The healthcare industry faces several challenges, including the need to shift to new payment models and deliver higher-value care while maintaining a qualified and capable staff. In this complex and dynamic environment, the amount of data that needs to be accessed, processed, analyzed, and shared is constantly increasing, particularly in larger-scale specialties like oncology. Healthcare providers now require smart tools to help sift through all this information and guide their decision-making. Artificial intelligence (AI) is a powerful tool that can address these challenges and transform the healthcare industry, offering unprecedented opportunities to improve patient outcomes, lower costs, and optimize staff performance.
AI machines can imitate human cognition functions such as problem-solving and recognizing patterns. They turn data input (e.g., patient charts, imaging, study result) into an output (e.g., image classification, diagnostic, suggested treatment plans) based on rules or algorithms. AI technologies can adapt, self-correct, and improve as more data is available. AI does not refer to one specific type of machine or field of study but is an umbrella term encompassing different subsets, such as machine learning (ML) or deep learning (DL), within the science and engineering of intelligent machines.
The primary benefit of AI is its ability to review and analyze vast amounts of data accurately in a fraction of the time it would take a human being. It can also complete high-volume repetitive tasks quickly and efficiently. In many instances, AI can do some tasks, such as detecting anomalies in imaging, with even more accuracy than a human could. Rather than replacing human reasoning or decision-making, AI can ensure that doctors have the information they need to make decisions at the right time. Overall, AI is a powerful tool that can provide the best quality of care while helping to meet the data demands of a value-based care model.
Value-based care (VBC) is a healthcare delivery model that aims to provide better patient outcomes while reducing the cost of care. In contrast to the fee-for-service model, value-based care rewards and reimburses providers for the quality of care, not the number of services delivered. Collecting and analyzing large amounts of patient data is crucial to the success of VBC in the following ways:
Sifting through enormous volumes of data to identify risks or patterns can be challenging and time-consuming for humans; this is where AI shines. These technologies can quickly analyze vast amounts of data, giving healthcare providers the data they need when needed and enabling higher-value care and improved patient outcomes.
Hospitals and providers must invest in effective data management solutions and infrastructure to accommodate the shift to value-based care and meet the increasing need for relevant data. AI technology is steadily becoming more integral to any healthcare system that desires to decrease inefficiency and improve the patient outcomes.
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References:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285156/#CIT0035
https://hitconsultant.net/2022/10/05/health-data-value-based-care-success/
https://www.valuebasedcancer.com/avbcc-video-highlights/3248-transforming-healthcare-delivery-with-artificial-intelligence