Statistics for Evidence Based Medicine

A.Y. 2019/2020
6
Max ECTS
76
Overall hours
SSD
MED/01
Language
Italian
Learning objectives
The general objective of the course is to develop the critical ability to evaluate the scientific evidence in support of the medical acts of prevention, diagnosis, treatment and rehabilitation with reference to the integration of anamnestic data, the physical examination and diagnostic tests, of the practical effectiveness of the therapy, and of the prognostic indicators.

In the training process of the physician, the acquisition of this ability contributes, in the ethical and deontological perspective, to the construction of a mental habitus capable of integrating, in the practice of daily practice, clinical knowledge deriving from direct personal experience, the values expressed by the assisted persons and the knowledge produced by good clinical and biomedical research. A habit that is now considered necessary for all doctors, and in particular for general practitioners, who are increasingly involved in health research and in the evaluation processes of the effectiveness of their professional practice.

As specific objectives, the course aims to develop the knowledge a practical skills for:
i) statistical methods that allow to describe and evaluate the different sources of variability;
ii) diagnostic tests and related measures of reliability and diagnostic relevance;
iii) basic principles of planning observational studies, interpretation of measures of disease occurrence and association between risk factors and disease occurrence;
iv) the relationships between statistics and the fundamentals of the inductive / deductive scientific method for empirical research with reference to the planning of observation and experimental studies and to the methods of statistical inference;
basic principles of ethics and the relationship with the methodology of biomedical research with specific reference to experimental studies of therapeutic efficacy.
Expected learning outcomes
The course aims to provide the methodological tools needed to learn, apply and evaluate, through critical analysis of the medical literature:
- the validity of anamnestic data and objective findings
- the concepts of reliability, accuracy and precision, repeatability and reproducibility of the measures;
- the usefulness of diagnostic tests and prognostic indexes;
- measures of disease occurrence and association with risk/benefit factors in epidemiology/clinical research;
- the identification of sources of imprecision and inaccuracy in epidemiological / clinical studies;
- the difference between studies based on observation and experimentation together with the main study designs in epidemiology / clinical research for the assessment of causal relationships, with reflection on the ethical aspects of biomedical research
- the effectiveness of therapies, rehabilitation practices, prevention programs, reported by observational and experimental studies.
Single course

This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.

Course syllabus and organization

Linea: Policlinico

Responsible
Course syllabus
- Data coding: how to structure a database
- The R software and the R Commander interface module
- Import data into R from an Excel file
- The descriptive statics with R Commader:
graphs, numerical summary indices, contingency tables
- Inference procedures with R commander:
hypothesis tests and confidence intervals for averages and proportions
- The search for general medical information on Medline and Health on the Net Foundation.
- Notes on guided diagnosis systems available on the Internet
- The PubMed database
(search with MeSH terms, search with keywords, basic and advanced methods)
-The Scopus database
(basic and advanced search, how to derive the authors' H index)
- the Impact Factor: The Journal of Citation Report database
- Systematic reviews: the Cochrane Library database
Prerequisites for admission
None
Teaching methods
Frontal lessons to explain the use of the software, by proposing examples carried out on topics related to individual activities. The lessons are followed by activities carried out directly by the students.
For the bibliographic research, a text is proposed to be developed on a pathology with series of questions organized in order to produce a structured research document. Students carry out the research by connecting their PC to the internet to access to the bibliographic databases. The results of their research are saved on a Word document. The teacher is available to answer questions and check the student's search method.
For the data analysis part, each student loads the R software on their personal computer and performs an analysis of data which are public and made available to users, following a track proposed by the teacher, who is available to answer questions and to check the correct application of statistical procedures.
Teaching Resources
Copy of the slides presented during the lectures
R commander manual
Online Help documentation on databases
Assessment methods and Criteria
The learning verification is carried out through two tests that each student must carry out individually using a Personal Computer.
The first test consists of a bibliographic research concerning a clinical pathology, assigned to the student during the evaluation of the professionalizing activity. The student has to answer several questions regarding the description of symptoms, diagnostic methods and therapeutic strategies so to completes an initial summary sheet. The information should be found on the documents referenced in Medline and Health on the Net Foundation. Subsequently specific articles which are related to clinical and epidemiological studies on the assigned pathology need to be searched. This shall be carried out on the PubMed, Scopus and Cochrane Library databases. The search activity also includes considerations on the impact factor of the journals on which the articles are found and the H index of the authors who are most active in the pathology.
The second test consists in the analysis of data using the R software. A data file is assigned to each student in order to perform a statistical analysis, solving issues regarding the synthesis of data by means of graphs and descriptive statistics and regarding comparisons between different therapies and prognostic factors using statistical inference procedures.
The tests described above will be carried out on the same day in which the exams of the statistics and evaluation of evidence in medicine course take place, at the end of the written test.
The results will be communicated through a special form on ARIEL
MED/01 - MEDICAL STATISTICS - University credits: 6
Informal teaching: 16 hours
Lessons: 60 hours
Shifts:

Linea: San Donato

Responsible
Course syllabus
- Data coding: how to structure a database
- The R software and the R Commander interface module
- Import data into R from an Excel file
- The descriptive statics with R Commader:
graphs, numerical summary indices, contingency tables
- Inference procedures with R commander:
hypothesis tests and confidence intervals for averages and proportions
- The search for general medical information on Medline and Health on the Net Foundation.
- Notes on guided diagnosis systems available on the Internet
- The PubMed database
(search with MeSH terms, search with keywords, basic and advanced methods)
-The Scopus database
(basic and advanced search, how to derive the authors' H index)
- the Impact Factor: The Journal of Citation Report database
- Systematic reviews: the Cochrane Library database
Prerequisites for admission
None
Teaching methods
Frontal lessons to explain the use of the software, by proposing examples carried out on topics related to individual activities. The lessons are followed by activities carried out directly by the students.
For the bibliographic research, a text is proposed to be developed on a pathology with series of questions organized in order to produce a structured research document. Students carry out the research by connecting their PC to the internet to access to the bibliographic databases. The results of their research are saved on a Word document. The teacher is available to answer questions and check the student's search method.
For the data analysis part, each student loads the R software on their personal computer and performs an analysis of data which are public and made available to users, following a track proposed by the teacher, who is available to answer questions and to check the correct application of statistical procedures.
Teaching Resources
Copia delle diapositive presentate durante le lezioni frontali
Manuale di R commander
Documentazione di Help on line sulle banche dati
Assessment methods and Criteria
The learning verification is carried out through two tests that each student must carry out individually using a Personal Computer.
The first test consists of a bibliographic research concerning a clinical pathology, assigned to the student during the evaluation of the professionalizing activity. The student has to answer several questions regarding the description of symptoms, diagnostic methods and therapeutic strategies so to completes an initial summary sheet. The information should be found on the documents referenced in Medline and Health on the Net Foundation. Subsequently specific articles which are related to clinical and epidemiological studies on the assigned pathology need to be searched. This shall be carried out on the PubMed, Scopus and Cochrane Library databases. The search activity also includes considerations on the impact factor of the journals on which the articles are found and the H index of the authors who are most active in the pathology.
The second test consists in the analysis of data using the R software. A data file is assigned to each student in order to perform a statistical analysis, solving issues regarding the synthesis of data by means of graphs and descriptive statistics and regarding comparisons between different therapies and prognostic factors using statistical inference procedures.
The tests described above will be carried out on the same day in which the exams of the statistics and evaluation of evidence in medicine course take place, at the end of the written test.
The results will be communicated through a special form on ARIEL
MED/01 - MEDICAL STATISTICS - University credits: 6
Informal teaching: 16 hours
Lessons: 60 hours
Shifts:

Linea: San Giuseppe

Responsible
Course syllabus
- Data coding: how to structure a database
- The R software and the R Commander interface module
- Import data into R from an Excel file
- The descriptive statics with R Commader:
graphs, numerical summary indices, contingency tables
- Inference procedures with R commander:
hypothesis tests and confidence intervals for averages and proportions
- The search for general medical information on Medline and Health on the Net Foundation.
- Notes on guided diagnosis systems available on the Internet
- The PubMed database
(search with MeSH terms, search with keywords, basic and advanced methods)
-The Scopus database
(basic and advanced search, how to derive the authors' H index)
- the Impact Factor: The Journal of Citation Report database
- Systematic reviews: the Cochrane Library database
Prerequisites for admission
None
Teaching methods
Frontal lessons to explain the use of the software, by proposing examples carried out on topics related to individual activities. The lessons are followed by activities carried out directly by the students.
For the bibliographic research, a text is proposed to be developed on a pathology with series of questions organized in order to produce a structured research document. Students carry out the research by connecting their PC to the internet to access to the bibliographic databases. The results of their research are saved on a Word document. The teacher is available to answer questions and check the student's search method.
For the data analysis part, each student loads the R software on their personal computer and performs an analysis of data which are public and made available to users, following a track proposed by the teacher, who is available to answer questions and to check the correct application of statistical procedures.
Teaching Resources
Copia delle diapositive presentate durante le lezioni frontali
Manuale di R commander
Documentazione di Help on line sulle banche dati
Assessment methods and Criteria
The learning verification is carried out through two tests that each student must carry out individually using a Personal Computer.
The first test consists of a bibliographic research concerning a clinical pathology, assigned to the student during the evaluation of the professionalizing activity. The student has to answer several questions regarding the description of symptoms, diagnostic methods and therapeutic strategies so to completes an initial summary sheet. The information should be found on the documents referenced in Medline and Health on the Net Foundation. Subsequently specific articles which are related to clinical and epidemiological studies on the assigned pathology need to be searched. This shall be carried out on the PubMed, Scopus and Cochrane Library databases. The search activity also includes considerations on the impact factor of the journals on which the articles are found and the H index of the authors who are most active in the pathology.
The second test consists in the analysis of data using the R software. A data file is assigned to each student in order to perform a statistical analysis, solving issues regarding the synthesis of data by means of graphs and descriptive statistics and regarding comparisons between different therapies and prognostic factors using statistical inference procedures.
The tests described above will be carried out on the same day in which the exams of the statistics and evaluation of evidence in medicine course take place, at the end of the written test.
The results will be communicated through a special form on ARIEL
MED/01 - MEDICAL STATISTICS - University credits: 6
Informal teaching: 16 hours
Lessons: 60 hours
Shifts:
Professor(s)
Reception:
On appointment (email)