title: Developing consensus measures for global programs: lessons from the Global Alliance for Chronic Diseases Hypertension research program.
abstract: 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.
  
  
  
  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.
  
  
  
  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.
authors.affiliation: Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia. Michaela.riddell@monash.edu.
authors.forename: Michaela A
authors.initials: MA
authors.lastname: Riddell
authors.affiliation: School of Nursing, Faculty of Health Science, University of Ottawa, Ottawa, Canada.
authors.forename: Nancy
authors.initials: N
authors.lastname: Edwards
authors.affiliation: Queen Mary University of London, London, UK.
authors.forename: Simon R
authors.initials: SR
authors.lastname: Thompson
authors.affiliation: Universidad Peruana Cayetano Heredia, Lima, Peru.
authors.forename: Antonio
authors.initials: A
authors.lastname: Bernabe-Ortiz
authors.affiliation: The George Institute for Global Health - India, Hyderabad, India.
authors.forename: Devarsetty
authors.initials: D
authors.lastname: Praveen
authors.affiliation: The George Institute for Global Health - Sydney, Sydney, Australia.
authors.forename: Claire
authors.initials: C
authors.lastname: Johnson
authors.affiliation: South African Medical Research Council, Cape Town, South Africa.
authors.forename: Andre P
authors.initials: AP
authors.lastname: Kengne
authors.affiliation: University of Ottawa Heart Institute, Toronto, Canada.
authors.forename: Peter
authors.initials: P
authors.lastname: Liu
authors.affiliation: Population Health Research Institute, Hamilton, Canada.
authors.forename: Tara
authors.initials: T
authors.lastname: McCready
authors.affiliation: Population Health Research Institute, Hamilton, Canada.
authors.forename: Eleanor
authors.initials: E
authors.lastname: Ng
authors.affiliation: Population Health Research Institute, Hamilton, Canada.
authors.forename: Robby
authors.initials: R
authors.lastname: Nieuwlaat
authors.affiliation: Medical University of South Carolina, Charleston, USA.
authors.forename: Bruce
authors.initials: B
authors.lastname: Ovbiagele
authors.affiliation: Department of Medicine, University of Ibadan, Ibadan, Nigeria.
authors.forename: Mayowa
authors.initials: M
authors.lastname: Owolabi
authors.affiliation: The George Institute for Global Health, University of Sydney, Sydney, Australia.
authors.forename: David
authors.initials: D
authors.lastname: Peiris
authors.affiliation: Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
authors.forename: Amanda G
authors.initials: AG
authors.lastname: Thrift
authors.affiliation: Sunnybrook Health Sciences Center, Toronto, Canada.
authors.forename: Sheldon
authors.initials: S
authors.lastname: Tobe
authors.affiliation: UniversitiTeknologi MARA, Selangor, Malaysia.|UCSI University, Selangor, Malaysia.
authors.forename: Khalid
authors.initials: K
authors.lastname: Yusoff
mesh_terms: D002908:Chronic Disease / Q000628:therapy*; D032921:Consensus; D003299:Cooperative Behavior; D014943:Global Health; D006801:Humans; D006973:Hypertension; D012108:Research Personnel
keywords: Consensus Measures; Hypertension; Implementation; Implementation Context; Low and middle income countries