Pritma Dhillon-Chattha, DNP, MHA, and RN are co-founders of Lavender.
As artificial intelligence (AI) evolves, it has become more widely used in mental health care.
It was apparent that 44% used the 3.5 version of ChatGPT, and 33% used the 4.0 version to “supporting answers to clinical questions” It has been revealed that it has become. It was found that 70% of the psychiatrists surveyed showed that AI tools would “make documentation more efficient” and “slightly agree/consent.” A study conducted by PsychologyJobs.com found out how psychologists view AI, 25% said “currently using AI in practice, and another 20% are considering the future.” It has been revealed. The top three use cases in social psychology are AI-driven chatbots for client interaction (21%), automated diagnostic tool for advanced therapy (16%), and natural language for text analysis It was a treatment (16%). ” However, in both surveys, some respondents expressed concern about the use of AI in their respective fields.
Concerns about AI in mental health care are effective and it is essential to discuss them and find solutions. AI is here to stay in mental health care, and avoiding it is not the right approach. Instead, mental health providers from all backgrounds, including psychiatrists, psychiatrist nurses, clinical psychologists, therapists, counselors and more, work together to understand and challenge the unique opportunities and challenges AI places on the field. It must be.
Important use cases for AI in mental health care
When people think about using AI in mental health care, therapy chatbots may come to mind first. Therapy chatbots may one day compensate for the work that mental health providers do and bridge the gaps in mental health care on a large scale, but the current lack of testing and regulations puts risks. It's causing it. In my view, it should not be used to use AI (at least, yet, yet). Instead, it is recommended that mental health providers focus on other AI use cases in this field.
There is an opportunity to use AI in supplemental ways rather than replacing the work done by mental health providers. First, there is an AI Note Taker. These are used by a variety of healthcare institutions to help document patient visits. Using AI Note Takers allows providers to capture conversations faster and more accurately. It also helps to strengthen patient connections. Instead of shifting focus to write down notes, they can be more present. Next is the AI-powered chatbot with questions and answers. This allows patients and healthcare providers to access information quickly. Finally, AI can be used to perform aggregated data analysis to provide insights that can help providers with clinical decision-making and show trends worth further investigation.
While these use cases have advantages, they also have disadvantages. One is that AI Note Takers can pose privacy risks and can make some patients feel uncomfortable. It is important to provide disclosure and obtain patient consent before using AI Note Taker during an appointment. With regard to AI chatbots, theoretically they can be used to achieve and sift medical information, but can produce incorrect or biased results. Alternative use cases for AI chatbots are used to use them to help patients and providers find facility opening hours, review internal policies (the ones my team uses AI), and each facility It is to provide access to non-medical information, such as finding business hours. Also, when it comes to using AI for data analysis, it is important for providers to keep an eye on the possibility of incorrect or biased output and to always reconfirm the work that AI tools generate.
The importance of responsible, safe and ethical AI implementation
Mental health providers that incorporate AI into their work provide opportunities to improve patient journeys by streamlining tasks and saving administrative burdens and time. However, it is important for leaders of mental health care organizations to implement AI in a responsible, safe and ethical way.
Evidence-based AI implementation should be practiced just as mental health providers practice evidence-based care. At the basic level, mental healthcare leaders need to ensure that the AI solutions they deploy to their teams are HIPAA compliant and carefully check how data storage is handled. Additionally, mental health leaders are encouraged to seek AI tools built with medical expertise.
Once mental healthcare leaders have decided which AI solutions to implement in their organization, they need to gain input from lawyers and healthcare team members to develop AI usage policies and procedures. Once the solution is implemented, you will need extensive training on how to use members of your healthcare team. Finally, you should periodically evaluate the AI solutions used by your organization to update usage policies and procedures as needed.
Why it's crucial for mental health providers to participate in AI conversations
As AI continues to become more common, it is most important for mental health providers to participate in AI conversations. They need to express their own ideas and be involved in developing and implementing AI solutions in mental health care.
Mental health care has many different areas, but unfortunately these different areas can be silenced. However, information sharing and collaboration will be essential in the future. There are many ways to make the fields more cohesive. For example, national and state associations representing different professions within mental health care can work together to create webinars and meetings that connect providers. You could also create working groups to help you navigate state and national policies regarding the use of AI in behavioral health. Leaders of private practices can share their experiences with one another. For example, owners of psychiatric practices can meet with owners of counselling practices in the same city and trade notes about their experiences using AI in the workplace. These are some ways providers can work together to navigate AI.
Ultimately, as a mental health provider, it is our professional obligation to know how AI works together to shape the industry. Through teamwork, we can improve both provider and patient journeys.
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