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Compared to other industries across the globe, it is debatable how much the implementation of new technology has led to true advancement or operating cost reduction in healthcare. Certainly, it has not had the same democratizing effect. In light of this observation, Ajay K Gupta and Ram Peruvemba decided to find out why. Once they got their answer, they committed themselves to start a company with the motive to solve the problem and to bring the benefits of modern tech to healthcare.
In 2013, Gupta and Peruvemba established HSR.health to build health tech solutions with the audacious goal of advancing the capacity of global public health – thereby improving lives and communities across the world. Since then, the founders have been successful in the effort. The company offers advanced and novel health risk insights to predict the spread and severity of disease, whether chronic, infectious, or social, and works to make those risk insights available to all organizations impacted by health risks. HSR.health has also found that industries outside healthcare have an appetite for insights into future health risks
Ajay explains, “We provide risk insights through our GeoMD Platform that make unexpected health events predictable. It is a health-focused spatial data infrastructure leveraging generative AI providing a conversation front end, purpose-built Large Language Models (LLMs) to curate and mine data from authoritative governmental and intergovernmental sources. Thus, it limits the risk of bias and error in the data used to train our Machine Learning (ML) models. Additionally, it improves the accuracy and equity of our solutions, a large and diverse set of authoritative data establishing the largest corpus of knowledge within healthcare globally, and geospatial visualizations to convey our results in multiple, ease-to-digest forms to meet the individual needs of different end users and stakeholders.”
The company pursues an aggressive patent strategy and formally announced its generative AI front end on November 28th this year. The conversational nature of such a front end (think ChatGPT) will enable more and more organizations to anticipate, mitigate, adapt to, and take advantage of future health risks.
The augmenting risk of exposure to climate change-induced natural disasters, an unexpected surge of workforce absenteeism due to influenza, an outbreak of a local epidemic or global pandemic, or health risks can now become a part of risk management and long-term planning instead of an unanticipated emergency.
Within healthcare, individual medical facilities, health systems, as well as large global public health organizations such as the World Health Organization – are better positioned to care for the sick and allocate resources to meet their needs.
Outside of healthcare, businesses can be in the know and take measures beforehand to hedge against the risk of supply chain disruptions because of illness-related productivity slowdowns across the manufacturing and shipping sectors, for instance.
HSR.health utilizes a number of tech components that can be referred to as Artificial Intelligence. Ajay explains, “We curate and mine data from authoritative sources through purpose-built Large Language Models (LLMs) helping us to have confidence that the data we use in our work is complete, comprehensive, and free from bias and error.” This enhances the quality of the company’s solutions as well as the client’s confidence in these solutions.
The business uses LLMs to effectively interface with users through the conversational, prompt-based front end to both understand what the user is asking and what information is needed to respond to the question.
Each of the company’s health risk indices, which involve advanced machine learning (ML) algorithms, range from predicting risks such as the number of flu hospitalizations per region to anticipating who among a population of expectant mothers is at the highest relative risk of a material and child health complication. This allows healthcare providers to match the available care resources with those most at risk.
Further, the continuous learning approach of ML algorithms essentially ensures the continual improvement needed in healthcare – in terms of both health risk stratification as well as mitigation, resulting in long-term improvements in care outcomes.
Like any other industry, the healthcare industry faces several challenges. A key challenge is being unable to anticipate future healthcare risks and have visibility into their potential impacts in economic terms. Both these challenges are addressed by HSR.health. The company anticipates future healthcare posture and conveys this in terms of health and economic implications.
For instance, wildfires cost lives and damage wildlands, urban areas, agricultural lands, animal habitats, and the built environment. Ajay says, “We leverage satellite data to assess in real-time the impact and damage to healthcare facilities (hospitals, clinics, labs, etc.) to have both better guidance on where to transfer patients for medical care in the immediate case, as well as what health and medical resources to re-establish post-disaster. This is a key component of the cost – and success of – the recovery.”
In the healthcare industry, generative AI is presently being used for the synthesis of published research articles, improving documentation and workflow for clinicians, searching and summarizing electronic health records, and is getting into clinical areas, such as medical imaging, and enhancing clinical trial processes.
HSR.health incorporates AI methods in numerous ways across a wide range of public health areas. Firstly, it is used for extraction and curation of data on health outcomes from authoritative, but non-standard sources – sources not typically used within healthcare. For instance, the company is leveraging its purpose-built LLM to form a dataset of historical disease outbreaks and prevalence data from sources including but not limited to reports (often written) published by the WHO. As well as ingesting climate change data from the EU’s Copernicus Programme and from the NASA Center for Climate Simulation.
Ajay says, “Our GeoMD Platform uses AI to draw conclusions from geospatial health data along with over 100 dimensions of alternative data, allowing the world’s decision-makers to better understand, anticipate, and mitigate adverse health events.”
Additionally, HSR.health incorporates generative AI into the present analytical results in an easy-to-digest and actionable format providing complementary and supplementary information to the analysis. Last but not least, it provides a user-friendly interface to engage with all of the health risk analytics.
“The natural language interface that generative AI creates is a game-changer for health risk analytics – bringing our risk insights to the masses without the need for coding or data analysis skills,” says Ajay.
What makes HSR.health further stand out in the industry is its motivating factor, which is the opportunity to leverage truly novel and innovative technology to advance the capabilities of public health.
Ajay says, “Machine learning models, geospatial analysis and visualization, and generative AI are all powerful and impactful on their own. We bring all these together with the generative GeoAI capabilities of our GeoMD Platform.”
Since its inception, HSR.health has worked on multiple projects for several clients. These include performing an assessment of personal protective equipment (PPE) for medical providers for State Coronavirus Task Forces (Maryland, California), Ventilator Needs Analysis for State Coronavirus Task Forces (Maryland), COVID-19 Risk Tracking in Africa for The Graph Network/World Health Organization, assessing the level of and health risks from the bioaccumulation of microplastics and their related toxins in our oceans and waterways for Natural Resources Canada (NRCan) and developing a suite of health risk indices due to natural disasters – hurricanes, ocean storm surges, wildfires, droughts, and floods, – in efforts supported by NASA, NOAA, FEMA, the USGS, NRCan, and the UK Hydrographic Office.
In addition, the company has worked on a NASA-funded effort to leverage crowdsource labeling of LANDSAT imagery for health- and wildland fire-related information. Ajay explains, “In our role, we surveyed first responders, firefighters, and emergency medical clinicians to identify the information regarding wildland fires that will better inform and speed their delivery of care and the allocation of necessary resources to impacted populations.”
In developing care deserts and health equity analysis for the Maryland Hospital Association, HSR.health has leveraged its proprietary Social Determinants of Health (SDOH) Risk Index to not just understand the health posture of a community, but also which communities may be the most at-risk from a lack of access to care. This information is essential for provisioning care into existing deserts to achieve equity in outcomes.
When asked about what’s next for the firm, Ajay says, “Based on what we’ve built, what we’ve been able to do during the pandemic, we are well on the way. Our people are absolutely fantastic. Our data science team, our public health team, our geospatial team, our leadership – are all among the best and brightest in the world.” In the long run, the company aims to save lives and reduce both local and global healthcare costs through the intelligent application of advanced tech.
“We’ve built many, powerful and novel risk indices that identify the driving factors underlying today and tomorrow’s health risks faced by humanity as well as their long-term economic consequences. Of course, we will always expand and add new risk indices. And the addition of a generative AI-based natural language, the conversational front end will bring these insights to the masses. 2024 will be about bringing these risk insights to the market directly through our platform and as many high-quality and appropriate data marketplaces as we can identify.”
Description of the Company: HSR.health operates in a remote work environment, with its team spread throughout the U.S. – coast-to-coast – and builds models to predict the spread and severity of disease – chronic, infectious, or social – allowing the world’s decision-makers to better understand, anticipate, and mitigate future health risks.
Pull Quote: “Machine learning models, geospatial analysis and visualization, and generative AI are all powerful and impactful on their own. We bring all of these technologies together with the generative GeoAI capabilities of our GeoMD Platform.”
Company Name: HSR.health
Founding Year: 2013
Office Locations: While a remote work company, HSR.health maintains a mailing address at 15200 Shady Grove Road, STE 305, Rockville, MD 20850.
Official Website of the Company: www.hsr.health
Name of the Featured Leader: Ajay K Gupta, CISSP, MBA
Designation of the Leader: Co-Founder & CEO
