PEGASI

We are committed to making medical information accessible, clear and useful for clinicians and patients in the developing world, while tracking epidemic and endemic diseases, and creating actionable insights that help strengthen our Healthcare systems.

We use our 4-step method to structure, process, aggregate and analyze Healthcare information. In the first two steps, we use PEGASI MED, our EHR platform for the developing world. PEGASI MED covers over 30 medical specialties, is accessible using any smart device, is built using international standards for clinical data management, complies fully with HIPAA / HITECH, and uses Machine Learning to support clinical decision making.

In a global scale, PEGASI MED's datalakes form PEGASI BI, aggregating and analyzing clinical information through advanced dashboards and Artificial Intelligence models, in order to create early epidemic warnings, locate endemic diseases, improve medical research through the review of prospective and retrospective records, and procure comprehensive patient attention.

Crisis management depends on having reliable sources of information readily available, both to detect trends and to act upon them. In Healthcare, information gathering is delegated to practitioners and support personnel dealing with everyday ailments. 

More than 70% of Healthcare information gathered in the developing world remains unstructured, on paper. Months go by until we have a clear snapshot of a city, state or country's status.

In everyday cases, accessibility, reliability and security of Healthcare information are factors that heavily contribute to adverse events, which affect 1 out of 100 hospitalized patients in Latin America. Yet, the COVID-19 crisis has shown us that lack of real-time access to this information has made our regions more vulnerable, as strategies cannot be devised based on accurate information.

That is why we are focusing on creating reliable and secure access to clinical information, in order to help clinicians in their everyday tasks, to support their decision-making with special algorhythms and to, finally, allow real-time Population Health monitoring.

After 20 years of experience in the Latin American Healthcare IT market, we created a 4-step method to structure, process, aggregate and analyze Healthcare information in order to track epidemic and endemic diseases. 

The first two steps we handle through PEGASI MED, our affordable, web based EHR platform. PEGASI MED works on any smart device and is available both offline and online. It is based on international Healthcare data structures, it's fully compliant with HIPAA / HITECH to ensure patients the security of their information, and allows Business Intelligence generation for local research.

Within the same platform, PEGASI MED users find all the tools needed to handle clinical information: 

• patients' demographic data handling, including personal records, appointments, ingress, egress and transfers;
• electronic medical records for over 30 different medical specialties (intensive care, emergency, pediatrics, gynecology, etc.);
• clinical and pathological laboratory management, which allows test results to be available to patients online;
• imagenology laboratory management through a RIS / PACS suite; and
• personalized statistics creation suite.

Data structured and processed by PEGASI MED is aggregated, anonymized and analyzed as Big Data in PEGASI BI, thus fueling our clinical decision support models and our endemic and epidemic disease tracking dashboards.

Our solution serves patients first, making healthcare information accessible, clear and secure for them. They become protagonists of their healing process and diminish their chances of being affected by an adverse event.

Our solution also serves physicians, by reducing manual work overload, automating data search and creating ideal circumstances for research.

Finally, our solution serves population as a whole. Patient aggregate data is used to track dangerous diseases and clusters of infection that could endanger us all.

One of the key aspects in our difficulty handling epidemics-turned-pandemics, such as COVID-19, is our inability to feed our analysis with real-time information that allows devising consensual strategies. If clustered anamnesis, vital signs, mechanical ventilation, paraclinical exams and intervention reports were readily available for situation monitoring, the outlook of epidemics would be completely different. And that's what we aim to do with PEGASI in the developing world: to provide a platform that is easily adopted by physicians, that anonymizes patient information for tracking diseases and that support clinical decision making through the use of Artificial Intelligence.

PEGASI's competition raises products of local scope, without adaptation for medical specialties and only available in Cloud, and only usable by physicians for local management of their information. Instead, PEGASI promotes regional reach with PEGASI MED, focusing on concepts such as access to a central medical record for regional patients and anonymization of information for Big Data purposes. PEGASI's team members also took the experience they had in the Banking and Fintech industry, and are the first to use data protection patterns reserved for financial information in order to insure information integrity.

PEGASI MED is the first EHR to offer synchronized local and Cloud facilities to overcome Internet shortages common in the developing world, while offering specialized forms for 30+ clinical specialties in a centralized format. In addition, all the information loaded in PEGASI MED can be analyzed as Big Data, for the production of clinical-administrative reports.

Finally, growth space for new AI models that support clinical decision making is always available, due to the unique way PEGASI MED's data is treated.

For PEGASI MED, our Backend is created using Microservices. Dominant pattern is CQRS (Command Query Responsibility Segregation). The deployment of our microservices is done using a Docker image, running on a Linux Box for local servers, and on AWS Docker swarms online. Both versions synchronize directly using B-SYNC, our Kafka-based sync component. Backend is developed is Node.js, while the Backend coupling is done using Apache Kafka. We model our Backends on HL7 FHIR REST resources, so that interoperability is available at deploy. Our Frontend is written in Angular 7, and it is used to create the Webapps that interact with the Node.JS backend. Our database is MongoDB for offline deployments, and Amazon DocumentDB clusters for online access. For Machine Learning, we run TensorFlow models for processing datasets from our datalake, for specific tasks.

Our stack is common in its usage, as seen in the MEAN stack website (http://meanjs.org/). However, Microservices are rarely used in Healthcare (even more in the developing world) due to needed data uncoupling, which we solved using a CQRS pattern and HL7 FHIR REST services. Also, data coupling with Kafka is not often done in Healthcare, and we got the technology from our Fintech forays. One of the most popular use cases can be found in https://kafka-summit.org/sessions/the-evolution-of-kafka-at-ing-bank/. There are also some use cases seen in low-latency Healthcare systems, as can be read about in https://kafka-summit.org/sessions/digital-transformation-healthcare-kafka/.

A demo of our technology can be accessed at http://demo2020.pegasi.io/. Username: demo. Password: passworddemo123.

PEGASI makes clinical information accessible, clear and secure, which reduces patient consultation time, increases the number of patients Healthcare services providers tend to everyday, and drastically raises the quality of care provided.

Furthermore, PEGASI's software prevents unnecessary repetition of paraclinical exams, which in turn decreases costs for patients and government alike, and diminishes paper and electricity usage.

In the long term, PEGASI seeks to improve Health for millions in Latin America by using Big Data analysis for real-time Public Health vigilance, Machine Learning for assisting clinical decision making, and treatment improvement by comparative analysis of over 50 million electronic health records.

Since our launch in November 2019, we serve 36,821 patients and 84 physicians. Our older versions have around 2,500,000 patients in them and are used by around 8,000 users, so we'd be looking to migrate all of them by January 2021. We also expect to have around 200,000 new patients by that time, for a total of 3,200,000 patients in our datalake by that time.

In 5 years, we expect to create Big Data out of around 16,000,000 electronic medical records (EMR).

We want to expand our operation to the following countries: Peru, Ecuador, Bolivia, Guatemala and Mexico, and contact investors and allies to open operations in selected countries in Africa. We already are beginning to expand our commercial strategy in Chile and Dominican Republic, but we want increase the number of countries where we have data capture points. This will quickly enrich the reach and diversity of our datalake, so we can produce business intelligence (BI) that's more interesting for governments, NGOs, multilateral organizations and the medical industry. 

We will also increase our team's size, which will allow us to develop industry-specific tools to gather information in a better way, and Data Science algorhythms to process the information that goes into our datalake. Finally, we designed several processes to fuel our LatAm expansion and establish a redituable operation to continue growing our data structuring and processing focal points.

We did a risk analysis during our time with Agora Partnerships, and that highlighted our main challenges, which we have tackled one at the time.

Our main barrier now is a commercial one, considering we think we've developed the technology base we need to handle the problem as we described earlier on, but are facing customer deals drop due to the coronavirus spread. We launched version 2.0 of our platform on November 2019 and were gathering enough commercial traction to create positive cashflow, but deals that were supposed to close in the next months were put into an hiatus due to uncertainty.

In the next five years we figure the greatest barrier will be customization for each country, as each one works with differente parameters that have to be implemented in order to have an efficient information gathering experience.

In our immediate plan is raising a USD $ 500,000 seed round or grant money. This should build our momentum and allow us to spread, even in times of uncertainties, and also to scale given investor outreach and new commercial partnerships.

Our five years' challenge will be solved by broadening the team and experts in that team, that can sinthesize for us the peculiarities of each country's Healthcare system, so we can expand faster by adding requirements to our platform.

We have 14 full-time people on our team:

• 4 officials
• 7 devs
• 2 QA / Implementation
• 1 Sales representative

We also have a medical advisor, that works with us on demand.

Our team has a over 20 years of joint commercial and implementation experience in the Healthcare IT of Latin America, developing solutions that take top technology and shape it in the way our stakeholders work. We also have a very strong technical background, coming from the Banking IT business, accustomed to applications used by millions every single day. Finally, we have a group of mentors, advisors and coaches that lead us through the latest technology in Healthtech, but also through tough commercial and design decisions.

We are part of the Young Leaders of the Americas Initiative (YLAI) 2016 cohort, Agora Partnerships' Class of 2018, Start-Up Chile's Generation 21, CENS (Chile's National Center for Healthcare Systems) Tech Challenge graduates, Socialab Ventures' Batch 1 and Katapult Accelerator's Batch 5. We also have Morris Sierraalta y Asociados as our law firm, Security Signal as our cybersecurity consultants, Amazon Web Services (AWS) as our supporters and Otto Health as a possible ally for distributing low-cost telehealth solutions around Latin America. Finally, we are partnering with Roche Laboratories in the Healthtech Builders Lab programme to develop pilots for handling Oncology information throughout Latin America.

We work in a Software as a Service (SaaS) model, where we charge USD $ 40 per license set (a physician, an administrative user and a technical user). For the Business Intelligence (BI) and the Digital Transformation Consultancy (DTC) models we work on a case by case basis, depending on the client's requirements.

Our sustainability is given by achieving a mass of 680 individual clients, or 40 corporate clients, in our SaaS business model. We are also looking to raise an USD $ 500,000 Seed round this year, to accelerate our expansion plan.

Having a community of incredible individuals that could help us think about, review and broadcast the ideas we have for tackling the difficult situation of healthcare information handling in the developing world is paramount to us. 

Our solution is not a solution designed for profit, it's a dream that we share in PEGASI ever since we started in this line of work: making Healthcare affordable and efficient for everyone, and using clinical information as a regional development tool. For this, we think Solve is a great platform to help us move forward with that dream.

We have been growing commercially in the past few months - Start-Up Chile has helped us align our product-market fit to the business models we're expanding in Latin American-, and in that sense we have a profitable operation that is highly scalable. However, what Agora Partnerships instilled in us in our previous acceleration was a desire for purpose and a clear route to accomplish it: we trust we can achieve our objective of turning developing Healthcare information into a tool for regional development, and we feel Solve has the key to unlock our full changemaking potential. We are seeking 3 specific resources: mentoring, especially regarding Artificial Intelligence -technologies in which we have experience but we also identify a huge opportunity for learning-; access to a network of key actors that can make the change we want to make long-lasting, and capital to expand our operation in a conscious, impact-driven way.

We would like to partner with multilateral organizations that manage Healthcare in the world, such as Red Cross, PAHO and WHO, to whom we can provide services for handling healthcare information. This would ultimately help us grow our Big Data repository more quickly, which would in turn provide more accurate information of endemic and epidemic diseases in the region.

We have been working for over 4 years on making Healthcare information a tool for regional development, by creating cost-effective technologies that allow patients to be protagonists, that make data accessible, clear and secure in order to prevent adverse events, and to have actionable data to make data-driven Public Health decisions.

We think we have a great technology ecosystem that allows an end-to-end management of everyday Healthcare information, and features that are solid enough to become standards in the developing world - but we need more resources to incorporate tools such as Artificial Intelligence, Machine Learning and advanced visualization methods, to really extract as much value as possible from the information we're obtaining everyday. That's where we want to invest this prize: into having a deeper impact and providing more analytic tools to strengthen our Healthcare systems.

We have been working for over 4 years on making Healthcare information a tool for regional development, by creating cost-effective technologies that allow patients to be protagonists, that make data accessible, clear and secure in order to prevent adverse events, and to have actionable data to make data-driven Public Health decisions.

We think we have a great technology ecosystem that allows an end-to-end management of everyday Healthcare information, and features that are solid enough to become standards in the developing world - but we need more resources to incorporate tools such as Artificial Intelligence, Machine Learning and advanced visualization methods, to really extract as much value as possible from the information we're obtaining everyday. That's where we want to invest this prize: into having a deeper impact and providing more analytic tools to strengthen our Healthcare systems.