AI In Patient Care: Potential Uses and Trends in the Industry

Take a look at any business—in any industry—and you’ll see that artificial intelligence (AI) is being used somewhere in a company’s business processes. The ability AI has to quickly process large amounts of data, recognize patterns, and make fast, accurate decisions far surpasses that of humans.

More recently, artificial intelligence in healthcare has really taken off, with healthcare professionals using the technology to better diagnose individuals, treat patients and manage their care. AI-driven tools, including machine learning algorithms and natural language processing (NLP), are used to analyze medical records, predict patient outcomes, and personalize treatment plans.

These are just some examples of artificial intelligence in healthcare. Here are several others that are becoming more common as AI gets better and better.

AI in Diagnosing Patients

AI tools allow doctors to make faster and more accurate, efficient diagnoses. Take machine learning algorithms for example. Using AI, providers can easily analyze large medical datasets, including data captured from image scans, patient history records, and electronic health records. Using these insights, doctors can identify patterns and predict potential diagnoses. Plus, AI systems can detect possible health anomalies and early disease indicators for diseases like cancer or heart disease with more precision and accuracy than humans.

Below, we’ll take a closer look at some examples of artificial intelligence in healthcare, focusing specifically on patient diagnostics.

Enhanced Imaging and Radiology

The use of healthcare AI tools have changed the way medical imaging and radiology is done. With the technology, healthcare professionals have access to a numerous tools that increase the accuracy and efficiency of patient diagnostics. Traditional imaging techniques, like X-rays, MRIs, or CT scans, generate a huge amount of data that requires a careful review by radiologists. AI algorithms, particularly those that rely on deep learning, are better at identifying patterns in these datasets. Their pattern-identification functions enable them to better detect anomalies and subtle changes in tissue that might not be visible to the human eye.

AI-Powered Diagnostic Tools and Applications

Improving imaging isn’t the only way AI-powered diagnostic tools and applications are changing healthcare processes. The technology has also had a major impact on how professionals diagnose and treat diseases. Take machine learning models for instance. The technology is trained on large datasets taken from patient records. Using the data, AI platforms can figure out how likely patients are to have specific health problems based on things like demographic information, symptoms, genetics, and more. For example, using AI tools on cardiac patients can help doctors quickly detect heart abnormalities based on data from their ECG. Or, in dermatology, doctors can quickly find skin lesions and suggest possible causes or treatment plans based on the information provided by the AI tool.

Examples of AI in Healthcare

Now that you understand how healthcare professionals are using AI to help with diagnostics, let’s take a look at a few examples of AI in healthcare:

• Google Health: Google Health uses an algorithm capable of detecting breast cancer in mammograms with greater accuracy than human radiologists.
• PathAI: PathAI enhances the accuracy of pathology diagnoses by analyzing tissue samples. In clinical trials, the tool has demonstrated a higher diagnostic accuracy rate than traditional methods.
• IBM Watson Health: IBM Watson Health uses AI to analyze large datasets and provides personalized treatment recommendations for cancer patients.

AI in Personalized Treatment Plans

Today’s patients are taking more control of their health—and they expect healthcare providers to do the same. They expect personalized treatment plans that meet their unique health goals. Using AI allows healthcare professionals to meet those expectations. They can create those treatment plans faster and more effectively. And with much-needed data insights. Here’s how healthcare AI tools can help:

Tailoring Treatments to Individual Patients

AI can analyze a patient’s unique health characteristics and medical history. Coupled with machine learning algorithms, these tools can evaluate data from various sources, including electronic health records, wearable devices, and patient-reported outcomes. They can also create treatment plans for individuals. This individualized approach ensures that therapies are more effective and better meet a patient’s specific needs. For example, AI can recommend medication dosage based on a person’s metabolic profile which helps to minimize side effects and maximizes benefits.

Using Predictive Analytics to Improve Treatment Outcomes

Predictive analytics tools allow doctors to understand the outcomes various treatments will have on patients. These insights, gathered by AI tools, help doctors to improve their decision-making and better care for patients. For example, AI tools can help a diabetic patient make the necessary lifestyle or medication changes based on their current or predicted blood sugar levels.

Genomics and Precision Medicine Data Improve Diagnoses

Looking at genomic data, AI algorithms allow providers to identify genetic mutations or biomarkers that are associated with specific diseases. The data also helps providers make more accurate diagnoses and treatment plans. For example, oncologists (doctors who specialize in treating cancer patients) can use AI tools to find genetic mutations known to further cancer progression. Doctors can then create personalized cancer therapies that target these specific genetic alterations.

Top Ways AI is Improving Efficiency in Healthcare

AI tools are improving how doctors make patient care and overall care quality better—from automating administrative tasks and improving resource management. Here’s how:

Streamlining Administrative Tasks

One of the biggest ways AI has improved healthcare is by freeing up the amount of time healthcare professionals spend on manual administrative tasks. For example, Podium’s AI Patient Coordinator can automate common front desk processes like patient inquiries, appointment scheduling, and payment collection. With Podium, healthcare facilities can speed up patient care and improve accuracy, freeing up time to focus on patient care rather than paperwork or other tedious tasks.

Scheduling and Resource Management

The key to improving operational efficiency while simultaneously automating processes and minimizing wasted resources, healthcare providers need better scheduling and management processes in place. AI-driven scheduling systems are a perfect choice. They allow healthcare providers to quickly analyze historical data and gather critical insights like team member availability or patient appointment patterns—both of which can be used to create more optimized schedules.

AI tools can also improve resource allocation. These solutions rely on data to predict patient admissions and discharges, ensuring healthcare facilities have the resources in place to handle fluctuating patient volumes.

Lowering Waiting Times and Enhancing Patient Flow

Long wait times are a huge complaint among patients. Using predictive analytics and real-time data processing, AI tools can better anticipate patient demand and adjust a healthcare facility’s workflow or resources as needed. For example, AI tools can predict busy times in an emergency department and allocate staff or resources to better manage the increase in patient volume. This helps to keep wait times low and helps patients get treated faster.

Additionally, doctors who use AI-powered triage systems can prioritize patients who need treatment quickly based on the severity of someone’s condition. Not only does this help to improve overall patient flow and efficiency, but it also helps to improve the overall patient experience by minimizing delays and accelerating time to treatment.

AI in Patient Monitoring and Support

As we’ve mentioned above, AI and healthcare are significantly improving the way doctors and nurses monitor, treat, and support patients. The result is an improved ability to deliver timely, personalized, and more effective patient care.

Remote Monitoring and Telehealth

Since the COVID-19 pandemic, telehealth services and remote monitoring have become more popular. AI has been central to the success of these practices. For example, with AI-powered tools or platforms, doctors and nurses can continuously monitor patients who have chronic conditions or watch those recovering at home. This reduces the need for in-person visits which can be difficult for some individuals.

Additionally, these systems have the ability to gather data from numerous sources, including home-based medical devices, healthcare sensors, and other devices. Using AI, healthcare professionals can watch for any signs of deterioration. For example, if someone is recovering from a surgery at home, AI tools can monitor vital signs like blood pressure, oxygen levels, heart rate, and medication doses. If anything is wrong, the tools can alert healthcare providers before the issue escalates into an emergency.

AI-Driven Wearable Technology

Wearable healthcare devices—like smartwatches and fitness trackers—are becoming increasingly more popular. Most are equipped with advanced sensors that doctors can use to continuously monitor someone’s health metrics, including activity levels, sleep patterns, heart rate, blood pressure, and even electrocardiograms (ECGS). To save doctors time (and alert them more quickly), AI tools analyze all this data and can quickly detect any anomalies or irregularities. For example, wearable technology devices can alert people or healthcare providers to an irregular heartbeat or a drop in blood sugar levels which allows for faster intervention.

Real-Time Data Analytics for Proactive Care

As we’ve mentioned above, AI tools and systems are able to process huge amounts of data from sources like EHRs, wearable devices, and other monitoring tools—all in real-time. With this real-time data, healthcare providers get faster access to insights that can help doctors identify healthcare patterns and correlations that otherwise would have been invisible.

Additionally, AI allows healthcare providers to intervene earlier, adjust treatment plans, and take more preventive measures. All this helps individuals to avoid potentially serious health consequences. For example, AI can help someone with diabetes better manage their disease by continuously monitoring glucose levels and predicting potential fluctuations. This allows doctors to adjust the individual’s diet and medication to avoid drops or spikes in their blood sugar levels.

Podium: Bringing AI in Patient Care to Healthcare Facilities

The use of AI in patient care is changing the way doctors and nurses care for patients. From speeding up treatment processes and automating administrative tasks, AI technologies are giving providers the necessary tools to better care for their patients. Additionally, by using new AI technologies, such as remote monitoring or wearable devices, healthcare professionals can create personalized healthcare plans, improve patient outcomes, and provide better care, faster.

As the healthcare industry keeps changing, healthcare facilities must find ways to embrace and utilize AI. With Podium’s CSR tool, you can automate your entire front desk process—from appointment scheduling to billing—to free up healthcare providers’ time. Plus, with our AI-powered employee, customers have access to help and support 24/7, enabling them to get answers to their healthcare needs faster. With access to faster, more personalized care, healthcare professionals can provide a better, more personalized patient experience.

Ready to learn more about Podium’s CSR tool? Watch a free demo today.