Lavni

Over 60 Million people are diagnosed with some kind of mental health condition in the US every year.  

Mental health assessments and diagnoses are critical components of therapeutic intervention. They provide a comprehensive understanding of a patient's mental health status, informing the development of personalized treatment plans.

The process of mental health assessments and diagnoses, while crucial for therapeutic intervention and personalized treatment plans, is often time-consuming, complex, and emotionally draining. This can lead to therapist burnout, compromising their ability to maintain focus, make accurate judgments, and empathize with patients. 

Consequently, this can result in misdiagnoses, ineffective treatment plans, and suboptimal patient outcomes.

Lavni’s AI-enabled clinical notes feature is a revolutionary solution that significantly enhances the efficiency and accuracy of clinicians’ work. 

This feature allows clinicians to complete session notes swiftly and accurately, ensuring that each client is properly diagnosed. 

By leveraging advanced ML models, Lavni streamlines the documentation process, reducing the time spent on administrative tasks and allowing clinicians to focus more on patient care.

Lavni not only improves the quality of healthcare services but also contributes to better health outcomes for clients. 

By leveraging advanced AI technology, we streamline the documentation process, reducing the time spent on administrative tasks and allowing clinicians to focus more on patient care.

In essence, Lavni’s AI-enabled clinical notes feature is a game-changer in healthcare, fostering a more effective and patient-centered approach to care.

To ensure our solution is meaningful and effective, we have actively involved the target population in the design and implementation process. We have conducted surveys, focus groups, and interviews with mental health professionals and patients to gather feedback and insights. We have also collaborated with mental health professionals to ensure that our AI-enabled clinical notes feature is aligned with their needs and workflows.

In addition, we have made a deliberate effort to address the stigma associated with seeking mental health care. We have designed our solution to be user-friendly and accessible, and we have included resources and information to help patients understand the importance of seeking care and feel more comfortable doing so.

Overall, our team's proximity to the communities we are serving and our commitment to engaging and listening to them have guided the meaningful design and implementation of our solution.

Our solution is innovative because it uses artificial intelligence to automate and improve the clinical documentation process for mental health clinicians. Our solution approaches the problem in a new or significantly improved way by:

• Using advanced machine learning models to generate accurate and concise session notes based on the audio or text input from the clinician and the patient. Our models are trained on large and diverse datasets of clinical notes and conversations and can adapt to different styles, formats, and preferences of the clinician.
• Providing a user-friendly and intuitive interface that allows the clinician to review, edit, and finalize the session notes with ease and speed. Our interface also provides feedback and suggestions to help the clinician improve the quality and completeness of the session notes.
• Integrating with existing electronic health record (EHR) systems and platforms, such as Lavni at mylavni.com, to streamline the workflow and data management of the clinician. Our solution can automatically upload, store, and share session notes with the relevant key stakeholders in the client's care team.

Our solution could catalyze broader positive impacts from others in this space by:

• Reducing the administrative burden and stress of the clinician, allowing them to focus more on patient care and satisfaction. Our solution can save up to 80% of the time and effort required to complete session notes, compared to traditional methods.
• Improving the quality and consistency of the clinical documentation, enhancing the diagnosis and treatment outcomes of the patient. Our solution can reduce errors, omissions, and biases in the session notes, leading to better clinical decision-making and patient safety.
• Increasing the accessibility and affordability of mental health care, especially for underserved and marginalized populations. Our solution can lower the costs and barriers of providing online mental health services, such as Lavni at mylavni.com, which connects patients with therapists and counselors who understand their background, identity, and experiences.

Our solution could change the market by:

• Creating a new standard and expectation for clinical documentation in mental health care. Our solution can set a new benchmark for the accuracy, efficiency, and usability of session notes, challenging other solutions to improve their performance and quality.
• Expanding the market size and potential for online mental health services. Our solution can attract more clinicians and patients to use online platforms, such as Lavni at mylavni.com, by offering a convenient, reliable, and secure way to document and manage their sessions.
• Driving innovation and collaboration in the field of artificial intelligence and mental health care. Our solution can inspire other researchers and developers to explore new applications and opportunities for using AI to enhance mental health care delivery and outcomes.

Our solution addresses the UN Sustainable Development Goal 3 for Good Health and Well-Being by providing a tool that improves the quality and accessibility of mental health care.

According to the UN, one of the targets of this goal is to “strengthen the prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcohol”. Our solution helps clinicians to diagnose and treat substance abuse disorders more effectively, by reducing the time and effort required to complete session notes.

Our solution also supports another target of this goal, which is to “by 2030, reduce by one-third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being”. Our solution helps clinicians prevent and treat mental health issues such as depression, anxiety, and PTSD, which are among the leading causes of disability and death worldwide. By enhancing the efficiency and accuracy of clinical documentation, our solution enables clinicians to provide better care and outcomes for their patients.

Our solution is aligned with the vision and mission of Lavni, which is to provide online mental health services that truly resonate with who you are. By using our AI-enabled clinical notes feature, clinicians can focus more on their patients’ needs, preferences, and goals, and deliver personalized and culturally sensitive care. Our solution also empowers patients to access mental health support from the comfort of their own space, using their own personalized avatars.

We believe that our solution can make a positive impact on the global mental health crisis, by improving the quality and accessibility of mental health care for both clinicians and patients. We hope that our solution can contribute to the UN Sustainable Development Goal 3 for Good Health and Well-Being, and help create a happier and healthier world for everyone.

• A generative model that creates accurate and brief clinical notes from what therapists and clients say. This model uses advanced techniques such as transformer-based neural networks, attention mechanisms, and natural language generation to create high-quality summaries of the session content. We train this model on a large and diverse collection of clinical notes and conversations that we gather from different sources, such as our online platform, public online repositories, and partner organizations. We make sure that the data we use is anonymous and follows ethical, HIPPA, and legal standards.
• A classification model that gives diagnoses and assessments based on the clinical notes created by the generative model. This model uses different methods such as deep learning, natural language understanding, and knowledge graphs to analyze the clinical notes and assign the correct diagnosis codes and assessment scores according to the clinical standards and guidelines. We train this model on a carefully selected set of clinical notes and diagnosis codes that come from expert reviewers, quality assurance teams, and user feedback.

To gather good data, we will use existing sources that are appropriate, reliable, and available for our solution. We will use public repositories, our online platform, partner organizations, and other data providers that offer high-quality and diverse datasets of clinical notes, conversations, diagnosis codes, speech recordings, and transcripts.

We are committed to ensuring ethical and responsible use of AI in our work. We are aware of the potential risks and challenges that our solution or its underlying technology may present, and we are taking proactive steps to address or mitigate them. Some of the risks and how we address them are:

• Privacy and security concerns. Our solution involves collecting, processing, and storing sensitive and personal data from our users and customers, such as their audio or text input, clinical notes, diagnosis codes, and feedback. We respect and protect the privacy and security of our users and customers by using encryption, anonymization, consent, and compliance techniques. We follow the HIPAA regulations and other relevant laws and policies to ensure that our data is secure and confidential. We also provide our users and customers with clear and transparent information about how we collect, use, and share their data, and give them the option to opt out or delete their data at any time.
• Ethical risks as the solution scales. Our solution may pose ethical risks as it scales to different contexts, domains, and populations, such as the potential for bias, discrimination, or harm. We strive to ensure that our solution is fair, inclusive, and beneficial for all our users and customers, regardless of their background, identity, or experiences. We use diverse and representative data sets to train and test our models, and we evaluate their performance and impact on various metrics such as accuracy, reliability, usability, and satisfaction. We also solicit feedback from our users and customers, as well as from external experts and stakeholders, to identify any issues or gaps in our solution and to improve its quality and value.

We have conducted a risk assessment for our solution using a framework that considers the technical, social, legal, and ethical aspects of our work. We have identified the potential hazards, vulnerabilities, and consequences of our solution, and we have developed mitigation strategies and contingency plans for each risk. We have also established a risk management process that involves regular monitoring, reviewing, and reporting of our risk status and actions.

Our impact goals for the next year and the next five years are:

• To improve the mental health outcomes of at least 5,000 clients in the next year and at least 100,000 clients in the next five years by providing them with accurate and timely diagnoses and treatment plans through our AI-enabled clinical notes feature.
• To reduce the administrative burden and burnout of at least 500 clinicians in the next year and at least 10,000 clinicians in the next five years by streamlining their documentation process and saving them an average of 30 minutes per session through our AI-enabled clinical notes feature.
• To increase the accessibility and affordability of mental health care for underserved and marginalized communities by partnering with at least 50 organizations in the next year and at least 500 organizations in the next five years that provide low-cost or free mental health services using our AI-enabled clinical notes feature.

We plan to achieve these impact goals by:

• Developing and deploying our AI-enabled clinical notes feature that leverages advanced ML models to automatically generate session notes based on the clinician’s voice input, speech recognition, natural language processing, and clinical knowledge base.
• Conducting rigorous testing and evaluation of our AI-enabled clinical notes feature to ensure its reliability, validity, security, and compliance with ethical standards and best practices.
• Providing training and support to clinicians and organizations that adopt our AI-enabled clinical notes feature to ensure its effective and efficient use.
• Collecting feedback and data from clinicians and clients who use our AI-enabled clinical notes feature to measure its impact and improve its performance.
• Seeking funding and partnerships with stakeholders who share our vision of transforming mental health care through innovative technology.

Our team consists of 3 full-time staff, 2 part-time staff, and 36 contractors.

2 years

Our approach to incorporating diversity, equity, and inclusivity into our work is based on our core values and mission. We believe that mental health care should be accessible, affordable, and culturally responsive for everyone, especially for the BIPOC community and other marginalized groups.

Some of the ways we demonstrate our commitment to diversity, equity, and inclusivity are:

Our leadership team is composed of people from diverse backgrounds, identities, and experiences. We have four co-founders who are women of color with expertise in mental health, technology, and social justice1.
Our platform connects clients with therapists and counselors who understand their unique needs and preferences. We use a matching algorithm that considers factors such as race, ethnicity, gender, sexuality, religion, language, and culture
Our therapists and counselors are trained and certified in providing culturally competent and trauma-informed mental health services. They also receive ongoing professional development and supervision to ensure the quality and effectiveness of their work.
Our pricing model is flexible and affordable for clients who have limited or no access to insurance or other financial resources. We offer a free plan that includes curated content, access to mentors, and community support. We also offer a therapy plan that costs $75 per week billed monthly or as little as $0 with insurance.
Our online platform is designed to be safe, confidential, and convenient for clients who face barriers to accessing traditional mental health care. Clients can use their own personalized avatar to communicate with their therapist in a virtual environment. 
We are always striving to improve our diversity, equity, and inclusivity practices by listening to feedback from our clients, therapists, partners, and stakeholders. We welcome suggestions and ideas on how we can better serve our community and create a positive impact on people’s lives.

Our strategy for achieving financial sustainability is based on a hybrid model that involves selling products and services to clients and organizations, as well as raising investment capital from impact investors and venture capitalists.

Our primary source of revenue is our therapy plan, which costs $75 per week billed monthly or as little as $0 with insurance. This plan offers clients unlimited access to our platform, including one-on-one sessions with a therapist, group sessions with other clients, and self-guided activities and resources. We also provide a free plan that includes curated content, access to mentors, and community support. This plan serves as a way to attract potential clients who may later upgrade to the therapy plan.

Our secondary source of revenue is our partnership program, which enables us to sell our products and services to organizations that offer mental health care to their employees, members, or beneficiaries. We collaborate with employers, schools, nonprofits, and government agencies to provide them with customized solutions that meet their needs and budget. We charge them a subscription fee based on the number of users and the level of service they require.

To support our growth and expansion plans, we intend to raise multiple rounds of VC funding to cover our overheads.

Our current operating costs and our projected operating costs for the next year are as follows:

• Our current operating costs are $21,500 per month, which include:

  • Human capital: $16,000 per month for salaries and benefits of our 38 part-time contractors, who work in various roles such as therapists, counselors, developers, designers, researchers, marketers, salespeople, and administrators.
  • Platform development and maintenance: $2000 per month for hosting, cloud computing, data storage, security, software licenses, and other technical expenses.
  • Marketing and outreach: $2000 per month for advertising, social media, events, webinars, podcasts, blogs, newsletters, and other promotional activities.
  • Research and evaluation: $500 per month for conducting user testing, feedback surveys, impact assessments, data analysis, and reporting.
  • Operational expenses: $1000 per month for rent, utilities, travel, legal fees, accounting fees, insurance, taxes, and other administrative costs.

• Our projected operating costs for the next year are $53,000 per month in Q1 to  $ 76,000 per month by Q4.

We are seeking to receive $100,000 in funding to continue our work in 2024. We selected this number based on our projected operating costs and our expected revenue streams. We believe that this amount will enable us to sustain and scale our impact while maintaining our financial viability.

We would use this funding for the following purposes:

• Human capital: $60,000 to hire 8 more part-time contractors, who will work in various roles such as therapists, counselors, developers, marketers, and salespeople, This will help us increase our capacity to serve more clients and partners and to improve our products and services.
• Platform development and maintenance: $15,000 to upgrade our platform to enhance its functionality and performance and to integrate new features like AI-enabled assessments and launching our mobile app. This will help us provide our clients and partners with a better user experience and a more personalized service.
• Marketing and outreach: $20,000 to increase our marketing budget to raise awareness and attract more clients and partners. This will help us expand our geographic reach and our target audience.
• Research and evaluation: $5,000 to invest more in research and evaluation to measure our impact and improve our products and services. This will help us demonstrate our effectiveness and efficiency and to learn from our feedback and data.

We imagine that this opportunity will help support our work in many ways. The Cure Residency will provide us with the resources, guidance, network, and exposure that we need to advance our solution and achieve our impact goals.

Some of the aspects of the Cure Residency that we would be most excited about are:

• Seed funding: We would be grateful for the financial support that would enable us to cover our operating costs and invest in our platform development and maintenance, marketing and outreach, research and evaluation, and human capital.
• Mentorship: We would be eager to learn from the experts and mentors who have experience and knowledge in mental health, technology, entrepreneurship, and social innovation. We would appreciate their feedback, advice, and support on various aspects of our work such as product design, business model, impact measurement, and scaling strategy.
• Lab space: We would be thrilled to have access to a state-of-the-art lab space where we can test and refine our platform and its features. We would also benefit from the opportunity to collaborate and interact with other innovators and researchers who are working on similar or complementary solutions.
• Educational programming: We would be keen to participate in educational programming that would enhance our skills and competencies in areas such as marketing strategy, fundraising, and pitching.
• Networking opportunities: We would be delighted to connect with potential clients, partners, investors, and stakeholders who are interested in our solution and who can help us grow our impact and reach. We would also enjoy meeting and exchanging ideas with other fellows who are working on different but related challenges in the mental health space.

Besides the seed funding the Cures Residency mentorship programs would be the most existing to us.