How best to leverage artificial intelligence in healthcare informatics
The much-hyped technology is expected to make significant impacts with EHRs, imaging studies and in data analytics.
Artificial intelligence is revolutionizing industries globally, and healthcare is no exception. In the field of healthcare informatics, AI is transforming the way patient data is analyzed, diagnoses are made and treatments are delivered.
This article delves into how AI is reshaping healthcare informatics and the profound impact it is having on clinical practice.
The basics of using AI in informatics
AI is the term used to describe how machines mimic human intelligence. Artificial intelligence tools like machine learning, natural language processing and neural networks are being used in healthcare informatics to analyze massive volumes of data, spot trends and produce predictions that help medical personnel make well-informed decisions.
A well-known example is IBM Watson Health, which utilizes AI to process and analyze large volumes of unstructured medical data. This capability helps physicians make more accurate and data-driven decisions, ultimately improving patient care.
AI in EHR management
AI is transforming the way healthcare providers manage and utilize electronic health records systems. EHRs contain vast amounts of structured and unstructured data that can be difficult to analyze using traditional methods.
AI-driven tools like natural language processing (NLP) and machine learning can sift through this data to uncover insights, detect anomalies and assist professionals with clinical decision-making. AI can help streamline administrative tasks, such as automating coding and billing processes, thereby reducing clinician workload and minimizing errors.
For instance, an article published in the Journal of American Medical Informatics Association (JAMIA) describes how AI-enabled EHR systems have increased the accuracy of patient recording and made real-time data analysis possible, leading to better patient care. To facilitate early interventions, these systems also can identify trends that may indicate the advancement of a disease or unfavorable outcomes.
By making EHRs more efficient and actionable, AI enables healthcare professionals to focus more on patient care while reducing the burden of manual data entry and interpretation.
AI-driven predictive analytics
One of the most promising uses of AI in healthcare informatics is predictive analytics. AI analyzes historical health data to predict future health outcomes, enabling clinicians to intervene at earlier stages. Predictive models can flag patients at high risk for conditions like heart failure, sepsis or hospital readmission, enabling timely and targeted interventions.
For instance, a study published in BMC demonstrated how AI models, as opposed to conventional grading methods, could more precisely forecast patient deterioration in hospitals. This skill lowers healthcare expenses by averting issues before they arise in addition to saving lives.
AI in medical imaging and diagnostics
AI is also making significant strides in medical imaging and diagnostics. Advanced algorithms can analyze medical images such as CT scans, MRIs and X-rays to detect abnormalities with high accuracy.
When it comes to diagnosing diseases like lung cancer, AI-based diagnostic technologies have proven to be on par with — and, in some cases, even better than — human radiologists. These tools can process large datasets quickly, providing faster and potentially more reliable diagnoses, leading to better patient outcomes.
For example, a study published in European Society of Radiology showed that an AI system outperformed human experts in breast cancer prediction.
Ethical considerations
While AI offers numerous benefits in healthcare, it is essential to address the ethical challenges that come with its implementation. Issues such as algorithmic bias, data privacy and the potential for AI-driven decisions to overshadow human judgment must be carefully managed.
It is critical for healthcare organizations to ensure that AI systems are transparent, explainable and free from biases that could negatively affect patient care.
Furthermore, while utilizing AI systems, there needs to be explicit protocols in place to safeguard patient privacy and data security. In the era of artificial intelligence, patient data is protected by frameworks such as the Health Insurance Portability and Accountability Act (HIPAA) in the U.S. and the General Data Protection Regulation (GDPR) in Europe.
It is essential to ensure that AI tools enhance, rather than replace, human oversight to sustain trust between patients and healthcare providers. "Augmented intelligence" highlights AI's role in assisting and strengthening human decision-making, rather than taking over those responsibilities.
Artificial intelligence is transforming healthcare informatics, providing powerful tools for data analysis, predictive modeling and diagnostics. As AI technologies continue to advance, their integration into healthcare will produce even more groundbreaking innovations, ultimately improving patient outcomes and reducing healthcare costs. However, the ethical implications of these tools must be carefully considered to ensure that AI benefits all patients equitably.
Herat Joshi, Ph.D, BE, PMP, FACHDM is data science team lead at Great River Health System