**6. Discussion**

The main challenges for wide adaptation of PGHD in clinical practice include usability and sustainable quality of results (i.e., patient motivation and adherence) [21, 37]. The presented system includes patient/clinician mobile applications, OHC FHIR server, and the MSN server. OHC FHIR server provides interoperability between all components. The framework provides several tools that can be used for ingestion, indexing, storage, integration, and surfacing of patient information. In this way, the PERSIST system represents an open digital integration hub that can deliver scale, speed, and flexibility to securely gain value through the integration of health systems. Further, the OHC enables innovation through near-real-time access to longitudinal patient records, where the APIs provide opportunities to flexibly design services that can seamlessly ingest discrete data from the source into a third-party application. The FHIR has also been recognized as an approach suitable for citizen developers, since it also supports "low-code/no-code" solutions [21]. Our future efforts will be directed toward transformation and ingestion of EHRs from existing IT platforms into FHIR ready server. Based on the studies, the main activities will involve the definition of an ontology that will correlate existing fields with specific FHIR resources. The information in existing EHRs is mostly stored as partially structured or unstructured text; therefore, a specific focus will be directed toward extracting information by using modern NLP techniques and data to concept mapping.

The other challenge relates to the patient's perspective and long-term sustainability and quality of collected information [36, 37]. Perceived complexity and trustworthiness represent also the main drivers of patient adherence [38]. Therefore, MSN delivers the necessary microservice infrastructure, where the services are distributed among the servers and can be replicated if needed. A fully articulated ECA was deployed for all six languages in order to implement more natural human-machine interaction, where the EVA realization framework transforms the co-verbal descriptions contained in EVA events into articulated movement generated by the expressive virtual entity. The EVA-Script language is actually applied onto the articulated 3D model EVA in the form of animated movement [43]. Trustworthiness is a clinical value, which has a significant impact on adherence mitigating pervasive threats to health [64]. The symmetric multimodal model for dialog systems enables the ECAs to deliver and to understand input/output modes, including speech, gestures, and

facial expressions. This makes the interfaces more familiar and trustworthy [38], where trustworthiness is one of the building blocks of patient compliance and responsiveness [65].

The RASA chatbot API is using PREMs and PROMs to see the patients' health status and the patients' perceptions of their experience while receiving treatment. In this case, we created several stories that contained probable conversations with patients. These are basically the intents that have to be executed, based on patient's responses [66]. Inclusion of multilingual ECAs have positive effect on patient adherence, as also several experiments imply. Further, ECAs contribute to long-term sustainability and familiarity [29] and decrease the complexity of user interfaces. Namely, having a virtual body that shows the nonverbal cues can provide easier understanding of the context, coherence for information exchange, and an increase for believability and trustworthiness to the virtual entity.

However, the phenomenon of "uncanny valley" may have significant negative impact on the overall user experience with articulated entities compared to "disembodied" agents as suggested in [67]. Thus, in the future, we will focus specifically on the synchronization issues of nonverbal behavior with speech.

### **7. Conclusions**

In this paper, a multilingual holistic approach toward sustainable collection of PGHD and PROs and their efficient integration into clinical workflow has been presented. Namely, the PGHD may contribute to personalized care and early identification related to psychological and physiological symptoms and negative health outcomes. The PERSIST system represents an opportunity to integrate the benefits and deliver them to the patients. The system consists of patient/clinician mobile applications, an OHC FHIR server, and a MSN server. The research and this study address several technologies from the prototype (proof-of-concept) perspective. The used technology was evaluated on modular basis, statistically, and on a short-termuse basis.

### **Acknowledgements**

This study is part of the project "PERSIST: Patient-centered survivorship care plan after cancer treatment" that has received funding from the European Union's Horizon 2020 research and innovation program (GA No. 875406). This work is partially financed by the HosmartAI project, funded by European Union's Horizon 2020 research and innovation programme under grant agreement No 101016834.

### **Conflict of interest**

The authors declare no conflict of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

*Multilingual Chatbots to Collect Patient-Reported Outcomes DOI: http://dx.doi.org/10.5772/intechopen.111865*
