The Health Manager
High quality academic research has traditionally been available only to a small number of privileged and highly educated people. This limited access to relevant and new research has become more obvious during COVID-19 pandemic, when the general public is searching for real time answers while doctors have become the only knowledge brokers being overwhelmed with the influx of questions and new information.
Our solution is a machine learning-based app that translates relevant health research into printable graphic summaries and short videos. A curation board ensures research integrity and accuracy while a creative team supported by Artifical Intelligence transforms the most relevant insights into understandable information design for patients and their relatives, health care workers and doctors.
Scaled globally, our solution provides patients, health care workers and doctors, particularly those in low-resource settings, with direct and free access to high quality health research overcoming language and knowledge barriers.
Whilst taking part in the Easterhackathon 2020, we discovered that medical doctors (which includes GPs and specialists) are confronted with an increased amount of questions from patients due to COVID-19. Simultaneously, GPs' workload is multiplied since they often help to fight the virus also in hospitals at the front line. We conducted qualitative research among academics and doctors from the University of Bern (Switzerland) and Bauhaus University Weimar (Germany) to understand the key concerns during this pandemic.
Besides, the scientific and medical communities are 'drowning' in the several thousands of COVID-19−related papers published in only a few months, we wondered:
How can we help doctors to stay informed and answer questions more efficiently?
Thinking on a global scale, these problems become more pressing since health workers are unevenly distributed worldwide, with over 40% of WHO Member States reporting <10 medical doctors per 10 000 people. Low- and middle-income countries need to face the pandemic with a much smaller health workforce, and thus doctors in these settings have very limited time for physical consultation or to keep updated with COVID-19 research. Therefore, an app based on information extraction technology could contribute to the knowledge transfer during any health crisis.
We have created and are testing the prototype for a website-based app (later stages moved to a downloadable mobile app) providing informed (evidence-based) overviews of scientific research in an easily understandable format, such as printable graphic summaries (ideal for health care workers) and short videos (ideal also for patients and their relatives).
The backend will provide the processing of a large number of scientific research texts using data ingested either from a search engine database of academic literature, through application programming interface (APIs) with humanly curated content (for quality assurance). Together with a team of data scientists and academic researchers we are developing a process where the content creation will be provided on an automated basis in order to deal with the large amount of available scientific data. Focusing on the key elements of the scientific article, such as the aim, methodology and outcomes of the research, the analysed text stemming from a curated and peer-reviewed database of pdf-based articles can be directly transformed into scripts and icon-based video content, both in an user-friendly and professional formats.
Our target population are patients or potential patients as well as relatives and anyone affected during a health crises. Having interviewed people within the immediate front-line of the COVID-19 crisis in order to create a fully functioning MVP, we are planning to test the app with a team of doctors from Spain, Germany and Switzerland using questionnaires and further interviews. Moreover, we have identified similar requests in other medical fields, for example influenza or diabetes. Interestingly, once the platform is developed, it can be easily adapted to other pathologies by training the algorithm with a pertinent article database.
Whilst the idea has the potential to extend to everyone worldwide with internet access, we expect to reach many of the 7,5 million COVID-19 patients (worldometer.com data as of June 11th) as well as their relatives directly through the app, plus many more people who seek information and education on the topic. In particular, we intend to offer this service to patients in countries where healthcare access is scarcely available. This is part of an overall aim to improve education and healthcare delivery for a number of people who lack the background and access to scientific and medical data.
We aim to support a large number of people from different backgrounds with a tool in response to pandemic outbreaks and diseases such as COVID-19, empowering people to effectively deal with crises through evidence-based answers that they would not get otherwise.
Healthcare workers and doctors will be the main disseminators of the platform and can not use the knowledge for them and their staff, but distribute knowledge effectively to patients.
Based on our research, our solution will provide time-saving and stress-relief through improved decision making processes, together with increased up-to-date knowledge and relevant statistics on protection and field experience.
- Prototype: A venture or organization building and testing its product, service, or business model
- A new technology
Enter your big text here to see that data can be extracted.
http://hh-berlin-thm-website.s3-website.eu-central-1.amazonaws.com/try-it-out/
Further our research is based on new extraction techniques working with NLP:
https://books.google.de/books?id=KabKDAAAQBAJ&pg=PAfrontcover&redir_esc=y&hl=en#v=onepage&q&f=false
https://www.kaggle.com/nmonath/knowledge-discovery-from-full-text-research-papers
https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge/tasks?taskId=558
https://datanatives.club/t/april-7th-5-pm-cet-covid-19-automated-nlp-based-question-answering/700
- Artificial Intelligence / Machine Learning
- Software and Mobile Applications
- Women & Girls
- Pregnant Women
- Children & Adolescents
- Elderly
- Rural
- Peri-Urban
- Urban
- Poor
- Low-Income
- Middle-Income
- Persons with Disabilities
- 3. Good Health and Well-Being
- 4. Quality Education
- 9. Industry, Innovation, and Infrastructure
- 10. Reduced Inequalities
100 People now
10,000 people next year
10 million people in 5 years
- Not registered as any organization
We are nine people on the team with the initiators being Daniela Marzavan and Sophie Gruböck:
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We bring in full interdisciplinary expertise and a fundamental insights also with data scientists stemming from Rumania, Germany, Australia, Ukraine, Canada, Spain, Switzerland, France and Italy. Please take a look at our devpost link for further info: https://devpost.com/software/the-health-manager/edit
This was the winning team of the EasterHackathon with the Charite Berlin:
Under construction with the team and the hope to receive help from SOLVE MIT.
- Organizations (B2B)
Any patient or member of the general public is the beneficiary and does not pay, but benefitS from better informed health care providers and easily digestible content overview of a topic transporting necessary and useful information more clearly and comprehensively.
THM will use a freemium and subsidy model working with doctors as the main user group to provide free content to the beneficiaries as the second user group. We will have a different price plan for high/medium/low-income countries.
Therefore doctors and their employers or hospitals will be the main “clients” and pay for the use of the app once they decide to use it above a certain threshold.
- Business model
- Product/service distribution
- Funding and revenue model
- Board members or advisors
- Legal or regulatory matters
- Monitoring and evaluation
- Marketing, media, and exposure
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