Unit NURSING BASED ON EFFICACY TRIALS

BIOENGINEERING AND MEDICAL INFORMATICS

Code	50696901
Location	PERUGIA
CFU	1
Teacher	Emilia Nunzi
Teachers	Emilia Nunzi
Hours	15 ore - Emilia Nunzi
Learning activities	Altro
Area	Altre attività quali l'informatica, attività seminariali ecc.
Sector	INFO-01/A
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	Introduction to metagenomics and consultation of sequencing data analyses (8 hours) • Introduction to metagenomics and characterisation of the human microbiome by 16S rRNA sequencing. • The human microbiome: role in health, disease and precision medicine applications. • Microbial diversity analysis (alpha and beta diversity). • Compositional taxonomic analysis. • Functional inference of the microbiome using PICRUSt2 and integrated interpretation of omics data. • Multivariate and association analyses applied to the microbiome. • Machine learning for microbiome-based sample classification. • Data management, analysis and consultation using informatics tools, cloud platforms and health information systems for digital health; principles of information retrieval and visualisation of omic data. • A case study: the ECAM project (Early Childhood Antibiotics and the Microbiome) (Bokulich et al. 2016, https://www.science.org/doi/10.1126/scitranslmed.aad7121). Consultation and interpretation of results obtained through the ETAG platform in the context of microbiome sequencing data analysis. Introduction to Biomedical Technologies (parts I and II) (7 hours) • Biomedical measurements: modelling of the measurement process, principles of metrology, uncertainty analysis, accuracy, precision, sensitivity and specificity; metrological quality of clinical data and measurement traceability. • Modelling and characterisation of biomedical sensors; data acquisition, processing, interpretation and representation of measurement data and information; monitoring and clinical diagnostics. • Critical evaluation of the reliability of measurements and information produced by biomedical devices. • General characteristics of biomedical equipment. • Safety and risk in the use of biomedical equipment. • Electrical safety of biomedical equipment. • Medical premises. • Electrocardiograph: acquisition, digitalisation and interpretation of biomedical signals. • Spatial signals: bioimaging. • Ultrasound. The sequencing data of the entire ECAM project are available on the ETAG 4Students platform.
Reference texts	Course notes prepared by the lecturer. Recommended reading: Shortliffe, E.H.; Cimino, J.J. (eds.). Biomedical Informatics: Computer Applications in Health Care and Biomedicine. Springer, 2014. Webster, J. Medical Instrumentation: Application and Design, 2009. Christe, B. Introduction to Biomedical Instrumentation. The Technology of Patient Care. 2009. Holton, T. Digital Signal Processing. Principles and Applications. 2009. Rossi, R.J. Applied Biostatistics for the Health Sciences. John Wiley & Sons, 2022. Izard, J.; Rivera, M. (eds.). Metagenomics for Microbiology. Academic Press, 2014.
Educational objectives	The objectives of the module are: to understand the role of biomedical technologies, health information systems, and digital platforms in supporting healthcare activities, patient monitoring, care safety, and evidence-based nursing; to acquire basic knowledge of computer systems, health information systems and digital tools used for the management, analysis and visualisation of biomedical information; to understand the fundamental principles of measurement science in the biomedical field, including modelling of the measurement process, uncertainty analysis, metrological quality, traceability and safety of biomedical equipment; to acquire basic knowledge of bioinformatics applied to the study of the human microbiome using 16S sequencing data, including machine learning methods for sample classification; to understand the structure of a bioinformatic workflow for omic data analysis, from biological data acquisition to taxonomic and functional interpretation using computational tools. The main skills (ability to apply acquired knowledge) will be: to recognise the main sources of clinical and biomedical data used in care practice and to critically assess their quality, reliability and relevance; to critically evaluate the metrological characteristics of quality, accuracy, precision and uncertainty of measurements obtained from biomedical sensors, devices and systems; to use and interpret information produced by biomedical applications and instruments in care settings; to consult, interpret, and critically evaluate sequencing data and the results of taxonomic, functional, and statistical analyses of the microbiome using dedicated IT tools; to formulate pertinent queries to generative artificial intelligence systems relating to the module contents, critically evaluating the responses obtained on the basis of acquired knowledge.
Prerequisites	The competencies and experience acquired in the first year are sufficient to follow the module: all necessary elements and support materials will be provided during the course. Since the module deals with tools and methodologies for the analysis and presentation of biomedical data, a basic familiarity with computer use and web navigation is helpful. The module is part of the integrated course pathway, drawing on and applying concepts addressed in the Epidemiology, Health Statistics and Evidence-Based Nursing modules. The proposed activities are self-contained and do not require specialist prior knowledge beyond that normally acquired in the first year of study. The epidemiological principles, methods for critical appraisal of the scientific literature and quantitative analysis tools covered in the parallel modules find in this module a concrete context of application on real data, fostering an integrated and mutually reinforcing understanding of the course contents.
Teaching methods	Lectures, supported by guided examples of conscious and critical use of generative artificial intelligence tools to support the study and analysis of the module contents, in the context of digital transformation applied to healthcare. Structured prompt examples will be provided for querying AI systems in relation to the course contents: assessment of measurement uncertainty in the reading of clinical instrumental data, determination of significant figures to be recorded in the clinical chart, interpretation of taxonomic and functional analyses of the microbiome. The didactic approach is grounded in the principles of human-computer interaction, with the aim of equipping students with the conceptual tools to query computer systems and artificial intelligence platforms in a pertinent and critical manner, building on a solid understanding of the disciplinary contents.
Other information	The module adopts an applicative and computational approach that is transversal to the integrated course. The principles of study design and population analysis (Epidemiology) are recalled in the analysis of the ECAM case study. The criteria of quality and reliability of clinical data, central to Health Statistics and Evidence-Based Nursing, are addressed from a metrological and bioinformatic perspective: from the assessment of measurement uncertainty in biomedical devices to the critical interpretation of taxonomic and functional microbiome analyses. The use of the ETAG 4Students platform provides a concrete example of a digital tool for the management and consultation of complex biomedical data, consistent with the digital competency profiles expected of nurses in modern healthcare. The guided use of generative artificial intelligence tools is aimed at developing students' ability to query such systems and critically evaluate the information they produce.
Learning verification modality	Oral examination covering the entire course programme. To ensure homogeneity in the assessment format across the modules of the integrated course, oral questions will be delivered as multiple-choice quizzes. Assessment of multiple-choice questions: The module carries a weight of 1 CFU out of a total of 5 CFU (6 points out of 30). Questions will be distributed between the two parts of the course in proportion to the hours delivered: — Biomedical technologies: 50% (e.g. 3 questions out of 6) — Metagenomics on ETAG: 50% (e.g. 3 questions out of 6)
Extended program	Introduction to metagenomics and consultation of sequencing data analyses (8 hours) The human microbiome: role in health, disease and precision medicine applications Introduction to metagenomics (16S sequencing) Microbial diversity analysis of samples (alpha and beta diversity) Compositional taxonomic analysis Multivariate and association analyses applied to the microbiome Machine learning for microbiome-based sample classification Data analysis using informatics tools Functional inference of the microbiome using PICRUSt2 and integrated interpretation of omic data A case study: the ECAM project (Early Childhood Antibiotics and the Microbiome) (Bokulich et al. 2016, https://www.science.org/doi/10.1126/scitranslmed.aad7121) on the ETAG 4Students platform Introduction to Biomedical Technologies (parts I and II) (7 hours) Biomedical measurements: principles of metrology, uncertainty analysis and metrological quality of clinical data General characteristics of biomedical equipment Modelling and characterisation of biomedical sensors; data acquisition, processing, interpretation and representation of measurement data and information; monitoring and clinical diagnostics Safety and risk in the use of biomedical equipment Electrical safety of biomedical equipment Medical premises Electrocardiograph Spatial signals: bioimaging Ultrasound Sequencing data and analysis results from the ECAM project, obtained through the ETAG platform, are made available to students for educational purposes. ETAG (Enhanced distributed platform for digital Treatment of Advanced Genomics big-data and analyses) is an open-source bioinformatic platform for the analysis of genomic and metagenomic data at high throughput, designed and developed by the Bio-DataScience group at the University of Perugia. A dedicated configuration, ETAG 4Student, has been developed for the educational needs of the Nursing degree programme, aimed at providing access to data and results derived from real microbiome studies. In this module, sequencing data and analysis results obtained through ETAG on the ECAM project will be used. Students will consult and interpret taxonomic, statistical and functional results derived from microbiome analysis, acquiring basic competencies in the management and interpretation of complex biomedical data relevant to modern nursing practice.
Obiettivi Agenda 2030 per lo sviluppo sostenibile	Achieved. SDG 3 – Good Health and Well-being: promoting the use of digital technologies and biomedical data to support evidence-informed healthcare practice. SDG 4 – Quality Education: fostering digital, bioinformatic and critical artificial intelligence competencies. SDG 9 – Industry, Innovation and Infrastructure: promoting the use of digital infrastructures and computational tools for biomedical data analysis.

EPIDEMIOLOGY

Code	50696902
Location	PERUGIA
CFU	2
Teacher	Chiara De Waure
Teachers	Chiara De Waure
Hours	30 ore - Chiara De Waure
Learning activities	Base
Area	Scienze propedeutiche
Sector	MED/42
Type of study-unit	Obbligatorio (Required)
Language of instruction	Italian
Contents	Definition and objective of the epidemiology. Measures of occurrence, association and impact. Introduction to study design. Observational and experimental study designs. Bias.
Reference texts	Ricciardi W, Boccia S [Editors]. Igiene - Medicina preventiva - Sanita' pubblica. Idelson Gnocchi 2021 Manzoli L, Villari P, Boccia A [Editors]. Epidemiologia e management in sanità. Elementi di metodologia. Edi. Ermes 2015
Educational objectives	The aim of the course is to provide students with the knowledge and skills to produce robust evidence and to critical appraise the evidence within the health sector.
Prerequisites	Knowledge of secondary school mathematic and biology
Teaching methods	Lectures and exercises
Other information
Learning verification modality	Written test with closed questions. For epidemiology 12 questions will be included in the final test.
Extended program	Definition and objective of the epidemiology: origins, development and fields of application. Measures of occurrence: meaning and calculation of prevalence and incidence measures. Measure of association: meaning and calculation of risk ratio and odds ratio. Measure of impact: meaning and calculation of attributable risks. Crude, specific and adjusted rates: meaning and calculation. Introduction to study design: general characteristics and applications of different study designs. Observational study designs: requisites, characteristics and stages of implementation of cross-sectional studies, cohort studies and case-control studies. Experimental study designs: requisites, characteristics and stages of implementation of trials. Random and systematic errors: definition, consequences and methods of their control. Tools for drafting and reading a research protocol and a research article.

SCIENTIFIC EVIDENCES FOR NURSING

Code	50696801
Location	PERUGIA
CFU	1
Teacher	Chiara De Waure
Learning activities	Caratterizzante
Area	Scienze infermieristiche
Sector	MED/45
Type of study-unit	Obbligatorio (Required)

Canale B

CFU

1

Teacher

Valerio Di Nardo

Teachers

• Valerio Di Nardo

Hours

• 15 ore - Valerio Di Nardo

Language of instruction

Italian

Contents

- Storia ed evoluzione dell’EBM; EBN: principi e metodologia; EBP: vantaggi, ostacoli e limiti; - Modello per le decisioni cliniche basate sulle evidenze: componenti - Paradigma tradizionale vs Paradigma Evidence Based - Rischi dovuti al mancato rispetto delle evidenze scientifiche - Ostacoli e limiti all’implementazione dell’EBP - La piramide delle evidenze - Livelli di evidenza e Forza delle Raccomandazioni/Grading delle pratiche raccomandate - Classificazione degli interventi terapeutici - Ricerca primaria vs ricerca secondaria - Ricerca quantitativa vs ricerca qualitativa - Studi osservazionali: tipologie; Studi sperimentali: tipologie. - Linee guida, percorsi, processi, procedure, protocolli - Strategie per ricercare informazioni: searching - Dove e come cercare le migliori informazioni

Reference texts

Paolo Chiari et Al., Evidece-Based clinical practice. La pratica clinico assistenziale basata su prove di efficacia. Seconda edizione. McGraw-Hill, Milano, 2011 D.F. Polit, C. Tatano Beck Fondamenti di Ricerca infermieristica-seconda edizione, McGraw Hill 2018 J.A. Fain La ricerca infermieristica leggerla, comprenderla e applicarla, McGraw Hill 2004

Educational objectives

- conoscere i principi generali della pratica basata sulle evidenze (EBP); - conoscere le principali fonti delle prove di efficacia; - conoscere le principali Banche dati biomediche o infermieristiche; - conoscere le principali strategie di ricerca delle prove di efficacia e dei relativi strumenti operativi (linee guida, procedure e protocolli); - leggere ,analizzare e valutare la qualità metodologica di uno studio clinico e di una linea guida;

Prerequisites

Conoscenza generale dei concetti di linee guida, buone pratiche, gold standard; Conoscere la differenza tra scienza e disciplina;

Teaching methods

Lezione frontale; Discussione di casi; Brainstorming; Analisi critica di articoli scientifici

Other information

Nessuna

Learning verification modality

Esame scritto

Extended program

Storia ed evoluzione dell’EBM; EBN: principi e metodologia; EBP: vantaggi, ostacoli e limiti; Il processo di ricerca infermieristico Classificazione e caratteristiche dei disegni di ricerca e fonti della letteratura Linee guida e ricerca bibliografica; Livelli di evidenza scientifica e forza delle raccomandazioni. Lettura e valutazione di un articolo ai fini dell’applicazione nella pratica clinico-assistenziale

Canale A

CFU

1

Teacher

Rosita Morcellini

Teachers

• Rosita Morcellini

Hours

• 15 ore - Rosita Morcellini

Language of instruction

Italian

Contents

Modern nursing is increasingly based on the application of scientific evidence to ensure high-quality care and improve patient outcomes. Scientific evidence, derived from clinical research, provides valuable information on which interventions and practices are effective, safe, and efficient. Using this evidence, therefore, allows nurses to make informed, personalized, and evidence-based clinical decisions.

Reference texts

Paolo Chiari et al., Evidence-Based Clinical Practice. Second edition.
McGraw-Hill, Milan, 2011

D.F. Polit, C. Tatano Beck, Fundamentals
of Nursing Research - Second Edition, McGraw Hill 2018

J.A. Fain, Nursing Research:
Reading, Understanding, and Applying It,
McGraw Hill 2004

Educational objectives

The course aims to provide the basic knowledge needed to provide effective, evidence-based nursing care, along with tools to help students stay up-to-date and find answers to questions posed in daily practice by consulting specific databases.
By the end of the course, students will be able to:
Identify the contribution of research to the management of care pathways and the phases of evidence-based practice
Identify the characteristics of epidemiological studies and the hierarchy of sources
Describe the requirements of a research article and an evidence-based guideline
Identify the main biomedical databases of secondary sources and how to use them
Formulate a clinical-care question to search the literature in biomedical databases
Use specific databases to search for evidence of efficacy
Understand the results of a research article by reading the text and tables
Read an evidence-based guideline
Formulate a quality assessment of a guideline
Choose a source consultation path to answer a clinical question
Independently find secondary literature sources
Begin to develop independent study skills.

Prerequisites

General knowledge of the concepts of guidelines, best practices, and gold standards; Understanding the difference between science and discipline.

Teaching methods

Lectures; Case discussions; Brainstorming; Critical analysis of scientific articles

Other information

none

Learning verification modality

Closed-answer written exam

Extended program

History and evolution of EBM; EBN: principles and methodology; EBP:
advantages, obstacles, and limitations;
The nursing research process
Classification and characteristics of research designs and sources of
literature
Guidelines and literature search; Levels of scientific evidence and
strength of recommendations.
Reading and evaluating an article for application in
clinical care practice

HEALTH STATISTICS

Code	50696701
Location	PERUGIA
CFU	1
Teacher	Fabrizio Stracci
Teachers	Fabrizio Stracci
Hours	15 ore - Fabrizio Stracci
Learning activities	Base
Area	Scienze propedeutiche
Sector	MED/01
Type of study-unit	Obbligatorio (Required)