LiteraSeed

LiteraSeed is a digitally native, picture-based communication platform that allows patients with low literacy and low health literacy to accurately and remotely self-report symptoms that may have otherwise gone unreported, unidentified, or misunderstood. The app integrates within messaging apps (e.g. SMS, WhatsApp) for scalable deployment into rural communities without requiring an in-person physician encounter. Longitudinal monitoring allows health departments to identify and track disease outbreaks in real-time. When compared to an in-person physician visit aided with a language interpreter, preliminary results (n=30) indicate that the LiteraSeed app identified missed symptoms that could have led to misdiagnosis or underdiagnosis in 20% of patient cases. On average, the app identifies 0.26 more symptoms per patient and most physicians rate the app 4 out of 5 or higher. Accurate and language-agnostic data, especially in geographically isolated communities, will improve global surveillance and the effective response to disease outbreaks.

The COVID-19 epidemic has highlighted the risks that communication barriers present in healthcare. Vulnerable populations, such as those with language and cultural barriers, and the economically or educationally disadvantaged, receive suboptimal care at an alarmingly higher rate than their counterparts.

In the U.S., low health literacy, language, and cultural barriers increase the risk of medical error by 2x, with miscommunication being a core factor. Almost 120 million Americans, or 36% of the U.S. population, have low health literacy, which disproportionately affects both racial and ethnic minority groups and patient populations that are uninsured, underinsured, or have Medicaid / Medicare.

Globally, the problem is further exacerbated. More than 400M people have no basic healthcare and 800M people, 16% of the world’s adult population, lack basic literacy skills, two-thirds of which are women. Health literacy is intrinsically tied to a country’s literacy rate and even in the most literate of countries health literacy rates remain low. Accurate and complete information communicated to the provider from the very first encounter is important to ensure proper care throughout the patient journey. It becomes critical when a pandemic upends normalcy, creating barriers that exacerbate disparities and leave the disadvantaged behind.

LiteraSeed aims to assist medically underserved patient populations with low literacy and low health literacy in overcoming communication barriers by providing a web-based application that uses pictures for the simple communication of their symptoms and health condition. Patients are guided through an image-based questionnaire led by algorithms that determine which question sets are relevant based on user inputs and a structured report is then generated in a doctor-friendly form and securely sent to the provider prior to the visit. The web app is developed using an agile development process and a React to Node.js tech stack with Firebase on the backend. 

By overcoming language and literacy barriers for effective health communication through a platform that is remote, language-agnostic, and scalable, we aim to globally advance access to healthcare. Better data collection will augment the diagnostic capabilities of lower-skilled medical staff in settings that are resource-limited, expanding regional capabilities and access to care. Decoupling the need for in-person medical visits by enabling remote patient evaluation reduces the risk of exposing providers to COVID. Longitudinal monitoring in geographically remote communities will help public health officials prepare, detect, and respond to emerging pandemics and health security threats at scale.

Motivation:

The motivation for this project is the tragic and preventable death of the founder’s young relative to anaphylactic shock while waiting to receive treatment in an Emergency Department. Improved communication and medical literacy could have resulted in the child receiving life-saving care.

Target Population:

• In the U.S., vulnerable groups (e.g., immigrants, refugees, low income) are at risk of miscommunication.

• Outside of the U.S., communities of low literacy, especially women, are at risk of miscommunication.

Why They Are Underserved:

• Healthcare systems have communication frictions. New and inexperienced staff may make the wrong judgment, while the patient's cultural, educational, and language barriers may prevent them from communicating efficiently.

• Miscommunication is a leading cause of medical error.

• Medical error is the third leading cause of death in the US, costing 250,000 lives every year in the U.S.

• The CDC attributes communication as the most common class of systems of care factor causing the U.S.’s high maternal mortality rates. 5 of the top 10 recommendations by the report to reduce pregnancy-related deaths are related to improving communication.
• In the U. S., language barriers make this situation significantly more challenging, increasing risk of more frequent and severe adverse outcomes by 19.6% when compared to English speaking patients.
• In the U.S., 78.9% of misdiagnoses are caused by miscommunication and result in 80,000 to 200,000 avoidable hospital deaths each year. 56.3% of those communication gaps are related to the history-taking during the patient-provider encounter.

Proposed Solution:

LiteraSeed provides a software application for obtaining, analysing, and assessing patient symptoms and historical data to dramatically improve patients' efficiency in communicating their present symptoms and history, allowing providers more hands-on time to make an accurate diagnosis and provide timely, cost-efficient, and appropriate care.

Design Process:

Our design process includes an awareness of key barriers, and keeping stakeholders engaged throughout solution development following human-centered design practices. 

• We have interviewed patients, had lived-experience, shadowed medical providers, and are piloting solution in a clinical setting with real patients at real appointments 

• We will continue to do UX research, needs-finding, focus groups, co-creation, etc. 

• We have implemented the design of a rigorous clinical study to measure efficacy.

The solution will understand the barriers to accessing healthcare and aims to bridge those gaps as perceived/experienced by the patient population, but it does not stop there. We engage medical providers in the design as well, and not only strive to improve access to care, but also through the patient journey by improving patient-provider communication, which is a significant factor in improving healthcare quality.

Problem

Miscommunication between patient and provider leads to inequitable healthcare access and lower-quality care, resulting in poorer outcomes and higher risks to patient safety that were further exacerbated by COVID.

Solution

Leverage people’s mobile devices and modern affordances of UX/UI design, to overcome language barriers so that all people have access to high-quality care. 

Population

Enable all people—especially the medically underserved and at-risk because of race, ethnicity, age, gender, or income—to communicate effectively so they can obtain high-quality healthcare. In doing so, access to healthcare for all people will be improved as a result.

We have two ongoing pilots where we are testing early versions of the web app and sourcing data to demonstrate clinical efficacy. These partnerships include Valleywise Health, the largest safety-net health system in Arizona, and Focused Family, a Federally Qualified Health Clinic providing mental and behavioral health services based in Phoenix, Arizona. Additionally, we also have a few other pilots in the pipeline, including one at Aga Khan University Hospital in Karachi, Pakistan. Our product is being tested for a number of factors such as usability, speed, stability, ease-of-use, workflow, etc. and the software is being redeployed with each iteration. Hence, the product is still at the prototype / R&D stage.

LiteraSeed is building a transformative, health condition monitoring platform for obtaining, analyzing, and assessing health information from patient populations with communication barriers. We offer an interactive frontend that helps patients overcome communication barriers in providing contextual and background data on their health condition. The key innovation is a universally accessible, picture-based user interface guided by user experience design and driven by machine learning (ML) suggestions for next best actions (NBAs). The AI / ML is being developed in partnership with Professor Hoda Eldardiry, Director of the Machine Learning Laboratory at Virginia Tech, and will identify personalized disease risk areas and modify the questionnaire accordingly to elicit the most accurate and priority symptoms from the patient. The goal is to help patients (in particular, those with limited English speaking and non- and mixed-literacy) describe precisely what they are experiencing in a way that can help doctors expedite the diagnosis and treatment process. This will result in more personalized and safer care for the patient.

Currently, we are in research and development with our app. To date, we have enrolled 30 people in our pilot study. 

In one year, we plan to enroll at least 1,000-5,000 patients in our studies across multiple healthcare sites worldwide, potentially more depending on statistical relevance to prove our technology is effective in meeting clinical outcomes.

In five years, we expect the technology to be available to consumers and health systems across the United States. At a minimum, around 4 million pregnant women each year could benefit from using our technology during pregnancy. We have plans to continue to expand to cover health conditions for children, men, and women (outside of OBGYN), which will allow us to positively impact healthcare for millions of more individuals across the United States and globally, starting in Pakistan and India. 

Full-time staff: 2

Part-time contractors: 1

Aziza Ismail: 

• Experienced first-hand through a personal tragedy in the family

• Human-centered design expertise
  

  • Completed undergraduate thesis on designing mobile literacy for unschooled adults (i.e., for adults with low-literacy) 

• 2 years of research, including shadowing doctors and medical providers during visits with patients. 

John Waldeisen: 

• Co-founder and CEO of Lucira Health (NASDAQ: LHDX)
  • First at-home COVID test cleared by FDA
  • Raised $20M from VCs and co-authored $26M in grant funding
  • Filed and granted 10+ patents in several countries
  • Grew company from 0 to 40+ employees
• Co-founder and CTO of Animalia Health
  • Raised $250k in funding and acquired in 2021
  • RNA-sequencing to assess pet microbiome and gut dysfunction
• Design, development, and implementation of clinically-validated tools for diagnosing disease

LiteraSeed is founded and led by a diverse team of both U.S. nationals and immigrants, male and female. By being a social impact-driven and focused on improving healthcare access to underrepresented patient populations, the company continues to attract the interests of underrepresented minority and otherwise diverse candidates. 

We believe that by being transparent with the information we share and listening to the voices of our communities, we can design a process and company culture that supports diversity and embodies inclusivity. 

In our recruitment efforts, we additionally reach out to communities or channels that cater to specific populations and we carefully draft job descriptions so as to encourage and not discourage female applicants from applying.

We are a social impact-driven startup and would love to join a powerful network of impact-minded leaders across industries and sectors.

Business Model: given the healthcare payer ecosystem is unlike that of any other sector, we will require access to various experts in the space to understand how we can better monetize our product and services. 

Monitoring & Evaluation: in the early stages of our solution development, collecting evidence is our top priority as we want to ensure we are building a truly positively impactful product that can improve healthcare access and quality for medically underserved populations. We also need to build the evidence to unlock the revenue streams to sustain that impact. 

Product / Service Distribution: any early-stage company that is ready to scale will benefit from introductions to more potential partners and clients that can use the product. In the early stages, we are looking to commit more pilots so we can obtain data and evidence, and involve more stakeholders in the design process of our product to truly deliver a positive impact throughout the patient journey and healthcare system. 

• Healthcare organizations, hospitals, and clinics.

  • Piloting and using our solution where it’s intended to make the most impact in improving patient-provider communication and encourage more positive outcomes.  

• Public health entities, government, and non-governmental.

  • Reaching our target patient populations in their own communities so we can help plug them into the healthcare system, while equipping them with the tools to ensure they can access higher-quality and safer care. 

• Community-based organizations and ethnic community-based organizations.

  • Engaging the various patient population communities in our design process, to understand and find out the deep unmet needs we can address with our solution. 

Two of our target populations are immigrants and refugees in the U.S. In our pilot studies, we primarily work with immigrants and refugees throughout the design and testing process of our product. We collaborate closely with Valleywise Health in Phoenix, AZ, a large safety-net health system, and other clinical (federally qualified health clinics) and non-clinical partners (e.g., non-profits) that work directly to serve these populations. 

Our founder's (Aziza Ismail) parents came to the U.S. as refugees many years ago and she can relate well to the lived experiences of newcomers to the U.S. They have experienced personal tragedy, including the loss of a young one, stemming from the problems of language and literacy barriers in accessing healthcare. Our lived experience makes us passionate about improving equitable access for all people by overcoming communication barriers. 

We are currently working with the refugee population at the Refugee Health Clinics at Valleywise Health, a safety net health system in Phoenix, Arizona. We are healthcare-focused and our project aims to support refugee self-sufficiency in the navigation and use of healthcare services. Working with refugees requires partnerships with various communities that speak different languages, and in order to support this process to be more inclusive of refugees in our design, we are applying for this prize. 

Our early product is focused on women's health issues through collaborations with both the Women's Clinic and Refugee Women's Health Clinics at Vallewyise Health in Phoenix, AZ. We also have a few other partnerships in the process of being initiated with clinics that primarily serve the health needs of teenage girls (e.g., sex-trafficked).

Our product helps make sure that women and girls are empowered to speak up about their healthcare, share their health concerns, ensure their needs are heard, and to. be empowered with information about their health to advocate for their best care. 

We have a collaboration with Professor Hoda Eldardiry, Director of the Machine Learning Laboratory at Virginia Tech, to co-develop patient risk assessment algorithms and diagnostic capabilities for medically underserved populations.  We need to support the research and development of our ML algorithms to improve diagnostic accuracy and risk assessment of people who cannot speak the same language as their medical provider, and we need to equip medical providers in under-resourced areas to be able to provide higher-quality care to those patients. 

We work with healthcare providers in the U.S. and internationally, starting in Karachi, Pakistan. We're also in early conversations with two health systems in India and plan to pitch more in North Africa and Europe. We believe that our focus on global impact and being a language-agnostic platform that can help people across borders to report symptoms of the disease will support and complement supply-chain management by unlocking insights into where there is more or less need for supplies for better response preparement.