In order to ensure that proper procedures are followed throughout the process, it is necessary for the clinician to review and analyze all of the information that has been gathered thus far. In the field of robotic process monitoring (RPM), artificial intelligence, which includes machine learning and deep learning, is one of the technologies that will have a significant impact on the analysis of data collected through RPM. These capabilities can contribute to additional preventive medicine by notifying clinicians so that they can communicate with the patient monitor in order to address any potential issues that may arise as a result of the analysis of data trends. AI can not only assist doctors in diagnosing and treating their patients more accurately and efficiently than ever before, but it can also help them save time and money by analyzing large amounts of data in a short period of time, which can save them both time and money. All of us are well aware that the amount of information that can be gathered grows in direct proportion to the efficiency with which the algorithms that are used to gather it perform. This is a widely acknowledged fact.

Physicians and clinicians must be involved in a successful RPM program, and information technology systems that are capable of supporting an RPM solution must be developed. That being the case, how does one go about connecting the electronic health record to the care management software, assuming it is even possible in the first place? It is necessary to know who will be in charge of this integration as well as who will be responsible for providing long- and short-term support for it in order to answer this question. These are the types of questions that must be answered before a successful RPM program can be implemented in an organization.

Some patients with chronic conditions such as congestive heart failure or COPD may require the use of a patient monitor on a regular basis, whereas other patients may require the use of a patient monitor less frequently or for a shorter period of time than these patients. It is critical for healthcare providers to classify patients and collect data in the most appropriate manner in order to provide them with the best possible care.

The device must be evaluated before a decision is made on whether or not to include it in the program. This is necessary in order to determine whether or not it will be used and to ensure that it is user-friendly for the patients. If patients are not confident in the device's use throughout the entire care cycle, it is possible that they will use the device incorrectly. A negative impact on the patient's outcome or experience while using the device could result as a result of this. In the event that portable patient monitor is at all possible, the device or wearable should be ready for use as soon as possible, if not immediately, after the patient receives the kit. Similarly, when it comes to technology, the healthcare organization must determine who will be available to assist patients in the event that they encounter technical difficulties while undergoing treatment. Additionally, the following factors should be taken into consideration:

Health and fitness trackers such as the Fitbit and the Apple Watch, which are becoming more and more consumer-centric in their design with each passing year, are becoming increasingly popular among patients who want to keep track of their health and fitness. There is a high level of familiarity with telehealth among patient monitors, which increases the likelihood that they will expect — or even request — remote patient monitoring (RPM) services when the situation necessitates them. The decision will almost certainly cause healthcare organizations that do not provide RPM to fall behind the curve in their respective fields as a result of this decision.