How AI For Clinical Workflows Helps Provide Better Care?

The healthcare system today faces significant challenges, including managing vast amounts of patient data, ensuring timely and accurate diagnoses, and dealing with administrative burdens that can detract from patient care. These issues can often lead to inefficiencies, increased costs, and suboptimal patient outcomes. 

AI for clinical workflows offers a promising solution. By integrating AI in healthcare, you can streamline operations, enhance diagnostics and treatment, and improve clinical decision-making.

This article explores how AI enhances clinical workflows, improving healthcare delivery and making the system more efficient.

What Is Clinical AI Workflow?

Clinical AI workflow is the integration of artificial intelligence into the various processes involved in patient care and medical practices to enhance efficiency in patient outcomes. This integration facilitates the streamlining of processes like medication management, treatment planning, resource allocation, and administrative tasks.  

For example, in radiology, AI algorithms can analyze medical images such as CT scans, X-rays, and MRIs to detect abnormalities the human eye may miss. AI can also help you automate routine administrative tasks like scheduling, billing, and documentation, allowing healthcare providers to focus more on patient care. 

Clinical Workflow Challenges that AI Solves

The healthcare industry grapples with numerous clinical workflow challenges that might affect the quality and effectiveness of patient care. AI technology empowers to address several of these critical issues: 

Data Overload 

Healthcare providers often need help handling overwhelming amounts of patient data from diverse sources, including electronic health records, medical imaging, and patient monitoring. Manually sorting through and analyzing this data is time-consuming and prone to errors. 

You can quickly analyze and process this data using AI, sifting through millions of data points in seconds and identifying key details and patterns that human eyes can miss. By highlighting the most relevant information and presenting it in an easy-to-digest format, AI helps you make informed and timely decisions.

Diagnostic Accuracy 

Accurate diagnoses are crucial in healthcare, as mistakes can result in incorrect or delayed treatments, potentially harming patients. Human error, fatigue, and the sheer complexity of medical data can contribute to diagnostic inaccuracies. 

AI significantly enhances diagnostic accuracy by leveraging advanced algorithms and machine-learning techniques. For instance, using AI, you can analyze trends in a patient’s symptoms, genetic data, and medical history to suggest potential health issues. This helps diagnose conditions that present with non-specific symptoms or are rare and difficult to identify.

Administrative Task Management 

Administrative tasks in healthcare include appointment scheduling, billing, medical record management, and much more. These tasks can take up significant time, diverting your attention from patient care and contributing to increased workload and stress. 

AI helps you simplify administrative tasks through data automation, which uses technology to manage and process data automatically. This process enables you to minimize the time spent on routine duties and focus more on delivering high-quality patient care. 

For instance, AI-powered scheduling systems can automatically handle appointment bookings and cancellations, send reminders, and resolve scheduling conflicts.

Key Applications of AI For Clinical Workflows

AI is transforming various aspects of clinical workflows by enhancing the efficiency and accuracy of critical processes such as scheduling, analysis, and routine tasks. Here are some key applications of AI for clinical workflows:

Patient Scheduling and Triage

With the help of AI, you can automate appointment booking and prioritize patient cases based on urgency, improving clinical workflow efficiency. For example, an AI system can analyze incoming appointment requests, automatically schedule them into available slots, and send reminders to patients. These AI systems can also assess urgency based on symptoms and historical data, prioritize critical cases, and alert you, ensuring timely care for urgent cases.

Automated Documentation

AI helps streamline routine paperwork by automating form completion and patient record updates. Leveraging AI tools with natural language processing can transcribe verbal notes into structured electronic health records and automatically populate form fields with relevant data, reducing time spent on documentation and improving productivity.

Clinical Decision Support Systems

Clinical decision support systems (CDSS) that AI powers enhance diagnostic accuracy and treatment recommendations by analyzing comprehensive patient data. For example, an AI-driven CDSS helps you identify patterns in lab results and medical history, recommend personalized treatment plans, and suggest further diagnostic tests if needed.

Billing & Claim Settlements

Automation helps simplify the medical billing services and claim settlement process in healthcare. It assists in managing tasks such as verifying insurance details, processing claims, and handling payments. For example, you can use AI solutions to detect discrepancies in the billing code, ensure compliance with insurance requirements, and expedite the claim process. This reduces errors and speeds up the reimbursement process.

Resource Allocation

AI tools can optimize resource management in healthcare. They enable the prediction of patient volumes, scheduling of staff, and management of equipment. For instance, AI tools can help you analyze historical patient data and current trends to forecast peak times and efficiently schedule staff shifts.

Benefits of AI-Powered Clinical Workflows

Incorporating AI into clinical workflows offers numerous benefits. Here are some of them:

Improved Efficiency and Productivity

You can use AI to automate routine clinical administrative tasks such as scheduling, documentation, and billing. This automation reduces the administrative burden, allowing you to focus on patient care.

Enhanced Patient Care

With the help of AI-driven tools, you can efficiently analyze patient data, including medical history, genetics, and lifestyle factors, to offer personalized treatment plans. This tailored approach improves diagnosis accuracy and ensures more efficient and timely interventions, leading to better patient outcomes. 

Resource Optimization

Integrating AI into clinical workflows can optimize resource management. This integration helps predict patient flow and manage inventory controls. This ensures that resources are allocated correctly, reducing waste and improving the overall efficiency of healthcare operations.

Reduced Medical Errors

AI supports clinical decision-making by providing evidence-based recommendations and identifying potential errors in treatment plans or medication dosages. This reduces the likelihood of misdiagnosis and enhances the accuracy of medical decisions, contributing to safe patient care.

How to Implement AI For Clinical Workflows?

Implementing AI for clinical workflow can transform healthcare delivery and enhance patient care and resource management. Here are some steps you can follow to implement AI for clinical workflow:

Integration with Existing Systems

Ensure AI tools work well with your existing systems, like EHRs and practice management software. This involves evaluating compatibility, ensuring smooth data transfer, and maintaining continuity of operations. 

For instance, integrating an AI-powered image analysis tool with your radiology imaging system can automatically detect and highlight abnormalities in scans, improving diagnostic accuracy and the review process.

Choosing the Right AI Tools and Platforms

Select an AI solution that aligns with the specific clinical needs and goals of your organization. Consider factors such as features, ease of use, scalability, and support for customization. Choosing the right platform is important for maximizing AI's benefits and addressing your workflow requirements. 

Data Privacy and Security Concerns

Addressing the concerns related to data privacy and security is essential when implementing AI into workflows. Ensure that the AI tools comply with regulations such as HIPAA or GDPR and enforce strong encryption and access controls to protect critical patient information.

Employee Training

Equip your healthcare staff with the knowledge and skills to use AI tools effectively. Provide training on the features and functionalities of each tool, emphasizing how to interpret and apply AI-generated insights to improve clinical decision-making.

Regulatory Compliance

Ensure that the AI implementations meet all the relevant regulatory and industry standards. This includes obtaining necessary certifications, adhering to documentation practices, and staying updated with evolving regulations.

Few AI Tools for Clinical Workflow Automation

Automating routine tasks and providing advanced analytics are essential to improve efficiency, reduce costs, and enhance patient care in healthcare settings. Here are a few AI tools that facilitate clinical workflow automation: 

Enlitic: Optimized Medical Imaging Data Management

Enlitic is an intelligent healthcare tool that facilitates medical imaging analysis and data management through advanced and deep learning technology. By leveraging advanced algorithms and machine learning, Enlitic enhances diagnostic accuracy, improves workflow efficiency, and supports data-driven decision-making in radiology. This allows you to deliver better patient care by effectively utilizing medical imaging modalities.

Enlitic offers several AI products that streamline the management and analysis of medical imaging data. 

• The ENDEX solution is designed to improve workflows and data analysis in radiology. It utilizes NLP and computer vision to standardize and enrich imaging data. By transforming new and historical medical images into a consistent, clinically relevant nomenclature, ENDEX corrects image routing issues and enhances the display of protocols, streamlining operations within radiology.
• ENCOG is a specialized AI-powered data anonymization tool that protects PHI (protected health information) while preserving clinically important data. It uses AI to remove personal identifiers from medical images, including embedded and private tags, using computer vision and NLP. By de-identifying these images, ENCOG helps keep patient information private and safely used for research and analysis. 

Regard: Automating Clinical Tasks

Regard is an AI-powered tool designed to assist clinicians in analyzing patient data and making informed decisions. It also provides diagnostic suggestions and drafts clinical notes, serving as an AI co-pilot that integrates seamlessly with electronic medical record systems. This integration optimizes clinical practice and streamlines administrative tasks.

Regard offers a range of AI-driven features that enhance the analysis and management of patient data.

• With Regard, you can identify and record complications and comorbidities that may be missed during manual documentation. This enhances the overall quality of patient data. 
• Regard uses generative AI to create possible diagnoses from patient data. This capability helps you to explore various possibilities, confirm or rule out conditions, and refine treatment plans.

Merative: AI Enhanced Healthcare Solutions

Merative is a healthcare tool that aims to provide innovative solutions for healthcare, including clinical decision support, imaging, and operational efficiency. It offers versatile and adaptable AI solutions such as Micromedex, Zelta, Merge, and more tailored to address operational challenges. These applications are designed to enhance diagnostic confidence and improve the clinical experience. 

Merative provides a suite of innovative solutions designed to improve the analysis and management of healthcare information. 

• Its AI solutions, Micromedex and DynaMedex, enable you to access current, reliable drug information at the point of care, helping you make better decisions for patients. 
• Zelta is a Merative AI solution designed to streamline clinical trials. This cloud-based, unified data management and acquisition platform features customizable modules, allowing it to adapt to the specific needs of your research. By offering tailored solutions, Zelta helps accelerate trial outcomes and address the complexities of modern clinical research.

Pieces Inpatient Platform: Clinical Gen AI for Frontline Care

The Pieces Inpatient Platform is a clinical AI solution that improves operational efficiency and patient care by automating the summarization, charting, and drafting of clinical notes directly within EHRs. This automation helps you address clinical burnout, enhance the quality of clinical documentation, and improve overall patient management.

Here are some of the features of the Pieces Inpatient Platform: 

• Provides a unified view of patient data in plain language to aid decision-making and care coordination. 
• Pieces help you identify and track the discharge barriers by analyzing patient data, including medical history, social factors, and current treatment plans. This analysis enables accurate discharge predictions and resource management.

Viz.ai: Enhancing Care Coordination with AI 

Viz.ai is a healthcare technology company that harnesses the power of AI to enhance patient outcomes through a comprehensive care coordination solution. It utilizes FDA-cleared algorithms to analyze medical images such as CT scans, EKGs, and echocardiograms, providing real-time insights and automated assessments. 

Viz.ai leverages innovative AI capabilities to support timely and accurate medical interventions. Here are some of its features: 

• Viz.ai utilizes sophisticated deep learning algorithms to analyze medical imaging and deliver real-time insights, accelerating the diagnosis and treatment.
• It offers a comprehensive set of AI-powered solutions to auto-detect suspected diseases across various therapeutic areas, enabling quicker diagnosis and treatment and facilitating prompt and effective patient care.

DeepScribe: Streamline Clinical Documentation

DeepScribe is an AI-powered, fully managed ambient platform that automates clinical note-taking by transforming patient conversations into customizable chart notes. It is a widely used AI medical scribe that helps you streamline clinical documentation and integrate seamlessly with EHR systems.

DeepScribe leverages advanced AI technology to streamline clinical note-taking and enhance accuracy. Here are some of its features:

• DeepScribe generates detailed and personalized clinical notes within seconds of a visit tailored to specific medical specialties. Clinicians can automatically translate their notes into comprehensive clinical documentation, saving time and improving decision-making accuracy. 
• DeepScribe allows you to integrate with EHRs to import patient data and provide context for more accurate documentation. 

How to Collect & Unify Data for Clinical AI Workflows?

Effective AI-powered clinical workflows depend on seamless data collection and unification from diverse sources. To achieve this, gathering comprehensive data from clinical systems such as EHRs, laboratory information systems, imaging systems, and patient management systems is essential. This includes structured data (patient demographics and medical history) and unstructured data (clinical notes, imaging reports), which provide a complete view of patient information.

Airbyte is a powerful tool that simplifies the process of collecting and unifying data from multiple sources. With its extensive library of pre-built connectors, Airbyte can link to diverse data sources, including EHRs, databases, and APIs. These connectors allow you to easily integrate data from disparate clinical platforms into a central repository. 

To ensure data quality and integrity for robust analysis, Airbyte provides features such as:

• ‍Gen AI workflow: Airbyte helps you streamline Gen AI workflow by enabling the direct loading of unstructured data into vector store destinations. You can unlock valuable insights and improve decision-making by efficiently integrating and organizing patient health records, lab results, and diagnosis reports. 
• ‍Custom Connector Support: Airbyte provides a connector development kit that helps you customize existing connectors or build new ones tailored to your organization’s needs. This flexibility supports the integration of diverse clinical data sources.
• ‍Change Data Capture: Airbyte's Change Data Capture (CDC) technique enhances data synchronization. This feature effortlessly captures and syncs data modifications from various source systems. Therefore, any changes or updates made to the source data are promptly reflected in the target system, maintaining data consistency and reliability.
• ‍Monitoring: Airbyte offers various ways to monitor your data pipelines. These options include connection logging for detailed reports, datadog integration for dashboard analysis, and OpenTelemetry integration for pushing metrics to self-hosted solutions. Using Airbyte’s monitoring features, you can quickly track data flow and maintain data integrity.

Additionally, Airbyte supports the automation of data pipelines, allowing for continuous data collection and updates. This ensures that your clinical AI workflows can access the most current information, enhancing the effectiveness of AI-driven insights and decision-making.

Conclusion

Incorporating AI for clinical workflow helps you address the existing challenges and foster a more responsive and patient-centered approach to healthcare. Various AI tools offer significant advancements in managing and utilizing clinical data. You can leverage these tools to automate clinical workflow tasks and improve the efficiency and effectiveness of healthcare systems. Embracing these advancements is the key to advancing patient care quality and achieving better clinical outcomes.

FAQ 

Can AI be used in clinical documentation?

AI is transforming clinical documentation by automating time-consuming tasks and improving accuracy. By leveraging text to speech voice conversion and NLP, AI tools can transcribe and structure clinical notes, reducing manual effort and ensuring data consistency. Additionally, AI can automatically populate electronic health records (EHRs) with relevant data, minimizing the risk of errors. 

What is an example of an AI-powered clinical workflow?

An example of AI-powered clinical workflow is using chatbots and large language models to automate the interpretation of healthcare-related data and increase contextual understanding for better decision-making. 

How to choose a clinical workflow automation tool?

Choosing a clinical workflow automation tool involves several steps, including recognizing needs, evaluating features and functionality, costs, integration and compliance capabilities, and more.