewardship in the acute care setting: advances and challenges. Current Infectious Disease Reports, 23(10). https://doi.org/10.1007/s11908-021-00760-3
Bakerjian, D. (2022). The advanced practice registered nurse leadership role in nursing homes. Nursing Clinics of North America, 57(2). https://doi.org/10.1016/j.cnur.2022.02.011
Beville, A. S. M., Heipel, D., Vanhoozer, G., & Bailey, P. (2021). Reducing central line-associated bloodstream infections (classic) by reducing central line days. Current Infectious Disease Reports, 23(12). https://doi.org/10.1007/s11908-021-00767-w
Essink, H. M., Knops, A., Liqui Lung, A. M. A., van der Meulen, C. N., Wouters, N. L., Molen, A. J., Veldkamp, W. J. H., & Termaat, M. F. (2020). Real-time person identification in a hospital setting: a systematic review. Sensors, 20(14), 3937. https://doi.org/10.3390/s20143937
Fregonese, L., Currie, K., & Elliott, L. (2023). Hospital patient experiences of contact isolation for antimicrobial resistant organisms about health care-associated infections: A systematic review and narrative synthesis of the evidence. American Journal of Infection Control, 51(11), 1263–1271. https://doi.org/10.1016/j.ajic.2023.04.011
Lowe, H., Woodd, S., Lange, I. L., Janjanin, S., Barnett, J., & Graham, W. (2021). Challenges and opportunities for infection prevention and control in hospitals in conflict-affected settings: A qualitative study. Conflict and Health, 15(1), 94. https://doi.org/10.1186/s13031-021-00428-8
Stewart, S., Robertson, C., Pan, J., Kennedy, S., Haahr, L., Manoukian, S., Mason, H., Kavanagh, K., Graves, N., Dancer, S. J., Cook, B., & Reilly, J. (2021). Impact of healthcare-associated infection on length of stay. Journal of Hospital Infection, 114(114), 23–31. https://doi.org/10.1016/j.jhin.2021.02.026
Scardoni, A., Balzarini, F., Signorelli, C., Cabitza, F., & Odone, A. (2020). Artificial intelligence-based tools to control healthcare-associated infections: A systematic review of the literature. Journal of Infection and Public Health, 13(8), 1061–1077. https://doi.org/10.1016/j.jiph.2020.06.006
Seibert, K., Domhoff, D., Bruch, D., Althoff, M., Fürstenau, D., Biessmann, F., & Wolf, K. (2021). Application scenarios for artificial intelligence in nursing care: rapid review. Journal of Medical Internet Research, 23(11), e26522. https://doi.org/10.2196/26522
Spoon, D., Rietbergen, T., Huis, A., Heinen, M., Dijk, M., Bodegom, L., & Ista, E. (2020). Implementation strategies used to implement nursing guidelines in daily practice: A systematic review. International Journal of Nursing Studies, 111. https://doi.org/10.1016/j.ijnurstu.2020.103748
Streefkerk, H. R. A., Verkooijen, R. P., Bramer, W. M., & Verbrugh, H. A. (2020). Electronically assisted surveillance systems of healthcare-associated infections: A systematic review. Eurosurveillance, 25(2). https://doi.org/10.2807/1560-7917.ES.2020.25.2.1900321
Whiteman, K., Yaglowski, J., & Stephens, K. (2021). Critical thinking tools for quality improvement projects. Critical Care Nurse, 41(2), e1–e9. https://doi.org/10.4037/ccn2021914
