The EAN Tool — User Experience Research Phase.

Role — UXR-HCI Specialist, Diagnostics Analyst

Year — 2019-2020

The EAN system UXR phase focused the ethnographic study on how well digital platforms serve patients in their needs of sharing their experiences, understanding their feelings as patients by putting on words what they and their relatives, friends and healthcare professionals are undertaking.

  • Goals — Define smooth and simple platform affordances towards a better interpersonal communication among patients. Generate the backstop epidiagnostic filter protocol for tracking speech keywords in conversational assessment. Design a distributed interrelational platform useful to multiple instances (hospitals) monitoring.
  • Challenges — Make patient-to-patient relationships easy to commit to. Delivering an empathetical, open, personal, warm and direct vis-à-vis experience. Realise HCI dynamics to design meetings as straightforward availabilities was very demanding.
  • Learnings — Big Data tracking of experiences, in this case via audio/conversational style, is meaningful to design better AI assisted diagnosers and nosographers through Natural Language Interpretation (NPI). With this research phase for The EAN Project we concluded that this clinical-technological progress can be achieved while beneficial for the therapeutical recovery of patients too. Make technology an interactive bridge among people.

Overview of the Project.

The EAN Project conforms a series of research studies on clinical ergonomics, patient assisted recovery and digital therapy initiated in Mars 2019, focused on UXR experimentation and the design of the EAN Tool, an intelligent platform that will help patients to upload follow-ups of their health status, and hold conversations with other patients participating in the project. By the tool, patients will be able to communicate among themselves and with their personal physicians, contributing to the research on clinical experiences in community hospitals.

The team is composed by physicians, UX researchers and ergonomists from Copenhagen (Denmark) and Madrid (Spain), in collaboration with the Kalavik Commons (Europe). This project is currently under development (beta goal for 2022).

More applications in different fields: education, banking, gamification, insurance companies, law buffets, video games, language learning, private sector human resources, etc. The important thing is the model, the system, the UXR of variables and the creation of markers (factors for the analysis) in an intelligent assistant that makes easier the contrast of data from the individual to the global banks of info (eg, the patient information environment contrasted with epidemiological nosographies). The important thing is the platform’s intelligent system, making the service an application of the interested audience niche.

Below — The EAN Tool conversation prototype sample

On the UX Research

The EAN Tool serves as an interactive, secure, bilateral, human support for the therapeutical process underpinning patients’s recovery. This way, the platform serves as an affective archive, that supports the therapeutical recovery and gives continuous opportunities for the patients to grow on personal emotional identifications and interpersonal communication strategies.

This technology covers two main goals. Regarding the person, the EAN Tool helps patients fulfil a therapeutical process on the distance, reaching significant others and strangers to talk, bring about and receive support from them, as well as it gives people the required amount of comfort and privacy, proper to Internet communication, for them to open up and express themselves to real people joining the experiment.

Regarding its scientific value, the EAN Tool underpins investigation by technical monitoring, helping researchers to analyse experimental results and interpret what individuals believe and say about their experiences and pathologies through contextualised conversations with actual people. Using an intelligent qualitative system, the platform reads collective (conversations) and individual (weekly voicelog) reports, tracking keywords and expressions within the patients’s speech that will help clinical ergonomists to better associate diseases with specific discourses.

Applications are immediate and multiple, for this work is aimed to be applied into general diagnostics, offering an interesting prognostic evaluation of the patient, and probabilistic values orienting physicians on further pathologies the patient might be suffering, not yet diagnosed, that however can appear attached to prior conditions (a co-pathology factor).

Further Details

EAN stands for a new type of strategy in experience-based diagnostic assessment: it materialises an intelligent platform acting as an Epidiagnostic Adaptive Nosographer, a software that works adapting the symptomatology of the patient, using the platform, to the possible pathologies present in our contemporary clinical knowledge.

Nosographies constitute the current texts, documents and reference material used for organising and classifying diseases. These patterns of general understanding on what and how humans are able to be diagnosed by physicians can be adapted epidemiologically, culturally, personally via new instruments implementing Artificial Intelligence in the assessment of experiences, text and qualitative analysis, and multifactorial interactive evaluators.

The EAN System, Experiments and Tool derived from the new lines of development presented by the PhD dissertation on neuropsychiatric assessment of experiences, defended and approved in 2019 at the ECyT National Institute at the University of Salamanca, entitled ‘Pain Assessment in 21st-Century Neuropsychiatry. Introducing Plural, Perspective, Situated Epistemic Frames for the Epidiagnostic Characterisation of Pain Experiences’.