AI-powered language services facilitate better data analysis and insightsAI-powered language services facilitate better data analysis and insights

One of the hallmarks of language in healthcare is its ability to connect, empower, diagnose and enable treatments between the patient and health provider. But what happens when language acts as an impenetrable barrier, making communication and caring difficult? Language limitations present subtle but major problems in healthcare settings, influencing outcomes in ways we do not completely understand.

Healthcare communication is being redefined by AI-powered language services, which make it possible for patients and providers to communicate more accurately and efficiently, leading to better health and patient satisfaction. A study conducted by the Agency for Healthcare Research and Quality indicated that hospital stays caused by language problems are 22 per cent longer and had a 14 per cent greater risk of readmission. In addition to lowering healthcare expenditures and increasing patient outcomes, AI-powered language services can help lower these risks.

The market for artificial intelligence in healthcare was valued at US$19.27 billion globally in 2023 with healthcare firms holding the biggest revenue share. The market is further projected to expand at a compound annual growth rate of 38.5 per cent between 2024 and 2030.

Through improved patient outcomes, streamlined communication, and raised care standards, AI-powered language services are redefining the healthcare industry. Improved patient satisfaction and decreased errors are now possible with real-time, seamless communication between multilingual healthcare personnel and patients thanks to remote medical interpretation. Significant data from medical records is quickly extracted using AI-driven clinical text analysis, which helps make informed decisions even easier.

Moreover, precise real-time transcription from clerking by speech recognition technology is transforming doctor-patient relations and freeing up medical staff to spend more time providing patient care. With its groundbreaking real-time clinical speech-to-text capabilities made for more than 200 African dialects, Intron, Nigeria’s first speech-powered EMR is leading the way in Africa for the future of clinical documentation while helping clinicians finish notes seven times faster and freeing up three extra hours per day.

Additionally, chatbots give virtual help by responding to patient inquiries and giving basic care guidelines, such as Amwell's chatbot, which provides patients with personalised health information and support. It can also help patients with medication adherence, appointment scheduling, and answering medical questions, thereby improving patient engagement and health outcomes.

AI-powered language services have a wide range of transformative applications in medicine. Through the utilisation of these technologies, healthcare providers can guarantee precise diagnosis, efficient treatment strategies, and superior patient care, hence leading to a notable improvement in patient outcomes. Furthermore, by offering individualised care, responding to inquiries about health, and resolving issues immediately, AI-powered language services improve the patient experience.

Increased efficiency benefits healthcare practitioners as well because AI-powered language services simplify repetitive procedures, optimise clinical workflows, and reduce staff burnout and lessen administrative workloads. Moreover, by lowering errors, maximising resource use, and raising patient satisfaction, these technologies lower healthcare costs.

Not to be overlooked, AI-powered language services facilitate improved data analysis and insights, empowering medical professionals to make data-driven choices, spot patterns, and raise the standard of care.

Notwithstanding the advantages of AI-powered language services in healthcare, there are drawbacks and restrictions to take into account. Concerns about data security and privacy have become pressing since they relate to sensitive patient data. Ethics and regulatory issues must also be considered to guarantee accountability and openness in AI decision-making.

Furthermore, there are frequent shortages of high-quality training data, which could cause biases in AI decision-making. Moreover, there are serious ethical issues with AI decision-making due to its propensity for bias. Future developments in machine learning (ML) and natural language processing (NLP) will help to overcome these obstacles by enhancing data analysis and artificial intelligence (AI) decision-making. Integrating with electronic health records (EHRs) will improve the accuracy and accessibility of data. Accessibility and diversity will rise with expansion into new markets and languages, eventually leading to better healthcare results worldwide.

These technologies have the potential to transform the healthcare industry by lowering expenses, improving data analysis, and bridging language barriers. We need to urge healthcare companies to adopt these solutions and make investments in more research and development as we keep pushing the envelope of what is possible.

By doing this, we will ultimately alter the healthcare system and enhance people's lives all around the world by harnessing the full potential of AI-powered language services.

Jennifer Orisakwe is a health researcher and data storyteller, who loves to explore the ways actions (and inactions) of healthcare stakeholders affect decision-making and outcomes.

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