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DATA COLLECTION
• Clinical audit requires
effective and accurate
information hence,
requires effective data
collection strategy..
Aim of the data collection
To test against the set
standards
To measure
performance.
Before designing data collection
Consider
• what data ?
• where is the data?
• who will collect?
• How it will be collected
?
• How much ( number)?
• How long should be
collected.?
• QUANTITATIVE OR
QUALITATIVE DATA?
•
Decide how to collect..
• Prospective?
• Retrospective.?
• Topic of the audit
influences the choice of
the method to be used
• It is also important that
your sample contains
current or recent
patients.
Clinical audit is about
improvement
we cannot change the
past but you can
change the future.
Ways of data collection
• Collecting from patient’s
records
• interviewing patients or
staffs by issuing
questionnaires or by
electronic recording
• Recording when an event
occurs
• Observing present practices
• looking at present policies
Questionnaires
Source of data..
• To be clear where to
look for the data
• Patients record
• Hospital information
system.
• Registers maintained in
dept..
HOW MANY CASES TO AUDIT..
• Clinical audit, however,
looks in to ‘what is
happening here?’ so
the answer does not
have to be as definitive
as it would need to be
in research.
• For research projects it
is very important that a
scientifically valid
sample is selected
SAMPLING METHODS
• Simple random sampling
• Consecutive sampling
or
• convenient sampling
An example ..
• A primary care team
planned an audit about
the care of patients
presenting with
hypertension..
key criterion:
Those who were on
treatment should have
their BP checked and
their result should have
been below 150/90 on
three occasion in the
past one year.
Data sheet
• necessary to satisfy
your audit aim.
• should enable you to
measure practice
against your audit
standards.
• So, do not collect
excess data..
Data collection form
• To be designed
according to standards.
• Specific instruction
needed if collected by
other person.
• Not to reveal patient
identity.
Patient
number(
mock
number)
pain scale Time of
evaluation
time of
analgesia
SAMPLE SIZE
sample ..
Referral forms are honored with in stipulated time in the medical
ward
standard 1: 100% of the forms are appropriately filled
standard : 2:95% of the urgent referrals with in 2 hours.
Standard: 3 : 95%routine honored with in 24 hours
Patient
details
( Bar
code)
Type of
the
refferal
Referral
form filled
appropriate
ly
Time at
which the
referral
form sent
Time at which
its honored
R/U y/n
Do a pilot study with your data
collection form
Why piloting ?
• To make sure it works..
• May require some
instructions
• some questions may be
ambiguous
• parameters may not be
relevant
• difficult to complete?
• may help us to redesign a
simple data collection form
Data analysis
• Descriptive stat
(numerical data)
Statistical tests( before
and after comparison)
Qualitative analysis
• Percentage of cases
meeting each standard-
1
• Percentage of cases
meeting each standard-
2.
Messages from data analysis
Discuss the results or out come....
• THANK YOU
clinical audit

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clinical audit

  • 2. • Clinical audit requires effective and accurate information hence, requires effective data collection strategy..
  • 3. Aim of the data collection To test against the set standards To measure performance.
  • 4. Before designing data collection Consider • what data ? • where is the data? • who will collect? • How it will be collected ? • How much ( number)? • How long should be collected.?
  • 6. Decide how to collect.. • Prospective? • Retrospective.?
  • 7. • Topic of the audit influences the choice of the method to be used
  • 8. • It is also important that your sample contains current or recent patients. Clinical audit is about improvement we cannot change the past but you can change the future.
  • 9. Ways of data collection • Collecting from patient’s records • interviewing patients or staffs by issuing questionnaires or by electronic recording • Recording when an event occurs • Observing present practices • looking at present policies
  • 11.
  • 12. Source of data.. • To be clear where to look for the data • Patients record • Hospital information system. • Registers maintained in dept..
  • 13.
  • 14.
  • 15. HOW MANY CASES TO AUDIT.. • Clinical audit, however, looks in to ‘what is happening here?’ so the answer does not have to be as definitive as it would need to be in research. • For research projects it is very important that a scientifically valid sample is selected
  • 16.
  • 17. SAMPLING METHODS • Simple random sampling • Consecutive sampling or • convenient sampling
  • 18. An example .. • A primary care team planned an audit about the care of patients presenting with hypertension.. key criterion: Those who were on treatment should have their BP checked and their result should have been below 150/90 on three occasion in the past one year.
  • 19. Data sheet • necessary to satisfy your audit aim. • should enable you to measure practice against your audit standards. • So, do not collect excess data..
  • 20. Data collection form • To be designed according to standards. • Specific instruction needed if collected by other person. • Not to reveal patient identity.
  • 21.
  • 22. Patient number( mock number) pain scale Time of evaluation time of analgesia
  • 23.
  • 25. sample .. Referral forms are honored with in stipulated time in the medical ward standard 1: 100% of the forms are appropriately filled standard : 2:95% of the urgent referrals with in 2 hours. Standard: 3 : 95%routine honored with in 24 hours Patient details ( Bar code) Type of the refferal Referral form filled appropriate ly Time at which the referral form sent Time at which its honored R/U y/n
  • 26. Do a pilot study with your data collection form
  • 27. Why piloting ? • To make sure it works.. • May require some instructions • some questions may be ambiguous • parameters may not be relevant • difficult to complete? • may help us to redesign a simple data collection form
  • 28. Data analysis • Descriptive stat (numerical data) Statistical tests( before and after comparison) Qualitative analysis
  • 29. • Percentage of cases meeting each standard- 1 • Percentage of cases meeting each standard- 2.
  • 30.
  • 31. Messages from data analysis
  • 32. Discuss the results or out come....