Recent innovations in artificial intelligence, especially machine learning, may usher in a new era of automation across anesthesiology.
Anesthesia delivery is steadily evolving. Over the years, the conventional anesthesia machine has evolved into an advanced care station. The new machines use advanced electronics, software, and technology to offer extensive capabilities for ventilation, monitoring, inhaled agent delivery, low-flow anesthesia, and closed-loop anesthesia. They offer integrated monitoring and recording facilities and seamless integration with anesthesia information systems. It is possible to deliver tidal volumes accurately and eliminate several hazards associated with the low pressure system and oxygen flush. Low-flow anesthesia and advanced ventilation modes are becoming more commonplace in most anesthesia systems nowadays. There are new modes of ventilation on machines that make the anesthesia machine ventilator like the ventilators used in the ICU. The new technology machines have electronic gas mixers, electronic vaporizers, digital flow meters, and software available that allow users to save gas and agent by using lower gas flows and lowering vaporizer settings.
Several companies are continuously looking for ways to enable customers to maximize their operational efficiencies. Main areas that are currently being focused upon are continued improvement of minimal flow anesthesia delivery, development of lung recruitment strategies typically only found in ICU, and the introduction of data analytics into their offerings. There have also been many attempts to incorporate automation into the practice of anesthesiology, though none have been successful. Fundamentally, these failures are due to the underlying complexity of anesthesia practice and the inability of rule-based feedback loops to fully master it. Recent innovations in artificial intelligence, especially machine learning, may usher in a new era of automation across anesthesiology.The anesthesia machines are being widely utilized as a part of almost all medical procedures as they are intended to give exact and consistent supply of medical gases (nitrous oxide and oxygen) blended with analgesic vapors (isoflurane) administered to patients at safe flow and pressure. Technological advancements, owing to increasing investments by major players in research and development, are enhancing the efficiency and reliability of these machines. Advanced anesthesia machines come with features integrated to ensure the safest possible experience for the patients, which are increasing their adoption, thereby augmenting the market growth.
Indian market dynamics
The Indian anesthesia equipment market in 2017 is estimated at Rs 181 crore, a 7.5 percent increase over 2016 and at 5625 units, a 10 percent increase over 5115 units in 2016 in volume terms. Prices across all segments declined by about 10 percent.
GE maintained its market share, with major contribution by 9100c NXT based on GE/Datex Ohmeda’s legacy of 100+ years of innovation and trust. Mindray entered the super value segment and had success with orders from government hospitals in 2017. These included Government of Andhra Pradesh, which procured 29 units; Bihar Medical Services and Infrastructure Corporation Limited (BMSICL) purchased 20 units; Government of Uttar Pradesh bought 70 units of mid-tier systems for its various district hospitals and healthcare facilities. Procurement was also made by Government of Kerala; new AIIMS facilities; and Rajendra Institute of Medical Sciences (RIMS), Ranchi. Some brands including Philips, Maquet, Schiller, and Omya, are not visible anymore.
Manufacturers are continuously introducing technological advances in their machine which focus both on patient safety and efficiency. The anesthesia machine of today is trending toward a compact ergonomic design for ease of use and surfaces that are easier to keep clean to reduce nosocomial infections. This machine has integrated cutting-edge monitoring that is versatile and customizable to increase diagnostic confidence.
Integrated systems. Recent models have added new ventilation modes and most manufacturers are trying to increase the similarities between their ventilator and anesthesia monitor interfaces. The new machine has ICU quality ventilation across all patient categories and has low flow and minimal flow anesthesia modes to improve anesthetic delivery and reduce financial impact. Anesthesia machine using the latest vent technology such as turbo vent ventilation with airway pressure release ventilation (APRV), and volume auto flow which provides protective ventilation therapy in the OR for all patient categories is worthy of the initial investment.
Many new advancements are also focused around IT integration and software enhancements but, generally, technology is moving anesthesia machines from mechanical to electronic systems where possible. Electronic controls and advanced algorithms can help clinicians improve clinical care and help administration manage costs, but it is important that any incorporation of electronics does not negatively impact the safety concepts behind the machine such as maintaining the ability to deliver fresh gas and agent to the patient even without power.
AI in anesthesia. Medical researchers, informatics specialists, and digital entrepreneurs have been exploring the use of artificial intelligence (AI) in the healthcare sphere for decades, but it is only within the past couple of years that the technology has really begun to take off. Indications are that in healthcare, AI, now commonly known as machine learning (ML) is set to explode, in fact. Imagine an environment in which machines capable of cognitive computing and processing vast amounts of data can support you with unprecedented accuracy, efficiency, and patient-specificity on everything from monitoring the depth of anesthesia, determining the amount of anesthetic gas to administer, somatosensory evoked potential monitoring, classifying patients, and mitral valve analysis to coding and billing.
At some point in the future, if a fully autonomous anesthesia system could be created and validated, then it could certainly result in profound effects on the workflow patterns and needs of anesthesia providers. These innovations may allow anesthesiology the freedom to reinvent itself from an intraoperative specialty to one of true perioperative medicine. Such changes are already underway with the emphasis on non-operating room subspecialties like pain medicine and critical care. For the time being, though, both the hopeful and dystopian futures are possible, and there is no way to reliably predict which outcome is more likely. As a specialty, anesthesiologists have tended to be early adopters of technology, and tend to be comfortable incorporating technological solutions to improve patient care. They should continue this trend and not only stay abreast of advances in AI, but make concerted efforts to integrate them into practice now so that they can be the authors of their own future improving provider productivity and each patient’s outcome by building and working in concert with narrow AI learning systems that create truly individualized, evidence-based clinical guidelines built in real time based on analysis of the entirety of medical literature and pooled patient data from electronic medical records.