Artificial intelligence in healthcare
Artificial intelligence in healthcare is an overarching term used to describe the utilization of machine-learning algorithms and software, or artificial intelligence (AI), to emulate human cognition in the analysis, interpretation, and comprehension of complicated medical and healthcare data. Specifically, AI is the ability of computer algorithms to approximate conclusions based solely on input data.
Can AI Help The Pharma Supply Chain Development?
Artificial Intelligence (AI) has proved itself as a game-changing technology, for every industry, and not just pharmaceuticals. In the past few years, people have witnessed the potential of AI, which can benefit the healthcare industry. AI is reinterpreting how scientists developed new drugs and discovered cures, along with how they diagnosed, and how drug adherence was dealt with.
Nevertheless, AI in the pharma supply chain has mainly been ignored in spite of having enormous technological and commercial opportunities in the industry. The time has come to make more investments in AI solutions, primarily targeting the established challenges with the pharma supply chain.
Big pharma is aware of the technological arms race carried out in the worldwide healthcare industry. Recently, people have witnessed an acquisition spree with a few large pharmaceutical companies grabbing biotech start-ups, devoting in state-of-the-art AI solutions, and hiring domestic data scientists to perform together with scientists. Moreover, technology in the pharma supply chain that links the lab to the market is holding up. With the globalization of the pharma industry and the demand growing for new product types, supply chains should also turn smarter.
An ideal supply chain for today and tomorrow is considered as one of the most reactive ones, but proactive as well.
It has the potential to anticipate, as well as accommodate the present and future trends, steering the forces and challenges. Multiple stress factors force the pharma industry to settle in a while developing new and quality medicines at a very affordable price. Numerous stress factors are increasing each year and adding up to the present, the real challenge, especially for the supply chain management.
When it comes to ecological pressures, regulators are forcing stricter environmental controls throughout the design, manufacture, and transportation of the pharma products to help limit the carbon emissions, as well as lessen plastic and water wastes. Multifaceted biologic drugs and gene therapies are growing increasingly famous, but also release enormous challenges for manufacturing and distribution networks, because of their sensitivity and mini life-cycle.
Besides, populations all around the world are growing old, along with the occurrence of associated chronic diseases such as cardiovascular disease, diabetes, cancer, and dementia. The criminal marketplace that sells falsified medicine is now worth more than $200 billion each year, making the safety of medicine quality a priority, including the progress of tamper-proof packaging technologies.
Artificial Intelligence Meets Medical Coding
Medical billing and coding is an integral component of healthcare. The medical coding outsourcing market alone is projected to reach16.9 billion dollars by 2021. However, coding accuracy is an ongoing challenge. To maximize efficiency and accuracy of the medical coding process, companies are testing the possibilities of Artificial Intelligence (AI) applications. The current problem is coding accuracy, and AI applications are improving the efficiency of the coding process.
The emerging technology, Computer-Assisted Coding (CAC), which works on Machine Learning and Natural Language Processing (NLP), is all set to transform the medical coding process. The CAC automatically identifies and extracts information from documents. It also analyzes the documentation and automatically recognizes relevant medical codes. In addition to processing codes and high volumes of data, AI can also reduce the standard work hours and human errors. AI helps providers address gaps in medical coding information. The AI reviews documentation and then guides the provider to adjust the documentation to ensure it accurately reflects the patient’s condition.
While utilizing AI to catch coding errors would be enough to justify its use, there are several other benefits that come along with it. AI’s potential for identifying false claims or suspect charges is one of the most obvious benefits. With healthcare fraud costing Americans around 68 billion dollars to 230 billion dollars yearly, having AI in place can immediately recognize suspicious activity. Additionally, AI is capable of identifying information that’s not explicitly stated in care providers’ documentation. Even with all of the benefits of accurate coding, doctors still fail to have a complete understanding of medical coding. Fortunately, AI can offer natural language software to apply appropriate codes even when a physician fails to document them thoroughly.
Medical coding is an essential component of how care is delivered and. Inaccuracy is a roadblock that needs to be addressed with the help of advanced technologies such as AI.
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