Vibesdoc

Vibesdoc is a patient engagement tool for prompt diagnosis using patients' case information gathered from a survey & genetic sequencing with an AI backend. This tool computes the probability of a diagnostic given a patient's case variables leveraging large data sets to increase accuracy. Because of the pandemic, we focused first on building a solution to help diagnose covid. However, the same code with few alterations can catch chronic conditions or identify rare diseases promptly. 

With Vibesdoc's survey results matching patient symptoms with diagnosis, we would promptly identify diseases and provide users with suggestions on practitioners and institutions that could help them alleviate those. It would also suggest further tests to verify diagnosis possibilities and provide selected professionals with a probability estimate of such results and an alert depending on the urgency of treatment required. The results would also be displayed in an explainable visual manner to help people understand.

To better understand our offering's market perception, we carried out a survey answered by more than 250 people anonymously. According to survey results and feedback gathered, the target market that would pay for such a solution and the most interested in pursuing it would be 20 to 40-year-olds, primarily female, college-educated, higher income, and interested in health.

From this research, we perceived that physicians and patients do not trust the power of an AI enough to rely on it solely for diagnosis. Nevertheless, when feeling sick, they would pay a premium price for a service that guides them on steps to take to get the needed help.

Patients would use Vibesdoc to understand better their symptoms and what they mean and find the right professional to help them. Physicians would also use the service as an additional tool to get more information from the patient before their visit.

Currently, people go to hospitals, labs or clinics to get guidance and testing for potential diseases. Patients have to rely on self-research on symptoms, practitioners, and tests before getting the needed aid to get treatment.

Vibesdoc is a tool leveraging big data to aid in the diagnosis, using existing tools such as EHRs/EMRs, genetic sequencing, rapid testing, cloud computing, and mobile internet access through a smartphone.  Although the application of such algorithms is not common, it is not a new technology, and neither are symptom checkers to recommend patients for further actions.

That said, the application for which Vibesdoc is intended is innovative in itself. Current patient engagement tools focus on a small part of the patient journey, such as optimising for SEO searches, or aiding in easier appointment booking, or simply allowing for a vast library of medical knowledge to be available online for patients to research.

Vibesdoc intends to merge these technologies and become more of an automated tool that will optimise general practitioners' role in identifying potential diagnosis and appropriately directing patients to further testing or specialist from a place of learned experience and not hunched guess. Thus, Vibesdoc power lies in the tool's synergistic nature, tailored by practitioners and field experts through enhanced collaborations with leading institutions to build a genuinely working tool that makes medicine understandable and actionable for people to participate voluntarily.

The current target market would be the low hanging fruit for the capabilities of our solution. Nevertheless, because many women from Central America & Caribbean urban centres are already used to taking rapid tests (for pregnancy, for example), then providing them with tools to get tested for more conditions (such as with genetic sequencing) would have a higher probability of catching on. From our survey results, we believe that these initial adopters will also promote such offerings first with their loved ones and then in their communities, as testing is heavily needed in the region regardless.

As institutions, practitioners, and patients start seeing local success examples of prompt disease detection, the solution would gain popularity and impact the entire healthcare system. An autonomous solution that would handle massive testing would also benefit governments from the region to fall back to in case of a future pandemic.

Utilising already FDA approved lateral flow assays, and genetic sequencing exams would also provide an option to provide testing in remote areas of the Americas for when needed as those are relatively low cost and easily shippable. Pairing such results with our survey would increase their reliability and utilise the ability to be further integrated with patient medical records.

Users who feel unwell would fill up a survey and get matched with further tests, diagnosis, and practitioners.

Our tool weighs heavily symptoms related to neurodegenerative conditions, such as ALS, as these patients and others with uncommon diseases already struggle to get diagnosed.

Although individually patients with such rare conditions are uncommon, collectively, they are a seizable mass that has gained pharma companies' attention.

People using Vibesdoc will better understand what they might be going through and find professionals to help them find treatment options.

Although we have completed our tool to increase the accuracy of covid antigen lateral assays, the solution proposed is much more than that. Our initial MVP is proof of how rapid testing can be improved when paired with big data AI, we believe genetic sequencing and medical data can follow suit. With a tool such as Vibesdoc, we could unlock the power of rapid testing using lateral flow assays and genetic markers to identify uncommon and chronic conditions in development. To allow for this tool to fulfil such capabilities, more unidentifiable data from further collaborations would be needed and tweaks in code to comply with regulations and expectations.

Using a framework that enabled the creation of a user-friendly, visually pleasing, yet robust solution that would be able to handle massive data requests through our Golang API and AWS & NGINX hosted servers.  We are currently modifying such a tool to work as a patient engagement tool to be subsidised by pharma and EHR companies to allow for an interactive tool to help them secure their market share by providing their clients with an edge for competing with others in the market. We believe that this algorithm's power should be further exploited by a complete evaluation of diseases, not just covid-19. Still, based on potential clients' feedback, we have landed on such a strategy to guide the continuation of such a tool.

Therefore the most impactful innovation, beyond a well-built tool, through which experts in respective fields pitch in to achieve it, the invention that Vibesdoc propose goes beyond the technology it epitomises. Unlike other patient engagement tools, we aim to tackle the symptom checker tool as a working solution to refer patients and guide them through complex healthcare systems.  The possibilities to build on top of such a tool are endless. Eventually, even health and medical records could be personalised and given to individuals to manage so that treatment would adapt to a person's genetics and complete case information.

Vibesdoc is designed for scale with a robust architecture utilising Facebook's react framework for the frontend and Google's Golang for the API connectivity with a Cloud NoSQL database. The architecture is built for future democratisation as the API would handle requests from other frontend surveys besides the one we have developed and the rest we will create.  Through Vibesdoc, we envision users constantly screened and tested for conditions whenever they feel unwell and want to seek help. This tool will be a great add on for practitioners, clinics, insurance companies, medical labs, and the entire supply chain alike. Vibesdoc optimises the whole patient flow for efficiency with the help of passed medical cases.

Currently, we developed the initial MVP using publicly available data from a nonSQL database hosted in NGINX. The ReactJS front-end survey and Golang API live in cloud solutions from Amazon and Google. The ML/AI algorithm is in R and Python. Most of the project is hosted in AWS and uses tools such as Sagemaker and S3 there.

Remote rapid testing using point of care and over the counter assays is a growing trend in the industry. https://www.ncbi.nlm.nih.gov/books/NBK447315/

Nevertheless, like many other healthcare solutions in the market, these tests and different lab results remain of little use for many due to lack of integrability with existing EHR/EMR systems. This feature will be critical in the development of Vibesdoc. https://www.nature.com/articles/d41586-020-01068-3

Vibesdoc would leverage existing tools by enhancing them with an interactive app that would engage patients in treatment, thus making it more participative. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4849541/

Numerous EHR/EMR companies have tried to do so but have not been compelling enough, leading to creating the patient engagement trend from which solutions such as PatientPop or ZocDoc have emerged.

Therefore by targetting users by symptom and diseases, instead of merely geographic location or web searches, we believe we would increase the conversion rate and optimise flows for people, institutions, companies, and patients alike. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3564521/

There is an up-and-coming trend of utilising genetic sequencing for precision medicine to increase the efficiency of healthcare systems and identify uncommon conditions promptly. 

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At the beginning of this project, we intended it to be a wholly private and nonprofit venture to avoid potential hurdles involving HIPAA and GDPR. Therefore, with our covid app, we are not collecting any identifiable data nor tracking users in any way. 

For this new iteration of the tool as Vibesdoc, we would enhance the tracking and monitoring capabilities for long term sustainability, with it we would be introducing privacy and security risk which we attempt to tackle by partnering with blockchain companies focusing on self-sovereign identity solutions to keep all that safe. 

Currently, the only metrics to measure usage and performance are those provided by AWS, displaying a constant but still low use of the application, averaging 3 per cent of its full capabilities for our 8 GB EC2 instances.

For this initial year, the goal is to land our initial private and public partnerships to develop an MVP that meets our vision for the project and complies with their requirements. After gaining feedback and experience from this, we plan to expand to neighbouring countries and ones in which we feel comfortable or have connections with a similar strategy. For the third year, the solution would have a more international outlook. The remote team we would handle to optimise for integrability and optimisation of exiting healthcare systems where deployed.

2 Full-time, 5 Contractors, 10 High-Level Advisors

Roberto Baldizon, our founder and team lead, has vast experience in business, engineering, and informatics, having launched and worked in ventures in Latin America, the Caribbean, and the United States. Our core team of advisors are field experts. Freddy holds a PhD in microbiology. Nina, Claire, and Felicia all have PhDs in mathematics and are accomplished data scientists. Anurag holds an MBA from a business school in London. Tal is a developer with robust experience in healthcare projects. And Jesse is a last-year resident in Osteopathic Medicine at a prestigious hospital in the Northeast USA. We all consider ourselves global citizens and have a pragmatic view of science and the potential applications of technology for bettering our world. Demographically, we all fit the initial target market which seems to perceive Vibesdoc the most highly, for which our personal experience and immediate networks will prove valuable.

No, but we all have had first-hand experience with people suffering from such conditions.