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COLLECTING AND HANDLING DATA
Dr. Zahraa Mohammed Mustafa
Public health and community medicine Lecturer
Faculty of Medicine, Beni Suef University
“I never guess. It is a capital
mistake to theorize before one has
data. Insensibly one begins to twist
facts and theories, instead of
theories to suit facts.
”
-- Sir Arthur Conan Doyle
DECISION-
MAKING IN
CLINICAL
PRACTICE
Much decision- making in clinical practice is based upon the interpretation of
history, examination, and investigations. Effective diagnosis requires a good
quality history (asking the right questions) and examination (being skilled in
eliciting clinical signs), and for this reason there is a big focus in undergraduate
and postgraduate clinical training on these skills. If a doctor ‘cuts corners’ with
their history taking, or has a sloppy examination technique, then key symptoms
and signs may be missed, leading to incorrect diagnosis and inappropriate
clinical management.
The science of
STATISTICS
deals with DATA
• Data comes from the Latin word “datum” which means “something
given”
• It refers to individual pieces of information
• It is measures without meaningful knowledge
• We use data to reach information and gain knowledge
DATA ‫المعطيات‬
/
‫البيانات‬
“A variable is any quantity that varies. Any attribute, phenomenon or
event that can have different values”
 notated by capital letters such as X and Y, is a characteristic of
interest for each person or thing in a population.
 Variables may be numerical or categorical.
 Numerical variables take on values with equal units such as weight
in pounds and time in hours.
 Categorical variables place the person or thing into a category.
Variable
‫المتغير‬
QUALITATIVE OR CATEGORICAL VARIABLES:
Where the answer to the question is a category from many legitimate mutually exclusive categories
appropriate to be an answer.
Example:
When asked about the Blood group, there are 4 possible appropriate mutually exclusive answers A, B, AB
and O and the individual will choose the one that applies to him.
(Mutually exclusive = cannot occur together, i.e., you cannot have more than one of these Blood groups).
Categorical variables may be one of three types:
The categories you
choose from have no
meaningful order.
Examples includes Blood
groups, residence,
nationality
There are only two categories
you choose from. Examples
include Sex (male-female),
Disease status (healthy-
disease), and Current
smoking status (smoker-
nonsmoker).
The categories you choose
from have a meaningful order.
Examples include Educational
level (illiterate, Primary,
Secondary and University),
Cancer stage (A1, A2, B1, B2,
C1 …etc.)
QUANTITATIVE VARIABLES:
Where the answer to the question is a number that may be one of two types
a) Discrete quantitative variables
b) Continuous quantitative variables
Integers without fractions
= Enumerated observation.
Examples include the number
of children per family, number of
molar teeth in the mouth,
number of beds in a hospital,
and RBCs count.
= Numbers with fractions
= Measurements.
Examples include
systolic blood pressure,
age, height, and fasting
blood sugar.
If there is a true zero (height, age and
weight), the variable is called
If the zero is relative (zero Degree
Centigrade or Zero IQ score)
Paper forms
Electronic data
capture
DR. ZAHRAA MOHAMMED MUSTAFA

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Lec.6 Data collection Dr Zahraa.pptx

  • 1. COLLECTING AND HANDLING DATA Dr. Zahraa Mohammed Mustafa Public health and community medicine Lecturer Faculty of Medicine, Beni Suef University
  • 2. “I never guess. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts and theories, instead of theories to suit facts. ” -- Sir Arthur Conan Doyle
  • 4. Much decision- making in clinical practice is based upon the interpretation of history, examination, and investigations. Effective diagnosis requires a good quality history (asking the right questions) and examination (being skilled in eliciting clinical signs), and for this reason there is a big focus in undergraduate and postgraduate clinical training on these skills. If a doctor ‘cuts corners’ with their history taking, or has a sloppy examination technique, then key symptoms and signs may be missed, leading to incorrect diagnosis and inappropriate clinical management.
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  • 9. • Data comes from the Latin word “datum” which means “something given” • It refers to individual pieces of information • It is measures without meaningful knowledge • We use data to reach information and gain knowledge DATA ‫المعطيات‬ / ‫البيانات‬
  • 10. “A variable is any quantity that varies. Any attribute, phenomenon or event that can have different values”  notated by capital letters such as X and Y, is a characteristic of interest for each person or thing in a population.  Variables may be numerical or categorical.  Numerical variables take on values with equal units such as weight in pounds and time in hours.  Categorical variables place the person or thing into a category. Variable ‫المتغير‬
  • 11. QUALITATIVE OR CATEGORICAL VARIABLES: Where the answer to the question is a category from many legitimate mutually exclusive categories appropriate to be an answer. Example: When asked about the Blood group, there are 4 possible appropriate mutually exclusive answers A, B, AB and O and the individual will choose the one that applies to him. (Mutually exclusive = cannot occur together, i.e., you cannot have more than one of these Blood groups).
  • 12. Categorical variables may be one of three types: The categories you choose from have no meaningful order. Examples includes Blood groups, residence, nationality There are only two categories you choose from. Examples include Sex (male-female), Disease status (healthy- disease), and Current smoking status (smoker- nonsmoker). The categories you choose from have a meaningful order. Examples include Educational level (illiterate, Primary, Secondary and University), Cancer stage (A1, A2, B1, B2, C1 …etc.)
  • 13. QUANTITATIVE VARIABLES: Where the answer to the question is a number that may be one of two types a) Discrete quantitative variables b) Continuous quantitative variables
  • 14. Integers without fractions = Enumerated observation. Examples include the number of children per family, number of molar teeth in the mouth, number of beds in a hospital, and RBCs count. = Numbers with fractions = Measurements. Examples include systolic blood pressure, age, height, and fasting blood sugar. If there is a true zero (height, age and weight), the variable is called If the zero is relative (zero Degree Centigrade or Zero IQ score)
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Editor's Notes

  1. Similarly, for test results to be reliable, they need to have been obtained in the correct manner. A blood test may need to be collected at a particular time (e.g. fasting sample), in a particular type of container, or transported in a particular way (e.g. blood ammonia samples need to be placed immediately on ice). Clinicians need to find out any particular requirements in advance of obtaining samples to ensure they can be processed and that the results are reliable.
  2. The same principles apply for collecting and handling data— the ability to perform statistical tests, and the quality of the results obtained, depends upon the data collected. High- quality data collection is a skill, and the way in which data are collected may affect the final results. It is important to consider what tests and analyses will be done prior to collecting data, to ensure the right data are obtained, and that these data are handled correctly.
  3. When the research question and study design are settled and we have decided which data to collect, we need to design the data collection forms. These are needed to provide a written or electronic record of the data collected and to facilitate data analysis using a computer. The forms can be paper or electronic. In the following sections, we give some specific and general guidance for paper and electronic forms.
  4. Paper forms • Try to make them clear and easy to fill out • Allow adequate space for inserting numbers and text • Consider using a colour other than white for the form to make them more attractive to work with • When more than one form is required, such as when the study involves follow- up on several occasions, it can be helpful to use a different colour for each occasion to help with tracking and filing • Long forms can be off- putting for people filling them in so consider how to make the form as short as possible while including all necessary questions
  5. Electronic data capture • Make sure each original data entry form or data collection session is kept for later checking. Save any edited forms in new files • Make sure each page of a form, or each form where there are several, can be uniquely identified with a particular subject so that they can be merged together correctly later • Keep careful audit trails with dates and file names and back up all data • Keep careful track of the master copy of data from where editing and/or additional data collection is taking place • Use filters to jump to later questions where particular questions are not applicable • Build in checks for impossible and/ or inconsistent values wherever possible to avoid data recording errors
  6. Data quality It is critical that data quality is monitored and that this happens as the study progresses. It may be too late if problems are only discovered at the analysis stage. If checks are made during the data collection then problems can be corrected. More frequent checks may be worthwhile at the beginning of data collection when processes may be new and staff may be less experienced.
  7. Data entry Introduction Data from research studies need to be coded before data are entered into a computer for statistical analysis so that all the data are numerical. This means that qualitative data, for example, data that require a ‘yes’ or ‘no’ reply, have to be converted to a number such as 1 for ‘yes’ and 0 for ‘no’