Skip to content. | Skip to navigation

Personal tools

Navigation

You are here: Home / Universities / McGill University / PECODR

PECODR

Abstract

Background: Information retrieval in primary care is becoming more difficult as the volume of medical information held in electronic databases expands. The lexical structure of this information may permit automatic indexing and improved retrieval.

Objective: To determine the possibility of identifying the key elements of clinical studies, namely  Patient-Population-Problem, Exposure-Intervention, Comparison, Outcome, Duration, & Results (PECODR), from abstracts of medical journals.

Methods: We used a convenience sample of 20 synopses from the journal Evidence-Based Medicine (EBM) and their matching original journal article abstracts obtained from PubMed. Three independent primary care professionals identified PECODR related extracts of text. Rules were developed to define each PECODR element and the selection process of characters, words, phrases and sentences. From the extracts of text related to PECODR elements, potential lexical patterns that might help identify those elements were proposed and assessed using NVivo software.

Results: A total of 835 PECODR related text extracts containing 41,263 individual text characters were identified from 20 EBM journal synopses. There were 759 extracts in the corresponding Pub Med abstracts containing 31,947 characters. PECODR elements were found in nearly all abstracts and synopses with the exception of duration. There was agreement on 86.6% of the extracts from the 20 EBM synopses and 85.0% on the corresponding Pub Med abstracts. After consensus this rose to 98.4% & 96.9% respectively. We found potential text patterns in the Comparison, Outcome & Results elements of both EBM synopses and PubMed abstracts. Some phrases and words are used frequently and are specific for these elements in both synopses and abstracts.
Conclusions: Results suggest a PECODR related structure exists in medical abstracts and that there may be lexical patterns specific to these elements. More sophisticated computer-assisted lexical-semantic analysis may refine these results, and pave the way to automate a PECODR indexing, and improve information retrieval in primary care.

Dawes, M., Pluye, P., Shea, L., Grad, R., Greenberg, A., and Nie, J.-Y. (2007). The identification of clinically important elements within medical journal abstracts: PatientPopulationProblem, ExposureIntervention, Comparison, Outcome, Duration and Results (PECODR). Informatics in Primary Care 15, 9-16.

PECODR slide show

PECODR (slide)

 

 

Proposed further research

 

Document Actions

« August 2017 »
August
MoTuWeThFrSaSu
123456
78910111213
14151617181920
21222324252627
28293031