10 Top Applications of Generative AI in Healthcare for Enhanced Documentation Efficiency, Safety, and Patient Communication
Generative AI has drastically reshaped the landscape of several industries, notably business, education, and entertainment – and is now poised to transform healthcare. Although generative AI in healthcare is still developing, the potential use cases and outcomes are promising.
One of the pillars of healthcare is providing quality care, often characterized by accuracy, timeliness, efficiency; all characteristics that can be improved by generative AI.
Ideally, artificial intelligence could dramatically improve productivity for healthcare organizations and reduce or even eliminate clinician burnout.
To get there, generative AI solutions for healthcare must prioritize healthcare security standards and patient safety. Some providers may be curious to try GPT healthcare solutions with tools like ChatGPT to streamline their workflow, but this could violate organizational policies and HIPAA regulations depending on the source of the solution.
Dolbey has recently released Fusion Narrate AI Assist, a generative AI solution designed to easily incorporate into healthcare workflows. We have come to learn about the many use cases for generative AI as well as the important attributes for success: meeting healthcare security requirements, ensuring patient safety, and being integrated with the provider’s workflow.
Keys to Success for Incorporating Generative AI in Healthcare
- Healthcare Security – For a generative AI solution to be viable in healthcare, it must employ several safeguards to comply with HIPAA regulations. This includes end-to-end encryption of data, data storage and access protocols, and Business Associate Agreements (BAAs) with any vendor that will have access to PHI. Removal of Protected Health information (PHI) before vendor processing is another feature that can enhance the security of a generative AI solution.
- Patient Safety – Documentation generated by AI should undergo a review and approval phase by providers to guarantee accuracy and completeness. This in turn means that providers will need to be trained on and familiar with the capabilities of generative AI, potential limitations of the technology, and proper use cases. The provider should always have the opportunity to review and correct AI-generated text before incorporating that text into any health record or communication.
- Integrated Workflow – Seamless integration into a healthcare provider’s workflow is paramount for any gen AI solution. The solution should enable providers to adjust the generated output for particular use cases, make the decision on when and how to effectively employ generative AI, and allow for customizations to meet their particular needs.
This article will highlight the top applications of generative AI in healthcare, and how they are used to enhance medical efficiency and improve patient care.
Top 10 Ways to Leverage Generative AI in Healthcare
- Inconsistency Checks in Medical Documentation
Among the most powerful applications of gen AI in healthcare is assistance with documentation.
Generative AI can be very good at identifying potential inconsistencies and discrepancies in medical documentation, such as inconsistent test results, imaging report conflicts, follow-up care confusion, contradictory progress notes, and medication errors.
Healthcare providers can use artificial intelligence to review medical documents for inconsistencies in real-time to catch potential errors and ultimately provide more accurate and clear communication to ensure patient safety and effective care management.
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- Drafting Email Reponses
Healthcare providers can be inundated with patient inquiries by email or built-in EHR messaging systems. It takes considerable time to respond to each message – which is not a resource providers have in excess. In many cases, an appropriate draft response to general inquiries can be predicted and formulated by generative AI.
For example, a patient might request follow-up guidance for a worsening sore throat or whether they should schedule a visit for a particular pain or symptom. In those cases, a suggested response with concise and specific guidance can be automatically created to be reviewed by the provider for accuracy and then sent directly back to the patient.
Alternatively, instead of suggesting an email response, AI can be used to improve a draft response to a patient. For example, a provider may write or dictate a few brief notes and then quickly augment those notes to build a complete personable and explanatory response with generative AI.
In either case, healthcare providers can streamline communication with their patients while maintaining professional and personalized care.
- Translation of Medical Terminology for Patient Understanding
Healthcare professionals have the expertise required to interpret imaging or pathology reports and the specialized medical terminology within them. That medical terminology, however, is inaccessible to most patients.
A patient might be alarmed by hearing that they have a benign prostatic hyperplasia or dyspepsia, for example, because they don’t understand those terms. A plain language description, like enlarged prostate or upset stomach, might be much more comforting alongside or in replacement of medical terminology.
With generative AI, medical reports that only a provider would understand can become accessible to patients without losing meaning. This can help bridge the communication gap between providers and patients by effectively translating medical terminology into plain language instantaneously.
- Language Translation Services
Generative AI is highly accurate at translating between many different languages, which can further bridge the gap between providers and patients.
For example, if the patient only speaks Spanish, then it would be helpful to provide the treatment plan in their native language. A treatment plan could easily and effectively be translated through generative AI.
Similarly, if a patient sends a message in a different language than the provider, the provider needs to first translate the message to their own language, then respond back in the patient’s language. This helps both parties understand one another and improves the accuracy of communication between the two.
- Radiology Impression and Recommendations
Impressions within a radiology report provide a summary and interpretation of imaging results. With generative AI, it’s possible to formulate a suggested impression from the radiologist’s detailed findings or results. Even recommendations, including detailed follow-up actions, can be suggested.
By effectively automating the impression and recommendation sections of radiology reports, radiologists can significantly reduce documentation time.
GenAI is already being integrated within several radiology reporting solutions, reflecting its utility and growing acceptance.
- Chart or Visit Summaries
Reviewing a patient’s full chart or even the notes for a current visit can be very time-consuming, when all that may be needed is a summary of the important diagnoses and progress for continued care. Generative AI is very effective at summarization and can be especially useful in condensing these charts or notes.
Proficient gen AI healthcare solutions, such as AI Assist, can offer customized summarization that can closely cater to certain provider needs.
For example, a pathologist may want a summary of an imaging report and findings from the ordering physician. A radiologist may instead want to receive a summary of the current reason for the exam and past imaging report findings. Both of which are easily accomplished by generative AI.
A summarization can also be tailored for particular care scenarios, such as providing a report summary for certification to hospice services.
- Discharge Instructions and Treatment Plans
Documenting discharge instructions and detailed treatment plans can be quite tedious and time-consuming, particularly for common conditions such as an ankle sprain, cough, or sore throat. Generative AI can be used to provide detailed draft documentation very quickly with limited medical information and instructions.
It’s much easier for a provider to simply review drafted documentation and remove or edit unwanted information than documenting from scratch for each patient.
This can ultimately lead to more comprehensive documentation for the patient compared to if the provider wrote or dictated all the information from scratch with their limited amount of time.
An example prompt request to draft discharge instructions and treatment plans might be: “Based on the report, thank the patient for coming into the urgent care and provide the following: a treatment plan in list form, follow-up instructions for their primary care physician, emergency conditions for returning, and instructions for returning if symptoms worsen or they develop new concerning symptoms.”
The results of this prompt would be clear and comprehensive – and would only require review from the provider to ensure accuracy and completeness. Speeding this process up contributes to improved patient care and communication between patient and provider.
- Differential Diagnosis and Treatment Options
Patients entrust and rely on healthcare providers for their extensive training and expertise to determine an accurate diagnosis and the best treatment. However, even the most experienced healthcare providers don’t know everything.
Generative AI models trained on medical diagnosis and treatment information can serve as valuable tools to support healthcare providers. Given the details of a patient’s medical documentation such as symptoms, lab results, imaging results, vitals, medications, and physical exam, generative AI can quickly suggest other potential diagnosis and treatment plans.
While this technology is not ready or intended to replace a provider’s expertise, the information can be helpful for a provider to consider. It may even offer possibilities a provider may not have initially thought about.
- Enhanced Documentation for Accurate Reimbursement
Another purpose of healthcare providers’ documentation is to provide evidence for appropriate reimbursement claims from insurance providers and Medicare.
This requires precise and comprehensive documentation, particularly for ICD-10 diagnostic coding.
For instance, in the case of an asthma diagnosis, the documentation should detail the severity of asthma – ranging from intermittent to severe persistent – and should include the presence of any exacerbations or status asthmaticus.
E/M (Evaluation and Management) and CPT (Current Procedural Terminology) coding also play a pivotal role in billing for patient consultations and visits. These codes are determined based on different levels of complexity which require certain amounts of supporting documentation.
Generative AI can review the current medical documentation and help identify areas where specificity is needed or additional areas to consider documenting if appropriate. Identifying these areas at the time of initial documentation can make it unnecessary to clarify later and ultimately ensure the most accurate level of reimbursement.
- Structured Reporting
Documenting a patient encounter is sometimes complicated by an EHR’s requirement to receive the input into structured text areas. An alternative approach is for healthcare providers to dictate a free-text summary of the visit without any specific order and allow for generative AI to process that dictation into a structured medical report.
The generated medical report can even be edited for readability and completeness before being inserted into the EHR.
Notes and Considerations
The leading generative AI models such as OpenAI ChatGPT, Anthropic Claude, and Google Gemini include medical documentation as part of their training materials and can be effective in many of the use cases above. This technology is rapidly developing, and the speed and accuracy at which these GenAI models can perform for healthcare will only continue to improve.
Additionally, gen AI models are being developed that are specifically intended for medical use and should provide even better results and reliability in the coming years.
Searching for a Generative AI Healthcare solution?
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Frequently Asked Questions
- What is generative AI in healthcare?
The most impactful innovation to the healthcare industry for many years was the introduction of the electronic health record. Generative AI is shaping up to be the next big innovation in healthcare.
Healthcare organizations consistently prioritize efficiency, and many healthcare providers have been driven towards burnout, which is where generative AI meets healthcare. Generative AI in healthcare can improve accuracy and timeliness in documentation and other areas, as well as improve overall efficiency at a healthcare organization.
A successful generative AI solution must meet healthcare security requirements, ensure patient safety, and become integrated with the provider’s workflow.
- How can generative AI be used in healthcare?
Generative AI can be applied to many areas of healthcare – the most prominent of which are in documentation, coding, diagnosis decision support, administrative activities, information gathering, and translation.
Much of this article covers the potential benefits to healthcare providers, but patients may experience similar improvements in their healthcare through AI. For example, patients may spend less time filling forms through expedited information gathering.
- Is generative AI in healthcare accurate?
As AI continues to develop, it is important to remember that it is an exceptional reference tool, but not an end-all-be-all solution. Artificial intelligence with human intervention may yield the best results most efficiently.
Gen AI models that are designed for medical use will also provide better results with higher accuracy and reliability as they continue to be developed and improved upon.
Try It Yourself with AI Assist
Are you interested in integrating generative AI into your healthcare workflow?
You can discover the extensive capabilities of generative AI with Fusion Narrate AI Assist.
Connect with us to arrange a discussion about incorporating generative AI into your processes or experience innovation firsthand with a 14-day free trial.
