About
Problem
In order to optimize healthcare, patient – doctor mutual understanding is crucial. Especially for older patients, focus on overall wellbeing will often influence treatment decisions. In a process of shared decision making (SDM) health professionals and patients communicate together in order to share their views about priorities, preferences, needs and wants. This leads to decisions that support the personal preferences and goals of a patient. Despite proven benefits of SDM in healthcare, it isn’t daily practice yet. Doctors can be trained in SDM – but patients should also practise expressing their needs.
Urgency
Improved patient-doctor communication leads to improved shared decision making and more cost-efficient and effective healthcare. Based on an experiment focusing on improving patient-doctor communication in the US, readmissions to hospitals dropped by almost 10%. In the end we expect to save billions of euros in Europe.
Aims
In order to enhance shared decision-making and to contribute to more effective healthcare, PrepDOC aimed to develop an application to prepare older people for conversations with healthcare professionals.
How
We have created dialogue scenarios in co-creation with older people and healthcare professionals, in which older people can repeatedly practice medical consultations and assess their communication skills. Please see an overview and a demo of the product below.
Product
Within the dialogue scenarios the player can interact with a virtual character. The choices of the player induce specific reactions of the character: emotional expressions, body movement and (spoken) text statements. The effectiveness of the communication strategy of the player is registered and afterwards results and feedback are provided. The dialogue scenario adapts to the player’s skills and knowledge and presents next steps for personalized communication skills training.
Partners
Utrecht University led the project. We contributed software technology for training and combined the various software components of our partners for the product. We performed and supported the product experiments and user tests, analysed results and disseminated our research.
DialogueTrainer was the business partner for the project. We contributed expertise about communication skills training, scenario development and scenario implementation. In co-creation with Vilans and older patients, we developed the dialogue scenarios for PrepDOC. In addition we performed market research and delivered the market projection for the PrepDOC product.
The School of Informatics at University of Edinburgh led the text analysis and integration work in PrepDOC. Our team was made up of experts in natural language processing and our main task was to match user utterances to sentences in dialogue scenarios with the aim to guide older patients through conversation with their healthcare professionals.
Vilans is the Dutch National Centre of Expertise in Long-Term Care. We contributed expertise about shared decision making with older adults. In co-creation with DialogueTrainer, we organized meetings with older adults to test the prototypes for PrepDOC with the end users. In addition we contributed to stakeholder research, e.g. insurers, to explore where the PrepDOC product should be launched.
University Politehnica of Bucharest has expertise in Natural Language Processing (NLP) techniques and was responsible for delivering a customized open-source NLP framework in Dutch and English that identifies the best matches in terms of semantic similarity between typed text or speech transcripts and pre-scripted sentences from the dialogue scenarios.
Funding
We received funding from EIT Digital within the Digital Wellbeing Action Line. The Digital Wellbeing Action Line leverages digital technologies to help people stay healthy with prevention and early detection or cope with an existing chronic condition. It includes both physical and mental wellbeing. The solutions generally rely on enabling consumers to be well-informed about their wellbeing, change their behaviour and use digital unobtrusive instrumentation to monitor and improve their quality of life, saving on high healthcare costs later in life.
