The section comprises many sub-sections, organized as follows:

The HIN project

The II generation Longitudinal–Electronic Health Record • Ricci, F.L.; Gaddi, A.V.; Rossi-Mori, A.; Russo, G. (a cura di). Verso il fascicolo sanitario elettronico (elementi di riflessione). Ra edizioni, ISBN 978-88-98929-00-9, 2014.

• Serbanati, L.D.; Ricci, F.L.; Mercurio, G.; Vasilateanu, A. Steps towards a digital health ecosystem, Journal of Biomedical Informatics, Volume 44, Issue 4, August., 2011.
(see the LUMIR Contenti, M.; Mercurio, G.; Ricci ,F.L.; Serbanati , LuMiR: The region-wide EHR-S in Basilicata. in C. Safran, S. Reti, H.F. Marin (eds.), Studies in Health Technology and Informatics 160, MEDINFO 2010 (Rank B) - Proceedings of the 13th World Congress on Medical Informatics, pp. 327-331, ISBN: 978-1-60750-587-7, DOI 10.3233/978-1-60750-588-4-327, IOS Press, 2010. system as a prototype experience) describes the health status of a citizen as a set of health issues, each of which is related to a set of electronic clinical documents. This approach would allow the generation of clinical cases as a basis for teaching, in accordance with the Case-Based Learning (CBL) Jin J., Bridges S.M. Educational technologies in problem-based learning in health sciences education: a systematic review. Journal of medical internet research 16(12,:e251), 1-13, doi:10.2196/jmir.3240 , 2014. approach, starting from an evolution–operating recursive function.

As this type of EHR does not exist yet, the attention turned to General Practitioners’ Electronic Medical Records (GPs’ EMRs), thus providing the initial impulse towards the HIN project.

The reasoning about time

Current medical professional competence involves making a diagnosis and choosing therapy as a response to the patient's condition.

Clinical reasoning is based on different cognitive systems: intuitive Intuitive: experience–based system that often leads to rapid, not well–informed, and recognition–based decisions and analytical. Analytical: decisions are taken after a deliberative, rational, information–based, and hypothetical–deductive process The outcome of reasoning is a diagnosis, that is the act of classifying the patient's condition within a nosographic class (disease). This process is generally aimed at defining a single, mostly acute or new-onset disease condition.

The increase in life expectancy and incidence of chronic diseases and disability conditions (epidemiologic transition) means that physicians nowadays are called to provide healthcare to patients with multiple chronic conditions, and likely affected by concomitant acute conditions, too.

Under these circumstances, the diagnosis is often more easily recognizable, still the physician needs to foresee and handle the evolution of the patient's overall condition over time.

Notwithstanding, current models of medical reasoning do not take enough into account the concept of time.

The four models

The HIN project features four specific models that emerge from the intersection of two main directions:

  • one direction highlights the distinction between the evolution of health issues for a generic patient, and for a real/realistic case;
  • another direction accounts for the Petri Nets’)-based formal robustness on the one hand, and on teacher’s and learner’s (end user’s) related usability on the other hand.


Each of the four models features:

  • a graphical scheme (graph or diagram) that formally / graphically represents the evolution of the clinical problem;
  • a sheet for each clinical problem (HI / Health Issue) that describes HIs’ characteristics (e.g. clinical information, therapies, etc.);
  • a sheet for each evolution that provides specific information about the evolution from one HI to another (e.g. the clinical parameters related to the evolution).

The fHINscene software is based on the f-HINe model

Model formalization

The formalisation in the HIN project is based on “place/transition” Petri Nets that feature Health Issues as place nodes, and evolutions as transition nodes; further, the Petri Net has a k-limited marking (k=1) for what concerns the HI places (safe net), and evolutions can only be fired once.

The characteristics of Petri Nets match with the properties of the evolutionary path of a subject’s health status


Evolution of a patient’s health status Petri Nets
Health issue Place
Evolution Transition
Evolution path of a Health issue Firing sequence
Health status Marking
Clinical history Reachability graph


Two are the models based on the Petri Nets:

  • The HIN model is the tool to formalise the description of an HI’s evolutionary path, for a generic person. HI nodes are graphically represented as circles.
  • The HINe model is the tool to formalise the description of an HI’s evolutionary path, for a real patient. HI nodes are graphically represented as squares/rectangles.


Petri Nets are useful for:

  • generate the suitable query to extract clinical cases (timely anonymised according to the norms) from General Practitioners’ Electronic Medical Records, in line with the learning objectives.
  • check the complexity of the extracted clinical exercise.
  • generate exercises related to the clinical cases extracted from GPs’ EMRs.
  • compare two HIN graphs and then measure their mutual distance.

A more detailed discussion about the formalisation of the HIN project is available here.

The end user models

The models of the HIN project are relatable to several use cases : each model needs in fact to address specific requirements to meet the peculiarities of each single scenario.

A general starting point for the generation of a real or realistic case study is the extraction of clinical cases from Electronic Medical Records. The description of an ideal clinical case to set up a didactic objective, needs to address specific features (e.g., several alternatives may be taken into account to increase the number of cases to be selected)

Some of these features may not be included in the description of the real case (an already occurred clinical case has no alternatives), nor other may be added (e.g., a clinical problem is only generated in one specific way)

  • The f-HIN model is the user-friendly tool the teacher uses to describe the evolutionary path of an HI related to a generic person. Under the mathematical perspective, it is equivalent to the formal HIN model. The sheets related to HIs and evolutions are the same as those in the HIN model. The HI nodes are represented as circles.
  • The f-HINe model is the user-friendly tool the teaching physician uses for the description of the evolutionary pathway of an HI related to a real patient. It shares the same mathematical properties as the formal HINe model. The sheets related to HIs and evolutions are the same as those in the f-HIN model. The HI nodes are represented as squares/rectangles. This model is more extensively described in the f-HINe model section.

The evaluation

In the first phases of the HIN project, it was not clear yet how to model a patient's medical history in terms of relationships between health problems during time. Therefore, the HIN project needed to rely on a valid paradigm for research and innovation based on: (i) a multidisciplinary and user-centric approach; (ii) a community-driven innovation path immersed in real-life environments; and (iii) a continuous verification with users.

In order for the HIN project to develop within an actual education/training environment, more suitable to teachers’ and learners’ needs, a Living Lab Although a specific definition of Living Lab is currently missing, the pursued approach recalls the definition provided from the ENoLL network, according to which a Living Lab is “an open–innovation, real–life setting, where innovation is driven by end users, and integrated in the process of new services, products, and social infrastructures co–creation –based approach was set up and pursued. Such approach involves active participation, continuous verification, and open innovation; further, users and stakeholders are the main foci for each phase of the process.

In particular, the previously introduced f-HINe model has been tested several times by several users in a number of real-life use cases. To this regard, valuable contributions in the testing and verification steps for both the HIN approach and the fHINscene software , have been provided from:

  • The Italian Society of Medical Pedagogy (SIPeM) – a special workshop was set up during the IX SIPeM National Congress, held in Naples (Italy) in 2018.
  • PhD candidates and undergraduate students from the "Sapienza" University of Rome – the f-HINe model is being adopted in some classes of the Degree in Medicine and Surgery, from 2019.
  • Researchers and professors from the "Federico II" University of Naples – a research project was developed, encompassing the Departments of Public Health, and of Veterinary Medicine and Animal Productions, to implement the f-HINe model to the whole range of medical sciences (both human and veterinary).


The use cases

A complex use case concerns the design and realization of actual cases as starting point for Case-Based Learning (CBL) Jin J., Bridges S.M. Educational technologies in problem-based learning in health sciences education: a systematic review. Journal of medical internet research 16(12:e251), 1-13, doi:10.2196/jmir.3240 , 2014. simulations.

It therefore comprises: the extraction of (anonimyzed) clinical cases from Electronic Medical Records, and the generation and management of realistic clinical cases as the core of the Learning system. This involves the modeling of the evolution of a patient’s health status during time.

Such use cases can be both performed manually, or semi–automatically, as showed in the following figure.

The learners log into the Learning Management System (LMS) and make practice with the exercises created by the teacher, and based on the real cases originally chosen. Students then interact with the f-HINe formalism, by adding or labelling HIs and evolutions. An automatic evaluation of learners' performances is then conducted by comparing their f-HINe diagram ) with the solution elaborated from the teacher.
The doctor teacher chooses the clinical case from the (anonymized) ones extracted from the EMR, by comparing the f-HIN diagram of the learning objective with the f-HINe diagram of the extracted clinical case. The latter is endowed with e.g., guidelines, references from the scientific literature, etc., and then stored.
The doctor teacher defines the clinical learning objective by drawing the f-HIN diagram with the main Health Issues and the existing evolutions between them.

The extraction of clinical cases

The extraction of a clinical case from a Problem–Oriented Medical Record (POMR) is based on the following steps:

  1. The f-HIN diagram of the ideal clinical history, objective of the selection, is drawn.
  2. All the possible evolutionary paths are analysed thanks to the analysis of the Petri Net underlying the equivalent HIN graph.
  3. Once the evolutionary paths have been chosen, the query is generated and launched on the POMR.
  4. The query will likely result in several (anonimyzed) cases, from which one will be chosen to be compared with the didactic objective: this will translate in a comparison between the HIN graph of the objective, with the HINe graph of the real clinical case.
  5. The main selection criterion in the previous step is the distance between the didactic objective (with its specific features), and the clinical case (with its peculiarities).


Browsing in a clinical case

In each clinical case, described as a health issue network, the complete semantics of the various problems identified by the GP, along with their evolution in time, is provided. This relates therefore to: causality or succession links, sequences of clinical reasoning, including generation of hypotheses and choices rationales.
The clinical history denotates the episode of care, to be intended as a (temporally ordered) list of the contacts the patient has with the services provided by the Healthcare System: episode of care and clinical history are in fact two alternative ways to refer to the same care process.

The fHINscene software

The fHINscene software manages clinical histories represented by means of the f-HINe model.

The software was developed via the QT cross-platform application framework and is based on the Qt Toolkit’s DiagramScene sample.

The software features two main functions:

  • Editor: it assists teachers and students in creating a new f-HINe diagram, whilst diagrams’ accuracy check is only allowed to teachers.
  • Comparator: it assists teachers in comparing two f-HINe diagrams for educational purposes, by making the analysis of all f-HINe diagrams created by the students easier.

Another functionality, currently under development, is related to the creation of a working environment for the development and deployment of f-HINe model–based exercises.

The student version of the fHINscene software (limited to the sole Editor function for the design of f-HINe diagrams) is available for all registered users.

Professors/Researchers interested to the full version of the fHINscene software can contact us here.

The “Federico” project

The Federico II University of Naples has launched in 2020 the initiative “Federico: projects for educational innovation“: in the first edition the project entitled HIN (Health Issue Network): Innovation of the Case-Based Learning Case-Based Learning (CBL) is a conceptual model that drives the instructional design. It makes use of "cases" instead of “contents”, as teaching resources. In other words, disciplinary "contents", concepts, and theories are introduced through cases that operationalize them. The purpose of this approach is to make the learning and the understanding of the "contents" of the didactic activity easier, for both undergraduate and post–graduate learners. approach for the analysis of the evolution of real/realistic clinical cases in teaching Medical and Veterinary Sciences was funded.

The project targets both university professors/researchers, also directly involved in clinical practice, introducing an innovative approach to improve the CBL methodology for health sciences education purposes. It also describes an innovative tool to query POMRs.

The overall goal of the project is to improve the clinical teaching of the Medical and Veterinary Sciences classes, thus improving the alignment with specific training needs, while pursuing a One Health The One Health holistic vision means a health care model based on the as ancient as new idea of integration between different disciplines. It is based on the recognition that human health, animal health, and ecosystem health are inextricably linked.
Such model is officially recognized by the Italian Ministry of Health, the European Commission and all international organizations as a relevant strategy in all those fields that benefit from the collaboration between different disciplines (e.g., doctors, veterinarians, environmentalists, economists, sociologists, etc.).
The One Health approach is called to be a key player to achieving global health, as it addresses the needs of the most vulnerable populations, accounting for the whole broad spectrum of the extant intimate relationship between their health, the health of their animals, and the environment they live in.
–like perspective.