- Erica Calogero
- Kathleen Verani
- Holly Le
- Bernhard Rischke
- Mohamad Atayi
- Adam Frimer
- Masoome Fazelian
- Andreas Rudolph
- Sebastian Herberger
- Jocelyn L
- RAHMAN SALMAN
- RISHABH CHAKRABARTY
- Augusto G
While waiting for the wave of Covid patients, Sebastian recognized that admitting symptomatic patients to the hospitals is inefficient and fills up capacities quickly, and unnecessarily. There had to be a better way to keep the not-so-heavy cases out of the hospital, but would you know they're ok? Welcome to the idea of hospital@home.
What it does
Vision statement: We slow the transmission and save the critical hospital resources by monitoring patients at home through hospital@home, a decentralized medical monitoring system.
During a pandemic crisis, such as the Covid-19 crisis it is vital to prevent a healthcare-system-meltdown.
- If not managed properly, the exponential growth of case numbers will overhelm the healthcare system, leading into the worst-case scenario of a “melt-down”.
- The first goal in the pandemic is to protect and and maximize the use of core healthcare assets, staff, beds and machines. The key strategy to implement this goal therefore has to be to keep Covid-19 cases out of hospitals for as long as possible, while making sure they`re safe.
Target Groups:The system is relevant for different target markets and user roles, such as public hospitals, or healthcare-system-responsible, and it enables them to securely monitor and support infected patients in homecare.
Needs:These are the most relevant needs that the system and the proof-of-concept is addressing:
- Robust system that can securely take care of patients with Covid-19 pneumonia for days, isolated and safe in their home environments, while being monitored for changes in vital signs and health status.
- Ability to securely monitor signs of deterioration in the group of patients at home by wearable monitoring, such as declining blood oxygen saturation (SpO2).
- Enable a central operator at hospital/ regional level to detect and react to these signs early enough, so that the patient at home can immediately be hospitalized, when in need.
- Enablement of data support for fact based management of healthcare infrastructure
- Full legal compliance for processing sensitive personnel data as by region of deployment and use (i.e. DSGVO)
Product:Key parts of the product concept are
- Open interface to wearable devices used locally including abilities to securely forward vital-sign-data into a central cloud infrastructure (i.e mobile app)
- Fault-tolerant stream processing of inbound datastreams within proven cloud infrastructure
- Features and processes that support the operator-in-duty to take educated decisions for hospitalization events for patients in need including implementation of these decisions.
- Features that support patient and operator communication.
- Features that support medical personnel to define and fine-tune the hospitalization decision.
- Analytics and features that support the management of the healthcare system.
Business Goals:Our product's proof of concept enables the following business goals:
Support the public good "preservation of human lives" during a pandemic
- Manage relevant parameters for over-utilization of hospitals
- Reduction of overall infection risk (decentralization of infected persons)
Enable a revenue perspective that supports ongoing implementation, operation and maintenance:
- Open source platform that is available globally
- Enablement of local or regional managed-cloud business cases
- Establish common and open platform for suppliers that work on interfacing solutions (i.e. sensors, emergency intervention services,….) including the ability to create business benefits.
- Cost optimization: Optimization of the scare, system-critical resource “hospital bed”, including related infrastructure of all kind.
Architecture and Design:The following characteristics describe the software architecture and the software design:
- Collection of data by means of a locally-deployed wearable monitor.
- Transmission of this health-related data by means of local desktop or mobile devices into a stream processing engine within a cloud based data-lake infrastructure. We base our proof-of-concept on the Google cloud platform, but from the technical perspective it is possible to use offerings from different cloud infrastructure providers as well.
- Stream processing by means of a pub-sub logic, including data-parsing and message processing, with data storage in SQL/NOSQL data warehouse
- The ingested and cleaned data is visualized in dashboards that are exposed as https services to the outside world (at current bokeh server)
- Users securely access data and dashboards by means of a identity-aware proxy
UI/UX:Using figma as a tool, we implemented mockups that demonstrate the interface design for these major building blocks and use cases:
- Mockup for the operator's dashboard
- Mockup of the patient app
Scroll through the assets above in the video section (graphical product, presentations, etc) and see the links further below to find more detailed information about the solution.
How we built it
For this hackathon, we started as a newly-founded global team of diverse qualifications and skills (healthcare, product management, backend-, and mobile-development, design, etc). We mostly did not know ourselves beforehand.
Starting from a common product vision, in an team effort, and using standard agile development methods, we
- Collected an initial set of user stories involving different roles (including users/ medical personnel).
- Ranked and evaluated the user stories including scoping of a minimum viable product.
- Mapped the user perspective to requirements and by this defined the feature scope of our product.
- Used the product concept to support downstream product development phases for UI/UX or software architecture.
- Implemented an initial set of software modules and created assets that cover identified and central requirements. These modules demonstrate the technical feasibility of important parts of the concept. Examples are features that demonstrate the data ingestion processes using big query.
- Implementated mockups for mobile patient apps and for the operator dashboards by UI/UX experts.
See the links further below to find more detailed information about our process and the deliverables.
Challenges we ran into
We did not face any substantial challenges.
Accomplishments that we are proud of
- As a newly established diverse and global team we almost instantly hit the road running.
- By means of different building blocks that integrate one into the other, we are able to show that it is realistically possible to implement the intended approach to monitor patients at home.
- Therefore it is secure to assume that a decentralized approach can be employed to help prevent meltdowns of health systems during an epidemic crisis.
What we learned
Experience and diversity is key
What's next for Hospital@Home
- Due to time restrictions, it was not possible to give each work package the depth of attention that a fully professional product concept would deserve. However it demonstrates the feasibility of the concept.
- Along the given lines, all deliverables need to be extended and further detailled-out (i.e user interviews with different roles and in a larger sample), once development activities on the scoped product reach the go-milestone, and decision.
- We are aware that the system processes highly sensitive personal information. Therefore the entire aspects of data security need to be detailed out and implemented (i.e. DGSVO) for example using thread modeling techniques.
- Due to the size of the solution, support by experienced technology providers might be of advantage in the realization phase.
You find further information about the working-results in the video section above and by following these links:
- Full project/ results documentation [Concepts, teams, etc. Link leads to an external site on atlassian.net]
- Prototype: Dashboard Design [Prototype of the dashboard for the operator. Link leads to an external site on figma.com]
- Patient App Prototype [Prototype of the App for the patient. Link leads to an external site on figma.com]
- Sourcecode of the different modules in our GitHub (official Try-out section)
Try It out