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Identification of clinically important PECODR elements within medical journal abstracts P atient-population-problem, E xposure-intervention, C omparison, O utcome, D uration, & R esults. Martin Dawes, Pierre Pluye, Laura Shea, Roland Grad, Arlene Greenberg, Jian-Yun Nie.

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martin dawes pierre pluye laura shea roland grad arlene greenberg jian yun nie

Identification of clinically important PECODR elements within medical journal abstractsPatient-population-problem, Exposure-intervention, Comparison, Outcome, Duration, & Results

Martin Dawes, Pierre Pluye, Laura Shea, Roland Grad, Arlene Greenberg, Jian-Yun Nie

evidence based practice
Evidence-Based Practice
  • See a patient
  • Have a question
  • Sometimes seek an answer
  • Firstly in secondary sources
    • E-B synopses eg GAC guidelines
  • Secondly in primary sources
    • Medline
questions
Questions

Unstructured = Unanswerable

Make them structured

  • P Do women > 50 years
  • E taking calcium
  • C compared to women taking nothing
  • O have fewer hip fractures
  • D over 5 years
  • R NNT of 30
problems solutions question
PROBLEMS - SOLUTIONS - QUESTION

Problems

  • Too much information
  • Information keeps changing

Solutions

  • Filters for evidence
  • MESH & PubMed clinical queries

Questions

  • Would PECODR indexing the clinical literature help me find information for my patient?
  • Can we identify PECODR elements in abstracts?
  • Would the words or groups of words used help us to automatically do this?
methods
METHODS

Pilot study

Convenience sample (N = 40)

  • 20 research articles (Evidence Based Medicine synopses)
  • 20 corresponding abstracts(PubMed)

Converted the information into a text file

Analyse the content: Qualitative and Quantitative

methods6
Methods
  • 6 themes defined: P, E, C, O, D, R
  • Extract text and allocate to a themes
    • extracts made from a word or words,
      • made up from a series of characters (the gold standard denominator)
  • Independently by two researchers
  • 10 rules developed iteratively

eg exclusive assignment « 1 extract 1 theme »

coding
Coding

<R> Despite major differences

<O> in blood pressure lowering,

<R> there were no

<O> outcome

<R> differences

<E> between atenolol

<C> and placebo in the four studies,

<P> comprising 6825 patients,

<D> who were followed up for a mean of 4·6 years

Should this be coded under C?

quantitative analysis9
Quantitative Analysis

So the method of coding seems to work

6 « PECODR » themes

quantitative analysis10
QuantitativeAnalysis

1. For each theme PECODR

Identification (inductive) of potential patterns or series of words

Compare theme patterns

comparison, compare, compared, comparing, etc,

2. For each pattern

Only for those with a pattern frequency of > 70% found in the themes

results pecodr by abstracts synopses
Results: PECODR by abstracts & synopses

PECODR exists in abstracts

docs extracts docs extracts

P 19 89 20 116

E 20 163 20 180

C 18 92 19 120

O 20 169 20 187

D 15 36 18 45

R 20 210 20 187

Total 759 835

results
RESULTS
  • P = Patient-population-problem

No pattern: Example, diabetic

E = Exposure-intervention

No pattern: Example, Amoxil

results13

4 more occurrences of the word “comparing” were in parts of the text that were not C extracts

All were in C extracts

RESULTS
  • C = Comparison: number of extracts assigned to C with C pattern and % of total C extracts found not assigned to C
results14
RESULTS
  • O = « Outcome »: number of extracts assigned to O with O pattern and % of total O extracts found not assigned to O
results15
RESULTS
  • R = Results: number of extracts assigned to R with R pattern and % of total R extracts found not assigned to R
results16
RESULTS

R (more)

Significance

results summary
Results Summary

Presence of text or text patterns

  • PECODR elements are present in the majority of abstracts with the exception of Duration (75%)

Patterns of PECODR

  • P & E = Medical or Drug Terms (thesaurus)
  • The other element related extracts contain some patterns
discussion
DISCUSSION

Limits

  • Pilot Study (N=40)
  • Exploratory study (rules developed iteratively for text extraction/ qualitative pattern identification)
  • Further Research
  • Textual Analysis using clever software with UdM to better identify patterns
  • Larger sample of papers
  • Do GP’s want a PECODR search engine?
conclusion
CONCLUSION
  • Possible standard textual patterns (lexico-semantics) may help automatically determine PECODR elements
  • If this is possible we may be able to develop a prototype of new technology for automatic information retrieval (aspectual Search Engine)
  • To index the clinical information according to needs' for the users (eg family practitioners)
  • That will help people answer clinical questions…maybe
slide20

Cost Effectiveness 1,300

Problem/Patient

Select

Exposure

Select Outcome

Select Duration

Old/Adult/Young

Diagnosis12,000

Heart attacks 2,300

Harm 1,780

Insulin 12,000

Mortality 60

>3 years n=20

Antihypertensive 6,000

DIABETIC

Therapy 28,000

Oral Hypoglycaemics 1,780

  • NNT 25 4.6 years
  • NNT 34 4.2 years
  • N/A
  • NNT 54 1.8 years
  • NNT 35 N/A

Prognosis 2,000

Male/Female

Aetiology 4000

Number under each heading represents articles

Martin Dawes