New AI Tool Rolled out by NextGen EMR System

The Electronic Medical Records (EMR) software vendor, NextGen Healthcare has announced the accessibility of its latest Artificial Intelligence tool tagged NextGen Ambient Assist, which aims to enhance provider efficiency. The AI tool leverages ambient listening technology to summarize patient visits directly into the EHR software system.

The Benefits of NextGen Software’s Ambient Assist Solution

The following advantages can be reaped by providers with the latest Ambient Assist solution available within the NextGen Software mobile application:

• Clinical workflows can be simplified as the Ambient Assist transfers AI-generated SOAP notes into the EMR Software. SOAP notes are a common technique of recordkeeping in healthcare settings, especially in professions such as medicine, nursing, physical therapy, and counseling.
• The fully automated AI solution helps to reduce documentation time by two hours every day, giving more time for providers to focus on delivering high-quality patient care.
• In 30 seconds after a patient encounter, the SOAP notes appear for the physician to review. This helps to boost clinical efficiency and reduce the chances of clinician burnout.
• Precise documentation prevails with NextGen’s Ambient Assist resulting in 90% documentation accuracy.

Features of the Ambient Assist

The revolutionary AI tool offers the following features to healthcare providers:

• The Ambient Assist is an intelligent tool that recognizes medical abbreviations for concise and effective documentation.
• The AI tool by NextGen EMR Software is completely technology-based meaning providers don’t need a medical scribe.
• Thorough automation: The physician doesn’t have to copy and paste anything into the EHR system.
• Auto-deletion feature for maximum patient privacy of sensitive data.

Final Takeaway

The AI Ambient Assist launched by NextGen Healthcare is a powerful, and intuitive tool that can be used by clinicians to document quickly, and accurately. By reducing clinical documentation time and post-visit note completion time, providers have more time to focus on patient diagnosis, and treatment to improve health outcomes.

Simply put NLP allows us to process human language, far beyond simple voice dictation. Let’s explore the applications for Natural Language Processing in present EMR software for clinicians, from documentation and even to interoperability.

What is Natural Language Processing

Natural Language Processing is an AI technology, which focuses on translating natural human language into computable instructions. It gives computers the ability to understand human language.

With recent advances in Artificial Intelligence, the applications of Natural Language Processing may even turn it into an essential tool for physicians to have in their EMR systems:

• Enhancing Data Extraction
  • Extracting data from clinical data to generate treatment plans, clinical notes, and reports.
• Automated coding and billing
  • Automatically assign medical codes to encounters, simplifying the billing and administrative burden.
• Sentiment analysis
  • NLP can help clinicians to gauge emotional states, by analyzing sentiments expressed in patient narratives.

Benefits of Natural Language Processing

There are many ways that clinicians can benefit from NLP in EHR software.

Improved Accuracy and Efficiency of Data Support:

NLP can allow healthcare professionals to dictate clinical notes into EMR software with natural human language. By eliminating the need for manual entry, clinicians can spend less time on documentation and more time with patients.

It also provides an easy way to ensure that accurate patient data is captured and can go a step further to reduce the potential for errors.

Enhanced Clinical Decision Support:

Natural Language Processing is able to analyze large amounts of patient information such as clinical notes, lab results, and reports.

NLP can identify hard-to-detect patterns, relationships, and trends in data and assist clinicians in diagnosis, predicting outcomes, and providing treatment plans – improving patient outcomes.

Streamlined Clinical Documentation:

A big chunk of clinical information is in documentation, in fact, up to 70% of meaningful information for clinicians is held in notes. It influences patient care, billing, and even legal compliance.

Conveniently NLP is a great solution for simplifying, accelerating, and automating a lot of this process, by automatically populating relevant fields with information extracted from patient narratives and ensuring they adhere to standardized codes and terminology.

There even are some Natural Language Processing (NLP) solutions in EHR software that are capable of documenting entire patient encounters from simply listening to clinician-patient conversations.

Interoperability and Data Sharing:

Additionally, NLP plays a huge role in interoperability in Electronic Medical Records software systems. Natural Language Processing can help to translate different medical terminology and concepts across different EMR systems seamlessly.

NLP makes it possible to easily analyze large amounts of clinical documentation – which can also be used on unstructured medical notes often found in EHR software systems. This can therefore be used to bridge the gap between EMR systems and enhance interoperability in Electronic Medical Records software.

3 EMR Software with Natural Language Processing

For modern EMR software, machine learning and AI tools are not a new trend, so there have already been EHR vendors quick to adopt NLP into their health IT systems.

AthenaHealth

One of the leading EHR software vendors, athenaHealth is partnered with Nuance to integrate voice recognition and NLP technologies such as speech recognition and transcription.

Epic EHR

Epic EHR, one of the most widely used EHR software systems, utilizes Azure Open AI to integrate GPT-4 into their EMR software, with features such as natural language queries.

Epic also has a partnership with Suki, the AI voice assistant company, which can generate clinical notes by listening to patient conversations.

Cerner

Cerner, another health IT software vendor, has been working on integrating NLP into their existing EHR software, to review and code encounter notes in seconds.

Healthcare professionals can also make use of dictation, and with Dragon Voice Recognition can easily document and make notes much faster than manually typing.

Conclusion

In conclusion, NLP in EHR software represents a significant leap toward more efficient, intelligent, and patient-centric healthcare systems. By leveraging the power of NLP, healthcare providers can unlock valuable insights from textual data, streamline administrative tasks, and ultimately improve the quality of care they deliver.

EHR vendor’s efforts to simplify the clinical charting process

Health IT vendors have been working hard to reduce the documentation burden on clinicians by streamlining the overall charting process. They have added new features and NLP solutions to enable providers to finish documentation quickly and easily. Here are some of the ways EMR vendors can improve documentation:

1. Implement voice recognition technology: Vendors of Electronic Medical Records (EMR) Software can incorporate voice recognition technology so that clinicians can dictate their notes and spend less time typing. In addition to increasing accuracy, this can lessen the requirement for manual documentation.
2. Use natural language processing (NLP): NLP technology can assist clinicians in swiftly locating pertinent patient information within an EHR system. NLP can extract and organize patient data by utilizing machine learning algorithms to evaluate unstructured data. This allows physicians to spend less time searching for the information they need, hence streamlining clinical documentation.
3. Streamline data entry: EMR providers can make data entry easier and more intuitive by removing additional fields and automating basic operations. This can cut down on the number of clicks and keystrokes needed to do a task, reducing the amount of time spent on documentation. This way, physicians can have more time to focus on their patients.
4. Mobile accessibility: Mobile EHR software applications can allow clinicians to access patient information on the go. This reduces the need to document information later. A more effective workflow is achieved by enabling mobile access, which enables doctors to enter data while interacting with patients.
5. Standardized documentation:  Many electronic health records vendors such as Epic EMR Software, athenahealth, CareCloud, and ChartLogic have developed standardized documentation templates that are easy to use and understand by the user. By providing a consistent format, clinicians can document patient information in a breeze. Repetitive and unnecessary typing is eliminated.

Benefits of streamlined clinical documentation

Streamlined clinical documentation is bliss for providers as they don’t have to spend time on administrative tasks now. Once the documentation burdens are reduced, healthcare providers have the opportunity to offer high-quality patient care which can in turn boost patient outcome levels.

When clinical documentation is streamlined, there are fewer chances of any errors. As documentation is standardized clinicians may make fewer mistakes. This can lead to more accurate and complete patient records supporting the provider’s decision-making process at the point of care.

Major EHR Software vendors that offer voice recognition technology

The following EMR Software vendors offer voice recognition technology to ease the documentation and charting process.

• Epic Software offers Haiku.
• Cerner provides Voice Assistant.
• Allscripts Healthcare Solution has the Dragon Medical feature.
• athenahealth EMR software offers athenaClinicals Voice.
• NextGen Healthcare’s voice recognition tool is called NextGen Virtual Visit.

All these voice recognition tools allow clinicians to dictate notes and recognize different accents to speed up the tedious documentation process. As technology advances, more health IT vendors are anticipated to include speech recognition features in their software systems to lessen clinicians’ documentation load and improve workflow efficiencies.

How can Artificial Intelligence technology support care delivery?

Enhanced Decision Making

Whilst it is common for humans to make mistakes, there is limited space for error in the healthcare industry because mistakes can result in fatalities. Technologies that are powered by machine learning and artificial intelligence can offer information that can support a doctor’s decision-making process. For example in sepsis diagnosis, AI algorithms are commonly used to alert physicians about any adverse events leading to severe sepsis, this can reduce death rates and admissions to the ER.

Early Patient Diagnosis

Artificial intelligence has also been used to facilitate the early diagnosis of cancer in patients, improving diagnostic accuracy and providing patients with a cancer-free life. When cancer is detected in its early stages, the chances of recovery are higher than in later stages, which can be life-threatening and even more unpleasant for the patient and their family members.

Boosting Patient Engagement and Patient Experience

Improving the whole care experience can assist patients in remaining satisfied with the healthcare treatments they require. Hospitals have utilized AI-powered technologies such as symptom checkers to triage patients and expedite healthcare processes. AI-powered chatbots can be used to organize online appointments and respond to daily queries, dramatically improving the patient experience.

AI algorithms are being used to send educational material and medication reminders to patients, keeping patients feel engaged in their healthcare process and improving medication adherence and overall wellness routine.

AI and Software Technology

Many EHR software vendors are using Artificial Intelligence technology in the design of Electronic Medical Records (EMR) Software systems making them more accurate and efficient. AI-enabled EMR Software solutions allow providers to promptly access and export patient data with the least error. It also enhances clinical decision making, for example, Epic EMR Software Systems’ AI solutions help clinicians to predict hospital readmissions and patient mortality rates. AI-designed software system improves interoperability options in clinical documentation. The seamless flow of data improves care coordination to enhance the patient treatment process.

AI-based speech-to-text technology embedded in the software can help streamline the clinical documentation process. As documentation time is reduced, physicians can now focus on their patients. A study was done by the AMA and the University of Wisconsin which revealed that 50% of healthcare providers’ time is spent on tedious admin tasks. With AI the administrative burden of clinical documentation is reduced.

Moving ahead

AI technology is transforming the way healthcare systems around the world run. It is allowing for more lives to be saved by lowering diagnostic errors and revealing previously unexplored prospects for improving patient engagement and experience. For AI to become mainstream, providers must regard it as an assisting tool that can be used to improve care delivery.

KLAS Report – Clinical Documentation Strategies

According to the latest  KLAS report, the healthcare market is embracing front-end speech recognition as the go-to clinical documentation platform.

Documentation Technology Solutions

The KLAS report examines different documentation technology tools and services and how they aid users.

Front-End Speech Recognition

The interviewed organizations revealed that front-end speech recognition technology has enhanced over the last few years. Front-end speech recognition is precise and offers the flexibility to be used in a variety of platform types.

Healthcare providers can use their smartphones to capture dictation and review patient notes. The only downside to the robust technology is its expensive price.

Transcription Services

As speech recognition tools are on the rise, healthcare organizations and clinicians are moving away from in-person scribes and transcription services. Though, respondents expressed that transcription services play a vital part in EHR software documentation.

Scribes and transcriptionists are useful for doctors who are hesitant to use speech recognition technology. Scribes can aid practitioners by assisting them in the tedious documentation process.

Virtual Scribes

94% of the respondents feel that virtual scribes have a positive impact on documentation time. Users revealed that virtual scribes complete clinical documentation at the end of the day.

Respondents said that the main issue with virtual scribes is the inconsistent quality of transcribers.

Computer-Assisted Physician Documentation

Respondents had affirmative views about computer-assisted physician documentation as they made code capture efficient, increased revenue, and reduced documentation time.

However, some physicians stay away from CAPD because they don’t fit with the clinician’s workflow and offer too many recommendations.

Developments in the Speech-Recognition Market

Ambient-speech recognition technology in the medical field is still a newer market and is developing. The ambient-speech recognition market is booming and KLAS is hopeful to measure the success of these solutions shortly.

Ambient speech recognition tools leverage automatic speech recognition and natural language processing (NLP) to document patient and provider conversations in the Electronic Health Records software. The powerful technology can help alleviate clinician burnout and improve provider satisfaction at work.