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Developing consensus measures for global programs: Lessons from the Global Alliance for Chronic Diseases Hypertension research program

  • On behalf of the GACD Hypertension Research Programme
  • Monash University
  • University of Ottawa
  • Queen Mary University of London
  • Universidad Peruana Cayetano Heredia
  • National Food and Nutrition Centre
  • The George Institute for Global Health
  • South African Medical Research Council
  • University of Ottawa Heart Institute
  • Population Health Research Institute, Ontario
  • McMaster University
  • Medical University of South Carolina
  • Tulane University
  • College of Medicine, University of Ibadan
  • University Hospital
  • University of Sydney
  • Sunnybrook Health Sciences Centre
  • Universiti Teknologi MARA
  • UCSI University
  • University of Ottawa
  • Mildmay Uganda
  • Global Evaluative Sciences
  • Makerere University
  • Intra Health Rwanda
  • Universidad Autonoma de Bucaramanga
  • Rwanda Ministry of Health
  • Universidad de Santander
  • National Institute of Health
  • London School of Hygiene and Tropical Medicine
  • Ministry of Health
  • Libin Cardiovascular Institute
  • Kilimanjaro Christian Medical College
  • World Health Organization
  • Northern Ontario School of Medicine
  • Queen's University School of Medicine
  • Changzhi Medical College
  • Peking University Health Science Center
  • Deakin University
  • University of the Witwatersrand, Johannesburg
  • University of Warwick
  • Rishi Valley Education Centre - Rural Health
  • Sree Chitra Tirunal Institute for Medical Sciences and Technology
  • Christian Medical College Hospital
  • Emory University
  • Public Health Foundation of India
  • Imperial College London
  • All India Institute of Medical Sciences, New Delhi
  • Samoan Ministry of Health
  • Pacific Research Centre for the Prevention of Obesity and Non-communicable Diseases (C-POND)
  • Loyola University Chicago Stritch School of Medicine
  • Johns Hopkins University
  • Kwame Nkrumah University of Science and Technology
  • New York University Grossman School of Medicine
  • Duke University
  • Brown University
  • Duke-NUS Medical School
  • Icahn School of Medicine at Mount Sinai
  • Moi University
  • Indiana University-Purdue University Indianapolis
  • Institute for Clinical Effectiveness and Health Policy
  • Federal Medical Centre Nigeria
  • University of Ibadan
  • University of California la Jolla
  • National Institute of Health

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Background: The imperative to improve global health has prompted transnational research partnerships to investigate common health issues on a larger scale. The Global Alliance for Chronic Diseases (GACD) is an alliance of national research funding agencies. To enhance research funded by GACD members, this study aimed to standardise data collection methods across the 15 GACD hypertension research teams and evaluate the uptake of these standardised measurements. Furthermore we describe concerns and difficulties associated with the data harmonisation process highlighted and debated during annual meetings of the GACD funded investigators. With these concerns and issues in mind, a working group comprising representatives from the 15 studies iteratively identified and proposed a set of common measures for inclusion in each of the teams' data collection plans. One year later all teams were asked which consensus measures had been implemented. Results: Important issues were identified during the data harmonisation process relating to data ownership, sharing methodologies and ethical concerns. Measures were assessed across eight domains; demographic; dietary; clinical and anthropometric; medical history; hypertension knowledge; physical activity; behavioural (smoking and alcohol); and biochemical domains. Identifying validated measures relevant across a variety of settings presented some difficulties. The resulting GACD hypertension data dictionary comprises 67 consensus measures. Of the 14 responding teams, only two teams were including more than 50 consensus variables, five teams were including between 25 and 50 consensus variables and four teams were including between 6 and 24 consensus variables, one team did not provide details of the variables collected and two teams did not include any of the consensus variables as the project had already commenced or the measures were not relevant to their study. Conclusions: Deriving consensus measures across diverse research projects and contexts was challenging. The major barrier to their implementation was related to the time taken to develop and present these measures. Inclusion of consensus measures into future funding announcements would facilitate researchers integrating these measures within application protocols. We suggest that adoption of consensus measures developed here, across the field of hypertension, would help advance the science in this area, allowing for more comparable data sets and generalizable inferences.

Original languageEnglish
Article number17
JournalGlobalization and Health
Volume13
Issue number1
DOIs
StatePublished - 15 Mar 2017
Externally publishedYes

Keywords

  • Consensus Measures
  • Hypertension
  • Implementation
  • Implementation Context
  • Low and middle income countries

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