Study Guide Evidence based Medical Practice Semester II 19 Mei 2015
Study Guide of Evidence-based Medical Practice Block
CURRICULUM
EVIDENCE-BASED MEDICAL PRACTICE
Aims:
1. To develop basic information skills and their integration with the evidence-based
practice in the primary care setting
2. To develop skills to obtain, appraise and use valid and reliable new information using
on-line resources
3. To develop skills to convey electronic and oral communication
Learning Outcomes:
1. Possess skills to gain access to on-line resources
2. Able to critically appraise medical literatures
3. Able to keep patient’s medical records and comprehend ethical and legal
imperatives
4. Able to communicate with colleagues and co-workers using oral, written,
electronic means
and
Curriculum Contents:
1. Internet searching
2. Association and causation
3. Principles and applications of statistical analysis
4. Effect size, hypothesis testing and confidence interval
5. Principle of critical appraisal (diagnostic test, clinical trial, prognosis study)
6. Record keeping and Clinical Practice
7. Presentation at the meeting.
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
PLANNERS TEAM
No
Name
Department
Phone
1
Prof. Dr. dr. I Gde Raka Widiana, SpPDKGH (Coordinator)
Internal Medicine
0816297956
Microbiology
08179747502
2
Ida Bagus Nyoman Putra Dwija,
S.Si.,M.Biotech
3
Dr. dr. I P. G. Adiatmika, Mkes
Physiology
08123811019
4
dr. Lanang Sidiartha, SpA
Pediatrics
08123966008
5
dr. I.B. Subanada, SpA
Pediatrics
08123995933
Name
Department
Phone
Prof. Dr. dr. I Gde Raka Widiana, SpPDKGH
Internal Medicine
0816297956
dr. Dewi Sutriani Mahalini, SpA
Pediatrics
08123641466
dr. Eka Gunawijaya, Sp A
Pediatrics
081338599801
dr. Lanang Sidiartha, SpA
Pediatrics
08123966008
dr. I.B. Subanada, SpA
Pediatrics
08123995933
Dr. dr. I P. G. Adiatmika, Mkes
Physiology
08123811019
dr. I Wyn. Sudhana, SpPD-KGH
Internal Medicine
08123914095
Dr.dr. Ketut Suega,Sp.PD-KHOM
Internal Medicine
081338728421
LECTURERS
No
FACILITATORS
Regular Class (Class A)
No
Name
Udayana University Faculty of Medicine, MEU
Group
Departement
Phone
Veue
2
Study Guide of Evidence-based Medical Practice Block
(3rd floor)
1
dr. I Putu Adiartha Griadhi,M.Fis
1
Physiology
081999636899
3nd floor:
R.3.09
2
dr. I Gusti Ayu Eka
Pratiwi,M.Kes.,Sp.A
2
Pediatric
08123920750
3nd floor:
R.3.10
3
dr. Gede Kambayana,Sp.PD-KR
3
Interna
08124683416
3nd floor:
R.3.11
4
dr. Ni Nyoman Margiani, Sp.Rad
4
Radiology
081337401240
3nd floor:
R.3.12
5
dr.Ni Putu Sri Widnyani,Sp.PA
5
Pathology
Anatomy
081337115012
3nd floor:
R.3.13
6
dr. A.A.Bagus Ngurah Nuartha, SpS.
(K)
6
Neurology
08123687288
3nd floor:
R.3.14
7
dr. Anak Agung Wiradewi
Lestari,Sp.PK
7
Clinical
Pathology
08155237937
3nd floor:
R.3.15
8
dr. Nyoman Paramita Ayu, Sp.PD
8
Interna
08123837372
3nd floor:
R.3.16
9
dr. Nyoman
Suryawati,M.Kes.,Sp.KK
9
Dermatology
0817447279
3nd floor:
R.3.17
10
dr. Kunthi Yulianti, SpKF
10
Forensic
081338472005
3nd floor:
R.3.19
English Class (Class B)
No
1
Name
dr. A.A. Ngurah Subawa,M.Si
Udayana University Faculty of Medicine, MEU
Group
Departement
Phone
1
Clinical
08155735034
Veue
(3rd floor)
3nd floor:
3
Study Guide of Evidence-based Medical Practice Block
Pathology
R.3.09
087777790064
3nd floor:
R.3.10
08123661312
3nd floor:
R.3.11
081805530196
3nd floor:
R.3.12
082237817384
3nd floor:
R.3.13
08179747502
3nd floor:
R.3.14
08123621422
3nd floor:
R.3.15
085238238999
3nd floor:
R.3.16
08123956636
3nd floor:
R.3.17
0817569021
3nd floor:
R.3.19
2
Dr.dr.Bagus Komang
Satriyasa,M.Repro
2
Pharmacology
3
dr. Pontisomaya Parami,Sp.An
3
Anesthesiology
4
dr. Pratihiwi
Primadarsini,M.Biomed,Sp.PD
4
Interna
5
dr. Putri Ariani Sp.KJ
5
Psychiatry
6
IBN. Putra
Dwija,S.Si.,M.Biotech
6
Microbiology
7
dr. I Made Agus Kresna
Sucandra,Sp.An
7
Anesthesiology
8
dr. Putu Budiastra,Sp.M (K)
8
Ophthalmology
9
dr. Putu
Patriawan,M.Sc.,Sp.Rad
9
Radiology
10
Desak Gde Diah Dharma
Santhi, S.Si, Apt, M.Kes
10
Clinical
Pathology
TIME TABLE
REGULAR CLASS
Day/Date
1
Time
09.00 – 10.00
Activity
Introduction
Tuesday
Udayana University Faculty of Medicine, MEU
Venue
Class
Room
Person-incharge
Prof. Raka
4
Study Guide of Evidence-based Medical Practice Block
May,19
10.00 - 12.30
Scenarios : Problems
identifications with clinical
questions
12.30 – 13.00
Break
13.00 – 16.00
Practical Work 1.
2015
Record Keeping
Class
Room
dr. Dewi
Computer
room
Dr.
Adiatmika
Computer
room
09.00 – 10.00
Lecture 1. Principal of critical
appraisal
Class
Room
dr.Eka
10.00 – 11.00
Lecture 2. Association and
Causation
Class
Room
dr.
Subanada
May,20
11.00 – 12.00
Individual Learning
2015
12.00 – 13.00
Student Project 1
Class
Room
dr. Lanang
13.00 – 13.30
Break
13.30 – 15.00
SGD
Discussion
Room
Facilitator
15.00 – 16.00
Plenary Session
Class
Room
dr. Eka,
dr.Subanada
09.00 – 16.00
Practical Work 2.
Computer
room
Dr.
Adiatmika
Class
Room
dr.
Subanada
Class
Room
dr. Lanang
Discussion
Room
Fasilitator
Class
Room
Lecture
2
Wednesday
3
Thursday
Searching articles (address
will be given)
May,
21.2015
09.00 – 10.00
Lecture 3: Effect size,
Hypothesis Testing and
Confidence Interval
10.00 – 11.00
Individual Learning
11.00 – 12.00
Lecture 4. Principles and
Application of Statistical
Analysis
12.00 – 13.00
Student Project 2
13.00 – 13.30
Break
13.30 – 15.00
SGD
15.00 – 16.00
Plenary Lecture 3,4
4
Friday
May,22.
2015
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
09.00 – 10.00
Lecture 5: Methodological
and Statistical Principles and
Application in Descriptive
Studies
Class
Room
dr. Eka
10.00 – 11.30
Student Project 3
11.30 – 12.00
Break
12.00 – 13.30
Individual Learning
13.30 - 15.00
SGD
Discussion
Room
Facilitators
15.00 – 16.00
Plenary Lecture
Class
Room
dr.Eka
09.00 -10.00
Lecture 6. Methodological
and Statistical Principles and
Application in Analytical
Studies
Class
Room
dr. Lanang
10.00 -11.30
Student Project 4
11.30 -12.00
Break
12.00 – 13.30
Individual Learning
13.30 – 15.00
SGD
Discussion
Room
Facilitators
15.00 – 16.00
Plenary session
Class
Room
dr. Lanang
09.00 – 10.00
Lecture 7. Diagnostic Test
7
10.00 – 11.30
Student Project 5
Wednesday
11.30 -12.00
Break
May,27.
12.00 – 13.30
Individual Learning
2015
13.30 - 15.00
SGD
15.00 – 16.00
5
Monday
May,25
2015
6
Tuesday
May,26
2015
Discussion
Room
Facilitators
Plenary session
Class
Room
Dr. Sudhana
09.00 – 10.00
Lecture 8. Clinical Trial
Class
Room
Prof Raka
10.00 – 11.30
Student Project 6
11.30 – 12.00
Break
12.00 - 13.30
Individual Learning
8
Thursday
May,28
Dr. Sudhana
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
2015
13.30 – 15.00
SGD
Discussion
Room
Facilitator
15.00 – 16.00
Plenary session
Class
Room
Prof Raka
09.00 – 10.00
Lecture : 9. Study about
Prognosis
Class
Room
dr. Eka
10.00 – 11.30
Student Project 7
11.30 – 12.00
Break
12.00 – 13.30
Individual Learning
13.30 – 15.00
SGD
Discussion
room
Facilitators
15.00 – 16.00
Plenary session
Class
Room
dr. Eka
09.00 – 10.00
Lecture: 10. How to Write a
Paper and Present at a
Meeting
Class
Dr. Suega
9
Friday
May,29
2015
10
Monday
10.00 – 11.30
Student Project 8
June,1.
11.30 – 12.00
Break
2015
12.00 – 13.30
Individual Learning
13.30 – 15.00
SGD
15.00 – 16.00
Plenary session
Room
Discussion
room
Facilitator
Class
Room
Dr. Suega
11.
Wednesday
Examination
June,3
2015
English Class
Day/Date
Time
08.00 – 09.00
Activity
Introduction
1
Practical Work 1.
Tuesday,
09.00 – 12.00
Record Keeping
Udayana University Faculty of Medicine, MEU
Venue
Person-incharge
Class
Room
Prof. Raka
Computer
room
Dr.
Adiatmika
7
Study Guide of Evidence-based Medical Practice Block
May 19,
Computer
room
2015
2
12.00 – 12.30
Break
12.30 - 15.00
Scenarios : Problems
identifications with clinical
questions
08.00 – 15.00
Practical Work 2.
Wednesday,
May 20,
Searching articles (address
will be given)
Class
Room
dr. Dewi
Computer
room
Dr.
Adiatmika
2015
08.00 – 09.00
Lecture 1. Principal of critical
appraisal
Class
Room
dr.Eka
09.00 – 10.00
Lecture 2. Association and
Causation
Class
Room
dr.
Subanada
10.00 – 11.00
Individual Learning
11.00 – 12.30
SGD
Discussion
Room
Facilitator
12.30 – 13.00
Break
13.00 – 14.00
Student Project 1
Class
Room
dr. Lanang
14.00 – 15.00
Plenary Session
Class
Room
dr. Eka,
dr.Subanada
08.00 – 09.00
Lecture 3: Effect size,
Hypothesis Testing and
Confidence Interval
Class
Room
dr.
Subanada
09.00 – 10.00
Individual Learning
10.00 – 11.00
Lecture 4. Principles and
Application of Statistical
Analysis
Class
Room
dr. Lanang
11.00 – 12.30
SGD
Discussion
Room
Facillitator
12.30 – 13.00
Break
13.00 – 14.00
Student Project 2
14.00 – 15.00
Plenary Lecture 3,4
Class
Room
dr.Lanang;
dr.Subanada
3
Thursday
May 21,
2015
4
Friday
May 22,
2015
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
08.00 – 09.00
Lecture 5: Methodological
and Statistical Principles and
Application in Descriptive
Studies
Class
Room
dr. Eka
09.00 – 10.30
Individual Learning
10.30 – 12.00
SGD
Discussion
Room
Facilitators
12.00 – 12.30
Break
12.30 – 14.00
Student Project 3
14.00 – 15.00
Plenary Lecture
Class
Room
dr.Eka
08.00 – 09.00
Lecture 6. Methodological
and Statistical Principles and
Application in Analytical
Studies
Class
Room
dr. Lanang
09.00 – 10.30
Individual Learning
10.30 – 12.00
SGD
Discussion
Room
Facilitators
12.00 – 12.30
Break
12.30 – 14.00
Student Project 4
14.00 – 15.00
Plenary session
Class
Room
dr. Lanang
7
08.00 – 09.00
Lecture 7. Diagnostic Test
Wednesday
09.00 – 10.30
Individual Learning
May,27
10.30 – 12.00
SGD
12.00 – 12.30
Break
12.30 – 14.00
Student Project 5
14.00 – 15.00
5
Monday
May 25
2015
6
Tuesday
May 26
2015
Discussion
Room
Facilitators
Plenary session
Class
Room
Dr. Sudhana
08.00 – 09.00
Lecture 8. Clinical Trial
Class
Room
Prof Raka
09.00 – 10.30
Individual Learning
10.30 – 12.00
SGD
Discussion
Room
Facilitator
12.00 – 12.30
Break
2015
8
Thursday
May 28
2015
Dr. Sudhana
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
12.30 – 14.00
Student Project 6
14.00 – 15.00
Plenary session
Class
Room
Prof Raka
08.00 – 09.00
Lecture : 9. Study about
Prognosis
Class
Room
dr. Eka
09.00 – 10.30
Individual Learning
10.30 – 12.00
SGD
Discussion
room
Facilitators
12.00 – 12.30
Break
12.30 – 14.00
Student Project 7
14.00 – 15.00
Plenary session
Class
Room
dr. Eka
08.00 – 09.00
Lecture: 10. How to Write a
Paper and Present at a
Meeting
Class
Dr. Suega
9
Friday
May 29
2015
10
Monday
09.00 – 10.30
Individual Learning
June 1
10.30 – 12.00
SGD
2015
12.00 – 12.30
Break
12.30 – 14.00
Student Project 8
14.00 – 15.00
Plenary session
Room
Discussion
room
Facilitator
Class
Room
Dr. Suega
11.
Wednesday
EXAMINATION
June 3
2015
Note :
1. Lecture
: Class Room 3.01, 3rd floor
2. Small Group Discussion : Discussion Room 3rd floor,west wing (Room 3.01-3.08)
3. Examination
and Room 3.21-3.24 beside the IT Room at 3rd Floor
: Class Room 1, 4th floor, east wing (R 401) & Discussion
Room ,3rd floor,west wing & Multi-function Laboratory,4 th
floor.
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
4. For activity of practical work record keeping and searching articles students have to
bring their own laptop, because the number of the personal computers in the
computer room is not enough.
MEETING
Meeting of Student Representatives
Meeting of the planners team with the student representatives (Regular and English class)
will be held on Monday,May 25.2015, from 10.00 - 11.00 in the class room. It is hoped that
the planners’ team will get some inputs and suggestions from the student representatives to
improve the next implementation of the program. For the meeting each discussion group
must choose one of his members as their representative.
Meeting of Facilitators
All facilitators will be invited to discuss all the block activities with the planners team on
Monday, May.25.2015 from 11.00 – 12.00 in the class room.
ASSESSMENT METHOD
The student final assessment (CBT) will be held on Wednesday, June,3.2015. The time of
examination will be informed letter. The minimal passing level is 70.
LEARNING PROGRAMS
CURRICULUM
EVIDENCE-BASED MEDICAL PRACTICE
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
INTRODUCTION TO THE BLOCK:
An Introduction to Evidence-Based Medical Practice
Curriculum and Evidence- Based Medicine
Raka Widiana
Aims:
1. To develop basic information skills and their integration with the evidence-based
practice in the primary care setting
2. To develop skills to obtain, appraise and use valid and reliable new information using
on-line resources
3. To develop skills to convey electronic and oral communication
Learning Outcomes:
1. Possess skills to gain access to on-line resources
2. Able to critically appraise medical literatures
3. Able to keep patient’s medical records and comprehend ethical and legal
imperatives
4. Able to communicate with colleagues and co-workers using oral, written, and
electronic means
Curriculum Contents:
1. Internet searching
2. Association and causation
3. Principles and applications of statistical analysis
4. Effect size, hypothesis testing and confidence interval
5. Principle of critical appraisal (diagnostic test, clinical trial, prognosis study)
6. Record keeping and Clinical Practice
7. Presentation at the meeting.
ABSTRACTS (I Gde Raka Widiana)
Since the early 1980s, medicine has been undergoing a continuing revolution. It has led to e
fertile development of EBM (evidence based medicine). The practice of EBM (evidence
based medical practice) may be perceived as a meta-field because it involves concepts and
tools from many disciplines, including statistics and bio-statistics, research design, computer
programming, database management, and mathematical modeling. EBMP applies medical
informatics which is used for the purposes of generating, organizing, and making accessible
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Study Guide of Evidence-based Medical Practice Block
and intelligible huge amounts of information. Learning the skills to manage information is of
paramount importance to modern physicians. The computer is an important tool to facilitate
this process. Those who learn the skills of using computers to manage information will have
a greater advantage over those who do not. In daily practice, EBMP is important to the
medical students because can help them to deal with problems which include how to find,
appraise, procure, apply and store the best evidence to diagnose, treat, and determine the
prognosis of patients. Skills in this area may help them to pursue life long, students
centered and problem based education. The teaching of EBMP consists of lecture,
searching articles, critical appraisal and application to problems that may be introduced in
clinical scenarios
SELF DIRECTING LEARNING
Basic knowledge that must be known:
1. Search related articles to the patients problems (diagnose, treat, and prognosis) in
the internet,
2. Critically appraise the related articles and procure from the internet
3. Apply the articles to patents problems
4. Store the best evidence to of patients in your personal electronic library.
SCENARIO
A 25 year old woman was consulted to a nephrologist with lupus GN. The patient had
been treated with methyl prednisolon for 3 months failed to get remission.The patient
has not married hope to get pregnant in the future (contraindicated for CYP).The
doctor knew MMF, a promising drug for LGN available in the market. However the doctor
was not sure the drug is save and effective he would like to find out best evidence in
the internet, but he was not so familiar with EBM and searching in the internet. Please,
help the doctor to find the best evidence to answer his problem
Learning Task:
1. Comprehend above scenario
2. Make clinical (foreground question) using acronym PICO
3. Search articles about therapy (randomized clinical trial) in internet (using
Highwire or other addresses)
4. Procure 3 related articles
5. Appraise and select one best article
6. Apply whenever you find valid and important best evident article
Self Assessment:
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
How to make clinical (foreground question) using acronym PICO using above
clinical scenario
How to search articles about therapy (randomized clinical trial) in internet
(using Highwire or other address)
How to procure related articles
How to appraise and select the best article
How to apply the valid and important best evident article to your patient’s
problems
LEARNING OBJECTIVE
Comprehend and skillful making clinical (foreground question) using acronym PICO,
searching articles in internet, procure related articles, appraise, select the best article and
apply the valid and important best evident article to patient’s problems
Scenarios: Problems Identifications with Clinical Questions
Dewi Sutriani Mahalini
Evidence based medical practice (EBMP) is the use of the best scientific evidence to
support the clinical decision making. The identification of the best evidence requires the
construction of an appropriate research question and review of the literature. Many
questions about patient care arise at the patient bedside. You cannot simply enter your
question directly into a database and expect to get an answer. There are 4 steps in EBMP:
1. Formulate an answerable question; 2. Track down the best evidence outcome available;
3. Critically appraise the evidence; 4. Apply the evidence. The first step of EBMP is to
convert an information need into a focused question. This part of the EBMP process is often
overlooked but is essential if a search is to be conducted efficiently. Questions often spring
to mind in a form that makes finding answers in the medical literature a challenge.
Dissecting the question into its component parts and restructuring it so that it is easy to find
the answers is an essential first step in EBMP. EBMP process starts with a clinical scenario
that needs the best answer. One way of defining a focused question is to use the PICO or
PECO framework. "PICO" is the acronym for this 4 part question which consists of the first
letters of Patients, Intervention/Exposure, Comparison, Outcome. PICO doesn't necessarily
work perfectly for all kinds of questions, the main thing is the break down your question into
separate concepts, regardless of the headings you put them under. You can usually identify
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
three of the four PICO elements. By far the most common type of clinical question is about
how to treat a disease or condition. In EBMP, treatments and therapies are called
‘interventions’ and such questions are questions of INTERVENTION. However, not all
research questions are about interventions. Other types of questions that may arise are:
ETIOLOGY and RISK FACTOR,
FREQUENCY,
DIAGNOSIS,
PROGNOSIS and
PREDICTION. In each case the PICO method can be used to formulate the question.
SCENARIO
Scenario 1:
A medical student, 19 years old, female came to a doctor with chief complaint of mass in her
left breast with 2 cm in diameter. Based on physical examination, the doctor didn’t sure if the
mass was a malignancy or not. The doctor told her to do mammography but she was
worried that mammography will expose her to x ray. She asked for ultrasonography. She
thought that ultrasonography was safer compared to mammography. The problem was the
doctor didn’t know if ultrasonography can accurately diagnosed breast cancer compared to
mammography.
Can you find the answer for scenario above by search for the best evidence from the
internet?
Scenario 2:
A 40 years old male came to a doctor. He had diabetes mellitus since 5 years ago but he
didn’t attend medical visit regularly. This morning, the patient came to laboratory; he wanted
to check for microalbuminuria, based on his friend’s advice. His friend also had diabetes
mellitus. Apparently, he was positive for microalbuminuria. He was told by a nephrologists
that irbesartan can prevent renal failure in diabetes mellitus patients with microalbuminuria.
He asked this doctor whether it was true or not, and if it was true what was the estimation
for the preventive effect. The doctor didn’t have data to answer that question. Could you
help this doctor to search for best evidence from the internet?
Scenario 3:
A marketing staff from a well-known laboratory came to a doctor to offer a homocysteine
serum test for diabetes mellitus patients. This staff said that this new marker, homocysteine,
can predict the mortality rate in patients if the level in serum was high. The doctor asked for
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Study Guide of Evidence-based Medical Practice Block
an evidence for that statement. The staff didn’t have the answer for the doctor question.
Could you help the marketing staff to search for the evidence from the internet?
Scenario 4:
A 40 years old man who work as a teacher in department of Agriculture, had diabetes
mellitus for 6 years, came to a doctor. The doctor said that he had mild decreased of renal
function (secondary to diabetic nephropathy). The doctor advised him to have low protein
diet and go to a dietitian to ask for a menu that he needed. He asked if the low protein diet
really necessary because other doctor advised him to have a low calories and normal
protein intake to maintain his nutritional status. This doctor told him that low protein diet was
needed to prevent the progression of renal failure. He was confused which doctor was right
and asked for an evidence. The doctor didn’t have an evidence to show his patient. Could
you help this doctor to find evidence from the internet?
Learning task:
Please fill the worksheet as defined in next page.
1. Identify what type of question of the above scenario?
2. Please, build up a clinical research question using PICO !
3. Formulate a clinical research question from scenario above !
Self assessment
1. Please describe the steps in EBMP !
2. Please describe the components of a good clinical questions !
3. Two additional elements of the well built clinical question are the type of question
and the type of study. This information can be helpful in focusing the question and
determining the most apppropriate type of evidence. Please describe the type of
questions and the typeof the study !
WORKSHEET TO BUILT UP CLINICAL RESEARCH QUESTIONS
Scenario # ..................
1. Type of question: Choose one of the term below:
a. Diagnosis
b. Therapy/ intervention
c. Prognosis/ Prediction
d. Etiology/Risk factors
e. Rate/Frequency
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Study Guide of Evidence-based Medical Practice Block
2. Built up a research question using PICO
P Population/problem=...........................................................................................
I Intervention
=............................................................................................
C Comparator/control =...........................................................................................
O Outcome
= ...........................................................................................
3. Clinical research question:
......................................................................................................................................
.
......................................................................................................................................
.
......................................................................................................................................
.
LECTURE 1: Principles of Critical Appraisal
Eka Gunawijaya
What exactly is critical appraisal and what is the difference between "appraising" an article
and simply reading it? If you have been conscientious enough to organize a literature
search, go to the library and copy a promising article, why can't we leave you alone to read
it over a coffee? Why do we ask you to put it through some complex process called critical
appraisal?
Critical appraisal is the process of systematically examining research evidence to assess its
validity, results and relevance before using it to inform a decision. Critical appraisal is an
essential part of evidence-based clinical practice that includes the process of systematically
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
finding, appraising and acting on evidence of effectiveness. Critical appraisal allows us to
make sense of research evidence and thus begins to close the gap between research and
practice. The aim of critical appraisal is to identify the quality of an article.
Appraisal is a technique which offers a discipline for increasing the effectiveness of your
reading, by enabling you to quickly exclude papers that are of too poor a quality to inform
practice, and to systematically evaluate those that pass muster to extract their salient
points. Critical appraisal is usually applied to quantitative studies (e.g. "randomized" or
"blinded" controlled trials, crossover trials, meta-analyses or systematic reviews) of the
effectiveness of different health and medical interventions. However, the skills can also be
applied to the assessment of qualitative studies of psychosocial and behavioral
interventions: e.g. observational or interview data obtained from case or cohort studies.
Furthermore, studies on the effectiveness of cognitive, behavioral and other psychosocial
interventions are also being conducted using quantitative research methodologies (e.g.
randomized controlled trials); especially where these interventions are used as part of a
combination therapy, which includes medication.
The medical literature is vast and rapidly expanding. Forays into the library can be
exhausting, as the reader is overwhelmed by the huge number of papers offered. When
reading, someone will cite interesting references, which spur the reader into a lengthy paper
haze. A major hazard of reading is to pursue a subject in too much depth. Instead of
following this haphazard course, the process of reading should be carefully planned to
provide a worthwhile return on the time invested. Establishing control over your reading
means following a number of steps: clarify your reasons for reading; specify your
information need; identify the relevant reports; critically appraise the papers
LECTURE 2: Association and Causation
I B Subanada
When reading a medical literature we sometimes encounter such phrases like “association
with”, “linked to”, and “related to”. The authors have avoided dogmatic statement of “causes”
or “produces”, statement like ”smoking causes lung cancer ” or “birth control pills produce
vein thrombosis”. Association is not necessarily a causality. Here is an analogy: a town has
a large number of unemployed people and a very high crime rate. It does not necessarily
follow that the unemployed are committing the crime. In other word the presence of
unemployment and crime tells us nothing at all about either the presence or direction of
causality. On the other hand, even if we are convince that we have pinpointed the
responsible etiology, we still think that some unsuspected risk factor is actually causing the
disease or an unappreciated co-intervention is responsible for the treatment effect.
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Study Guide of Evidence-based Medical Practice Block
Concept of causation
There are two concepts of causation: First, contributory cause. In most medical
phenomena, there is no single specific cause of a disease. In physics we consider that
metal will expand because of heat and shrink when cold, therefore expansion in a metal is
mathematically caused by heat only as a single cause. Generally, however, most of
diseases are caused by multi-factorial etiology. A risk factor may be a contributory cause.
The second concept of cause is often called necessary cause. In the 19th century, Robert
Koch developed a series of conditions that must be met before a microorganism can be
considered the cause of a disease. Such conditions are related to what is known as Koch’s
Postulates, which include a requirement that organism is always found with the disease. In
the real medical world most of medical phenomena can only be explained by contributory
cause as cause and effect relationship. For instance, even though cigarettes have been well
established as a risk factor, it is a contributory cause for the development of lung cancer, but
cigarette smoking is not necessarily the condition for development of lung cancer, since not
every one with lung cancer has smoked cigarettes. In order to describe the model of cause
and effect relationship, we can construct it into two perspectives:
LECTURE 3: Effect Size, Hypothesis Testing
and Confidence Interval
I.B. Subanada
In analytical studies, investigators seek to determine effect size of the outcome of interest
between variables or between groups and to determine whether there is a statistical
significant of those effect sizes (hypothesis testing).
Most investigations are conducted on only sample or subset of larger group of individuals or
subset of population. Researcher, therefore, are confronted with the question of whether
results of the investigation in the sample would be similar if the investigation included the
entire population or whether chance in the selection of samples (by random sample)
produced unusual results in their sample. Hypothesis testing is a method, which is used to
answer this question. Hypothesis testing is based on null hypothesis, assuming there is no
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Study Guide of Evidence-based Medical Practice Block
difference between groups being compared or there is no relationship between variables. Pvalue, therefore, is the probability that observes data, or outcome, that would have occurred
by chance (just due to sampling variation) when the null hypothesis is true. If P- value is
small, probability of chance would be also small and one may doubt about the null
hypothesis, which thus can be rejected. If P-value is large, the chance may be great and the
data are plausibly consistent with the null hypothesis, which thus cannot be rejected.
LECTURE 4: Principles and Application of
Statistical Analysis
Lanang Sidiartha
Statistical analysis is basically a method to assist us to answer a question under study
(research question). The research question is commonly formulated in a study hypothesis.
A study hypothesis in an analytical study mostly contains one or more independent
variables and one dependent variable. The relationship between independent and
dependent variable is an important issue in statistical analysis. Regarding this issue, it is not
our intention to describe basic statistics, since this subject will be applied for nonstatisticians. Many computer programs packed with statistical soft ware are available and
easy to operate. However, this subject aims to guide the student to understanding the
principle of selecting statistical analysis and interpreting the results and the meaning
parameters in statistics.
Statistics have three purposes in the analysis of health research studies
1. To make estimates of the strength of relationship or magnitude of differences
2. To be used in hypothesis testing, which is allows us to draw inferences about
population from samples, obtained from the same population.
3. To adjust to the influence of confounding variables on these estimates and
inferences.
When selecting a specific statistical method, we must think about variables. A variable
expresses or represents data in the mathematical procedures that are part of statistics.
About variable, we should identify:
1. What the function of each variable, and
2. What type of data is represented by each variable
With regard to the function of variable, we have to distinguish dependent variable from
independent variable. Dependent variable can be identified as the outcome or end-point of
a study. On the other hand, there may be no, one, or several independent variables that
may be identified as risk factors or treatment of interest. The third is confounding variable,
which needs to be taken into account when hypotheses are to be tested and estimates are
to be made.
With regard to the type of data, we have to categorize them as continuous and discrete.
Continuous data are defined as data that provide the possibility of observing any of an
infinite number of equal spaced numerical values between any two points in its range of
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Study Guide of Evidence-based Medical Practice Block
measurement, for examples, blood pressure, serum cholesterol, age, and weight. Discrete
data can only a finite or limited number of values in their range of measurement, for
examples, number of pregnancies, stage of disease, and gender. For each of these
variables, we can select two values between which it is not possible to imagine other value.
For instance, there is no number of hypertension stages between stage 1 and stage 2. Then
data can be defined further by their scale of measurement. Continuous data are measured
on scales, called ratio or interval scales. Discrete data, on the other hand, can be
measured as nominal (such as treatment, gender, race, and eye color) and ordinal scales
(such as stage of the disease and levels of education).
For the purpose of selecting a statistical procedure or interpreting the result of such
procedure, it is important to distinguish between three categories: 1) continuous (contain a
great number of possible values), 2) ordinal (data are ordered one higher than the next and
with at least three), and 3) nominal (only two possible values, such as alive or dead)
variables. Continuous variable can be rescaled to ordinal or nominal variable. For example,
data of blood pressure (in continuous) can be categorized to stage of hypertension (stage 1,
stage 2, and stage 3) as ordinal variable or can be categorized to normal and hypertension
as ordinal variable. Continuous variables contain more information than ordinal variable and
nominal variables. Thus, continuous variables are considered to be at higher level than
nominal variables.
Thus in selecting statistical procedure, the initial steps are:
1. Identify one dependent variable and all independent variables, if present, on the
basis of the research question.
2. Determine for each variable whether it represents continuous, ordinal, or nominal
data.
The three basic statistical procedures: univariable, bivariable and multivariable analysis
LECTURE 5. Methodological and Statistical Principles and
Applications in Descriptive Studies
Eka Gunawijaya
A typical sequence for studying a topic begins with observational studies of a type that is
often called descriptive. This type of study often explore distribution of diseases and healthrelated characteristics in the population (How common is TB patients in Bali) or the
sensitivity and specificity of a diagnostic test. Descriptive studies are usually followed by
analytical study that to evaluate associations to discover cause and effect relationship (Does
TB vaccination lower the incidence of lung TB in Bali). Descriptive studies is characterized
by a set of measurements contains one dependent variable and no independent variable.
A univariate analysis is therefore commonly used to test the data. There are three
application of this method:
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Study Guide of Evidence-based Medical Practice Block
1. Descriptive studies (e.g. case series), only one sample might be presented
2. To determine mean or percentage, point estimation and confidence interval of
particular groups.
3. Comparing two measurements of same characteristic on the same or very similar
individuals (using paired data).
In continuous dependent variable, data are usually assumed to come from population with a
Gaussian distribution. Population mean is an estimate of primary interest and dispersion is
measured by the standard deviation or variance.
For ordinal dependent variable, we do not assume a particular distribution of population
data (distribution free or non-parametric). Estimate of population is median defined as midpoint of a collection of data.
For nominal dependent variable, we determine only the presence or absence of the
condition, and we can estimate the frequency of condition occurs in the population. The data
is assumed to have either a binomial or Poisson distribution.
Estimating the sample size for descriptive study including studies of diagnostic test is based
to that investigator is aiming to calculate descriptive statistics, such as means and
proportions (prevalence, incidence, mortality rate) of particular disease in a single
population.
Descriptive studies commonly report confidence intervals, a range of values about the
sample mean or proportion. A confidence interval is a measure of the precision of the
sample estimate. The investigator sets the confidence level, such as 95% or 99%. An
interval with a greater confidence level (say 99%) is wider, and therefore more likely to
include the true population value, than an interval with a lower confidence level (say 95% or
90%). The width of confidence interval depends on sample size. The more sample size
the .narrower the width.
LECTURE 6. Methodological and Statistical Principles and Applications in
Analytical Studies
Lanang Sidiartha
Based on variable, statistical analysis was divided to bivariate analysis if consist of one
independent variable and one dependent variable and multivariate analysis if consist of one
dependent variable and two or more independent variable or two or more dependent
variable and one independent variable. There are 5 steps to choose appropriate statistical
analysis. First, identified the study hypothesis or research question; second, identified how
many variable was compared; third, identified the variable is it related or unrelated variable;
fourth, identified scale of measurement of data; and fifth, identified the criteria for parametric
test and non-parametric test. Study hypothesis was classified as comparative hypothesis,
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Study Guide of Evidence-based Medical Practice Block
associative hypothesis and correlative hypothesis, each of them has different statistical
analysis. Variable or set of data was classified as related group if it was take from the same
subject.
LECTURE 7: Diagnostic Test
Principles In Critical Appraisal
Sudhana
The fundamental principle of diagnosis testing rests on the belief that individual with a
disease are different from individual without disease and that diagnostic test can distinguish
between these two groups. Ideally, diagnostic test have the following features: (1) all
individuals without the disease under study have one uniform value on the test, (2) all
individuals with the disease have a different but uniform value for the test, thus, (3) all test
results would coincide with the results of diseased or those of the disease-free group. If this
was the situation in reality, then one perfect test could distinguish disease from health.
However, none of these three conditions is usually present. Variation exist is due to same
factors coming from subjects being studied, instrument being used and the observer.
Subject variation is condition of the individual subject being tested may vary from
performance to performance, resulting in changes in phenomenon being assessed.
Instrument variation may occur as a result of technical methods used to perform the test.
Errors may occur because of variations when using the same testing instrument (intrainstrument error) or when using different instrument (inter-instrument error). Observer
variation may occur as a result of the observer who assesses the results. Errors may occur
because of the variation in measurement by the same observer (intra-observer variation) or
error using different observers (inter-observer variation).
The test or criterion used to unequivocally define the disease is known as a gold standard.
The gold standard may be a biopsy, an angiogram, an autopsy, or any established test. The
use of a gold standard tests that is possible to be 100% correct in making a diagnosis.
There might be a cheaper or more convenient test. In diagnostic test, we can ask whether
the test measures up to the gold standard. The investigator classifies each patient as either
having the disease or being disease-free according to the gold standard test, and as
positive or negative by the test being evaluated. They then can calculate the number of
individuals for whom the test and the gold standard test agree and the number for whom
they disagree and display their result in2X2 table as follows:
Total
Test
(+)
(-)
A
C
a+c
Udayana University Faculty of Medicine, MEU
b
d
b+d
a+ b
c+d
a +b+c+d
Predictive
Value
Positive
23
Study Guide of Evidence-based Medical Practice Block
Sensitivity
Specificity
Table 1. Table 2 x 2 table
We can determine, a = number of individuals with the disease and test positive: true
positive; b = number of individuals diseased free and test positive: false positive; c =
number of individuals with the disease and test negative: false negative; d = number of
individuals disease-free and test negative: true negative. Then, a + c = total number of
individuals with the disease and b + d = total number of disease-free individuals. From these
components we can calculate sensitivity = a/(a+c) and specificity = d/(b + d) of the test.
If we want to critically appraised an article about diagnosis, we are confronted with V I A,
that stands for valid, important and applicable which appraises the validity, importance and
applicability of the report.
1. The validity will questions whether evidence about the accuracy of a diagnostic test
valid
2. The importance query of whether this (valid) evidence demonstrate an important
ability to accurately distinguish patients who do and don’t have specific disorder
3. The applicability may ask of whether we can apply this valid important diagnostic test
to specific (our) patients.
To step on a critical appraisal, an important issue about the test being studied that we need
to define is what is normal and what is abnormal. Both parameters will be applied to the test
being studied and the gold standard.
We can define the normalcy from six approaches:
1. Gaussian: mean ± 2standard deviations – this one assumes a normal distribution for
all tests and results in all “abnormalities” having the same frequency
2. Percentile 5-95%- has the same basic defect as the Gaussian definition
3. Culturally desirable: when “normal” is that which preferred by society, the role of
medicine gets confused
4. Risk factor: changing risk factor necessarily changing risk
5. Diagnostic: range of result beyond which target disorder became highly probable
6. Therapeutic: range of result beyond which treatment does more good than harm.
Means we have to keep up with the advances in therapy.
Problem may arise with parameters in continuous variables. With such tests, several
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
Fig 1. Receiver operating characteristic (ROC) curve for some cutoff points of a continuous
variable.
Values of sensitivity and specificity are possible, depending on the cutoff point chosen to
define a positive test. This trade- off between sensitivity and specificity can be displayed
using a graphic technique. This technique originally developed in electronic equipment
called receiver operating characteristic (ROC) curves. We select several cutoff points and
determine sensitivity and specificity at each point. We then graph the sensitivity (or truepositive rate) on Y-axis as a function of 1-specificity (false-positive rate) on X-axis. An ideal
test is one that reaches the upper left corner of the graph (100% true positives and no false
positives). A worthless test follows the diagonal from the lower left to the upper right
corner (see fig.1). The area under curve (AUC), which does ranges from 0.5 for useless test
to 1.0 for prefect test, is useful summary of the overall accuracy of a test and can be used to
compare the accuracy of two or more tests.
LECTURE 8: Clinical Trial
Principle in Critical Appraisal
Raka Widiana
Some treatments are so clearly advantageous that they require no formal assessment; this
is true of antibiotics for pneumonia and surgery for serious trauma. However, this situation is
relatively rare in clinical medicine. Usually the effects of treatment are much less obvious
and most interventions require research to establish their value. Not only must specific
interventions be shown to do more good than harm among patients who use them (i.e. they
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
are theoretically effective or efficacious), but they should also do more good than harm in
patients to whom they are offered (i.e. they should be practically effective). In studies of
efficacy it is advantageous to include who are likely to be compliant. Practical effectiveness
is determined by studying outcome in a group of people offered treatment, only some of who
will be compliant. The most accurate method for measuring effectiveness is a clinical trial.
Clinical trials are a special kind of cohort study in which the conditions of study – selection
of treatment groups, nature of interventions, management during follow up, and
measurement of outcomes – are specified by the investigator for the purpose of making
unbiased comparisons. Clinical trials are more highly controlled and managed than are
cohort studies (observational study). The investigators are conducting an experiment,
analogous to those done in the laboratory. They have taken it upon themselves (of course,
with their patient’s permission) to isolate for study the unique contribution of one factor by
holding constant, as much as possible, all other determinants of the outcome. Hence, other
names for clinical trials are experimental and intervention studies.
We need to define exactly what is meant by ‘clinical trial’; briefly the term may be applied to
any form of planned experiments which involves patients and is designed to elucidate the
most appropriate treatment of future patients with a given medical conditions. Perhaps the
essential characteristic of a clinical trial is that one uses results based on a limited sample of
patients to make inferences about how treatment should be conducted in the general
population of patients who will require treatment in the future. Randomized controlled trials
(RCT) are the standard of excellence for scientific studies of the effects of treatment in
clinical trial.
RANDOMIZED CONTROLLED TRIAL
The structure of an RCT is shown in Figure-1. The patients to be studied are first selected
from a larger number of patients with the condition of interest. They are then divided, using
randomization into two groups of comparable prognosis. One group, called the experimental
or treated group, is exposed to an intervention that is believed to be helpful. The other
group, called a control or comparison group, is treated the same in all ways except that its
members are not exposed to the intervention. The clinical course of both groups is then
observed and any differences in outcome are attributed to the intervention.
The main reason for structuring RCT in this way is to avoid bias (systematic error) when
comparing the respective value of the two or more kinds of treatments. The validity of RCT
depends on how well they result in an equal distribution of all determinants of prognosis,
other than the being tested, in treated and control patients.
Experimental
Intervention
NOT IMPROVED
Population of
patients with
IMPROVED
SAMPLE
the condition
Udayana University
Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
TIME
OUTCOMES
IMPROVED
Comparison
NOT IMPROVED
Intervention
Figure 1: The structure of a RCT
SAMPLING
Any RCT requires a precise definition of which patients are eligible for inclusion. The early
stages of protocol development may proceed with only a rough outline of the intended type
of patient, but before the RCT gets underway this must be transformed into detailed
specification. The main objective is to ensure that patients in the RCT may be identified as
representative of some future class of patients to whom the RCT finding may be applied as
shown in Figure 2.
The kinds of patients that are included in an RCT determine the extent to which conclusions
can be generalized to other patients. Of the ma
CURRICULUM
EVIDENCE-BASED MEDICAL PRACTICE
Aims:
1. To develop basic information skills and their integration with the evidence-based
practice in the primary care setting
2. To develop skills to obtain, appraise and use valid and reliable new information using
on-line resources
3. To develop skills to convey electronic and oral communication
Learning Outcomes:
1. Possess skills to gain access to on-line resources
2. Able to critically appraise medical literatures
3. Able to keep patient’s medical records and comprehend ethical and legal
imperatives
4. Able to communicate with colleagues and co-workers using oral, written,
electronic means
and
Curriculum Contents:
1. Internet searching
2. Association and causation
3. Principles and applications of statistical analysis
4. Effect size, hypothesis testing and confidence interval
5. Principle of critical appraisal (diagnostic test, clinical trial, prognosis study)
6. Record keeping and Clinical Practice
7. Presentation at the meeting.
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
PLANNERS TEAM
No
Name
Department
Phone
1
Prof. Dr. dr. I Gde Raka Widiana, SpPDKGH (Coordinator)
Internal Medicine
0816297956
Microbiology
08179747502
2
Ida Bagus Nyoman Putra Dwija,
S.Si.,M.Biotech
3
Dr. dr. I P. G. Adiatmika, Mkes
Physiology
08123811019
4
dr. Lanang Sidiartha, SpA
Pediatrics
08123966008
5
dr. I.B. Subanada, SpA
Pediatrics
08123995933
Name
Department
Phone
Prof. Dr. dr. I Gde Raka Widiana, SpPDKGH
Internal Medicine
0816297956
dr. Dewi Sutriani Mahalini, SpA
Pediatrics
08123641466
dr. Eka Gunawijaya, Sp A
Pediatrics
081338599801
dr. Lanang Sidiartha, SpA
Pediatrics
08123966008
dr. I.B. Subanada, SpA
Pediatrics
08123995933
Dr. dr. I P. G. Adiatmika, Mkes
Physiology
08123811019
dr. I Wyn. Sudhana, SpPD-KGH
Internal Medicine
08123914095
Dr.dr. Ketut Suega,Sp.PD-KHOM
Internal Medicine
081338728421
LECTURERS
No
FACILITATORS
Regular Class (Class A)
No
Name
Udayana University Faculty of Medicine, MEU
Group
Departement
Phone
Veue
2
Study Guide of Evidence-based Medical Practice Block
(3rd floor)
1
dr. I Putu Adiartha Griadhi,M.Fis
1
Physiology
081999636899
3nd floor:
R.3.09
2
dr. I Gusti Ayu Eka
Pratiwi,M.Kes.,Sp.A
2
Pediatric
08123920750
3nd floor:
R.3.10
3
dr. Gede Kambayana,Sp.PD-KR
3
Interna
08124683416
3nd floor:
R.3.11
4
dr. Ni Nyoman Margiani, Sp.Rad
4
Radiology
081337401240
3nd floor:
R.3.12
5
dr.Ni Putu Sri Widnyani,Sp.PA
5
Pathology
Anatomy
081337115012
3nd floor:
R.3.13
6
dr. A.A.Bagus Ngurah Nuartha, SpS.
(K)
6
Neurology
08123687288
3nd floor:
R.3.14
7
dr. Anak Agung Wiradewi
Lestari,Sp.PK
7
Clinical
Pathology
08155237937
3nd floor:
R.3.15
8
dr. Nyoman Paramita Ayu, Sp.PD
8
Interna
08123837372
3nd floor:
R.3.16
9
dr. Nyoman
Suryawati,M.Kes.,Sp.KK
9
Dermatology
0817447279
3nd floor:
R.3.17
10
dr. Kunthi Yulianti, SpKF
10
Forensic
081338472005
3nd floor:
R.3.19
English Class (Class B)
No
1
Name
dr. A.A. Ngurah Subawa,M.Si
Udayana University Faculty of Medicine, MEU
Group
Departement
Phone
1
Clinical
08155735034
Veue
(3rd floor)
3nd floor:
3
Study Guide of Evidence-based Medical Practice Block
Pathology
R.3.09
087777790064
3nd floor:
R.3.10
08123661312
3nd floor:
R.3.11
081805530196
3nd floor:
R.3.12
082237817384
3nd floor:
R.3.13
08179747502
3nd floor:
R.3.14
08123621422
3nd floor:
R.3.15
085238238999
3nd floor:
R.3.16
08123956636
3nd floor:
R.3.17
0817569021
3nd floor:
R.3.19
2
Dr.dr.Bagus Komang
Satriyasa,M.Repro
2
Pharmacology
3
dr. Pontisomaya Parami,Sp.An
3
Anesthesiology
4
dr. Pratihiwi
Primadarsini,M.Biomed,Sp.PD
4
Interna
5
dr. Putri Ariani Sp.KJ
5
Psychiatry
6
IBN. Putra
Dwija,S.Si.,M.Biotech
6
Microbiology
7
dr. I Made Agus Kresna
Sucandra,Sp.An
7
Anesthesiology
8
dr. Putu Budiastra,Sp.M (K)
8
Ophthalmology
9
dr. Putu
Patriawan,M.Sc.,Sp.Rad
9
Radiology
10
Desak Gde Diah Dharma
Santhi, S.Si, Apt, M.Kes
10
Clinical
Pathology
TIME TABLE
REGULAR CLASS
Day/Date
1
Time
09.00 – 10.00
Activity
Introduction
Tuesday
Udayana University Faculty of Medicine, MEU
Venue
Class
Room
Person-incharge
Prof. Raka
4
Study Guide of Evidence-based Medical Practice Block
May,19
10.00 - 12.30
Scenarios : Problems
identifications with clinical
questions
12.30 – 13.00
Break
13.00 – 16.00
Practical Work 1.
2015
Record Keeping
Class
Room
dr. Dewi
Computer
room
Dr.
Adiatmika
Computer
room
09.00 – 10.00
Lecture 1. Principal of critical
appraisal
Class
Room
dr.Eka
10.00 – 11.00
Lecture 2. Association and
Causation
Class
Room
dr.
Subanada
May,20
11.00 – 12.00
Individual Learning
2015
12.00 – 13.00
Student Project 1
Class
Room
dr. Lanang
13.00 – 13.30
Break
13.30 – 15.00
SGD
Discussion
Room
Facilitator
15.00 – 16.00
Plenary Session
Class
Room
dr. Eka,
dr.Subanada
09.00 – 16.00
Practical Work 2.
Computer
room
Dr.
Adiatmika
Class
Room
dr.
Subanada
Class
Room
dr. Lanang
Discussion
Room
Fasilitator
Class
Room
Lecture
2
Wednesday
3
Thursday
Searching articles (address
will be given)
May,
21.2015
09.00 – 10.00
Lecture 3: Effect size,
Hypothesis Testing and
Confidence Interval
10.00 – 11.00
Individual Learning
11.00 – 12.00
Lecture 4. Principles and
Application of Statistical
Analysis
12.00 – 13.00
Student Project 2
13.00 – 13.30
Break
13.30 – 15.00
SGD
15.00 – 16.00
Plenary Lecture 3,4
4
Friday
May,22.
2015
Udayana University Faculty of Medicine, MEU
5
Study Guide of Evidence-based Medical Practice Block
09.00 – 10.00
Lecture 5: Methodological
and Statistical Principles and
Application in Descriptive
Studies
Class
Room
dr. Eka
10.00 – 11.30
Student Project 3
11.30 – 12.00
Break
12.00 – 13.30
Individual Learning
13.30 - 15.00
SGD
Discussion
Room
Facilitators
15.00 – 16.00
Plenary Lecture
Class
Room
dr.Eka
09.00 -10.00
Lecture 6. Methodological
and Statistical Principles and
Application in Analytical
Studies
Class
Room
dr. Lanang
10.00 -11.30
Student Project 4
11.30 -12.00
Break
12.00 – 13.30
Individual Learning
13.30 – 15.00
SGD
Discussion
Room
Facilitators
15.00 – 16.00
Plenary session
Class
Room
dr. Lanang
09.00 – 10.00
Lecture 7. Diagnostic Test
7
10.00 – 11.30
Student Project 5
Wednesday
11.30 -12.00
Break
May,27.
12.00 – 13.30
Individual Learning
2015
13.30 - 15.00
SGD
15.00 – 16.00
5
Monday
May,25
2015
6
Tuesday
May,26
2015
Discussion
Room
Facilitators
Plenary session
Class
Room
Dr. Sudhana
09.00 – 10.00
Lecture 8. Clinical Trial
Class
Room
Prof Raka
10.00 – 11.30
Student Project 6
11.30 – 12.00
Break
12.00 - 13.30
Individual Learning
8
Thursday
May,28
Dr. Sudhana
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
2015
13.30 – 15.00
SGD
Discussion
Room
Facilitator
15.00 – 16.00
Plenary session
Class
Room
Prof Raka
09.00 – 10.00
Lecture : 9. Study about
Prognosis
Class
Room
dr. Eka
10.00 – 11.30
Student Project 7
11.30 – 12.00
Break
12.00 – 13.30
Individual Learning
13.30 – 15.00
SGD
Discussion
room
Facilitators
15.00 – 16.00
Plenary session
Class
Room
dr. Eka
09.00 – 10.00
Lecture: 10. How to Write a
Paper and Present at a
Meeting
Class
Dr. Suega
9
Friday
May,29
2015
10
Monday
10.00 – 11.30
Student Project 8
June,1.
11.30 – 12.00
Break
2015
12.00 – 13.30
Individual Learning
13.30 – 15.00
SGD
15.00 – 16.00
Plenary session
Room
Discussion
room
Facilitator
Class
Room
Dr. Suega
11.
Wednesday
Examination
June,3
2015
English Class
Day/Date
Time
08.00 – 09.00
Activity
Introduction
1
Practical Work 1.
Tuesday,
09.00 – 12.00
Record Keeping
Udayana University Faculty of Medicine, MEU
Venue
Person-incharge
Class
Room
Prof. Raka
Computer
room
Dr.
Adiatmika
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Study Guide of Evidence-based Medical Practice Block
May 19,
Computer
room
2015
2
12.00 – 12.30
Break
12.30 - 15.00
Scenarios : Problems
identifications with clinical
questions
08.00 – 15.00
Practical Work 2.
Wednesday,
May 20,
Searching articles (address
will be given)
Class
Room
dr. Dewi
Computer
room
Dr.
Adiatmika
2015
08.00 – 09.00
Lecture 1. Principal of critical
appraisal
Class
Room
dr.Eka
09.00 – 10.00
Lecture 2. Association and
Causation
Class
Room
dr.
Subanada
10.00 – 11.00
Individual Learning
11.00 – 12.30
SGD
Discussion
Room
Facilitator
12.30 – 13.00
Break
13.00 – 14.00
Student Project 1
Class
Room
dr. Lanang
14.00 – 15.00
Plenary Session
Class
Room
dr. Eka,
dr.Subanada
08.00 – 09.00
Lecture 3: Effect size,
Hypothesis Testing and
Confidence Interval
Class
Room
dr.
Subanada
09.00 – 10.00
Individual Learning
10.00 – 11.00
Lecture 4. Principles and
Application of Statistical
Analysis
Class
Room
dr. Lanang
11.00 – 12.30
SGD
Discussion
Room
Facillitator
12.30 – 13.00
Break
13.00 – 14.00
Student Project 2
14.00 – 15.00
Plenary Lecture 3,4
Class
Room
dr.Lanang;
dr.Subanada
3
Thursday
May 21,
2015
4
Friday
May 22,
2015
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
08.00 – 09.00
Lecture 5: Methodological
and Statistical Principles and
Application in Descriptive
Studies
Class
Room
dr. Eka
09.00 – 10.30
Individual Learning
10.30 – 12.00
SGD
Discussion
Room
Facilitators
12.00 – 12.30
Break
12.30 – 14.00
Student Project 3
14.00 – 15.00
Plenary Lecture
Class
Room
dr.Eka
08.00 – 09.00
Lecture 6. Methodological
and Statistical Principles and
Application in Analytical
Studies
Class
Room
dr. Lanang
09.00 – 10.30
Individual Learning
10.30 – 12.00
SGD
Discussion
Room
Facilitators
12.00 – 12.30
Break
12.30 – 14.00
Student Project 4
14.00 – 15.00
Plenary session
Class
Room
dr. Lanang
7
08.00 – 09.00
Lecture 7. Diagnostic Test
Wednesday
09.00 – 10.30
Individual Learning
May,27
10.30 – 12.00
SGD
12.00 – 12.30
Break
12.30 – 14.00
Student Project 5
14.00 – 15.00
5
Monday
May 25
2015
6
Tuesday
May 26
2015
Discussion
Room
Facilitators
Plenary session
Class
Room
Dr. Sudhana
08.00 – 09.00
Lecture 8. Clinical Trial
Class
Room
Prof Raka
09.00 – 10.30
Individual Learning
10.30 – 12.00
SGD
Discussion
Room
Facilitator
12.00 – 12.30
Break
2015
8
Thursday
May 28
2015
Dr. Sudhana
Udayana University Faculty of Medicine, MEU
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Study Guide of Evidence-based Medical Practice Block
12.30 – 14.00
Student Project 6
14.00 – 15.00
Plenary session
Class
Room
Prof Raka
08.00 – 09.00
Lecture : 9. Study about
Prognosis
Class
Room
dr. Eka
09.00 – 10.30
Individual Learning
10.30 – 12.00
SGD
Discussion
room
Facilitators
12.00 – 12.30
Break
12.30 – 14.00
Student Project 7
14.00 – 15.00
Plenary session
Class
Room
dr. Eka
08.00 – 09.00
Lecture: 10. How to Write a
Paper and Present at a
Meeting
Class
Dr. Suega
9
Friday
May 29
2015
10
Monday
09.00 – 10.30
Individual Learning
June 1
10.30 – 12.00
SGD
2015
12.00 – 12.30
Break
12.30 – 14.00
Student Project 8
14.00 – 15.00
Plenary session
Room
Discussion
room
Facilitator
Class
Room
Dr. Suega
11.
Wednesday
EXAMINATION
June 3
2015
Note :
1. Lecture
: Class Room 3.01, 3rd floor
2. Small Group Discussion : Discussion Room 3rd floor,west wing (Room 3.01-3.08)
3. Examination
and Room 3.21-3.24 beside the IT Room at 3rd Floor
: Class Room 1, 4th floor, east wing (R 401) & Discussion
Room ,3rd floor,west wing & Multi-function Laboratory,4 th
floor.
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Study Guide of Evidence-based Medical Practice Block
4. For activity of practical work record keeping and searching articles students have to
bring their own laptop, because the number of the personal computers in the
computer room is not enough.
MEETING
Meeting of Student Representatives
Meeting of the planners team with the student representatives (Regular and English class)
will be held on Monday,May 25.2015, from 10.00 - 11.00 in the class room. It is hoped that
the planners’ team will get some inputs and suggestions from the student representatives to
improve the next implementation of the program. For the meeting each discussion group
must choose one of his members as their representative.
Meeting of Facilitators
All facilitators will be invited to discuss all the block activities with the planners team on
Monday, May.25.2015 from 11.00 – 12.00 in the class room.
ASSESSMENT METHOD
The student final assessment (CBT) will be held on Wednesday, June,3.2015. The time of
examination will be informed letter. The minimal passing level is 70.
LEARNING PROGRAMS
CURRICULUM
EVIDENCE-BASED MEDICAL PRACTICE
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Study Guide of Evidence-based Medical Practice Block
INTRODUCTION TO THE BLOCK:
An Introduction to Evidence-Based Medical Practice
Curriculum and Evidence- Based Medicine
Raka Widiana
Aims:
1. To develop basic information skills and their integration with the evidence-based
practice in the primary care setting
2. To develop skills to obtain, appraise and use valid and reliable new information using
on-line resources
3. To develop skills to convey electronic and oral communication
Learning Outcomes:
1. Possess skills to gain access to on-line resources
2. Able to critically appraise medical literatures
3. Able to keep patient’s medical records and comprehend ethical and legal
imperatives
4. Able to communicate with colleagues and co-workers using oral, written, and
electronic means
Curriculum Contents:
1. Internet searching
2. Association and causation
3. Principles and applications of statistical analysis
4. Effect size, hypothesis testing and confidence interval
5. Principle of critical appraisal (diagnostic test, clinical trial, prognosis study)
6. Record keeping and Clinical Practice
7. Presentation at the meeting.
ABSTRACTS (I Gde Raka Widiana)
Since the early 1980s, medicine has been undergoing a continuing revolution. It has led to e
fertile development of EBM (evidence based medicine). The practice of EBM (evidence
based medical practice) may be perceived as a meta-field because it involves concepts and
tools from many disciplines, including statistics and bio-statistics, research design, computer
programming, database management, and mathematical modeling. EBMP applies medical
informatics which is used for the purposes of generating, organizing, and making accessible
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and intelligible huge amounts of information. Learning the skills to manage information is of
paramount importance to modern physicians. The computer is an important tool to facilitate
this process. Those who learn the skills of using computers to manage information will have
a greater advantage over those who do not. In daily practice, EBMP is important to the
medical students because can help them to deal with problems which include how to find,
appraise, procure, apply and store the best evidence to diagnose, treat, and determine the
prognosis of patients. Skills in this area may help them to pursue life long, students
centered and problem based education. The teaching of EBMP consists of lecture,
searching articles, critical appraisal and application to problems that may be introduced in
clinical scenarios
SELF DIRECTING LEARNING
Basic knowledge that must be known:
1. Search related articles to the patients problems (diagnose, treat, and prognosis) in
the internet,
2. Critically appraise the related articles and procure from the internet
3. Apply the articles to patents problems
4. Store the best evidence to of patients in your personal electronic library.
SCENARIO
A 25 year old woman was consulted to a nephrologist with lupus GN. The patient had
been treated with methyl prednisolon for 3 months failed to get remission.The patient
has not married hope to get pregnant in the future (contraindicated for CYP).The
doctor knew MMF, a promising drug for LGN available in the market. However the doctor
was not sure the drug is save and effective he would like to find out best evidence in
the internet, but he was not so familiar with EBM and searching in the internet. Please,
help the doctor to find the best evidence to answer his problem
Learning Task:
1. Comprehend above scenario
2. Make clinical (foreground question) using acronym PICO
3. Search articles about therapy (randomized clinical trial) in internet (using
Highwire or other addresses)
4. Procure 3 related articles
5. Appraise and select one best article
6. Apply whenever you find valid and important best evident article
Self Assessment:
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Study Guide of Evidence-based Medical Practice Block
How to make clinical (foreground question) using acronym PICO using above
clinical scenario
How to search articles about therapy (randomized clinical trial) in internet
(using Highwire or other address)
How to procure related articles
How to appraise and select the best article
How to apply the valid and important best evident article to your patient’s
problems
LEARNING OBJECTIVE
Comprehend and skillful making clinical (foreground question) using acronym PICO,
searching articles in internet, procure related articles, appraise, select the best article and
apply the valid and important best evident article to patient’s problems
Scenarios: Problems Identifications with Clinical Questions
Dewi Sutriani Mahalini
Evidence based medical practice (EBMP) is the use of the best scientific evidence to
support the clinical decision making. The identification of the best evidence requires the
construction of an appropriate research question and review of the literature. Many
questions about patient care arise at the patient bedside. You cannot simply enter your
question directly into a database and expect to get an answer. There are 4 steps in EBMP:
1. Formulate an answerable question; 2. Track down the best evidence outcome available;
3. Critically appraise the evidence; 4. Apply the evidence. The first step of EBMP is to
convert an information need into a focused question. This part of the EBMP process is often
overlooked but is essential if a search is to be conducted efficiently. Questions often spring
to mind in a form that makes finding answers in the medical literature a challenge.
Dissecting the question into its component parts and restructuring it so that it is easy to find
the answers is an essential first step in EBMP. EBMP process starts with a clinical scenario
that needs the best answer. One way of defining a focused question is to use the PICO or
PECO framework. "PICO" is the acronym for this 4 part question which consists of the first
letters of Patients, Intervention/Exposure, Comparison, Outcome. PICO doesn't necessarily
work perfectly for all kinds of questions, the main thing is the break down your question into
separate concepts, regardless of the headings you put them under. You can usually identify
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Study Guide of Evidence-based Medical Practice Block
three of the four PICO elements. By far the most common type of clinical question is about
how to treat a disease or condition. In EBMP, treatments and therapies are called
‘interventions’ and such questions are questions of INTERVENTION. However, not all
research questions are about interventions. Other types of questions that may arise are:
ETIOLOGY and RISK FACTOR,
FREQUENCY,
DIAGNOSIS,
PROGNOSIS and
PREDICTION. In each case the PICO method can be used to formulate the question.
SCENARIO
Scenario 1:
A medical student, 19 years old, female came to a doctor with chief complaint of mass in her
left breast with 2 cm in diameter. Based on physical examination, the doctor didn’t sure if the
mass was a malignancy or not. The doctor told her to do mammography but she was
worried that mammography will expose her to x ray. She asked for ultrasonography. She
thought that ultrasonography was safer compared to mammography. The problem was the
doctor didn’t know if ultrasonography can accurately diagnosed breast cancer compared to
mammography.
Can you find the answer for scenario above by search for the best evidence from the
internet?
Scenario 2:
A 40 years old male came to a doctor. He had diabetes mellitus since 5 years ago but he
didn’t attend medical visit regularly. This morning, the patient came to laboratory; he wanted
to check for microalbuminuria, based on his friend’s advice. His friend also had diabetes
mellitus. Apparently, he was positive for microalbuminuria. He was told by a nephrologists
that irbesartan can prevent renal failure in diabetes mellitus patients with microalbuminuria.
He asked this doctor whether it was true or not, and if it was true what was the estimation
for the preventive effect. The doctor didn’t have data to answer that question. Could you
help this doctor to search for best evidence from the internet?
Scenario 3:
A marketing staff from a well-known laboratory came to a doctor to offer a homocysteine
serum test for diabetes mellitus patients. This staff said that this new marker, homocysteine,
can predict the mortality rate in patients if the level in serum was high. The doctor asked for
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Study Guide of Evidence-based Medical Practice Block
an evidence for that statement. The staff didn’t have the answer for the doctor question.
Could you help the marketing staff to search for the evidence from the internet?
Scenario 4:
A 40 years old man who work as a teacher in department of Agriculture, had diabetes
mellitus for 6 years, came to a doctor. The doctor said that he had mild decreased of renal
function (secondary to diabetic nephropathy). The doctor advised him to have low protein
diet and go to a dietitian to ask for a menu that he needed. He asked if the low protein diet
really necessary because other doctor advised him to have a low calories and normal
protein intake to maintain his nutritional status. This doctor told him that low protein diet was
needed to prevent the progression of renal failure. He was confused which doctor was right
and asked for an evidence. The doctor didn’t have an evidence to show his patient. Could
you help this doctor to find evidence from the internet?
Learning task:
Please fill the worksheet as defined in next page.
1. Identify what type of question of the above scenario?
2. Please, build up a clinical research question using PICO !
3. Formulate a clinical research question from scenario above !
Self assessment
1. Please describe the steps in EBMP !
2. Please describe the components of a good clinical questions !
3. Two additional elements of the well built clinical question are the type of question
and the type of study. This information can be helpful in focusing the question and
determining the most apppropriate type of evidence. Please describe the type of
questions and the typeof the study !
WORKSHEET TO BUILT UP CLINICAL RESEARCH QUESTIONS
Scenario # ..................
1. Type of question: Choose one of the term below:
a. Diagnosis
b. Therapy/ intervention
c. Prognosis/ Prediction
d. Etiology/Risk factors
e. Rate/Frequency
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2. Built up a research question using PICO
P Population/problem=...........................................................................................
I Intervention
=............................................................................................
C Comparator/control =...........................................................................................
O Outcome
= ...........................................................................................
3. Clinical research question:
......................................................................................................................................
.
......................................................................................................................................
.
......................................................................................................................................
.
LECTURE 1: Principles of Critical Appraisal
Eka Gunawijaya
What exactly is critical appraisal and what is the difference between "appraising" an article
and simply reading it? If you have been conscientious enough to organize a literature
search, go to the library and copy a promising article, why can't we leave you alone to read
it over a coffee? Why do we ask you to put it through some complex process called critical
appraisal?
Critical appraisal is the process of systematically examining research evidence to assess its
validity, results and relevance before using it to inform a decision. Critical appraisal is an
essential part of evidence-based clinical practice that includes the process of systematically
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Study Guide of Evidence-based Medical Practice Block
finding, appraising and acting on evidence of effectiveness. Critical appraisal allows us to
make sense of research evidence and thus begins to close the gap between research and
practice. The aim of critical appraisal is to identify the quality of an article.
Appraisal is a technique which offers a discipline for increasing the effectiveness of your
reading, by enabling you to quickly exclude papers that are of too poor a quality to inform
practice, and to systematically evaluate those that pass muster to extract their salient
points. Critical appraisal is usually applied to quantitative studies (e.g. "randomized" or
"blinded" controlled trials, crossover trials, meta-analyses or systematic reviews) of the
effectiveness of different health and medical interventions. However, the skills can also be
applied to the assessment of qualitative studies of psychosocial and behavioral
interventions: e.g. observational or interview data obtained from case or cohort studies.
Furthermore, studies on the effectiveness of cognitive, behavioral and other psychosocial
interventions are also being conducted using quantitative research methodologies (e.g.
randomized controlled trials); especially where these interventions are used as part of a
combination therapy, which includes medication.
The medical literature is vast and rapidly expanding. Forays into the library can be
exhausting, as the reader is overwhelmed by the huge number of papers offered. When
reading, someone will cite interesting references, which spur the reader into a lengthy paper
haze. A major hazard of reading is to pursue a subject in too much depth. Instead of
following this haphazard course, the process of reading should be carefully planned to
provide a worthwhile return on the time invested. Establishing control over your reading
means following a number of steps: clarify your reasons for reading; specify your
information need; identify the relevant reports; critically appraise the papers
LECTURE 2: Association and Causation
I B Subanada
When reading a medical literature we sometimes encounter such phrases like “association
with”, “linked to”, and “related to”. The authors have avoided dogmatic statement of “causes”
or “produces”, statement like ”smoking causes lung cancer ” or “birth control pills produce
vein thrombosis”. Association is not necessarily a causality. Here is an analogy: a town has
a large number of unemployed people and a very high crime rate. It does not necessarily
follow that the unemployed are committing the crime. In other word the presence of
unemployment and crime tells us nothing at all about either the presence or direction of
causality. On the other hand, even if we are convince that we have pinpointed the
responsible etiology, we still think that some unsuspected risk factor is actually causing the
disease or an unappreciated co-intervention is responsible for the treatment effect.
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Study Guide of Evidence-based Medical Practice Block
Concept of causation
There are two concepts of causation: First, contributory cause. In most medical
phenomena, there is no single specific cause of a disease. In physics we consider that
metal will expand because of heat and shrink when cold, therefore expansion in a metal is
mathematically caused by heat only as a single cause. Generally, however, most of
diseases are caused by multi-factorial etiology. A risk factor may be a contributory cause.
The second concept of cause is often called necessary cause. In the 19th century, Robert
Koch developed a series of conditions that must be met before a microorganism can be
considered the cause of a disease. Such conditions are related to what is known as Koch’s
Postulates, which include a requirement that organism is always found with the disease. In
the real medical world most of medical phenomena can only be explained by contributory
cause as cause and effect relationship. For instance, even though cigarettes have been well
established as a risk factor, it is a contributory cause for the development of lung cancer, but
cigarette smoking is not necessarily the condition for development of lung cancer, since not
every one with lung cancer has smoked cigarettes. In order to describe the model of cause
and effect relationship, we can construct it into two perspectives:
LECTURE 3: Effect Size, Hypothesis Testing
and Confidence Interval
I.B. Subanada
In analytical studies, investigators seek to determine effect size of the outcome of interest
between variables or between groups and to determine whether there is a statistical
significant of those effect sizes (hypothesis testing).
Most investigations are conducted on only sample or subset of larger group of individuals or
subset of population. Researcher, therefore, are confronted with the question of whether
results of the investigation in the sample would be similar if the investigation included the
entire population or whether chance in the selection of samples (by random sample)
produced unusual results in their sample. Hypothesis testing is a method, which is used to
answer this question. Hypothesis testing is based on null hypothesis, assuming there is no
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Study Guide of Evidence-based Medical Practice Block
difference between groups being compared or there is no relationship between variables. Pvalue, therefore, is the probability that observes data, or outcome, that would have occurred
by chance (just due to sampling variation) when the null hypothesis is true. If P- value is
small, probability of chance would be also small and one may doubt about the null
hypothesis, which thus can be rejected. If P-value is large, the chance may be great and the
data are plausibly consistent with the null hypothesis, which thus cannot be rejected.
LECTURE 4: Principles and Application of
Statistical Analysis
Lanang Sidiartha
Statistical analysis is basically a method to assist us to answer a question under study
(research question). The research question is commonly formulated in a study hypothesis.
A study hypothesis in an analytical study mostly contains one or more independent
variables and one dependent variable. The relationship between independent and
dependent variable is an important issue in statistical analysis. Regarding this issue, it is not
our intention to describe basic statistics, since this subject will be applied for nonstatisticians. Many computer programs packed with statistical soft ware are available and
easy to operate. However, this subject aims to guide the student to understanding the
principle of selecting statistical analysis and interpreting the results and the meaning
parameters in statistics.
Statistics have three purposes in the analysis of health research studies
1. To make estimates of the strength of relationship or magnitude of differences
2. To be used in hypothesis testing, which is allows us to draw inferences about
population from samples, obtained from the same population.
3. To adjust to the influence of confounding variables on these estimates and
inferences.
When selecting a specific statistical method, we must think about variables. A variable
expresses or represents data in the mathematical procedures that are part of statistics.
About variable, we should identify:
1. What the function of each variable, and
2. What type of data is represented by each variable
With regard to the function of variable, we have to distinguish dependent variable from
independent variable. Dependent variable can be identified as the outcome or end-point of
a study. On the other hand, there may be no, one, or several independent variables that
may be identified as risk factors or treatment of interest. The third is confounding variable,
which needs to be taken into account when hypotheses are to be tested and estimates are
to be made.
With regard to the type of data, we have to categorize them as continuous and discrete.
Continuous data are defined as data that provide the possibility of observing any of an
infinite number of equal spaced numerical values between any two points in its range of
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measurement, for examples, blood pressure, serum cholesterol, age, and weight. Discrete
data can only a finite or limited number of values in their range of measurement, for
examples, number of pregnancies, stage of disease, and gender. For each of these
variables, we can select two values between which it is not possible to imagine other value.
For instance, there is no number of hypertension stages between stage 1 and stage 2. Then
data can be defined further by their scale of measurement. Continuous data are measured
on scales, called ratio or interval scales. Discrete data, on the other hand, can be
measured as nominal (such as treatment, gender, race, and eye color) and ordinal scales
(such as stage of the disease and levels of education).
For the purpose of selecting a statistical procedure or interpreting the result of such
procedure, it is important to distinguish between three categories: 1) continuous (contain a
great number of possible values), 2) ordinal (data are ordered one higher than the next and
with at least three), and 3) nominal (only two possible values, such as alive or dead)
variables. Continuous variable can be rescaled to ordinal or nominal variable. For example,
data of blood pressure (in continuous) can be categorized to stage of hypertension (stage 1,
stage 2, and stage 3) as ordinal variable or can be categorized to normal and hypertension
as ordinal variable. Continuous variables contain more information than ordinal variable and
nominal variables. Thus, continuous variables are considered to be at higher level than
nominal variables.
Thus in selecting statistical procedure, the initial steps are:
1. Identify one dependent variable and all independent variables, if present, on the
basis of the research question.
2. Determine for each variable whether it represents continuous, ordinal, or nominal
data.
The three basic statistical procedures: univariable, bivariable and multivariable analysis
LECTURE 5. Methodological and Statistical Principles and
Applications in Descriptive Studies
Eka Gunawijaya
A typical sequence for studying a topic begins with observational studies of a type that is
often called descriptive. This type of study often explore distribution of diseases and healthrelated characteristics in the population (How common is TB patients in Bali) or the
sensitivity and specificity of a diagnostic test. Descriptive studies are usually followed by
analytical study that to evaluate associations to discover cause and effect relationship (Does
TB vaccination lower the incidence of lung TB in Bali). Descriptive studies is characterized
by a set of measurements contains one dependent variable and no independent variable.
A univariate analysis is therefore commonly used to test the data. There are three
application of this method:
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1. Descriptive studies (e.g. case series), only one sample might be presented
2. To determine mean or percentage, point estimation and confidence interval of
particular groups.
3. Comparing two measurements of same characteristic on the same or very similar
individuals (using paired data).
In continuous dependent variable, data are usually assumed to come from population with a
Gaussian distribution. Population mean is an estimate of primary interest and dispersion is
measured by the standard deviation or variance.
For ordinal dependent variable, we do not assume a particular distribution of population
data (distribution free or non-parametric). Estimate of population is median defined as midpoint of a collection of data.
For nominal dependent variable, we determine only the presence or absence of the
condition, and we can estimate the frequency of condition occurs in the population. The data
is assumed to have either a binomial or Poisson distribution.
Estimating the sample size for descriptive study including studies of diagnostic test is based
to that investigator is aiming to calculate descriptive statistics, such as means and
proportions (prevalence, incidence, mortality rate) of particular disease in a single
population.
Descriptive studies commonly report confidence intervals, a range of values about the
sample mean or proportion. A confidence interval is a measure of the precision of the
sample estimate. The investigator sets the confidence level, such as 95% or 99%. An
interval with a greater confidence level (say 99%) is wider, and therefore more likely to
include the true population value, than an interval with a lower confidence level (say 95% or
90%). The width of confidence interval depends on sample size. The more sample size
the .narrower the width.
LECTURE 6. Methodological and Statistical Principles and Applications in
Analytical Studies
Lanang Sidiartha
Based on variable, statistical analysis was divided to bivariate analysis if consist of one
independent variable and one dependent variable and multivariate analysis if consist of one
dependent variable and two or more independent variable or two or more dependent
variable and one independent variable. There are 5 steps to choose appropriate statistical
analysis. First, identified the study hypothesis or research question; second, identified how
many variable was compared; third, identified the variable is it related or unrelated variable;
fourth, identified scale of measurement of data; and fifth, identified the criteria for parametric
test and non-parametric test. Study hypothesis was classified as comparative hypothesis,
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associative hypothesis and correlative hypothesis, each of them has different statistical
analysis. Variable or set of data was classified as related group if it was take from the same
subject.
LECTURE 7: Diagnostic Test
Principles In Critical Appraisal
Sudhana
The fundamental principle of diagnosis testing rests on the belief that individual with a
disease are different from individual without disease and that diagnostic test can distinguish
between these two groups. Ideally, diagnostic test have the following features: (1) all
individuals without the disease under study have one uniform value on the test, (2) all
individuals with the disease have a different but uniform value for the test, thus, (3) all test
results would coincide with the results of diseased or those of the disease-free group. If this
was the situation in reality, then one perfect test could distinguish disease from health.
However, none of these three conditions is usually present. Variation exist is due to same
factors coming from subjects being studied, instrument being used and the observer.
Subject variation is condition of the individual subject being tested may vary from
performance to performance, resulting in changes in phenomenon being assessed.
Instrument variation may occur as a result of technical methods used to perform the test.
Errors may occur because of variations when using the same testing instrument (intrainstrument error) or when using different instrument (inter-instrument error). Observer
variation may occur as a result of the observer who assesses the results. Errors may occur
because of the variation in measurement by the same observer (intra-observer variation) or
error using different observers (inter-observer variation).
The test or criterion used to unequivocally define the disease is known as a gold standard.
The gold standard may be a biopsy, an angiogram, an autopsy, or any established test. The
use of a gold standard tests that is possible to be 100% correct in making a diagnosis.
There might be a cheaper or more convenient test. In diagnostic test, we can ask whether
the test measures up to the gold standard. The investigator classifies each patient as either
having the disease or being disease-free according to the gold standard test, and as
positive or negative by the test being evaluated. They then can calculate the number of
individuals for whom the test and the gold standard test agree and the number for whom
they disagree and display their result in2X2 table as follows:
Total
Test
(+)
(-)
A
C
a+c
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b
d
b+d
a+ b
c+d
a +b+c+d
Predictive
Value
Positive
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Sensitivity
Specificity
Table 1. Table 2 x 2 table
We can determine, a = number of individuals with the disease and test positive: true
positive; b = number of individuals diseased free and test positive: false positive; c =
number of individuals with the disease and test negative: false negative; d = number of
individuals disease-free and test negative: true negative. Then, a + c = total number of
individuals with the disease and b + d = total number of disease-free individuals. From these
components we can calculate sensitivity = a/(a+c) and specificity = d/(b + d) of the test.
If we want to critically appraised an article about diagnosis, we are confronted with V I A,
that stands for valid, important and applicable which appraises the validity, importance and
applicability of the report.
1. The validity will questions whether evidence about the accuracy of a diagnostic test
valid
2. The importance query of whether this (valid) evidence demonstrate an important
ability to accurately distinguish patients who do and don’t have specific disorder
3. The applicability may ask of whether we can apply this valid important diagnostic test
to specific (our) patients.
To step on a critical appraisal, an important issue about the test being studied that we need
to define is what is normal and what is abnormal. Both parameters will be applied to the test
being studied and the gold standard.
We can define the normalcy from six approaches:
1. Gaussian: mean ± 2standard deviations – this one assumes a normal distribution for
all tests and results in all “abnormalities” having the same frequency
2. Percentile 5-95%- has the same basic defect as the Gaussian definition
3. Culturally desirable: when “normal” is that which preferred by society, the role of
medicine gets confused
4. Risk factor: changing risk factor necessarily changing risk
5. Diagnostic: range of result beyond which target disorder became highly probable
6. Therapeutic: range of result beyond which treatment does more good than harm.
Means we have to keep up with the advances in therapy.
Problem may arise with parameters in continuous variables. With such tests, several
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Fig 1. Receiver operating characteristic (ROC) curve for some cutoff points of a continuous
variable.
Values of sensitivity and specificity are possible, depending on the cutoff point chosen to
define a positive test. This trade- off between sensitivity and specificity can be displayed
using a graphic technique. This technique originally developed in electronic equipment
called receiver operating characteristic (ROC) curves. We select several cutoff points and
determine sensitivity and specificity at each point. We then graph the sensitivity (or truepositive rate) on Y-axis as a function of 1-specificity (false-positive rate) on X-axis. An ideal
test is one that reaches the upper left corner of the graph (100% true positives and no false
positives). A worthless test follows the diagonal from the lower left to the upper right
corner (see fig.1). The area under curve (AUC), which does ranges from 0.5 for useless test
to 1.0 for prefect test, is useful summary of the overall accuracy of a test and can be used to
compare the accuracy of two or more tests.
LECTURE 8: Clinical Trial
Principle in Critical Appraisal
Raka Widiana
Some treatments are so clearly advantageous that they require no formal assessment; this
is true of antibiotics for pneumonia and surgery for serious trauma. However, this situation is
relatively rare in clinical medicine. Usually the effects of treatment are much less obvious
and most interventions require research to establish their value. Not only must specific
interventions be shown to do more good than harm among patients who use them (i.e. they
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are theoretically effective or efficacious), but they should also do more good than harm in
patients to whom they are offered (i.e. they should be practically effective). In studies of
efficacy it is advantageous to include who are likely to be compliant. Practical effectiveness
is determined by studying outcome in a group of people offered treatment, only some of who
will be compliant. The most accurate method for measuring effectiveness is a clinical trial.
Clinical trials are a special kind of cohort study in which the conditions of study – selection
of treatment groups, nature of interventions, management during follow up, and
measurement of outcomes – are specified by the investigator for the purpose of making
unbiased comparisons. Clinical trials are more highly controlled and managed than are
cohort studies (observational study). The investigators are conducting an experiment,
analogous to those done in the laboratory. They have taken it upon themselves (of course,
with their patient’s permission) to isolate for study the unique contribution of one factor by
holding constant, as much as possible, all other determinants of the outcome. Hence, other
names for clinical trials are experimental and intervention studies.
We need to define exactly what is meant by ‘clinical trial’; briefly the term may be applied to
any form of planned experiments which involves patients and is designed to elucidate the
most appropriate treatment of future patients with a given medical conditions. Perhaps the
essential characteristic of a clinical trial is that one uses results based on a limited sample of
patients to make inferences about how treatment should be conducted in the general
population of patients who will require treatment in the future. Randomized controlled trials
(RCT) are the standard of excellence for scientific studies of the effects of treatment in
clinical trial.
RANDOMIZED CONTROLLED TRIAL
The structure of an RCT is shown in Figure-1. The patients to be studied are first selected
from a larger number of patients with the condition of interest. They are then divided, using
randomization into two groups of comparable prognosis. One group, called the experimental
or treated group, is exposed to an intervention that is believed to be helpful. The other
group, called a control or comparison group, is treated the same in all ways except that its
members are not exposed to the intervention. The clinical course of both groups is then
observed and any differences in outcome are attributed to the intervention.
The main reason for structuring RCT in this way is to avoid bias (systematic error) when
comparing the respective value of the two or more kinds of treatments. The validity of RCT
depends on how well they result in an equal distribution of all determinants of prognosis,
other than the being tested, in treated and control patients.
Experimental
Intervention
NOT IMPROVED
Population of
patients with
IMPROVED
SAMPLE
the condition
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TIME
OUTCOMES
IMPROVED
Comparison
NOT IMPROVED
Intervention
Figure 1: The structure of a RCT
SAMPLING
Any RCT requires a precise definition of which patients are eligible for inclusion. The early
stages of protocol development may proceed with only a rough outline of the intended type
of patient, but before the RCT gets underway this must be transformed into detailed
specification. The main objective is to ensure that patients in the RCT may be identified as
representative of some future class of patients to whom the RCT finding may be applied as
shown in Figure 2.
The kinds of patients that are included in an RCT determine the extent to which conclusions
can be generalized to other patients. Of the ma