The WHO-ILAR COPCORD Bhigwan (India) model: foundation for a future COPCORD design and data repository

Arvind Chopra1

  • 1Bharati Hospital & Medical College Center for Rheumatic Diseases, Hermes Elegance, 1988 Convent St., Camp, Pune 411 001, India. crdp@vsnl.net

Clinical Rheumatology
|April 14, 2006
PubMed

Insights

The Community-Oriented Program for Control of Rheumatic Diseases (COPCORD) collects data on rheumatic musculoskeletal disorders (RMS). A revised, standardized COPCORD model is proposed to improve global data collection and control strategies.

Area of Science:

  • Rheumatology
  • Public Health
  • Epidemiology

Background:

  • The Community-Oriented Program for Control of Rheumatic Diseases (COPCORD) was established by the International League of Associations for Rheumatology (ILAR) and the World Health Organization (WHO) to address the global burden of rheumatic musculoskeletal disorders (RMS).
  • Current COPCORD initiatives collect symptom data (pain, disability) during population surveys, with potential follow-up stages for education, risk factor identification, and control strategies.
  • While several regions have implemented COPCORD, variations in methodology (sample size, data collection, classification) necessitate standardization.

Purpose of the Study:

  • To highlight the need for a standardized COPCORD model to improve global data collection on rheumatic musculoskeletal disorders (RMS).
  • To propose a revised COPCORD model based on the successful COPCORD Bhigwan (India) fast-track initiative.
  • To advocate for collaboration between WHO-ILAR COPCORD and the Bone and Joint Decade (BJD) for a unified approach to controlling RMS.

Main Methods:

  • Review of existing COPCORD methodologies and their variations across different countries and regions.
  • Analysis of the COPCORD Bhigwan model as a successful fast-track approach for collecting significant data on rheumatic disorders.
  • Proposal for a future COPCORD design incorporating a uniform, standardized core program with regional flexibility and a longitudinal observational phase.

Main Results:

  • Significant data on rheumatic disorders has been generated through COPCORD initiatives, particularly the long-running COPCORD Bhigwan model.
  • Identified inconsistencies in current COPCORD methodologies, including differences in sample size, data collection techniques, and classification systems.
  • The need for a centralized COPCORD data repository and a unified approach to RMS control has been established.

Conclusions:

  • The current global COPCORD model requires revision to ensure standardization and enhance data comparability.
  • A proposed future COPCORD design emphasizes a standardized core program with regional adaptability, incorporating recent rheumatological advances and socioeconomic considerations.
  • Collaboration between global initiatives like WHO-ILAR COPCORD and BJD is crucial for effectively controlling the burden of rheumatic musculoskeletal disorders worldwide.

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