The healthcare sector has seen remarkable shifts as it adapts to evolving patient care needs and business standards. Patients today expect convenience, digital communication tools, and coordinated care. The rise of digital health technologies has made it easier for patients to get involved in their own health journey, and for providers to streamline care processes and share medical information.
Healthcare organizations are adapting to these changes by creating more flexible and robust systems. This includes the adoption of generative artificial intelligence (AI), and at its core, large language models (LLMs), to help organizations accomplish business and clinical goals.
Here are the main priorities and challenges facing healthcare in 2024:
It’s a fundamental priority to reduce disparities in healthcare access and outcomes so all individuals, regardless of their socioeconomic status, can receive quality care. This includes addressing barriers, such as geographical location, cost, cultural factors, and other social determinants of health (SDOH).
It’s crucial that healthcare organizations provide personalized treatment plans, enhance communication, and offer coordinated care to meet rising patient expectations. Furthermore, patients need to be informed and involved in their healthcare decisions.
Providers must shift the focus from treating illnesses to preventing them to improve the overall health of the population and reduce healthcare costs. The encouragement of regular check-ups, vaccinations, and healthy lifestyle choices can have a significant impact, and digital solutions play a significant role in helping patients manage their own preventative care.
It’s essential that the healthcare system as a whole switch from a fee-for-service reimbursement model to a value-based reimbursement model, which ensures that providers are incentivized to provide the most effective care over the most expensive care.
With the rise of cyberattacks in healthcare, healthcare organizations are prioritizing cybersecurity. They must ensure that patient information remains secure with robust policies to maintain trust, comply with regulations, and avoid devastating financial losses.
Investing in digital health technologies, like telemedicine, electronic health records, and AI can improve patient care, streamline operations, and reduce the administrative burden on clinicians.
Shortages of healthcare professionals, including doctors, nurses, and allied health workers can strain healthcare systems, affecting the quality and availability of care. This can also put significant strain on existing staff, as a 2023 National Institute of Health (NIH) study found that 49.9% of healthcare workers experienced burnout; burnout being the highest amongst nurses. What’s more, the employee churn rate at hospitals is 22.7%, significantly higher than the national average of 3.8% across industries.
The increasing cost of healthcare services and treatments poses a challenge for both consumers and healthcare systems, with healthcare spending increasing by 4.1% in the US 2022. Healthcare expenses are expected to continue climbing, pressuring organizations to find cost-effective solutions without compromising quality. Another issue is inflation, as organizations are forced to pay higher wages to accommodate cost of living demands, they must also increase costs for services to support operating expenses.
As the global population ages, there is a growing demand for healthcare services, particularly for the elderly, who may require specialized care and management of multiple chronic conditions.
Although improvements in healthcare treatments have occurred, some research suggests that millennials are the first generation to have a lower life expectancy than the previous generation. Much of this decline can be attributed to the increase in sedentary lifestyles, obesity, and the availability of processed foods.
Healthcare organizations are embracing generative AI technologies to help them adapt to changing demands and improve the healthcare system as a whole. Here are the main benefits of generative AI for healthcare.
As healthcare systems embrace generative AI tools, they’re able to meet patient demands more quickly, reduce the workload on clinicians, and diagnose and treat ailments more effectively. Here are some of the top use cases for generative AI in healthcare.
Chatbots are a great way to streamline care operations. They can provide automated responses to frequently asked questions, schedule appointments, suggest relevant resources, and escalate to a human resource when necessary. This can reduce the workload on healthcare staff, allowing practitioners to spend their energy helping the patients in need instead of performing mundane tasks.
AI-powered document comparison engines can help healthcare organizations ensure compliance with healthcare regulations by automatically comparing policies, guidelines, and legal documents to check for adherence to standards.
Build more holistic, comprehensive medical records by co-creating reports with specialists based on data culled from large databases and disparate EHR systems. Summarize medical documents, look for data duplications, and perform patient matching.
Simplify the imaging process through
automation of analysis, anomalies detection, and radiology assistance. AI tools can help identify early signs of cancer, Alzheimers, and more with more accuracy than the human eye, which can
Generate informative, disease-specific content for personalized education to help patients manage their illnesses. Deliver tailored recommendations via email or text to support preventative care and keep patients out of the ER.
It’s time for healthcare organizations to adopt generative AI tools to meet the evolving needs of patients and stay ahead of the market. Still, adopting AI is more of a marathon than a sprint.
Since AI is only as good as the data it trains on, you’ll need to get your data ready for AI, first and foremost. Then, you’ll need to make sure your AI solution resides in a secure, compliant environment in order to avoid disastrous security breaches and compliance violations.
All of this is time-consuming and complex, but Cloudticity can help you accelerate your AI journey on AWS. Get the data ready, build a secure, compliant foundation, and create a proof of concept. Contact us today to get started with generative AI in healthcare!