ACHDM

American College of Health Data Management

American College of Health Data Management

Why leveraging AI portends promise to aid healthcare

Organizations implementing the technology hope to reap benefits in improving efficiency and reducing the burden of care.



This article is Part 2 in a 3-part series. Read Part 3: Why AI offers long-term benefits in improving outcomes.

As artificial intelligence continues to expand its role in healthcare, it is revolutionizing how providers diagnose, treat and manage chronic conditions like diabetes. AI technology helps streamline care, reduce the burden on clinicians and improve patient outcomes. 

Here, we’ll explore how providers use AI to enhance their practices, focusing on tools like electronic health records systems (EHRs), AI-driven documentation and advanced data summarization. These innovations not only improve the accuracy and efficiency of care but also pave the way for better patient education and outcomes.

Documenting, managing chronic diseases 

In managing chronic diseases like diabetes, accurate documentation and comprehensive tracking of a patient’s medical history are critical. Providers rely heavily on EHR systems to record diseases, comorbidities, treatments and test results. However, the sheer volume of data and the complexity of patient histories can make maintaining comprehensive and accessible records challenging. 

AI has become a vital tool in overcoming these challenges. EHR systems equipped with AI enable providers to more easily document disease treatment and track test results. This not only saves time but also ensures that critical information is not overlooked. 

For example, AI can flag potential comorbidities that a provider might not immediately consider, ensuring that the full scope of a patient's health is considered when making treatment decisions. 

The integration of AI in EHRs also enhances the accuracy of patient records. By analyzing both structured and unstructured data, AI helps providers gain a more comprehensive understanding of a patient’s medical history. This knowledge streamlines care by enabling providers to avoid repeating treatments that have proven ineffective or caused adverse effects. Moreover, AI can assist in surfacing relevant data during consultations, enabling providers to offer more informed medical advice and recommendations.

More knowledge, better recommendations 

One of AI's most promising applications in healthcare is its ability to help providers quickly access and synthesize vast amounts of medical data. 

For example, the search and summarization tool in Meditech Expanse is an AI-powered feature that enables providers to extract valuable insights from both structured and unstructured data within the EHR. This tool can quickly summarize a patient’s medical history, previous treatments and test results, giving clinicians the information they need to make informed decisions. 

The Expanse search and summarization function not only saves time, but it also reduces the likelihood of errors by ensuring that no critical information is missed. By bringing relevant data to the forefront, it aids providers in making accurate diagnoses and tailoring treatments to individual patients. 

This personalized approach to care is particularly beneficial in managing chronic conditions like diabetes, where the nuances of a patient’s medical history can significantly impact treatment effectiveness. 

Furthermore, the ability to access detailed patient histories and previous treatment outcomes helps providers avoid prescribing medications or treatments that have not worked well in the past. This knowledge is crucial in preventing adverse effects and optimizing treatment plans, ultimately leading to better patient outcomes.

Ambient listening technology, documentation 

In addition to enhancing data management, AI is transforming how providers document patient encounters. One of the most significant burdens on clinicians is the time-consuming task of documenting patient visits. Traditionally, this process has required providers to take detailed notes during or after consultations, leading to increased workloads and potential burnout. 

Ambient listening technology, powered by AI, is changing this dynamic. These systems can listen to patient-provider interactions in real time and automatically generate detailed documentation. This reduces the time clinicians spend on paperwork, enabling them to focus more on patient care. AI-driven documentation tools not only improve efficiency but also enhance the accuracy of medical records by capturing the nuances of patient-provider conversations. 

The integration of AI in generating documentation also helps maintain consistent and thorough records across all patient encounters. This consistency is critical in chronic disease management, where ongoing monitoring and accurate documentation are essential for tracking disease progression and adjusting treatment plans as needed. 

AI’s role in diagnoses, treatment 

AI's ability to analyze vast amounts of data and identify patterns that may not be immediately apparent to human providers is one of its most powerful capabilities. 

In diabetes management, AI can assist in accurately diagnosing the condition and its related complications. By analyzing data from various sources, including lab results, imaging studies and patient-reported outcomes, AI can help providers identify early signs of complications such as neuropathy, retinopathy or kidney disease. 

AI's can help forecast a patient’s risk of developing complications based on their medical history and lifestyle factors. This predictive capability enables providers to implement preventive measures early, potentially reducing severe complications and improving long-term patient outcomes. 

A study published in Future Healthcare Journal titled Artificial Intelligence in Healthcare: Transforming the Practice of Medicine discusses how AI is reshaping medical practices, particularly in improving diagnostic accuracy and optimizing treatment plans. The study emphasizes that AI’s ability to analyze complex datasets and provide real-time insights is revolutionizing patient care, leading to better outcomes and more personalized treatment approaches. 

Looking ahead 

The integration of AI into healthcare is not just about improving efficiency. It is about enhancing the quality of care that providers can offer their patients. From accurately documenting medical histories and managing chronic diseases to supporting providers in making informed treatment decisions, AI plays a crucial role in reducing the burden of care for clinicians while improving patient outcomes. 

Empowered patients, equipped with AI tools and providers whose workloads are eased by AI-driven efficiencies will collectively lead to better health outcomes. This synergy between patient empowerment and reduced provider burden is a promising path toward more effective and personalized healthcare. 

As AI continues to evolve, its applications in healthcare will undoubtedly expand. The future of healthcare is being shaped by AI, and its potential to transform patient care is only beginning to be realized. The next article in this series will delve into how these empowered patients and more focused providers are working together to achieve even better outcomes. 

Randall Brandt, PA-C, has nearly 30 years of experience as a physician assistant at Mile Bluff Medical Center in Mauston, Wis., and played a pivotal role in his organization's MEDITECH Expanse implementation.


This article is Part 2 in a 3-part series. Read Part 3: Why AI offers long-term benefits in improving outcomes.

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