Research has found out that the costs of healthcare are rising at a faster rate than inflation. Experts argue that healthcare costs will increase by more than 20 percent of America’s GDP by 2025. As the US physician shortage grows, doctors are working hard to treat patients. Medical professional schedules are tight such that they lack a human element that inspired their pursuit of medicine.
Artificial intelligence appears intimidating in the healthcare sector. The majority of doctors feel threatened by AI because of the belief that it can take away their jobs in the coming years. To some medical professionals, AI is an enabler, an accelerant, and not a threat. AI can be good business to the vendors and assist instead of replacing medical professionals. The following are the three ways in which AI is changing healthcare.
Faster
The speed of healthcare operations is essential. For the case of Viz.ai stroke detection simulation, every second of the reduced time of treatment is equivalent to saving more than 1.9 million patient’s brain cells. The deep learning algorithms implemented in Viz.ai simulation save many minutes and even save hours of the brain. Studies have shown that Viz.ai led to a significant reduction in a patient with a disability.
Less expensive
Since healthcare cost is increasing, a strategy that leads to cost-cutting measure is useful. For instance, Athelas uses computer vision and machine learning to recognize morphology types of cells from prick blood. Therefore, clinicians can save money on every patient by keeping patients compliant with therapeutics, detecting adverse events earlier, and reducing hospitalizations. Many patients use AI countrywide daily. Such include those on inflammatory drugs, immune-suppressive anti-psychotics, and those on aggressive anti-cancer chemotherapy.
Besides saving money, AI reduces the risk and strain of hospital visits and enables chemotherapy patients to obtain significant results from their homes. Suki is another AI-powered clinical electronic assistant that utilizes natural language processing. It types notes that doctors could have typed. In summary, Suki helps medical practitioners to reduce documentation time by approximately 76 percent. The company launched a version of Suki that has a voice platform known as Suki speech service, featuring a new intent extractor.
More accurate
There are particular tasks that are boring and tedious to human beings. Researchers at Google released a report stating that Google AI could perform better than doctors for specific kinds of breast cancer detection. AI has the potential to improve decision choices accuracy by splitting noise from signal and keeping doctors to focus on the future. For instance, AI can help doctors answer questions accurately, such as positive and negative cases of COVID-19 cases. Accurate modeling might result in better and well-thought decisions in the healthcare sector.
Prosperous healthcare powered by AI
The integration of accuracy, cost, and speed can bring a lot of relief to patents. Nevertheless, the promise of boosted efficiency, cost, and speed is inadequate to influence patient welfare meaningfully. Currently, many companies sell software programs that boost the diagnostic accuracy of tests. Such is particular in fields that involve visual imaging or diagnosis such as radiology or pathology. Engineers should develop AI-powered products for healthcare with a vivid understanding of medial workflows to overcome risks and inertia of change. They need to be direct and consider the economic stimulus to doctors and employers.
Luckily increasing cost burdens and rewards, availability of EMR data for analysis, emergency of payment techniques such as bundled payments, and health data publications can help fasten the benefits of AI in the healthcare sector.
Many firms have mastered that the algorithms are not products, and for them to evolve a successful business, they need to cultivate technological determinations. They also need to challenge their teams to learn the complexity of healthcare and deliver their products on the clinicians’ side. Finally, it is essential to prove the business model on ROI, together with clinical improvements. True progress will be achieved when firms can harness AI to boost patient outcomes and align the firm’s rewards to hospitals.
