In many countries around the world, women giving birth still face substantial risks to their own lives and that of their baby. Women travel for days to reach facilities that are understaffed, unsafe, and unequipped to provide life-saving surgical care. They are pushed into financial catastrophe as a result of paying for surgical care, if they are able to afford it all, and they return home with little support in the way of post-operative care.
Today, 70 percent of the world lacks access to safe, affordable, timely surgery. A third of global disease burden is amenable to surgical care, ranging from cancers and injuries, to obstructed labor and congenital anomalies such as cleft lip. Substantial progress has been made over the past decade to improve global access to safe, affordable, timely surgical care, but vast global disparities still persist. Could Big Data and AI-enabled health care delivery services answer some of health care’s most complex research challenges?
One of the biggest problems in the health care analysis today relates to unstructured data in electronic health records (EHR), which relates to data stored in clinical notes, operation reports, and pharmacy scripts. More than 80 percent of health care information is inaccessible, and there are no real solutions in the market that stably digest and understand these free-form clinical data. However over the past few years, there have been significant efforts to tackle how we understand unstructured data so that we can derive larger insights into disease treatment patterns, possible at the individual level but also at a population level, using high-level AI-augmented techniques such as natural language understanding (NLU) to make sense of unstructured data. Researchers in the NLU space are familiar with some of the big players in the space, such as IBM Watson, Amazon Comprehend, 3M, and Google. But alongside these initiatives, some exciting smaller companies, such as Clinithink, Droice Labs, and Linguamatics, are making huge steps in understanding. The importance of these approaches relate to their potential to transform health care by developing horizontal AI applications that augment and strengthen the whole health care system and improve patient care and physician workflow.
The implementation of robust, scalable, and impactful technologies that are equity-oriented, evidence-based, and data-driven have the potential to accelerate access to health care for all where a key example of potentially huge impact is surgery. Every year 18 million deaths occur that could be prevented by the provision of surgical care that is safe, affordable, and timely. In addition to this, surgical safety initiatives — augmented by AI — that are rolled out globally have the potential to reduce the current estimated 4.2 million post-operative death rates that occur each year. Improving surgical outcomes and strengthening surgical systems worldwide will be essential to achieve universal health coverage, and technologies which accelerate access to high-quality health care will play a crucial role in this urgently required health system innovation. What role can physicians play?
Physicians are equipping themselves with core data science skills which enable them to perform complex analyses and generate insights from these data, unlocking new areas of research in the fields of AI, big data, and natural language processing. Others are polishing up on their biostatistics, advocacy, and implementation skills, enabling them to contribute to initiatives that improved access to safe surgery. They are contributing to efforts to plan and implement national surgical plans which strengthened surgical systems in settings where surgery is still largely inaccessible for those who many need it the most.
The key motive that is driving this skill diversification in our workforce today is simple. Within 20 years, 90 percent of health care jobs will require some element of digital skills, according to the recent Topol review on the digital health care workforce. Globally, the health care workforce needs guidance and expertise on the evaluation of these new technologies, using processes grounded in real-world evidence. As technologies like artificial intelligence will impact all levels of health care — the clinician, the patient, and the system — it is important to consider current limitations, such as bias, privacy, security, and lack of transparency. This gives us an opportunity to have an awareness of digital health technologies as we begin to use them in our practice, so we are able to understand their limitations and potentially harmful impacts on patients if they are not developed with bias considered at every stage.
Access to health care for all on a global scale will only be realized through the strengthening of surgical systems and the opportunities for digital surgical innovation are huge. An education in global and digital health – in training, as well as in medical school – would allow the workforce to appreciate the complexities in health care delivery that exist today around the world. This theoretical knowledge, alongside the existing biological context provided in medical school, would allow the future workforce to consider the vast health inequities that cause suffering for the majority of the global population, alongside a roadmap to develop some of the most promising solutions.
It would empower students, doctors and surgeons alike, to ask questions like: How is it that a heavily pregnant mother has to walk for days to reach a facility to receive urgent care that is life-threatening for her and her baby? Why is it that she is told that nothing can be done for her preventable and treatable surgical condition? And how do we develop, implement, and evaluate the digital solutions that would offer hope around the world, so that everyone is able to benefit from these technologies?
The author is an anonymous medical student.
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