Telemedicine Research Innovation

Technological advancement in the medical industry has been steadily growing since the inception of the National Institutes of Health (NIH) in 1887. Unfortunately, early access to these breakthroughs has been only accessible to Americans who can pay cash to access these technologies or by individuals who are enrolled with an insurance company that allows the use of the technology (specified by the insurance company and implemented into a managed care plan). For instance, the introduction of medical and scientific advances such as the CT scanner in 1972 and being able to implant a cardiac stent in 1986 comes at an increased cost to recipients of the technology. Despite notable health technology like a glucometer which is available through medical coverage and affordable to the general public, most medical technology when first brought to market is expensive and out of reach for most Americans. Especially those in minority communities. 

Generally, aspects of healthcare such as healthcare delivery, which is convenient, quickly accessible, and easy to schedule, are difficult to achieve for individuals who are on government insurance plans such as Medicare and Medicaid.  Many factors contribute to this, yet there continues to be an alarming disproportionate burden of illness among persons from poor economic backgrounds, in which racial and ethnic minority groups make up the largest portion of the population who experience health disparities.

This plan to solve this problem is to design a system to address the needs of the populations affected by gaps in the healthcare management and research system used here in the U.S. The 18.5% Hispanic or Latino population, along with the 13.4% African-American population are the biggest groups. Including the 5.9% Asian-American, the 0.2% Pacific Islander, and the 1.3% Indian-American population as last stated in a 2019 census count.  Docfully will start its research here in San Diego where there are diverse minority groups in the population, and it will identify them during onboarding and their initial health assessment.  

Docfully’s focus will be on populations that are close to 50% and 30% of the Average Median Income (AMI) here in San Diego, including individuals and families. In 2021 the AMI in San Diego is $95,100. So 50% AMI of a family of 1 is $42,450 and 30% is $25,4507. These economic metrics will help Docfully target the “very low income” and “Extremely low income” groups that have a very high probability of having health disparities.  We accomplish this with these individuals through our platform and mobile app that utilizes video-conferencing, health data collection, facial recognition technology through cameras, and machine learning to deliver to an individual a "health score" from physiological data, social determinants of health data, and mental health data collected. This system will be unique to each patient. Each patient has a dashboard with their aggregated score and is designed to connect patients to minority and/or culturally sensitive medical professionals which we hope to partner with from local organizations such as private hospitals, university hospitals, and federally qualified health clinics (FQHCs). We are looking to connect individuals that are immobile, without reliable transportation, and far from a facility and connect them to a medical provider of an FQHC and a case manager from a community-based organization with the help of our videoconferencing platform and hired outreach staff which will be dispatched to the patient's home.

Partnering with Universities in this process such as the University of California San Diego and San Diego State University will help in fulfilling IRB requirements for research. along with partnering with Community-Based Organizations (CBO) that have already identified individuals and families who fall under the demographics we are looking for. Using the database of CBOs as a resource, Docfully wants to target 10 individual encounters a month for the duration of the project (Individuals and families). Docfully defines a successful encounter as completion of an “Initial Health Assessment” and completion of the “Social Determinants of Health'' survey. An added benefit will be to have a telemedicine exam scheduled to engage with a medical professional. And give each individual the option to enroll in local or state-run research projects giving each individual using our platform the ability to participate and connect to partnering universities and organizations with local research projects while working with Federally Qualified Health Clinics.

We want to target the “very low income” and “Extremely low income” groups that have a very high probability of having health disparities. Poverty is one obstacle that can affect our patients’ health. It is an insidious, self-perpetuating problem that affects generations of families. Beginning in utero and continuing throughout an individual’s life, poverty affects health via complex mechanisms. Life expectancy, learning abilities, health behaviors, and risks for developing the disease are affected by poverty, as are educational, work, and lifestyle opportunities. The degree to which an individual’s health outcome is affected is filtered by his or her level of “host resistance” to poverty. Poverty does not automatically determine an individual’s health status, although it can significantly influence it. 

Previously, healthcare was provided for these individuals through enrollment in a managed care plan such as Health Maintenance Organization (HMO), provided by employer-based insurance plans, or enrollment in governmental insurance such as Medicare or Medicaid. These care plans were designed to manage the cost of care by controlling the use of technology or medical procedure to keep the cost low. They would negotiate with specific doctors and medical device companies to work in their network at a certain price point or salary to provide care. The development of this HMO network created the accessibility gap for minorities to primary care and the participation of disease-specific research that continues today. Even though managed care plans have expanded to “disease management groups” intending to reduce and monitor chronic conditions, minority groups are still falling in the healthcare gaps that these “care models'' are meant to eliminate and therefore, are failing to improve the quality of care of these groups. 

The project is being developed using “Patient-Centric Design'' to improve health outcomes using a value-based model. Past approaches to healthcare delivery have left many minority Americans unsatisfied and suspicious of our healthcare system. Especially in black and Latino communities where the dissatisfaction is highest. This is one of many sentiments felt by African-Americans. By providing a better experience with healthcare accessibility among these populations we wish to serve, the adoption of this system can spread. With greater adoption, we can promote more preventative care to improve, engage, empower, and motivate individuals, families, and communities to enhance the quality of life and sustain health gains. We do this through our platform in the form of data collection and satisfaction surveys. Also connecting them to minority providers or culturally sensitive providers is how we can show sensitivity and fullfill their needs withgout bias. Using this approach, we can build the trust of the U.S. healthcare system back into these communities.

In 2020, we performed a pilot during the apex of the COVID-19 pandemic among homeless individuals housed in a downtown San Diego hotel to test our theory of adoption of telemedicine technology to supplement the lack of continued managed care among this population. This pilot was funded by a contribution of $25,000 from “The Alliance Healthcare Foundation” in the form of a grant. The result of the 10-month pilot was over 120 individual encounters where we monitored their vital signs to track trends and anticipate possible medical episodes that would require an emergency room visit. At the same time, we performed weekly monitoring of individuals for any signs or symptoms of COVID-19. Among the 120 individuals we encountered over the 10 months, there were five occurrences where an ambulance was called. One of these calls where transportation to the emergency room was recommended was the result of a routine telemedicine visit we had for one of the patients. Another result of the 10 month pilot was one enrollment into an insurance plan, and two primary care doctor switches from the patients. We would like to expand on the study performed in 2020 with a larger group and improve our product that uses telemedicine software.

It is at this time, we established our mandate to reduce health disparities for minority groups who suffer because of these inefficiencies. My other team memebers has experince in the healthcare feild. Ronald Kutsch (Software advisor), Manager at Advantu a software company the works with risk management of medical softwear. Faith Quenzer (Physician advisor) Emergency medicine physician and researcher at Temecula Valley Hospital. Zixiang Su (Data Scientist), Lead Data Scientist at LexisNexis Risk Solutions a softwear company that does credit analysis for companies.

After our pilot in 2020 we continued to pursue partnerships with the organizations we were working with. Unfortunatly these organizations required that we improve our infastructure in order to pursue a partnership. We went to our original grantor but they were unable to offer us further funding to improve our team and infrastucture. Without further funding we could not hire a key part of our system's plan the community heath worker to act as outreach partners to the indivuals we wish to serve. So 65% of the prize money would go to hiring personelle to deliver our solution. Most of our labor woiuld be the community health workers along with a case manager and softwaer developer. 25% would go to improving our platform and developing a mobile appication. The remaining 10% would go to operations.

The team lead will be myself Jacques Stroud. I was originally raised in chicago in a middle class income family in an african american community. I noticed the disparities my community faced which lead to my desire to become a medical professional at a young age. I gaduated college with a bachelors in biology but didn't go strait to medical school due to burn out. I took a break and pursued other opportunities but found myself back pursuing  a carrer in the medical feild. I started gaining further insight on my community in 2015, due to my experiences as an EMT in Chicago. This is where I noticed health disparities among the African-American population, and while working as a home health nurse assistant for a 30-year-old Latino male who suffered from Cerebral Palsy. With this most recent patient experince, I encountered inefficiencies in the delivery of the patient’s Medicaid-managed care plan. These noticeable inefficiencies were not an isolated occurrence but were repeated among other members of his Latino community. The events lead me to researching the deficiencies in healthcare with underserved populations.

There are other companies and organizations that has videoconferencing as a feature, but for our platform we will connect patients with providers and researchers for virtual exams and research projects using videoconferencing on tablets we will provide. Another innovative way our solution will connect people is during exams we will provide a community health worker to troubleshoot technical problems with tablets or with the patients personal laptop for virtual exams. Our platform will also help doctors and researches by having a "note taking" feature. This will allow providers and researchers more time with patients and not worry about missing information because they didn't write it down. Thus saving providers time at the end of the day when they have to prepare submission of exams notes for reimbursement. And for researchers this feature can behave like a second notetaker when conducting interviews and examination of patients. But the innovative feature we want to provide for patients and providers is a scoring system and recommendation system taking into account three different factors that affect health. Physical factors, mental/behavioral factors, and social factors. Our machine learning algorithm and predictive model will give a different weight for these factors in our algorithm to produce a "Health Score" for the patient and provide treatment "recommendations" to the provider. If the scoring system is effective in helping providers with recommendations to help treat patients and possible research programs to participate in, then we can license our Heath Score software to other hospital systems to help their providers in recommended treatments and research programs that can benefit their patients.

Our one goal is to build more trust in the African American and Latin X community around the US healthcare system. By providing this service and connect these individuals and families to more medical resources and provide an innovative system for healthcare delivery we can earn the trust of this community. How we will measure our success is through an NPS score. If we can rank close to or higher that our local hospitals and clinics then we know we have succeed. To achieve this we need to target and partner with managers of smaller clinics and doctor's offices located in African American or Latin X communities. Our main user would be a healthcare provider such as a doctor or therapist who treats members of the community. Providers need a simple platform/app that their patients can use to communicate for their primary care and health literacy needs. Our platform and future mobile app will allow providers to have a virtual exam with their patients without requiring them to visit a facility. As well as researchers to access more patients from this community to participate in their research. 

Another impact goal we would like to create with this model is to keeps patients out of the ER. We want to examine how many 911 calls are made in certain communities as well as how many visits local hospital emergency departments receive in a day, a week, and a month. By tracking one of these key indicators we can see if our solution is having an impact on the community by showing a decline in visits over a 6 month to a years time. Also if we are able to sustain our program for over 5 years we should make a considerable difference in the community by reducing the amount of ER visits from members of the community.

As stated in the previous question ways we will measure our progress will be through NPS scores of near or higher than local hospitals and clinics. Measurement of emergency room visits from local hospital and show in reduction in weekly or monthly visits of a few years. And lastly we can show our progress by working with local providers with patients in the area of scheduling appointments. Our target populations have notorious inconsistency with making provider appointments due to a variety of issues. From lack of reliable transportation, to last min scheduling conflicts and just plane forgetting we want to reduce the amount of "no shows" a provider experiences working with these populations. Our solution which which requires a tablet or laptop for utilizing and accessing video conferencing helps solve this dilemma for providers. many individuals in the community has a cellular phone of a tablet and even a laptop but because of the lack of up-to-date mobile technology or software, is what makes it difficult to connect with a provider through videoconferencing. Having wifi to connect to the internet is another hurdle many in the communities we wish to self have a hard time to jump over in order to connect with a provider. It is bridging this great digital divide to providing access to a provider or researcher on our platform using hardware and cloud services we provide for synchronous telemedicine communication is how we bridge the gap. This method is how we increase scheduled medical appointments for the medical provider in the targeted minority communities, at the same time decreasing “No Shows'' ratios that occur when scheduling appointments for these populations. In a sample of culturally diverse patients at a safety net hospital, race and ethnicity were strongly associated with the likelihood to miss appointments. Missed appointments also were associated with medical complexity, major mental illness, and emergency room utilization. Thus, efforts to decrease missed appointments may need to focus on sub-populations with this demographic and clinical profiles. The healthcare industry loses more than $150 billion a year due to No Shows alone.

Medical providers who aren't culturally sensitive to minorities lack the awareness of the challenges African Americans and other minorities face when dealing with the US healthcare system. When it comes to healthcare among African Americans there is a lack of trust, fear, barriers to access, uneven quality and experienced racism in clinical practices. Minority researchers and providers also need help to connect with patients. We want to reduce these barriers for patients and providers using software and community health workers for outreach to help build relationships with community members which will decrease individuals entering ER's on a frequent basis.We are developing software to change healthcare delivery for all Americans. An example of what we want our platform to help with is minority seniors to age in place. Many seniors suffer from chronic conditions such as diabetes, heart disease, and high blood pressure, as well as behavioral issues such as depression due to changes in their social and economic status. Because of these and other factors connecting to medical providers can be difficult. From lack of reliable transportation, forgotten appointments, lack of connecting to available specialist, and lack of adequate insurance or no insurance. Our platform will allow seniors to connect with various medical providers (not just doctors) across the state and possible the country to receive diagnosis, treatment, and preventative care through virtual exams through our videoconferencing feature. We also want medical providers get the full picture of their patients by providing recommendations on treatment through our machine learning "health score" algorithm taking into account social factors as well. By connecting underserved populations to a better delivery system, earning their trust by connecting them with culturally sensitive providers, granting access to research projects geared towards their health needs, and allowing them the power to take control of their health by providing the tools to access providers even though their is a digital divide is how we have an impact on the community we wish to serve.

Our platform will provide videoconferencing to connect providers, researchers and patients for virtual exams.The video-conferencing feature of our platform is based on webRTC software. Because WebRTC is web-based software anyone can access it by opening a browser on a computer, a laptop, or a cellphone. The ability to utilize face-to-face communication on any device gives the ability to communicate with a medical professional anywhere. This will be our primary synchronous communication method.

But the innovative feature we want to provide for patients and providers is a scoring system and recommendation system taking into account three different factors that affect health. Physical factors, mental/behavioral factors, and social factors. Our machine learning algorithm and predictive model will give a different weight for these factors in our algorithm to produce a "Health Score" for the patient and provide treatment "recommendations" to the provider. For continued communication after their primary visit with a medical provider, we will use asynchronous communication using a machine learning model. Its proprietary machine-learning model will use logistic regression and boosted trees. The model takes patient attributes like vital signs and medical history, and social information into consideration and tries to find splits in those attributes based on the correlation with their health status. The model will combine all the important and predictive attributes and output a probability that indicates how likely a patient is what we will call "sick". All the predictions made are based on patient data in the training set. These models learn directly from the data without any prior statistical modeling, thus producing more objective results while focusing on prediction generalizability for diagnostic purposes on diverse populations. through the probability we can provide recommendations to providers. On the patient side these probabilities will be calculated into the "Heath Score" we will develop for every patient.

1 full time personelle, and 3 part time personelle

We started the company in 2015, and been working to connect underserved populations to a better heath delivery system for the last 7 yrs.

To establish diversity it starts with a diverse advisory board. Me and two members of my medical advisory board, come from minority communities where community members suffer from multiple chronic conditions. Access to primary care and health literacy are par and sub-par in neighborhoods where there are a low number of affordable clinics to services community members. Because of this many minorities has a higher chance of developing a chronic condition compared to their counterparts who has a higher level of access to primary care. Because of this I've tried to partner with culturally different members of my team to create this solution. Ronald Kutsch (Caucasian/Software advisor), Manager at Advantu a software company the works with risk management of medical softwear. Faith Quenzer (Phillpino/Physician advisor) Emergency medicine physician and researcher at Temecula Valley Hospital. Zixiang Su (Chinese/Data Scientist), Lead Data Scientist at LexisNexis Risk Solutions a softwear company that does credit analysis for companies.

We've developed a B2B business model where we will offer our services and platform to clinics and doctor's offices that have minority medical providers or work in minority communities. We want to offer a per member/ per month rate for the service and platform, or a per month subscription fee just to use our platform. We will connect patients of these clinics and offices to a minority physician using our platform if a primary care physician isn't available. Our platform will connect patients to a physician but also connect patients to other professional services such as a therapist or case management if our machine learned "Health Score" feature recommends it. This feature comes from from inputed social and behavioral data inputed by patients and professionals working with the patient. The collection of the data for each virtual visit and each time the patient visits the platform updates the score.

We have raised over $100,000 to build our initial platform and perform our 1st pilot in 2020. With our platform and revised business model we want to sell our services to local doctor's offices and clinics in a subscription model approach. We will continue to raise capital through seed investments to get us to our next milestone. As we increase sales we will continue to seek investment capital from angel investors an early stage VC firms for our series A and other series for growth and continued sales.

We have received other grants from local organizations such as the Black Chamber of Commence and the Better Business Bureau in 2022. This year we received a small grant from the University of California San Diego and potentially will work with their medical hospital by the end of the year.