Doctrin – Best Use of Digital Health FINALIST – 2018
Doctrin is a digital health company which creates solutions to streamline and digitalise the patient journey.
The system asks patients to answer a survey of symptoms and medical history which is passed onto the caregiver to speed up decision making in triage, consultations and follow-ups. It is currently being rolled out in Capio’s 83 primary care centres. Doctrin claims that the increased efficiency has increased availability of treatment with doctors able to see twice as many patients per day, rising from 25 to 50.
Briefly describe the organisation giving number of facilities, staff, revenue numbers.
Doctrin wants to radically change health care through intelligently digitalising the patient journey. Founded 2016, HQ in Stockholm, 36 employees, 2016 revenue in USD 29 000, 2017 revenue in USD 610 000, 2018 estimated revenue USD 2.5 million.
What is the nature of the service in which the organisation is using digital health?
Doctrin’s purpose is to radically change health care through intelligently digitalising the patient journey. We help caregivers improve medical quality while giving the patient a better experience and making sure health care resources are used more efficiently. With a medical team of physicians, we are one of few platform companies which combine digital solutions with medical content.
Video is convenient for the patient, but it doesn’t save time for the physician and does not improve medical quality. We look at each step of the patient journey to evaluate what is the best means of interaction. Automatic, asynchronous (chat based) or a face to face meeting when that’s required.
Before the first care contact the patient fill in their symptoms and medical history (anamnesis) through their mobile phone or other device. The system consists of more than 100 000 questions and have a dynamic component which means patients only answers questions relevant for their condition i.e. the answers they provide. The health care personnel receive a structured report of the patient’s medical history enabling them to spend their time more efficiently. The report is used to make medical assessments in triage, consultations as well as follow ups. With an intelligent triage (prioritising tool) the health care personnel can guide the patient to appropriate health care level. Making sure patients who need care the most get it first.
A roll-out is underway in health care provider Capio’s 83 primary care centres, which means 750 000 listed patients will be able to use our platform by the end of 2018. We also have several public and private health care providers who have started pilots with us in Q1.
What is the nature of the digital health offering? Please describe the main IP component of this service.
Doctrin Flow is based on a polygot environment, largely built on a microservice architecture. Hidden behind cloud flare, for extra security, the system consists of many different technologies and packages. The frontend is served by a React/Redux layer, communicating through a Seneca mesh to the microservice layer. The microservices are built in Node.js which utilizes Hapi.js for the REST endpoints. Load balancing is performed by different layers of NGINX implementation.
In the backend layer, in addition to the Node.js microservices, some functionality/business rules (mainly transaction intensive) is driven by .NET/C# running in a high performance, in-memory fully ACID compliant OODB and application framework called Starcounter. This framework is aimed at transactional data, whilst documents and similar data (pictures, files, anamnesis reports, white labling etc) is stored in a MongoDB cluster.
To orchestrate the Node.js services, we utilize docker for a simpler, and more efficient, deployment, and kubernetes to orchestrate the components.
The hardware is split between unix (mainly Ubuntu) for the Node.js services, and windows for .NET/C# based applications, and most service and client communication is through REST and Websockets.
To summarize, we make sure our technology fulfil all of the special requirements that exist within the health care industry, in addition to making sure it’s scalable and configurable as well as being pragmatic; using the most suitable technology available to solve the problem.
When did the organisation start delivering this service en masse?
- Month : Dec
- Year : 2016
What are the main key performance indicators? How does the organisation measure the success of the project?
Results have been successful with KPIs including the following:
– Current roll-out underway; 750 000 patients in 83 primary care centres will access the plattform by the end of 2018 (in a country with 10 million habitants).
– 98% patient satisfaction
– 97% of patients would recommend the platform
– 67% less antibiotics prescriptions compared with the average primary care unit
– Enables increased availability (patient consultations performed everyday 8 a.m.-10 p.m. Mon-Thurs and 8 a.m. to 5 p.m. Fri-Sat)
– Twice as many visits per doctor and day (50) compared with the average emergency (25)
How has the digital health enabled service impacted on patient/care recipient outcomes?
Instead of creating a health care system around the hospital or GP center we build it focusing on the patient, creating a patient journey where they seamlessly go from digital to physical health care. The digital and physical formats aren’t mutually exclusive but rather complementary. When integrating digital tools in the existing health care system we can truly use the potential of technology.
– From a patient perspective this means increased availability and a positive patient experience where you get immediate help (98% patient satisfaction, 97% of patients would recommend the platform).
– From a HCP and health care provider perspective this means full transparency enabling continuous quality evaluation of medical consultations and follow up with patients who aren’t satisfied in addition to making sure doctors follow medical guidelines.
– The standardised data (from automatic anamnesis and written text in the chat based system) opens possibilities to use machine learning and AI for more customized health care and quality development.
The atomisation saves both patients and HCP time since the digital or physical consultation can be spent on actual care rather than gathering medical history.