Recursive Health

Every year, 76 million recommended cancer screening tests are not completed.  Breast cancer: 25% of screenings are missed.  Colon cancer: 38%.  Lung cancer: 95%.  Of the more than 600,000 cancer deaths that occur every year, an estimate 300,000 are avoidable with effective screening.

Cancers caught late are 2.5X more expensive to treat and are 7X more deadly.  Meanwhile, cancer treatments are proliferating at astounding rates and investors have nearly tripled investment in new diagnostic techniques over the past 3 years.  

Unfortunately, if patients are not identified and engaged proactively to get these tests completed, society will not realize the incredible gains on new technologies.

There is no effective infrastructure to implement best practices for screening programs, despite multiple pilots across academic institutions demonstrating over 100% increases in compliance with improved identification and outreach.  Hospitals across the country are not seeing the benefit of these programs because they are unaware and, for those who are aware, the programs are human capital-intensive and complicated to implement.

Recursive Health is an integrated digital platform that uses best practices from the world's leading healthcare institutions to systematically identify patients in need of screening and reach out to them with personalization based on nuanced patient archetypes, rather than one-size-fits all communications.

Our platform innovates on two fronts:  identification of patients eligible for screening and in personalized outreach.

Identification of patients: using a backbone of TalkDesk (a leading integrated digital health platform) and our own in-house algorithms, we comb through records to determine who needs to be screened based on established guidelines.  For instance, a patient who is 65 and has been smoking for 30 years, but who does not have a chest CT scan in the system, may be a candidate.  At this stage, we also ingest demographic information that allows us to build a profile and an outreach mechanism that is personalized on the level of the individual patient.  Age, geography, language, race and gender all factor into how a patient is likely to respond to outreach.

Personalized outreach: using the risk information gained from our identification algorithms, we then funnel the use case through our systematic outreach engine.  This means that every patient gets the timing (day, night, day of week), modality (text, phone, email, mail) and content (language, age-appropriateness, cultural context) that works best for them.  Over time, we continue to optimize this ability to maximize compliance with hundreds of slight A/B variations across the system.  This is a major competitive advantage derived from learning at scale.

After identification and outreach occur, the full-circle scheduling integrations and reminder interactions close the loop with providers and patients.  No additional workflows or tasks are generated for providers, and insurance covers all screening tests, making this process free for patients.

This product is a win-win for all stakeholders - a rarity in modern U.S. healthcare.

Patients - Improved early diagnosis and outcomes, lower cost of care for those who have positive findings due to early treatment.

Physicians - Improved preventive care ratings, CMS reimbursement and outcomes.  Increasingly, these metrics are being mandated for public reporting and reimbursement will hinge more and more on these measures over time.

Insurers - Cost of treatment is lower if cancers are caught early.  Cancer care is extremely expensive, so all parties - especially payers - would prefer a to remove a nodule or small mass before it becomes metastatic and requires neo-aduvant chemo, radiation or invasive resection.

Hospital systems - Ample evidence exists from pilots across the country supporting the net profitability of cancer screening programs.  Fee-for-service systems make money in two ways:  on the diagnostic tests themselves, and on the downstream revenue from positive findings, which often require procedural work.  Capitated models benefit due to the early diagnosis and lower cost of overall care vs. a stage 3-4 diagnosis.  Given that their bottom line is directly effected by overall costs of care, screening programs are well documented to be cheaper overall than treating advanced cancers.

Brandon Busuito (Founder, CEO) - Practicing ER physician with Harvard Medical Faculty physicians.  Dual degree MBA/MPA at MIT/Harvard.  Previous founder of scaled digital health platform (500,000 users) and YC alumnus.  Background in engineering, public health and consulting experience commercializing medical diagnostics at Mass General.  I see patients with late cancer diagnoses every day in the ER.  I witness the abject failure of our system to get people in for screening sooner.  It is clearly not enough for us to add some fine print their discharge instructions.  More can and should be done to engage these patients and catch disease sooner.

Brian Ayers (Founder, CTO) - General surgery resident at Mass General, background in computer engineering, MBA, previous founder in healthcare technology space.  Deep expertise in AI development in healthcare and published more than 20 peer-reviewed journal articles on various topics from AI to device technologies and patient experience.  Brian is on the other end of the care spectrum from Brandon.  He is directly involved in removing tumors, parts of lungs, mastectomies and other invasive means of treating advanced cancers.  He feels a strong connection to his patients and agrees that we, as a healthcare community, can do more to reach these people before it's too late.

We are extremely well-suited to execute on this company from a network, problem access and technical skills point of view.  Brian and I are dedicated to solving this problem for our patients and have a demonstrated ability to manage and grow complex technology companies in the healthcare space.

Our solution is innovative in its approach to proactively engage the patient in an individually tailored approach. Currently patients are left largely to their own accord to obtain recommended cancer screening. The most prevalent current solutions rely on the patient to initiate engagement with the healthcare system to obtain the recommended testing. Some centers have recognized the effectiveness of engaging patients proactively, but their solutions are very manually intensive and not scalable. Our solution is digitizing these manual efforts to partner with patients in guiding them through the entire screening process. We do this in a manner that is personalized for each patient. Such an approach could have a profound impact on the entire cancer screening space as it more effectively obtains screening in a way that is scalable. Moreover, it is a reproducible process that could have positive impact on other spaces and the entire market when applied to other areas such as vaccinations and follow-up of incidental findings on imaging. This will fundamentally change the way patients engage with the healthcare system.

Our solution aims to be a foundational model from which we can help address the UN sustainable development goal 3 for Good health and well-being. Our process allows us to identify patients that are currently experiencing inequity in the preventative health market, and proactively engages them to find solutions that are personalized to their current socioeconomic position. Our platform will serve as a scalable and cost-effective solution that allows all patients more equal access to the recommended preventative services, to help increase healthy lives and promote well-being for all patients at all ages. 

Our solution leverages AI to be able to provide patient specific recommendations and outreach that is cost-effective and scalable to all patients regardless of age, race, gender, or socioeconomic background. Our datasets will be high resolution patient data queried directly from each provider’s EMR. This will be multimodal including both structured and unstructured data such as lab values, imaging results, and clinical notes. Our proprietary algorithms will use this data to identify what preventative care is currently recommended for each patient from societal guidelines and be able to tell for which ones the patient is out of data. The second part of the process then uses proprietary process to determine what method and content of outreach will best engage each specific patient to aid and motivate them to complete the recommended screening. 

Ethical AI Principles: Our development process adheres to established ethical AI principles, prioritizing transparency, fairness, accountability, and user privacy. We ensure that our algorithms are unbiased, avoiding discrimination based on factors such as race, gender, or socioeconomic status. Regular ethical reviews are conducted throughout the development lifecycle.

Data Privacy and Security: We prioritize robust data privacy measures to safeguard patient information. Compliance with healthcare data protection regulations, such as HIPAA, is a non-negotiable aspect of our solution. Encryption, access controls, and regular security audits are integral components of our data protection strategy.

Explainability and Transparency: Our AI models are designed to be explainable, providing healthcare professionals with insights into how decisions are made. Transparency in the algorithmic processes enhances user trust and facilitates clearer communication between the AI system and healthcare practitioners.

Founders: 2

Advisory board: 5

Full-time employees: 0

The founders have been dedicated to this company for 3-4 months and plan to be for the indefinite future.  We have been meeting multiple times weekly and are enrolled in the Harvard iLab, MIT Sandbox, MIT 100k, Harvard President's Innovation Challenge and other similar programs, several of which have awarded cash stipends based on the quality of the work.

Diversity, equity and inclusion is central to the work we must do to succeed in solving this problem.  Many of the communities and groups that are hardest hit by low cancer screening rates and higher diagnosis rates are those in socioeconomically disadvantaged areas.  Language is a significant barrier to care, making culturally-tuned solutions an absolute imperative.  Within the company, we aim to reflect our customers.  Hiring in ways that match those who we serve will be paramount to our success and in the development of our competitive business advantage.

Our operational model is designed for seamless integration into existing healthcare infrastructures, ensuring minimal disruption while maximizing the impact of our cancer screening solution. The operational plan involves a multi-faceted approach, encompassing team organization, stakeholder engagement, and resource accessibility.

Our interdisciplinary team comprises AI specialists, healthcare professionals, data scientists, and project managers. This diverse composition allows us to address the technical, clinical, and operational aspects of our solution comprehensively. Clear lines of communication and collaboration are established to ensure effective knowledge transfer and synergy across different expertise areas.

Our execution plan involves phased implementation, starting with pilot programs in select healthcare facilities. This approach allows us to fine-tune the platform based on real-world feedback and ensures a smooth scale-up to broader deployment. Rigorous training programs are conducted for healthcare professionals to maximize the effective utilization of our solution.

Our pricing model will consist of a traditional SAAS setup.  Annual licensing fees will be based on ROI and breakeven projections.

It is critical to focus on downstream revenue implications in early pilots.  We must be able tomato a credible argument that engaging with us will not make financial situations in an already strained system worse.

Specifically, we'll offer a subscription-based, tiered approach to meet diverse user needs. Plans provide access to core features, with pricing tiers reflecting the scale and complexity of healthcare operations. Basic plans cater to smaller practices, while premium plans, with advanced analytics and customization, serve larger institutions. This transparent and scalable pricing structure ensures cost-effectiveness, flexibility, and affordability, empowering healthcare providers to seamlessly integrate our software into their workflows while optimizing operational efficiency.

Founding Expenses: Initial funding is allocated to legal and regulatory compliance, software development, and infrastructure setup. This phase includes hiring key personnel, such as developers, compliance officers, and project managers. Legal fees cover entity formation, licensing, and adherence to healthcare regulations.

$5,500

Software Development: The largest portion of the budget is dedicated to software development, encompassing coding, testing, and refinement. This includes the creation of an intuitive user interface, robust security features, and integration with healthcare systems. A portion of the budget is set aside for potential iterations based on beta testing and user feedback.

$350,000

Infrastructure and Technology: Funds are allocated for cloud services, servers, and cybersecurity measures to ensure a secure and scalable platform. Ongoing software updates and maintenance are factored in, along with the acquisition of necessary licenses and tools.

$75,000

Marketing and Launch: A significant portion is earmarked for marketing strategies to create awareness and attract early adopters. This includes digital marketing, website development, and promotional materials. Initial user acquisition costs and partnerships with healthcare providers are considered to drive early adoption.

$25,000

Requested: 100k

1. Development and Technology (40% - $40,000):

   • Software development and coding: $20,000
   • Cloud services and server costs: $12,000
   • Cybersecurity measures: $8,000

2. Marketing and Launch (20% - $20,000):

   • Digital marketing: $10,000
   • Website development: $5,000
   • Promotional materials: $3,000
   • User acquisition costs: $2,000

3. Founding Expenses (15% - $15,000):

   • Legal and regulatory compliance: $7,000
   • Licensing and permits: $4,000
   • Initial team hiring and salaries: $4,000

1. Collaborative Environment:

   • Facilitates Networking: Being co-located with other healthcare startups creates a collaborative ecosystem. The proximity allows for organic networking, fostering potential partnerships and collaborations within the healthcare industry.

2. Access to Resources:

   • Flexible Workspace: The personalized and flexible workspace, coupled with access to conference rooms, quiet rooms, and event spaces, ensures that the software company has the resources it needs for varied activities, from focused development work to hosting events or meetings.

3. Learning Opportunities:

   • Education Center: The on-site education center provides a structured environment for continuous learning. This is particularly valuable in the dynamic healthcare sector, allowing the company to stay abreast of industry trends, regulatory changes, and emerging technologies.