MSN Project: Using an Acuity Tool for Nurse-Patient Staffing or Acuity Based Staffing in Nursing (Essay Sample)

MSN Project: Using an Acuity Tool for Nurse-Patient Staffing or Acuity Based Staffing in Nursing Student’s Name Department, University Course Professor’s Name Date Introduction In March 2019, nurses in New York threatened to go on strike because of the issue of ‘safe staffing’. As McGeehan (2019) writes in The New York Times, the New York State Nurses Association union of more than 10,000 nurses threatened to strike because of the poor levels of staffing; demanding a sharp increase in the number of nurses. Shanna Murphy, a nurse who works in neonatal intensive care, claimed that she has not forgotten the new mother who became furious when she thought her wailing baby was being ignored (McGeehan, 2019). The baby needed soothing, as Ms. Murphy indicated, but she was preoccupied with another patient whose health was more unstable and required almost continual monitoring. As a nurse, Ms. Murphy indicated that she is frequently forced to choose between patients depending on their health state, because she cannot be able to manage them concurrently. Yet, she also needs time for her family. At the helm of the covid-19 pandemic, and in view of the challenging environment that nurses were predisposed to, Aiken (2021) indicated that, as nurses deserve better, so do their patients. Indeed, healthcare delivery today has become like a basic need in society. With the rise of incommunicable diseases and a host of many other illnesses, the need for more resources in the healthcare system has become pertinent. Lack of adequate resources in the healthcare system is a threat to the wellbeing of a nation. Yet, Trepanier, Lee and Kerfoot (2017) underscore that irresponsible use of healthcare resources is the primary cause of healthcare issues; poor quality care, non-patient centered care, unaffordability, nurse burnout and dissatisfaction among others. In retrospect, the proposed acuity-based staffing is an effective tool for ensuring effective and responsible use of healthcare resources. The acuity-based system is data driven. More often, it has always been difficult to strike the right balance between diagnosis, treatment, and continued care for the duration of a patient's stay in hospital. The tendency toward remuneration based on patient outcomes complicates this delicate balance. The use of an acuity-based system has a host of benefits because it contribute to keeping that balance diagnosis, treatment, and continued care of the patient, while considering the bigger financial picture. The acuity-based system seeks to generate staffing patterns depending on patient data. For example, the staffing pattern can include additional nurses if the data indicates that some patients require greater care. Similarly, if the data indicates that a given patient only needs light and not intense care, the nursing personnel required can either remain the same or be significantly lowered. It is a more responsive means of addressing both nurse-patient care needs. MSN Project: Purpose/Problem Statement The nurse-to-patient ratio is one of the issues that affects healthcare delivery. According to Trepanier et al. (2017), and in the United States, the nurse-to-patient ration in critical care must be 1:2 at all times. The ratio in the emergency is supposed to be 1:4 or fewer at all times. Although these are the required ratios, the National Nurses United report indicates that nurses are often required to care for more patients than it is safe. This clearly compromises patient care and opens a window for a host of negative outcomes both for the patient and for the nurse. Moreover, another major problem that jeopardizes the quality of healthcare provision is nurse dissatisfaction and burnout (Gligor & Domnari, 2020). The American healthcare system has been quite concerned about Registered Nurse burnout, which has been notable and even documented in numerous hospitals. Among other things, the mishandling of personnel and resources, lack of follow-through, extended shifts, and strained personal expectations are among some of the issues that lead to dissatisfaction and burnout. Overworking will generally make a person exhausted and unhappy, thereby affecting performance and quality of care (Gligor & Domnari, 2020). These factors collectively not only contribute to experiences of burnout but also have impacts on the psychological, mental, and emotional states of both nurses and patients. These factors are directly correlated to the nurses and patients’ wellbeing. The purpose of the MSN project is to propose the use of acuity-based staffing tool to improve patient outcomes and nurse satisfaction in the emergency department. The intent is to enhance the quality of healthcare delivery as well as the wellbeing of both the nurse and patient. The model seeks to enhance their safety, as well as high quality and person-centered care. MSN Project: Implications for Advanced Nursing Practice Today more than ever, acuity-based systems have become significantly reliable. The system is much more consistent, accurate, and based on scientific data. It is also based on evidence-based practice, as well as the capability to pull information either from electronic health records or from a single source of truth. With the help of patient acuity technology, many thriving healthcare organizations are leveraging patient information and automatically matching it with employee data. Pairing data on patient needs with staff information is powerful and can drive a host of efficiencies for healthcare organizations. One of the positive implications of patient-nurse care matching is cost savings. According to Austin, (2020) study, nurse staffing has a major implication on not only quality but also financial outcomes. In particular, the acuity-based system is critical in the identification of nurse needs based on the patient acuity data (Long, 2020). For example, when patients are more and with more needs, the acuity-based system will help a facility to increase the number of nurses to attend to these patients. Increased number of nurses to cater for the increased patient needs will enhance the quality of service delivered. This in turn will enhance patient outcomes and therefore reduce the costs incurred during readmissions. On the other hand, employ turnover can also be a costly issue. In retrospect, focusing on equitable assignments can enhance nurse engagement and return impactful savings. For example, in every 350 RN FTEs in a nursing personnel budget, a 1% turnover rate can cost the average hospital about $300,000 on a yearly basis (Long, 2020). Taking a proactive approach to foster nurse satisfaction is critical in achieving significant savings in the long-term. Other implications include contributing to a culture of safe, high quality, and person-centered care. For example, the acuity-based staffing system is critical in helping healthcare entities to understand the capacity in which a given nursing staff can be able to meet patients needs, and thereby effectively and accurately addressing them. This is key in helping achieve the best patient outcomes, which in turn translate to cost savings. MSN Project: Financial Management As proposed in the MSN project, the creation of the acuity-based staffing system requires financial resources. The first financial resource needed will cater for research on the model. A facility would have to hire a financial expert who has adequate knowledge about the implementation of an acuity-based staffing system. The estimated costs for the expert are shown in table 1 (appendix). The healthcare entity will also need to incorporate mapping costs. The facility will have to track all the patient records, staff rosters, shift schedules, nurse information, dependency levels across wards, any staff rosters, and evidence based nursing regimens. The cost for mapping and gathering these data is estimated in table 1. Once the mapping and gathering of required data has been done, a software company will be hired to create an acuity-based software for the system. The costs are estimated in table 1. The system will align, track, assess, match, identity, assist, and monitor all the data that is established in the software. The software will be critical in allocating nurses and also assessing patient needs. In the current technological dispensation, the acuity-based system requires an electronic infrastructure which is definitely a software or website system. The software or website is not really costly to construct; its cost will basically depend on the complexity and conciseness that characterizes it. Finally, the system also requires maintenance costs. The success of the system is predicated on various variables. These variables are critical in determining adequate staffing, high quality, and person-centered care. The critical variables to consider are patient needs and nurse characteristics. Patient Needs Patient characteristics inherently dictate staffing demands to a considerable extent (Long, 2020). In addition to sickness or state, it is important to focus on the patient's current state, emergency needs, complexity of their condition, age, length of stay, functional status, activities of daily living, and requirement for transportation, among other things, which all have an impact on acuity. Each of these factors influences the patient's nursing care requirements. In fact, the nursing workload intensity is also influenced with these needs. Nursing Characteristics Nursing staff characteristics must be taken into account. For example, it is very critical to identify a nurse’s training, education, skills, and even preferences and therefore match their skills with the needs of a particular patient....