Towards an Ontology-based Medication Conversational Agent for P r EP and PEP (2020)

Abstract: ABSTRACT: HIV (human immunodeficiency virus) can damage a human’s immune system and cause Acquired Immunodeficiency Syndrome (AIDS) which could lead to severe outcomes, including death. While HIV infections have decreased over the last decade, there is still a significant population where the infection permeates. PrEP and PEP are two proven preventive measures introduced that involve periodic dosage to stop the onset of HIV infection. However, the adherence rates for this medication is low in part due to the lack of information about the medication. There exist several communication barriers that prevent patient-provider communication from happening. In this work, we present our ontology-based method for automating the communication of this medication that can be deployed for live conversational agents for PrEP and PEP. This method facilitates a model of automated conversation between the machine and user can also answer relevant questions.

## introduction hiv can cause a dangerous infection that can lead to aids, a disease that can lead to severe immunological symptoms and eventual death. common modes of infection include sexual contact, blood transfusion, or the sharing of drug paraphernalia. while the rates have dropped over the last few decades, hiv infection is not uncommon. for example, there is an infection rate of 2 million globally @xcite and 39,782 within the united states @xcite . in addition, a segment of the american population with hiv are unaware of the hiv status (centers for disease @xcite , and therefore at risk of spreading the disease to other individuals. advances in medication introduced prep and pep. pep refers to the use of antiretroviral drugs for people who are hiv-negative after a single highrisk exposure to stop hiv infection, while prep is a prevention method for people who are hivnegative and have high risks of hiv infection. both of these treatments require consistent adherence to the dosage in order to be fully effective, but adherence is an issue for patients subscribed to it. providers in particular are concerned about the consistent adherence to @xcite @xcite . it has been reported that if prep adherence is high, rates of hiv infection will be sizeably reduced @xcite . however, adherence to prep is no different than other challenges with medications, such as the patient comprehending the administration of the medication and remembering to take it @xcite . on top of that, the centers for disease and control (cdc) specifically prescribes periodic counseling, and coordinating with patients on a one-on-one basis (centers for disease @xcite . but time burdens and manpower to conduct counseling pose another challenge @xcite . in a previous study, @xcite utilized an ontology-based method to model the dialogue for the counseling of the hpv vaccine. in this study, we tailor the method for prep and pep counseling with the intent that this could be employed in portable tools for drug users to use. a benefit of using an ontology approach, other than exploiting network-based model for dialogue, is the potential to link the ontology to representations of health behavior models (like the transtheoretical model). systems that leverage health behavior models, according to @xcite , have demonstrated to be more impactful on affecting health behaviors of users. also, an ontology that models dialogue can yield standardization and sharing. @xcite noted from their literature review on pubmed that there is limited ontology-centric studies for health-based dialogue management. @xcite simulation studies have also shown evidence that automated counseling, specifically conversational agents for vaccines, could impact the health attitudes and beliefs that can lead to improved uptake with perceived high usability. ontologies are artifacts that represent and encode domain knowledge for machines to understand a domain and their physical environment. according to one school of thought, if machines have symbolic understanding of their domain and environment, it could potentially provide nearautonomous operation of tasks. imbuing software with autonomous task of dialogue interaction requires some measure of intelligence. intelligent agents are defined as having reactive, proactive and social ability features @xcite . reactive refers to the software ability for timely response to the environment. proactive refers to the initiative driven aspect of the software to accomplish tasks, and social ability involves the software handling external interaction with the environment (virtual or physical). how these qualities manifest vary by the architectural approach (reactive agents, reasoning agents, etc.) which is beyond the scope of discussion. researchers mention the use of internal data models within the architecture of the agents @xcite . the models' role in the system is to provide the agent with decision making capabilities to perform autonomously in the environment. this would include 1) representing the domain knowledge for the agent, 2) providing information of the surrounding environment of the agent, and 3) cataloging the previous actions of the agent (e.g., for the agent to learn). according to hadzic and colleagues, these models could be manifested as a group of ontologies @xcite . furthermore, they state some inherit benefits such as producing shared communication models between agents and systems, information retrieval, organization of the agent's task, and analytical and reasoning of the knowledge @xcite . the ontology-based solution also attempts to solve some of the issues with reasoning agents like the transduction problem and the representation/reasoning problem @xcite . the transduction problem is how to translate the world or domain that the agent is embodied in into symbolic representations. the representation and reasoning problem pertains to the challenge of manipulating the symbolic representations and applying reasoning for the agent. with ontologies, we can model a domain space or the environment using predicate logic that is syntactically encoded into a machine-readable artifact. within the context of this work, this method maps utterances of the user and the machine to concepts represented in our ontological model. also, with the availability of reasoners, like pellet @xcite or hermit @xcite , we can perform reasoning based on the encoded model to generate inferred dialogue context information. from a natural language processing (nlp) standpoint, dialogue is essentially a sequence of utterances between multiple agents. our work utilizes a finite state transition network to model the dialogue @xcite , and then encodes this sequence model of the utterances within the ontology. we also employ some lightweight nlp methods to help the agent discern participant utterances, alongside with the reasoning capacities of the agent. for the design of the dialogue system, we utilize a deterministic and planned approach to automate the counseling versus a generative approach in order to cover certain main points to communicate to the drug user. this gives us the control needed to ensure the conversational agent delivers the appropriate counseling. the dialogue will center around a closed world domain -specific to only prep and pep, and hiv infection. the following sections will cover the development of the conversational agent and discussion through results of a trindi tick assessment for dialogue system evaluation and future steps with our work. ## discussion the apparent limitations of the system is highlighted by criterion 3.1, 3.6, and 3.7. the limitation with respect to context is primarily due to lack of a mechanism to handle personalized information. one of the benefits of using ontologies demonstrated by health researchers was the potential to tailor information if we were to capture user information @xcite . previous studies have demonstrated the use of user context ontologies to reason with user data. we assume that this component could be integrated to support personalized contextual information based on group identification or past previous behavior of the user. another limitation is the negatively specified information, where if a user were to ask "what if i do not have insurance to pay for prep?" technically the system would not analyze the negative token "not" and focus on the more salient entities of the response. however, a response can be generated by the system, but whether it would accurately respond to the question is unknown, and is determined by the scope of the ontology. in regards to dealing with no answer, the system awaits for the response of the participant. the reasonable solution is to implement a software code subroutine either on the dialogue system level or on the interface level that times out whenever the user does not provide a timely response. nonetheless, exploring how this can be done on the ontologylevel would need to be investigated and engineered into the ontology. other aspects highlighted by our preliminary trindi tick assessment underline adherence to criteria regarding handling indistinguishable responses, sub-dialogue branches, and the quality and quantity of information. also, the quality of the system responsiveness, we theorize, would be dependent on the scope of the knowledge encoded in the ontology. ## conclusion in this paper we present our ontology-based system for handling dialogue for prep and pep counseling. this system also handles questions that are queried from a knowledge base, called the ontology of prep and pep (opp). overall the objective of this work is to demonstrate the feasibility of using an ontology-driven approach to manage automated counseling for prep and pep through a computerbased agent. figure 6 shows overall deployment on how the engine will interface with external natural language clients whether they are mobile or terminals (desktops or kiosks). our eventual goal is to develop a deterministic, planned-based approach within the domain of prep and pep medication adherence (closed domain) and test our approach with live participants. previous research @xcite has found limited use of ontologies for medical-based dialogue agents. solutions addressing prep or pep adherence that researchers have examined include social networks @xcite and telehealth solutions @xcite @xcite . with the former, there has not been any evidence that shows that social networks can address adherence or awareness @xcite , and with the latter, telehealth solutions are limited to the availability of a professional and may not be cost effective @xcite . having an automated agent that can provide real-time and high availability to counsel and inform patients may offer an alternative, but further research is needed to foresee this possibility. limitations and future direction the ontologies that drive the system are currently in draft format and additional work is needed to expand them to include more personalized content, such as where prep and pep can be obtained and information for nonprofit organizations that can provide support, etc. researchers have conducted simulations to fine tune a formal plan to counsel individuals on the hpv vaccine. our future work would need to model standard practices for medication counseling adherence that typically happen between patients and providers. this would include conducting simulation studies and working with providers to develop, and then model the counseling flow using the phido framework. also, from the sample dialogue of the simulation, we can parse out potential questions that can be used to test the question answering component. lastly, the demonstration of our work is based on text-based modality, and we are working towards interfacing the system to a voice interface to capture the user utterances and evoke the utterance of the machine.