Module 2-Discussion 1-Patient and Process Flows.edited
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Health Care Operations and System Management
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Health Care Operations and System Management
Module 2: Discussion 1: Patient and Process Flows
Reducing queues and wait time is a major focus in healthcare’s quest to improve quality
and patient satisfaction. Examples of four scenarios where queues are prevalent include
Emergency Department Waiting Times, outpatient clinic appointments, Pharmacy Prescription
filling and refill, and Surgical Waiting Lists. Using relevant quantitative data and the four steps
necessary to improve patient and process flow can be incorporated into each highlighted
scenario.
The Emergency Department (ED) is often filled with patients waiting to be evaluated
before being assigned to the appropriate treatment programs and departments. This can be a huge
issue in cases where the emergency department needs more staff during busy hours or in
unpredicted events such as accidents. Applying the four steps, healthcare facilities can first use
predictive models and historical data to forecast seasonal and patient demands. Aligning the
capacity with the available resources and demand can be done by ensuring that the emergency
department collaborates with other departments and restructuring staffing levels based on the
predicted demand levels. Some bottlenecking approaches that can be incorporated in this
scenario are streamlining triage processes and improving the collaboration and coordination of
communication among departments (Sasanfar et al., 2021). In this case, managing and
monitoring patients with tracking systems can include analyzing digitally collected data to
highlight recurring issues and identify trends in the emergency department queues.
In the outpatient clinic appointments scenario, understanding patient demand steps can be
incorporated using predictive analytics tools and appointment data to predict demand and its
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patterns. To align the demand capacity with the resources, more healthcare professionals can be
tasked with outpatient appointments duties, optimization of appointment scheduling systems to
increase efficiency, and extra resources such as support staff and examination spaces can be
allocated to improve the wait time and queues (Sasanfar et al., 2021). Some of the
debottlenecking approaches that can be applied in this scenario include Streamlining
appointment processes for efficiency in patient flow and encouraging interdepartmental
collaboration.
The four steps follow the same incorporation procedures for surgical waiting lists and
pharmacy prescription scenarios. For one, predictive tools and historical data can be used to
forecast the demand in the two departments. Also, additional resources can be allocated to align
with the demand in surgical waiting lists and pharmacy medication filling. Innovating
approaches such as extending hours and using a variety of facilities can also be used for the
debottlenecking process in both surgical and pharmacy queues situations. Finally, the procedures
used in structuring surgical waiting lists and pharmacy filling can be evaluated to identify areas
needing improvement.
Some quantitative metrics that can be used to measure outcomes in all four scenarios
include; patient satisfaction scores, complication rates, care outcomes, the number of patients
served within a specific time, and wait time length, among other things. According to the
MWXvideo (2014) video, good data is essential in improving patient flow, and all these metrics
have the potential to offer healthcare facilities having issues in the same highlighted scenarios
the opportunity to structure effective information systems tools that help collect, monitor, and
analyze data for efficiency improvement.
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References
MWXvideo. (2014, July 10). Optimizing patient throughput [Video file]. Retrieved
from
https://www.youtube.com/watch?v=NFYzciRTut8
Sasanfar, S., Bagherpour, M., & Moatari-Kazerouni, A. (2021). Improving emergency
departments: Simulation-based optimization of patients waiting time and staff allocation
in an Iranian hospital. International Journal of Healthcare Management, 14(4), 1449–
1456.