Oatmeal Health

Health equity in action

Underserved communities have long endured disparate access to quality cancer care and a lack of culturally appropriate supportive care services. This leads to unnecessary death that could be easily prevented if the challenges of access and awareness could be overcome.

We are committed to reducing disparities associated with cancer screening and diagnosis. We are focused on creating solutions to improve health services and outcomes for communities disproportionately affected by cancer, starting with lung cancer and eventually including breast, colorectal, cervical, and prostate cancers.

Lung cancer is the #1 cancer killer in the US, with over 130,000 deaths expected in 2023. Screening with low-dose CT scans (LDCTs) can reduce lung cancer deaths by 20% and improve the 5-year survival rate of new cancer diagnoses 10-fold. Consequently, the US Preventive Services Task Force (USPSTF) recommends annual LDCTs for adults aged 50-80 with 20+ pack-year smoking histories, and the Center for Medicare and Medicaid Services has mandated that all US payors - private and public - cover these scans without copays. Yet, despite institutional support for prevention, screening rates remain under 6% of eligible adults.

Access to recommended lung cancer screening is particularly low in underserved populations including Black, Native American, LatinX, and rural communities, resulting in inordinate late-stage cancer diagnoses. Only 5% of the 14.5 million screening-eligible Americans receiving care at Federally Qualified Health Centers (FQHCs), community health centers that serve vulnerable populations, receive preventative scans.

The key barriers causing this disparity include limited budgets, resources, technology, and staffing at FQHCs, as well as financial constraints, lack of awareness, and lack of access to transportation among patients. However, the current approach to cancer awareness is fragmented and disorganized. There is a desperate need for a streamlined, comprehensive system rather than more awareness months and ribbons, which have proven ineffectual at meaningfully increasing screening rates.

We aim to address the unmet need for accessible, systematic preventative cancer screening focused on health equity for marginalized and medically underserved populations. Our solution targets the significant care gaps that currently result in late-stage diagnoses and poor outcomes.

We offer a tech-enabled clinical service that provides end-to-end management of cancer screening for underserved populations. Our solution leverages multifaceted machine learning methodology to identify patients with elevated cancer risk using electronic health record (EHR) data, ensure compliance with USPSTF-mandated screening guidelines to enable early diagnosis and intervention, risk stratify screening findings to optimize ongoing surveillance, and provide culturally sensitive patient education.

Example: One of our current pilots at Lowell Community Health Center in Massachusetts serves 35K mostly low-income patients annually.  Lowell has been an amazing partner for Oatmeal, allowing us to start a pilot in the coming months while we build and validate our lung cancer screening eligibility identification model. We will deploy our solution along with the clinical staff at their health center. Our solution is fourfold:

1. Identify: Identify patients who are eligible for lung cancer screening per USPSTF screening guidelines using EHR data.

2. Screen: Schedule an appointment at an imaging center and ensure compliance therewith.

 3. Risk stratify abnormal findings (i.e. pulmonary nodules) to advise on follow-up and specialist referral.

 4. Rescreen: Educate and intermittently re-screen the patient.

To these ends, our services include:

- AI analysis of electronic medical records to identify patients eligible for cancer screening.

- Assistance scheduling imaging appointments, coordinating transportation, and incentives to improve access.

- Culturally sensitive education and virtual care to improve adherence to screening and overall engagement with healthcare. 

- AI evaluation of imaging results to determine the malignancy risk of identified nodules and recommend appropriate follow-up steps.

- Ongoing support, education, and reminders for annual re-screening to ensure continuity of care.

This comprehensive, tech-enabled clinical approach streamlines the fragmented cancer screening process, tailors it to individual needs, and reduces barriers to access for underserved groups.

We have already piloted our solution with Federally Qualified Health Centers serving over 200,000 underserved patients.

Our innovative use of machine learning technologies, including large language models and unsupervised learning algorithms, combined with a dedicated clinical team, offers a sustainable way to scale impact and improve outcomes systematically. Moreover, our revenue model based on fee-for-service billing provides a path to financial sustainability today. Finally, our objective to optimize cancer screening at scale is supremely well aligned with the US healthcare system's push toward value-based care, positioning us to negotiate value-based contracts in the future.

Our solution directly targets key gaps in access to cancer screening and care for at-risk populations. This approach enables the potential for meaningful impact and scalability, across 1400+ FQHCs serving 30M Americans, payors, VBCs, and ACOs.

90-second introduction to Oatmeal Video - 

We develop scalable solutions to correct deep-seated inequities in cancer screening, starting with lung cancer and eventually moving into other cancer markets. 

Racial disparities exist in the incidence, morbidity, and mortality rates of lung cancer. Smoking is responsible for the majority of lung cancers, and racial disparities also exist in smoking outcomes. Black smokers are less likely than white smokers to stop smoking or engage in evidence-based tobacco treatment.

Consequently, Black males have a higher annual lung cancer incidence (104.8 cases per 100,000 black males versus 85.9 cases per 100,000 white males) and mortality rate (90.1 cases per 100,000 black males versus 69.9 cases per 100,000 white males).

To make matters worse, disadvantaged patients are considerably less likely to get screened for lung cancer, even if they qualify for free screens. We see this in high proportion of cases where lung cancer is detected in later stages for disadvantaged groups and the rate of later stage lung cancer detection in those same groups. For example, in the US black patients are 10% less likely than white patients to get lung cancer screening even when they qualify, and black patients are 15% less likely than white patients to have lung cancer diagnosed early. 

We aim to directly address racial, ethnic, and socioeconomic healthcare inequities by focusing specifically on improving preventative cancer screening for underserved populations. Our solution targets communities facing barriers due to race, income, geography, etc.

Our partnerships with Federally Qualified Health Centers allow us to reach vulnerable populations that large health systems fail to adequately serve. Our initial pilots will reach over 200,000 underserved patients in just the first 6 facilities with which we have contracted. Our eventual goal is to scale nationwide, going zip code by zip code, to provide our solution to millions of at-risk individuals lacking access currently. 

By enhancing early detection of cancers through proactive screening, we expect to significantly improve health outcomes for marginalized groups that currently have poor morbidity and mortality rates for diseases like lung cancer. If successful, we will be able to scale up quickly to working with 150,000 patients annually in the short term, and millions in 10 years once we achieve scale. Many of these patients would likely not have been screened otherwise, newly enabling early intervention and treatment at a significant scale.

For payors, we are likely able to save $200 million over 10 years for every 10,000 eligible patients screened due to the high costs of late-stage treatment. This corresponds to an average of $237K saved per early detection. For patients, early-stage lung cancer detected by low-dose CT has an 80% 5-year survival rate, a dramatic improvement from the 18.6% survival rate among all new lung cancer diagnoses. 

Our solution has the potential for substantial social impact by addressing systemic inequities in access to potentially life-saving cancer screening. Our scalable solution expects to reach millions in underserved communities and lead to significantly improved health outcomes.

As CEO, Govette has spent the last 2 years in conversations with well over 100 health centers, health executives, patients, and industry experts to learn about the precise challenges responsible for the dismal 5% lung cancer screening rate among marginalized communities served by FQHCs. In addressing this pressing issue, Govette has assembled a team and advisory board whose unique blend of personal experiences and backgrounds uniquely equips us to make a meaningful impact. See our leadership team: https://oatmealhealth.com/lead...

Some of the reasons we are well-positioned to address this issue include:

1. Personal Experiences: Our team lead, who was raised in a low-income household and faced significant adversity growing up, knows firsthand what it is like to lack access to healthcare. As a patient at a Federally Qualified Health Center, he understands the pain and challenges that people from underserved communities face. Govette lost his mother, aunt, and both grandparents to Breast and Lung Cancer; none had received USPSTF-recommended preventive screening.  This personal experience is at the very core of our mission as a company.

2. Diverse Backgrounds: Our team is incredibly diverse, both racially and socioeconomically. We believe that diversity is a key strength when it comes to understanding and addressing the unique needs of our target population. This diversity ensures that our approach is inclusive and representative of the communities we aim to serve.

3. Community Engagement: We actively engage with the communities we serve. We conduct extensive outreach, hold community meetings, and engage in open dialogues to understand our patients' specific needs and concerns. This ongoing engagement helps us gain deep insights into their challenges.

4. Community-Centered Approach: The design and implementation of our solution are guided by the input, ideas, and agendas of the communities we serve. We believe in a bottom-up approach, wherein community members play a vital role in shaping the solution. We prioritize their voices and collaborate with them to create a solution that truly reflects their needs and desires.

5. Cultural Sensitivity: We are highly attuned to the cultural and social aspects of the communities we serve. Our team's diverse backgrounds ensure that we approach the problem with cultural sensitivity, understanding the nuances and intricacies that influence healthcare decisions.

6. Holistic Approach: We understand that healthcare disparities are often interconnected with other social determinants of health such as housing, education, and employment. Our approach is holistic, addressing not only the lack of screening but also the broader factors that affect the health and well-being of our target population.

In summary, our team's personal experiences, diversity, community engagement, and community-centered approach make us uniquely qualified to design and deliver a solution that resonates with the communities we are serving. We are not outsiders trying to impose solutions; we are insiders who have walked the same path and are dedicated to making a meaningful difference in the lives of those who face barriers to healthcare access.

Our solution is unique because it combines innovative machine learning technology and clinical implementation. Our team has a clear understanding that all medical staff are extremely busy and that this has traditionally led to very low utilization of software solutions. By combining AI and clinical implementation we are able to both leverage AI to find underserved patients and deploy our clinical staff to facilitate the delivery of care. The end result are patients who are finally able to get lung cancer screening and medical systems that can focus on delivering care to the patients who need it. 

Existing software-as-service solutions are inaccessible to our partner FQHCs as these clinics are unable to take the financial risk of investing in additional technology or dedicate additional already-overstretched staffing to cancer screening. On the other hand, a naive approach of manually scrubbing the Electronic Health Record for screening candidates would not be economically viable, costing hundreds of dollars of skilled time per patient screened. Our AI-enabled clinical services solution enables implementation of an economically viable, easily scalable screening program at no financial risk to our partner clinics.

We have the potential to catalyze broader positive impacts by setting a new standard in cancer prevention and awareness. By creating an organized and personalized approach to cancer screenings, we aim to inspire others in the healthcare space to adopt a similar strategy. A more streamlined and individualized system for cancer prevention could become a model for various healthcare sectors, encouraging a shift towards more personalized and effective approaches to public health issues.

In terms of market impact, our innovative solution could revolutionize the preventive care market by showing that it is possible to reach and screen patients at scale. By simplifying the overwhelming complexity associated with cancer awareness and prevention, we anticipate increased engagement from healthcare providers, health plans, pharmaceutical companies, and the public. Our streamlined approach can lead to cost-efficiency, improved patient outcomes, and a significant reduction in burden on the healthcare system.

Overall, our solution endeavors to drive a paradigm shift in cancer prevention and awareness, aiming to be a catalyst for change across the healthcare industry.

Our solution directly aligns with UN Sustainable Development Goal 3 for Good Health and Well-Being. The alarming rise in cancer cases among individuals under the age of 50, as indicated by the provided data, underscores the urgent need for comprehensive preventive healthcare solutions.

DATA: https://www.theguardian.com/so...

Our approach starts with a simple hypothesis: with only ~5% of eligible patients receiving lung cancer screening, significantly increasing the screening rate will significantly decrease premature mortality from late stage lung cancer. From there, we designed our approach to tackle the drivers of poor compliance such as patient identification, outreach, and clinical implementation. 

Our patient screening strategy leverages AI to connect factors in the EMR to build a risk profile for patients. This can be used to find patients who are likely eligible for screening, but may also be used by clinicians to identify critical health risks that may be communicated to the patient. 

Having developed a list of patients who are likely candidates we then engage in screening patients in the shortlist for eligibility. Our dedication to engaging with communities, understanding their unique needs, and developing partnerships with healthcare providers and pharmaceutical companies demonstrates our commitment to creating a holistic solution. 

We further leverage our connection to the community to provide personalized education, coaching, and care to patients. We make sure that they understand the process and that they are able to make it to the appointment. We then guide them through the results and help them determine the next steps depending on their scan results.

By fostering collaboration and education, we strive to empower individuals to take proactive steps toward their health and well-being, aligning with the broader vision of Goal 3.

Oatmeal Health aims to combine a tech-enabled clinical service that optimizes healthcare delivery with 3 AI technologies:

1. Phase 1 - Electronic Health Record (EHR) informatics: We are developing unsupervised and semi-supervised machine learning methods using multimodal EHR data to identify patients who meet USPSTF guidelines for lung cancer screening. The USPSTF currently recommends screening for all individuals ages 50-80 who have a 20+ pack-year smoking history and have not quit smoking within the past 15 years - details that are often missing from patient records and are not readily imputable using off-the-shelf methods. Our technology leverages both unstructured patient notes (using validated NLP tools and fine-tuned LLMs to surface key features) and structured data including lab tests, prescriptions, diagnosis codes, and procedural codes to impute a patient's eligibility for screening. It does so by efficiently embedding the patient's EHR onto a low-dimensional subspace to enable subsequent supervised learning with a limited number of gold-standard chart-reviewed eligibility labels. A naive supervised-only approach would fail given the massive dimensionality of the EHR.
2. Phase 2 - Computer Vision: We will implement one of the various FDA-approved AI computer-aided diagnosis algorithms within our clinical workflow to automatically identify pulmonary nodules on screening CTs and risk stratify these nodules for malignant potential. Moreover, we will partner with our clinical advisors to develop clinical decision support algorithms using our AI malignancy risk score to decide on referral to pulmonology and/or decreased time to re-screening.
3. Phase 3 - Generative AI: Our initial approach involves developing educational messaging and videos that are tailored to the patient’s gender, age, language, culture, race, ethnicity, and community, taking into account their unique identity and background. By doing so, we aim to foster cultural sensitivity and improve patient compliance with preventive screenings. Seeing someone who looks and speaks like the patient can help to establish trust and enhance the patient’s engagement with their healthcare journey. Eventually, we plan to develop a generative AI to act as a patient's personalized screening coach, learning from our initial experience with manually-developed educational materials to further personalize patient engagement.

We work to ensure ethical and responsible use of AI by 1) adjusting for biases in our models, 2) complying with the highest standards of data privacy, and 3) ensuring equitable provision of clinical services.

In designing our screening candidate identification algorithm, we exhaustively search for racial and gender disparities in our training data and model output. We then attempt to iteratively adjust for these factors to "de-bias" our algorithm as much as possible.

Regarding data privacy, we adhere strictly to HIPAA, GDPR, and NIST standards in handling patient data. We do not maintain protected health information on our systems any longer than necessary, destroying these data as soon as candidate identification is complete.

Finally, providing equitable screening services to marginalized patient communities is a core component of our mission. Access to cancer screening in the United States is deeply inequitable, with minority and rural patients experiencing far lower screening rates and far higher incidences of late-stage lung cancer than urban White patients. By working primarily with FQHCs servicing the most disadvantaged members of society, we aspire to correct this disparity at scale.

Our immediate impact goal is to commence lung cancer screenings. By the end of 2023, we aim to screen our first 100 patients at Lowell Community Health Center in Massachusetts and the Stigler Health & Wellness Center in Oklahoma.

Looking ahead to the next five years, our overarching impact goals are to 1) expand to breast, colorectal, prostate, and cervical cancers, and to 2) scale our solution across the United States, systematically expanding zip code by zip code. We intend to offer our tech-enabled services to millions of patients, providing them with zero-cost preventive screening services.

Our plan to achieve these goals involves utilizing our initial limited resources efficiently to launch and start screening patients. As funding and revenue improve, we will scale our operations methodically, expanding our reach and impact. Crucially, we will collaborate with health plans, including Medicare, Medicaid, and commercial insurers, to fund our expansion. Demonstrating the cost-effectiveness of early cancer detection, we will garner support to drive our mission forward.

Specifically, we plan to: 

Enhancing Access to Healthcare Services:
a. Establish at least 15 community healthcare centers in underserved minority communities within the next two years.
b. Conduct regular health fairs, providing free health screenings and consultations to at least 3,000 individuals from minority backgrounds annually.
c. Collaborate with local healthcare providers to offer free screenings, and primary care visits to 80% of uninsured or underinsured minority residents in our current expansion states, including Arizona, California, Massachusetts, Oklahoma, and Alaska. (More states to follow in the future)

Culturally Tailored Health Solutions:
a. Conduct cultural sensitivity training for healthcare staff, aiming to reach 90% of all healthcare professionals in our organization within the next year.
b. Incorporate cultural advisory boards to tailor healthcare practices for at least five distinct minority communities, ensuring their unique needs are met within the next two years.
c. Offer multilingual support in healthcare facilities, ensuring that at least 80% of our minority patients can receive services in their preferred language within the next 4 years.

Advocacy for Policy Changes:
a. Collaborate with advocacy groups to propose and support at least two policy changes aimed at reducing healthcare disparities for minorities in the next year.
b. Engage with legislators and stakeholders to advocate for increased funding for healthcare programs targeting minority communities, aiming for a 30% increase within the next three years.
c. Establish a health policy fellowship to engage minority community leaders in the policy-making process, empowering at least 10 leaders annually to advocate for healthcare policies beneficial to their communities within the next two years.

4 people:

• Jonathan Govette, Founder, and CEO - Full-time
• Yuri Ahuja, MD PhD Co-Founder, and CTO - part-time until fundraise
• Ashish Basuray, PhD, Co-Founder, and COO - part-time until fundraise
• Ryan LaRanger PhD, Technical Director - part-time until fundraise

The company is led by our CEO and Co-Founder, Jonathan Govette, an experienced healthcare startup founder and executive, Dr. Yuri Ahuja MD PhD, our CTO, a Harvard Medical School graduate with venture-capital experience and deep knowledge of machine learning and medical informatics, and Dr. Ashish Basuray PhD, our COO, an experienced healthcare/scientific entrepreneur and management consultant.  

We have been working on Oatmeal Health officially since May 19th, 2022

At Oatmeal Health, we are dedicated to fostering diversity, equity, and inclusivity across all facets of our work. Our approach encompasses multiple dimensions to create a workplace that is reflective of our commitment to these principles.

Diversity in Leadership: Our leadership team is deliberately crafted to embrace diversity. We believe that diverse leadership enriches our decision-making processes and brings different perspectives to the table. See our leadership team: https://oatmealhealth.com/lead...

Team Goals for Diversity, Equity, and Inclusion (DEI): a. Recruitment and Hiring: We have set goals to actively recruit and hire talent from diverse backgrounds, ensuring our team is representative of the diverse communities we aim to serve. b. Inclusive Policies: We strive to implement inclusive policies that promote equal opportunities, growth, and advancement for all team members, irrespective of their background. c. Training and Awareness: Our goal is to provide regular training on diversity, equity, and inclusion to sensitize our team and foster a culture of understanding and acceptance.

Actions Taken: a. Diversity Training: We conduct regular diversity training sessions to educate our team about the importance of diversity and how it positively impacts our work and mission. b. Diverse Hiring Panels: When recruiting new team members, we ensure diverse hiring panels to minimize unconscious bias and promote fair assessment of candidates. c. Partnerships and Collaborations: We actively seek partnerships and collaborations with organizations that share our commitment to diversity and inclusivity, allowing us to broaden our perspectives and outreach.

Inclusive Decision-Making: We involve team members from different backgrounds in decision-making processes. Diverse perspectives are encouraged and valued during discussions and planning stages to promote equitable decisions that benefit everyone involved.

Community Engagement and Outreach: We engage with diverse communities and stakeholders to understand their unique needs and challenges. By actively involving them, we tailor our solutions to be more inclusive and relevant.

Our commitment to diversity, equity, and inclusivity is not only essential for our organizational growth but also aligns with our mission to serve diverse populations effectively. We recognize that fostering a diverse and inclusive environment is an ongoing journey, and we are steadfast in our dedication to continually improve and ensure that our workplace and solutions reflect these values.

Operational Model and Plan:

1. Executive Team Structure and Roles:

   • Jonathan Govette, Founder and CEO, oversees business development, managing strategic alliances, outreach efforts, and ensuring technological development aligns with the organization's goals. He founded a SaaS referral management platform in 2010 and partnered with organizations like Amazon, Bronx Partners, and Cedar Sinai to commercialize the software to 100s of organizations in the United States. 
   • Yuri Ahuja, MD PhD, Co-Founder and CTO, is a licensed physician in Internal Medicine at NYU Langone Health with nearly 10 years of graduate academic experience in machine learning and medical informatics. He is a subject-area expert in phenotype identification and risk prediction using Electronic Health Record data, having published over 10 high-impact papers (5 first-author) on the subject.
   • Ashish Basuray, PhD, Co-Founder, and COO, brings 20 years of entrepreneurship, management consulting, grant management, and pedogeological theory. He co-founded PreScouter, a scientific advisory that works with the F500s on front-end innovation. He then started Firstlook AI, an AI-driven healthcare company that leverages a proprietary layer-on AI technology that enables rapid EMR processing. 
     

1. Engagement with Key Stakeholders:

   • Implementing Partners: Top-down, bottom-up partnerships with the National Association of Community Health Centers, State Primary Care organizations, and FQHCs.  
   • Users (Patients): Gather feedback through surveys, focus groups, and direct interactions to tailor our solution to patient needs. Prioritize user experience and ease of access.
   • Healthcare Professionals: Conduct regular meetings and workshops to involve healthcare professionals in shaping the solution. Understand their requirements for seamless integration and user-friendly workflows.

2. Tools and Resources Acquisition:

   • Funding and Revenue Model: Secure funding through partnerships, grants, health plans, Medicare, Medicaid, and commercial insurers. Develop a sustainable revenue model by showcasing the cost-effectiveness of early cancer detection to attract investments and grants.
   • Technology Stack: Leverage existing cutting-edge technologies in AI, machine learning, and health informatics. Collaborate with technology partners and experts to access and implement the most appropriate tools for our solution.

3. Implementation Process:

   • Pilot Testing: Conduct a pilot phase in a selected region to fine-tune the solution, gather user feedback, and identify areas for improvement.
   • Scalable Deployment: Gradually scale the solution zip code by zip code, ensuring that the necessary infrastructure, staffing, and partnerships are in place for each expansion phase.
   • Continuous Iteration and Improvement: Implement an agile development approach, allowing for continuous iterations based on user feedback and technological advancements. Ensure the solution evolves to meet changing needs and emerging technologies.

4. Compliance and Regulations:

   • Compliance Team: Form a specialized team to monitor and ensure compliance with all healthcare regulations, especially regarding patient data privacy and security.
   • Regular Audits and Reviews: Conduct periodic internal audits and reviews to assess compliance and make necessary adjustments to adhere to evolving regulatory requirements.

This operational model and plan showcases a structured approach to manage the organization, engage stakeholders, acquire necessary tools, and implement the solution effectively. The division of responsibilities and emphasis on compliance and continuous improvement ensure the feasibility and success of the solution.

In short, we have 2 revenue models: 1) fee for service delineated by a per member per year fee, and 2) value-based contracts. The former is well-suited for the current healthcare reimbursement landscape, whereas the latter anticipates the ongoing trend toward value-based care. 

To expand on this, our approach to financial sustainability is multifaceted:

1. Investment:

   • Capital Raising: Initiate fundraising efforts to secure the necessary capital to build and scale our team and technology.

2. Revenue Generation:

   • Fee For Service: Generate revenue at first via existing Current Procedural Terminology (CPT) codes.
   • Diversified Revenue Streams: Offer a range of fee-for-service CPT codes, including shared-decision making visits, smoking cessation consultations, and AI CPT codes for malignancy assessment of nodules.
   • Value-Based Care for Health Plans: Collaborate with payors to implement value-based care models wherein we fully own patients' cancer risk for capitated payments. Offer outcome-based pricing structures and performance-driven reimbursements, incentivizing health plans to engage with our solution and improve patient outcomes in a cost-effective manner.

3. Grants and Partnerships:

   • Grant Acquisition: Leverage partnerships with non-profit entities to access a wide array of publicly available grants. By providing tech-enabled services for their patients, we can secure grants that support our mission while offering essential care to underserved communities.
   • Strategic Alliances: Forge partnerships with non-profits and governmenta organizations to mutually benefit from funding opportunities, ensuring sustainable funding streams to support our operations.

By combining these approaches, Oatmeal Health aims to achieve financial sustainability. Investment infusion, diversified revenue streams including value-based care arrangements with health plans, and strategic grant acquisitions will empower us to continue our mission of providing crucial healthcare services to marginalized communities, ultimately making a lasting impact on public health.

See the following Google Document: 

https://docs.google.com/spread...

Oatmeal Health has formalized agreements with our anchor partner FQHCs to commence screening patients for lung cancer using our proprietary AI screening solution. We anticipate this pilot to demonstrate efficacy at 2 FQHC partners - the Health & Wellness Clinic in Stigler, OK, and Lowell Community Health Center in Lowell, MA - in Q1 2024. 

Upon successful deployment of our solution at these clinics, we plan to scale the solution to other FQHCs. We would initially scale by establishing a call center to schedule appointments for patients identified by our screening candidate identification algorithm. The next layer of the solution is to implement an FDA-approved AI for nodule interpretation at FQHCs. Beyond that, we plan to develop patient outreach with culturally sensitive (language, ethnicity, gender, age) education via text, videos, and email via generative AI.

If we are selected as the Challenge winner, Oatmeal Health would use the $100,000 as follows: 

$22,000 for EHR training data to build a more robust AI model; $15,000 for servers/GPU time; $15,000 for software development; $11,500 legal for contracting with FQHCs, $25,000 for living expenses, and $11,500 on administrative overhead/salaries of attendee(s).

We are extremely excited to work alongside more experts in the field and learn from everyone.  

Oatmeal Health has entered and won 4 different contests in 2023 to promote Health Equity including:

• 1st place winner - CUNY/Firefly Accelerator, 
• MassChallenge x2 - early stage, health tech cohorts
• Health Gorilla's inaugural class, only accepted 3 startups nationally. 

Participating in the Cure Residency program would immensely support and elevate the work of Oatmeal Health. The aspects of the Cure Residency that excite us the most include:

1. Seed Funding:

   • Seed funding would be pivotal in scaling our operations, especially in reaching marginalized communities in targeted states.
   • It would enable us to invest in advanced technologies, enhance our diagnostic capabilities, and effectively reach and screen a larger population.

2. Mentorship:

   • Access to experienced mentors would provide invaluable guidance, helping us navigate the complex healthcare landscape more effectively.
   • Expert advice on healthcare regulations, market dynamics, and strategic planning would refine our approach and decision-making processes.

3. Educational Programming:

   • Educational programs tailored to healthcare startups would augment our understanding of the healthcare industry, its trends, and emerging technologies.
   • Knowledge gained would enable us to adapt swiftly, align our strategies with industry advancements, and make informed decisions.

4. Networking Opportunities:

   • Access to a network of like-minded innovators, healthcare professionals, and potential collaborators would broaden our horizons and foster beneficial partnerships.
   • Interacting with a diverse community could spark fresh ideas, collaborations, and opportunities for growth and expansion.