# Instance-Based Learning Following Physician Reasoning for Assistance during Medical Consultation
## 5 Medical Consultation Flows
### Selecting an Already Defined Case Type
### Interoperability of Health Information

Health terminological standards were taken into account due to the relevance of the interoperability of information in the Medical Informatics area. In particular, the national drug dictionary of Uruguay and a terminology server provided by the Hospital Italiano de Buenos Aires (HIBA) were integrated into the proposed approach. #### 7.5.1 Integrating the National Drug Dictionary of Uruguay

A National Drug Dictionary (DNMA) is defined by _Salud.uy_ in order to standardize the information and vocabulary for clinical and logistical use applied to pharmaceutical and related products. DNMA acts as a standard of drug reference terminology for the network of healthcare service providers in Uruguay. Access permissions were requested from the DNMA in order to import the national dictionary of medicines into the proposed approach. Importing the national drug dictionary helped build a functional model, in which physicians can make pharmacological indications using a wide range of drugs. #### 7.5.2 Using the Terminology Server of Hospital Italiano de Buenos Aires

A terminology server allows linking the free text entered by a physician in a medical record to different health classifications, such as ICD9-CM, ICD10, or LOINC [4]. The use of a terminology server allows clinical information to be recorded in a structured form, using clinical terminology standards. Terminology standards enable interoperability of clinical information, and also allow information to be re-used for other purposes, such as clinical decision support, data analysis, and research. The proposed system is able to use the terminology server supported by HIBA. The terminology server publishes its terminological terms grouped in different domains. This work has been successful in using terminology services for the domains that cover: reasons for consultation, diagnoses, procedures, and studies, which are required for the Uruguayan medical records model. ## 8 Discussion

The experimental evaluation of the proposed instance-based learning method focused on the practical aspect of the research. Thus, the evaluation was performed on a real use scenario, where the proposed approach demonstrated advantages over the original implementation of Praxis. Additionally, results were better in terms of writing times when using a pre-loaded CKB, containing typical workday clinical scenarios. Regarding the usability of the proposed system, a survey performed on a group of advanced medical students showed a high rate of approval. The implemented prototype was highlighted as an appropriate tool for medical practice and useful at medical consultations. Furthermore, and despite the lazy nature of the proposed method, the results showed that the learning approach was able to produce suggestions in reasonable execution times, even when dealing with large volumes of data. Specific strategies can be applied to reduce uncertainties, including using expert knowledge to design and generate useful realistic instances for learning, and expanding

Figure 9: Best features of the proposed approach, according to the survey performed on students. the similarity metrics considered for the comparison of clinical information. In this regard, a recommendation for the practical aspect of the research is gathering and organizing as much information as possible about clinical practice in a systematic way, in order to help the automatic system to expand its base of knowledge to generate more accurate suggestions. In turn, a physician should be properly trained to register all the relevant data for the proposed learning-based system, without omitting any important information. In this context, the main research lines for future work are related to evaluate the proposed system in a professional work environment of healthcare attention, with the aim of improving the accuracy of the learning method based on professional feedback. Thus, a future work line includes studying the proposed approach with the help of professional physicians.