Advanced Access Scheduling System in Healthcare Essay

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Advanced access scheduling is referred to as a system that allows patients to be examined on the same day or in the near future, depending on their desire. Typically, a patient schedules an appointment within 24 hours, which allows for a small number of scheduled appointments for physicians and a relatively flexible schedule. All clients can be offered an appointment, whether they need emergency care or a doctor’s consultation. Even though Advanced access scheduling may be more convenient for the patients, it comes with new challenges for medical personnel.

The system was created on the basis of vital standards to improve the provision of medical and sanitary care. First of all, it balances supply and demand. Thus, it allows you to meet the needs of the client and create a schedule for the doctor for more successful time management (Abou Malham et al., 2018). Moreover, the system significantly reduces the number of missed visits as the patient is informed about the new model. Additionally, Advanced access enhances the ability to conduct and integrate interprofessional practices between physicians and other staff to respond more quickly to client needs.

However, despite the obvious benefits, clinicians may face some challenges within this system. First of all, the system involves the rejection of the division into routine and urgent requests for medical assistance. Thus, physicians feel uncomfortable considering the system to be imperfect due to the rejection of their beliefs and previous experience with other planning systems (Oliver et al., 2019). Because urgent care is no different from routine care during the processing of applications, physicians cannot point to the fact that non-urgent care may be provided later. As a result, hospital staff may be skeptical about meeting demand with Advanced Access scheduling.

Additionally, logistical problems can be noted in the difficulties of using this system. When applying the model, the system must provide accurate data on the number of patients who visit each doctor in the hospital. This requires taking into account the number of available places and limits on the time and general level of customer demand for visits. It is difficult for physicians to predict the number of visits on the same day, as it can vary significantly and interfere with the construction of time management.

At the same time, the quantity of demand is difficult to measure and will primarily depend on the supply of appointment times rather than on demand for the services of doctors themselves. Since the number of visits is extremely difficult to measure and isolate retrospectively, it is important for medical staff to obtain possible data prospectively. This poses some challenges, as it requires close follow-up of patient appointments to all available physicians and requests from other healthcare professionals to revisit the client.

Another serious difficulty for physicians is the backlog in prescribing and finding ways to reduce it. In this regard, after the application of the system, the medical staff will be forced to see more patients every day over the course of several weeks. However, in some situations, there is a higher demand than available services, resulting in doctors not having enough time to provide care to patients.

In conclusion, it should be said that to date, the system remains imperfect and may cause many difficulties among medical personnel. Although Advanced Access scheduling allows for a more precise schedule, patients are not sorted into urgent and routine cases. In the long term, this may prove to be a problematic link in the delivery of health services. Additionally, physicians have a distrust of the system due to the abandonment of previous distribution systems and the need to reduce retention in appointments.

References

Abou Malham, S., Touati, N., Maillet, L., & Breton, M. (2018). . Medical education online, 23(1), 14-38. Web.

Oliver, D., Deal, K., Howard, M., Qian, H., Agarwal, G., & Guenter, D. (2019). . BMJ open, 9(3), 7-20. Web.

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