Proactive Approach and Technological Inclusion of AI in Workforce

Policy Analysis – Proactive approach and Technological inclusion of Artificial Intelligence Systems (AIs) in Workforce Allocation
Your Name
Subject and Section
February 22, 2020
Introduction
It is a common knowledge among health professionals that aside from treating patients, other non-medical related issues arise due to the ‘human factor’, which causes the unpredictability of both internal and external factors in the workplace. While some of these problems might relate to technical issues (i.e., treatment related) most of them are usually related to administrative (i.e., workforce allocation) and logistical problems (i.e., long queues). In line with this article, the author would like to discuss the inherent problem in terms of long patient queues and insufficient workforce allocation during (unpredictable) peak hours. This policy suggestion arises from the fact that inefficient workforce allocation leads to lesser nurse-to-patient ratio, which then increases the risks of injuries and burnout among the patients and the nurses, respectively. As according to Carlson and Keith (2017), inadequate patient-nurse ratio is one of the most daunting problems known to healthcare providers as it could to fatal problems such as “higher rates of patient falls, infections, medication errors and even death”. Accordingly, the author would like to initially focus on “leadership practices” that can address this problem, before providing an alternative suggestion (i.e., AI use) to resolve this problem.
Need for a Policy
In solving the problem of long queues and inefficient allocation of workforce, many administrators try to add more staffs and nurses. While this might be an effective policy in the short rune, long-term problems such as (1) underutilization of nurses and (2) frequent turnovers, (3) higher burnout rates and even (4) bankruptcy, could result in cases when there is an excessive nurse-to-patient ratio (Mossberger, 2018). Accordingly, several studies show that effective and proactive leadership can help address this problem. As stated earlier in this article, addressing the problem on short-staffing needs the guide of a leader. It must be noted, however, that ‘leaders’ differ from ‘managers’, in more ways than one. As according to Hassmiller (2006), a nurse leader educates, collaborate, negotiate, provides compassion, as well as determine every opportunities that could help solve the issue at hand. From this statement, it follows that nurse-leaders must be able to solve the problem systematically. This starts with looking behind the imminent issue and identifying its root cause.
For example, in the case of short-staffing, some of the potential problems could be staff tardiness, inefficient queuing system, lack of information about number of customers, or even financial constraints. In doing this, nurse-leaders must always be aware of all factors that could affect their decision making, including legal and administrative ones. One example of this is the knowledge about the required ‘patient-to-nurse ratio’ in different departments (i.e., “one-to-three nurse-patient ratio limit for pediatrics”) as allowed by the policy-making bodies CITATION ANAnd \l 1033 (Carlson, Keith, 2017).
Alternative Solution
If the problem is about the difficulty in queuing system or small space that could accommodate the patients, then certain innovations could then be leveraged. One example of a recent innovation in managing the number of clients is an Intelligent Patient Queue Management System (IPQMS) which notifies patients to return to the center when they’re number is near CITATION Advnd \l 1033 (Advantech.com, n.d.). However, using IPQMS or other AI Systems could increase the costs for operations, which could then lead in an increase in the prices of services. Thus...