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How to Improve Patient Appointments with the Help of AI

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Covid-19 has changed the way medical practitioners went about things. Doctor’s routine, patient appointments and even the equipment and the resources were running a little thing even before the pandemic. Patients had to wait weeks and sometimes even months to schedule an appointment or a surgery. Now with the pandemic, all of these resources are being depleted and have reached a breaking point.

Furthermore, as the doctor’s offices and labs were closed down due to Covid-19 resulting in a huge backlog of patients with conditions other than Covid-19 had become a major issue for the health care sector. Whether patients want to book an appointment with their previous doctor or find a new one, doing so has almost become impossible.

Not only this, but patients have now become more cautious and now require more guidance in order to get the desired outcome. Considering the existing methods, there is a lot of hindrance when it comes to the smooth functioning of the administrative tasks.

Not all hope is lost and there still is a lot more that can be done to improve the patient experience. The use of Artificial intelligence (AI) seemed like a farfetched thing in the last few decades but now it has become a reality. By linking up the management software systems with AI, it will now be possible to deliver the most efficient services to the patients who once waited for weeks and were still not satisfied with the outcome.

Traditional process

The current workflow for booking an appointment involves the following steps:

-1 Patient is directed to the specific department whenever he/she calls

-2 The person looks up for a time for the patient after looking up the schedule.

-3 Once the patient confirms the allotted time, the appointments gets scheduled.

The above mentioned steps for scheduling can take place through a phone call or the website of the hospital. However, these processes are much hefty looking in real and require a lot of human resource, time and effort.

Challenges with the current set of processes

The problems that occur in these traditional scheduling methods are as follows:

-1 Doctor may reschedule or may not be available at times. This information will then be shared with the patient and a new time or doctor will be scheduled for their appointment.

-2 Rescheduling by the patients due to any unforeseen circumstances.

-3 Patients not showing up for the scheduled appointment.

-4 Due to emergencies, many appointments might have to be rescheduled for some other time.

Taking these challenges in consideration, an AI based solution can help materialize the resources by ten folds, especially when talking about the Healthcare facilities with an OPD unit.

AI for Appointment Management

Bearing in mind the challenges faced by healthcare industry in scheduling makes it imperative for AI to come into place and help practitioners achieve their maximum output. With the help of AI, there will be a lesser number of patients not showing up for their appointments. Since the chat bots are available 24/7, the AI powered system will have a better understanding of the patients and will be able to answer their queries more effectively than the traditional method of communication. The machine learning and Natural language processing works in different ways when it comes to AI based systems.

In one instance, patients will be able to schedule their appointments with the help of an SMS system where the data will be collected through texts or via email. This way, they will be able to get reminded, reschedule their appointment, and also give pre-visit instructions to the patients. After the visit, patients will be provided with their reports as well.

This will not only ease the patient’s experience but will also be able to track relevant information through patient surveys which will help the health care facility get insights about the latest trends of the patients. With the information available 24/7, time and resources can thus be managed more efficiently and in advance.

As there are many small and repetitive tasks involved in scheduling a patient’s appointment, human resource is not able to do more in their own respective fields as they get busy with such hectic and time consuming procedures.

Breakdown of tasks

All in all, patients get frustrated with such waiting times and lengthy procedures that they have to go through in seeing their doctor. Lack of digital solutions is a major challenge especially in the post-covid world.

With the help of AI, all these problems can be addressed much effectively with automation of such processes.

Data for AI

Data is a major part of AI. Since machine learning and Natural Language Processing (NLP) is the core of such automation, large sets of data are required for a deeper understanding of the patient’s requirements. The number of data that we are talking about here is just too vast to be managed by individuals.

The processing power of such large amounts of data through AI gives the patients an advantage in choosing the doctor that is best fit for their condition. For example, AI will be able to better assist a young adult suffering through a knee injury. The reason being, the most likely cause of that individual getting an injury would be due to sports and upon learning about the patient, AI will be able to direct the patient to a doctor practicing in the domain of sports and not to someone practicing the knee injury for the elderly. Both these doctors will have different ways to handle the patient and even the post surgery rehabilitation will be a lot different because of the domains they come from.

The current scenario is well suited for AI based solutions as they can help patients choose the best suitable doctor which in result makes it a lot more flexible considering the backlog of patients because of the pandemic.

While AI may give off an impression of something too far-fetched, the current pandemic has accelerated the demand for such a solution. Given the existing state and the growing impacts they will have over the long haul, we can hope to see more noteworthy selection of AI driven doctor to patient link up now, and sooner rather than later.

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