Tag Archives: robotics

Innovative RPM Developments that will revolutionize Care Delivery

The efficiency and effectiveness of Remote Physiological Monitoring (RPM) has allowed it to emerge as a popular practice in the healthcare industry. RPM has greatly increased the accessibility of healthcare, especially for chronic care patients. It has also allowed care providers to increase their revenue through the CPT reimbursement codes. The industry shift towards a patient-centric, Value-Based Model has allowed for sustained growth for RPM devices in the market. The current innovations in RPM devices have the opportunity to reshape the overall Patient experience. 

Remote Surgery Robots

How COVID-19 is accelerating RPM growth

The COVID-19 Pandemic has expedited the large-scale adoption of RPM. As health centers across the world focus on treating COVID-19, patients with other conditions have been encouraged or instructed to avoid health facilities. This has caused a large deficiency in the transfer of care. This disproportionately affects small clinics that need periodic cash flow and chronic care patients who require frequent clinic visits. RPM devices allow patients to bypass the restrictions by monitoring their health conditions from home. These machines help patients and providers stay up to date with their care plan progress. It also allows clinics to recover some of their lost revenue due to the pandemic. Moving forward, it appears that RPM will increasingly become an integral part of care delivery. 

Robot Assistants

The prospect of robotic devices has long been entertained in the healthcare industry. Developments in Artificial Intelligence (AI) and Machine Learning (ML) in the past decade have made a future with these devices more realistic. Acting as a personal assistant to long-term patients is one way that robots could make their way into mainstream healthcare. Many patients with chronic conditions require periodic monitoring and extended hospital stays. Robot Assistants could track the vitals of the patients and input the results into the patient’s Electronic Health Record (EHR). These machines would be especially beneficial to patients at rural or undermanned health clinics. It is at such places where Robot Assistants would significantly enhance the quality of care without replacing a human. A significant issue associated with Robot assistants are liability/legal concerns. Should any issues arise while the patient is under the robot’s care, it is unclear who would be responsible. 

Remote Surgery Robots

A more complicated manner in which Robots can enter the industry is through Remote Surgery. These machines can assist surgeons by simplifying complex procedures in ways that are not humanly possible. For example, they can use AI or ML to improve the accuracy of existing practices. Another benefit of Remote Surgery is the opportunity for long-distance procedures. An advanced Remote Surgery Robot could allow for a surgeon to perform on a patient thousands of miles away. The primary hurdle facing Robot devices involve high development and operational costs. Both the software and hardware of these machines are extremely intricate in nature. If this concern is addressed, Robots could become a cornerstone of modern healthcare.

Wearable Devices

Wearable RPM devices are already in common use by chronic care patients across the country. In a more loosely defined manner, fitness and smartwatches can also be considered as they perform many similar tasks as a medical RPM device. In this sense, over 20% of Americans already use one of these wearable devices. The main reason wearable RPM devices have yet to take off is the lack of multi-use devices. While a smartwatch has multiple functions, many medical RPM devices have very specific uses. This causes many patients to shy away from making a financial commitment to these products. An example of how this issue can be solved is exemplified in DexCom’s partnership with Apple. DexCom is using the Apple Watch as a platform for people to access their Glucose monitoring products. By using an established, multi-dimensional platform, DexCom is able to generate a larger outreach. A breakthrough in wearable RPM devices would greatly benefit patients with diabetes or cardiovascular issues. A device that they could wear around the clock would provide medical professionals with the data to better understand their condition. 

Future of RPM

The RPM market has significant potential for growth in the upcoming decades. The shift towards a more patient-centric focus has resulted in a positive outlook for future RPM development. Advancements in the overall quality and scale of RPM devices can transform the Patient Care Journey of tomorrow. 

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Could AI Transform the Way Healthcare Operates?

Artificial Intelligence (AI) involves the use of machines to perform human activities such as comprehension, interpretation, and analysis. AI has been an emerging force in all computerized fields and has gained significant attention amongst health tech innovators in the past few years. While AI remains heavily experimental, the results have been extremely promising with regard to the future potential of AI-based procedures. The prospects of AI-related technology have the opportunity to transform the future of healthcare delivery. 

Current Status of AI in Healthcare

AI is still in the early stages of development in the health tech industry and it has yet to fully penetrate the market. However, AI investment is projected to grow from $600 million to $6.6 billion between 2014 and 2021, indicative of the large and growing demand for such services. AI is already used by many health systems for everyday activities such as streamlining workflows, patient education, diagnosis, and predictive analysis. Including these practices has helped clinics save millions of dollars and serve patients more efficiently. Thanks to the rapid growth of AI, the healthcare industry will experience an influx of innovative techniques to help solve modern healthcare problems. 

Machine Learning in Healthcare

Machine Learning (ML) is a method within AI in which machines are given the opportunity to learn through experience rather than constant programming. In essence, this trains machines to think like humans and learn from practical examples. Areas of healthcare where ML is already prevalent include data collection, diagnosis, and clinical trials. This method is being experimented in the health industry due to the abundance of data needed to make informed decisions. ML can allow computers to process millions of data points in just seconds, resulting in a faster and more efficient result. In the future, effective use of ML could hold the key to vaccine development and cancer treatment. One hurdle ML faces is that it would need large-scale testing in order to become readily available for use in all areas of healthcare. This is due to ML being rooted in experience-based learning rather than rigid programming. 

Precision Medicine

Precision Medicine involves diagnosis and treatment plans that are specialized to the individual patient. This method greatly differs from traditional diagnosis and treatment as it analyzes millions of relevant variables to produce a patient-specific care plan. AI/ML-based machines can analyze more variables than humans could in a fraction of the time. One intriguing aspect of this technique is Whole-Genome Sequencing, which involves the analysis and discovery of an individual’s entire DNA sequence. AI/ML makes this technique possible by simplifying an extremely complex process. Ultimately, a streamlined version of Precision Medicine can shift healthcare away from standardization and towards personalized care. Like many AI techniques, Precision Medicine is highly developmental and will likely require large financial investments. Additionally, this method is quite controversial as it is still unproven and involves information about patients’ DNA. 


Robots are a clear example of how AI could be put into practice in the near future. Many large or high-budget clinics already employ the use of robotic machines. These instruments can carry out different tasks depending on their design. During the COVID-19 Pandemic, robots are being used to direct patients within a health facility to eliminate the risk of patient to care provider transmission. They have proven to be very effective in guiding patients when a human is unavailable. In a non-Pandemic context, robots would be useful in rural or undermanned health clinics, where similar situations could arise. Robotic AI machines could also be used for long term care patients who need daily monitoring and reminders related to their treatment. One area where Robotic-based AI can drastically reduce discrepancies in rural health accessibility is through Remote Treatment. Robotic devices could allow doctors to operate on patients without being physically present. The incorporation of Virtual/Augmented Reality devices could help with both clinical training as well as virtual appointments. The main obstacle associated with robots is that providers must make a significant financial commitment. This will subsequently make healthcare costlier for all parties involved, including patients and the Federal Government. 

AI and robotics in healthcare

Artificial Intelligence is opening the door for more efficient and accessible health care. The astronomical increase in AI investment proves the effectiveness of new developmental methods. If the industry is able to address the remaining financial obstacles, we can experience AI leading the healthcare industry into the future. 

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