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

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

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...

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Published in:Globalization and Health
Main Author: Riddell M.A.; Edwards N.; Thompson S.R.; Bernabe-Ortiz A.; Praveen D.; Johnson C.; Kengne A.P.; Liu P.; McCready T.; Ng E.; Nieuwlaat R.; Ovbiagele B.; Owolabi M.; Peiris D.; Thrift A.G.; Tobe S.; Yusoff K.; de Villiers A.; He F.; MacGregor G.; Jan S.; Neal B.; Chow C.; Joshi R.; MacMahon S.; Patel A.; Rodgers A.; Webster R.; Keat N.K.; Attaran A.; Mills E.; Muldoon K.; Yaya S.; Featherstone A.; Mukasa B.; Forrest J.; Kalyesubula R.; Kamwesiga J.; Lopez P.C.; Tayari J.-C.; Lopez P.; Casas J.L.; McKee M.; Zainal A.O.; Yusuf S.; Campbell N.; Kilonzo K.; Marr M.; Yeates K.; Feng X.; Yuan J.; Li X.; Lin C.-P.; Yan L.; Zhang J.; Wu Y.; Ma J.; Wang H.; Ma Y.; Nowson C.; Moodie M.; Goudge J.; Kabudula C.; Limbani F.; Masilela N.; Myakayaka N.; Gómez-Olivé F.X.; Thorogood M.; Arabshahi S.; Evans R.; Mahal A.; Oldenburg B.; Srikanth V.; Heritier S.; Kalyanram K.; Kartik K.; Suresh O.; Maulik P.; Salam A.; Sudhir T.; Thankappan K.; Thirunavukkarasu S.; Thomas N.; Clifford G.; Prabhakaran D.; Thom S.; Shivashankar R.; Mohan S.; Reddy K.S.; Krishnan A.; Faletoese S.; Ieremia M.; Ulberg C.; Viali S.; Pillay A.; Sukhu A.; Schultz J.; Siitia J.; Snowdon W.; Cárdenas M.K.; Gilman R.H.; Miranda J.J.; Diez-Canseco F.; Ponce-Lucero V.; Sacksteder K.; Gyamfi J.; Ogedegbe O.; Apusiga K.; Cooper R.; Ntim M.; Plange-Rhule J.; Rotich J.; Binanay C.; Finkelstein E.; Bloomfield G.; DeLong A.; Hogan J.; Inui T.; Naanyu V.; Fuster V.; Horowitz C.; Kimaiyo S.; Kofler C.; Menya D.; Kamano J.H.; Vedanthan R.; Velazquez E.; Were M.; Dolan J.; Irazola V.; Krousel-Wood M.; Augustovski F.; Beratarrechea A.; Chen J.; He J.; Mills K.; Poggio R.; Rubinstein A.; Shi L.; Webber L.; Akinyemi R.; Arulogun O.; Hurst S.; Waddy S.; Warth S.; Gebregziabher M.; Uvere E.
Format: Article
Language:English
Published: BioMed Central Ltd 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015260273&doi=10.1186%2fs12992-017-0242-8&partnerID=40&md5=7c1790c09fb595d0c6e6662dfa08963d
id 2-s2.0-85015260273
spelling 2-s2.0-85015260273
Riddell M.A.; Edwards N.; Thompson S.R.; Bernabe-Ortiz A.; Praveen D.; Johnson C.; Kengne A.P.; Liu P.; McCready T.; Ng E.; Nieuwlaat R.; Ovbiagele B.; Owolabi M.; Peiris D.; Thrift A.G.; Tobe S.; Yusoff K.; de Villiers A.; He F.; MacGregor G.; Jan S.; Neal B.; Chow C.; Joshi R.; MacMahon S.; Patel A.; Rodgers A.; Webster R.; Keat N.K.; Attaran A.; Mills E.; Muldoon K.; Yaya S.; Featherstone A.; Mukasa B.; Forrest J.; Kalyesubula R.; Kamwesiga J.; Lopez P.C.; Tayari J.-C.; Lopez P.; Casas J.L.; McKee M.; Zainal A.O.; Yusuf S.; Campbell N.; Kilonzo K.; Marr M.; Yeates K.; Feng X.; Yuan J.; Li X.; Lin C.-P.; Yan L.; Zhang J.; Wu Y.; Ma J.; Wang H.; Ma Y.; Nowson C.; Moodie M.; Goudge J.; Kabudula C.; Limbani F.; Masilela N.; Myakayaka N.; Gómez-Olivé F.X.; Thorogood M.; Arabshahi S.; Evans R.; Mahal A.; Oldenburg B.; Srikanth V.; Heritier S.; Kalyanram K.; Kartik K.; Suresh O.; Maulik P.; Salam A.; Sudhir T.; Thankappan K.; Thirunavukkarasu S.; Thomas N.; Clifford G.; Prabhakaran D.; Thom S.; Shivashankar R.; Mohan S.; Reddy K.S.; Krishnan A.; Faletoese S.; Ieremia M.; Ulberg C.; Viali S.; Pillay A.; Sukhu A.; Schultz J.; Siitia J.; Snowdon W.; Cárdenas M.K.; Gilman R.H.; Miranda J.J.; Diez-Canseco F.; Ponce-Lucero V.; Sacksteder K.; Gyamfi J.; Ogedegbe O.; Apusiga K.; Cooper R.; Ntim M.; Plange-Rhule J.; Rotich J.; Binanay C.; Finkelstein E.; Bloomfield G.; DeLong A.; Hogan J.; Inui T.; Naanyu V.; Fuster V.; Horowitz C.; Kimaiyo S.; Kofler C.; Menya D.; Kamano J.H.; Vedanthan R.; Velazquez E.; Were M.; Dolan J.; Irazola V.; Krousel-Wood M.; Augustovski F.; Beratarrechea A.; Chen J.; He J.; Mills K.; Poggio R.; Rubinstein A.; Shi L.; Webber L.; Akinyemi R.; Arulogun O.; Hurst S.; Waddy S.; Warth S.; Gebregziabher M.; Uvere E.
Developing consensus measures for global programs: Lessons from the Global Alliance for Chronic Diseases Hypertension research program
2017
Globalization and Health
13
1
10.1186/s12992-017-0242-8
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015260273&doi=10.1186%2fs12992-017-0242-8&partnerID=40&md5=7c1790c09fb595d0c6e6662dfa08963d
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. © 2017 The Author(s).
BioMed Central Ltd
17448603
English
Article
All Open Access; Gold Open Access
author Riddell M.A.; Edwards N.; Thompson S.R.; Bernabe-Ortiz A.; Praveen D.; Johnson C.; Kengne A.P.; Liu P.; McCready T.; Ng E.; Nieuwlaat R.; Ovbiagele B.; Owolabi M.; Peiris D.; Thrift A.G.; Tobe S.; Yusoff K.; de Villiers A.; He F.; MacGregor G.; Jan S.; Neal B.; Chow C.; Joshi R.; MacMahon S.; Patel A.; Rodgers A.; Webster R.; Keat N.K.; Attaran A.; Mills E.; Muldoon K.; Yaya S.; Featherstone A.; Mukasa B.; Forrest J.; Kalyesubula R.; Kamwesiga J.; Lopez P.C.; Tayari J.-C.; Lopez P.; Casas J.L.; McKee M.; Zainal A.O.; Yusuf S.; Campbell N.; Kilonzo K.; Marr M.; Yeates K.; Feng X.; Yuan J.; Li X.; Lin C.-P.; Yan L.; Zhang J.; Wu Y.; Ma J.; Wang H.; Ma Y.; Nowson C.; Moodie M.; Goudge J.; Kabudula C.; Limbani F.; Masilela N.; Myakayaka N.; Gómez-Olivé F.X.; Thorogood M.; Arabshahi S.; Evans R.; Mahal A.; Oldenburg B.; Srikanth V.; Heritier S.; Kalyanram K.; Kartik K.; Suresh O.; Maulik P.; Salam A.; Sudhir T.; Thankappan K.; Thirunavukkarasu S.; Thomas N.; Clifford G.; Prabhakaran D.; Thom S.; Shivashankar R.; Mohan S.; Reddy K.S.; Krishnan A.; Faletoese S.; Ieremia M.; Ulberg C.; Viali S.; Pillay A.; Sukhu A.; Schultz J.; Siitia J.; Snowdon W.; Cárdenas M.K.; Gilman R.H.; Miranda J.J.; Diez-Canseco F.; Ponce-Lucero V.; Sacksteder K.; Gyamfi J.; Ogedegbe O.; Apusiga K.; Cooper R.; Ntim M.; Plange-Rhule J.; Rotich J.; Binanay C.; Finkelstein E.; Bloomfield G.; DeLong A.; Hogan J.; Inui T.; Naanyu V.; Fuster V.; Horowitz C.; Kimaiyo S.; Kofler C.; Menya D.; Kamano J.H.; Vedanthan R.; Velazquez E.; Were M.; Dolan J.; Irazola V.; Krousel-Wood M.; Augustovski F.; Beratarrechea A.; Chen J.; He J.; Mills K.; Poggio R.; Rubinstein A.; Shi L.; Webber L.; Akinyemi R.; Arulogun O.; Hurst S.; Waddy S.; Warth S.; Gebregziabher M.; Uvere E.
spellingShingle Riddell M.A.; Edwards N.; Thompson S.R.; Bernabe-Ortiz A.; Praveen D.; Johnson C.; Kengne A.P.; Liu P.; McCready T.; Ng E.; Nieuwlaat R.; Ovbiagele B.; Owolabi M.; Peiris D.; Thrift A.G.; Tobe S.; Yusoff K.; de Villiers A.; He F.; MacGregor G.; Jan S.; Neal B.; Chow C.; Joshi R.; MacMahon S.; Patel A.; Rodgers A.; Webster R.; Keat N.K.; Attaran A.; Mills E.; Muldoon K.; Yaya S.; Featherstone A.; Mukasa B.; Forrest J.; Kalyesubula R.; Kamwesiga J.; Lopez P.C.; Tayari J.-C.; Lopez P.; Casas J.L.; McKee M.; Zainal A.O.; Yusuf S.; Campbell N.; Kilonzo K.; Marr M.; Yeates K.; Feng X.; Yuan J.; Li X.; Lin C.-P.; Yan L.; Zhang J.; Wu Y.; Ma J.; Wang H.; Ma Y.; Nowson C.; Moodie M.; Goudge J.; Kabudula C.; Limbani F.; Masilela N.; Myakayaka N.; Gómez-Olivé F.X.; Thorogood M.; Arabshahi S.; Evans R.; Mahal A.; Oldenburg B.; Srikanth V.; Heritier S.; Kalyanram K.; Kartik K.; Suresh O.; Maulik P.; Salam A.; Sudhir T.; Thankappan K.; Thirunavukkarasu S.; Thomas N.; Clifford G.; Prabhakaran D.; Thom S.; Shivashankar R.; Mohan S.; Reddy K.S.; Krishnan A.; Faletoese S.; Ieremia M.; Ulberg C.; Viali S.; Pillay A.; Sukhu A.; Schultz J.; Siitia J.; Snowdon W.; Cárdenas M.K.; Gilman R.H.; Miranda J.J.; Diez-Canseco F.; Ponce-Lucero V.; Sacksteder K.; Gyamfi J.; Ogedegbe O.; Apusiga K.; Cooper R.; Ntim M.; Plange-Rhule J.; Rotich J.; Binanay C.; Finkelstein E.; Bloomfield G.; DeLong A.; Hogan J.; Inui T.; Naanyu V.; Fuster V.; Horowitz C.; Kimaiyo S.; Kofler C.; Menya D.; Kamano J.H.; Vedanthan R.; Velazquez E.; Were M.; Dolan J.; Irazola V.; Krousel-Wood M.; Augustovski F.; Beratarrechea A.; Chen J.; He J.; Mills K.; Poggio R.; Rubinstein A.; Shi L.; Webber L.; Akinyemi R.; Arulogun O.; Hurst S.; Waddy S.; Warth S.; Gebregziabher M.; Uvere E.
Developing consensus measures for global programs: Lessons from the Global Alliance for Chronic Diseases Hypertension research program
author_facet Riddell M.A.; Edwards N.; Thompson S.R.; Bernabe-Ortiz A.; Praveen D.; Johnson C.; Kengne A.P.; Liu P.; McCready T.; Ng E.; Nieuwlaat R.; Ovbiagele B.; Owolabi M.; Peiris D.; Thrift A.G.; Tobe S.; Yusoff K.; de Villiers A.; He F.; MacGregor G.; Jan S.; Neal B.; Chow C.; Joshi R.; MacMahon S.; Patel A.; Rodgers A.; Webster R.; Keat N.K.; Attaran A.; Mills E.; Muldoon K.; Yaya S.; Featherstone A.; Mukasa B.; Forrest J.; Kalyesubula R.; Kamwesiga J.; Lopez P.C.; Tayari J.-C.; Lopez P.; Casas J.L.; McKee M.; Zainal A.O.; Yusuf S.; Campbell N.; Kilonzo K.; Marr M.; Yeates K.; Feng X.; Yuan J.; Li X.; Lin C.-P.; Yan L.; Zhang J.; Wu Y.; Ma J.; Wang H.; Ma Y.; Nowson C.; Moodie M.; Goudge J.; Kabudula C.; Limbani F.; Masilela N.; Myakayaka N.; Gómez-Olivé F.X.; Thorogood M.; Arabshahi S.; Evans R.; Mahal A.; Oldenburg B.; Srikanth V.; Heritier S.; Kalyanram K.; Kartik K.; Suresh O.; Maulik P.; Salam A.; Sudhir T.; Thankappan K.; Thirunavukkarasu S.; Thomas N.; Clifford G.; Prabhakaran D.; Thom S.; Shivashankar R.; Mohan S.; Reddy K.S.; Krishnan A.; Faletoese S.; Ieremia M.; Ulberg C.; Viali S.; Pillay A.; Sukhu A.; Schultz J.; Siitia J.; Snowdon W.; Cárdenas M.K.; Gilman R.H.; Miranda J.J.; Diez-Canseco F.; Ponce-Lucero V.; Sacksteder K.; Gyamfi J.; Ogedegbe O.; Apusiga K.; Cooper R.; Ntim M.; Plange-Rhule J.; Rotich J.; Binanay C.; Finkelstein E.; Bloomfield G.; DeLong A.; Hogan J.; Inui T.; Naanyu V.; Fuster V.; Horowitz C.; Kimaiyo S.; Kofler C.; Menya D.; Kamano J.H.; Vedanthan R.; Velazquez E.; Were M.; Dolan J.; Irazola V.; Krousel-Wood M.; Augustovski F.; Beratarrechea A.; Chen J.; He J.; Mills K.; Poggio R.; Rubinstein A.; Shi L.; Webber L.; Akinyemi R.; Arulogun O.; Hurst S.; Waddy S.; Warth S.; Gebregziabher M.; Uvere E.
author_sort Riddell M.A.; Edwards N.; Thompson S.R.; Bernabe-Ortiz A.; Praveen D.; Johnson C.; Kengne A.P.; Liu P.; McCready T.; Ng E.; Nieuwlaat R.; Ovbiagele B.; Owolabi M.; Peiris D.; Thrift A.G.; Tobe S.; Yusoff K.; de Villiers A.; He F.; MacGregor G.; Jan S.; Neal B.; Chow C.; Joshi R.; MacMahon S.; Patel A.; Rodgers A.; Webster R.; Keat N.K.; Attaran A.; Mills E.; Muldoon K.; Yaya S.; Featherstone A.; Mukasa B.; Forrest J.; Kalyesubula R.; Kamwesiga J.; Lopez P.C.; Tayari J.-C.; Lopez P.; Casas J.L.; McKee M.; Zainal A.O.; Yusuf S.; Campbell N.; Kilonzo K.; Marr M.; Yeates K.; Feng X.; Yuan J.; Li X.; Lin C.-P.; Yan L.; Zhang J.; Wu Y.; Ma J.; Wang H.; Ma Y.; Nowson C.; Moodie M.; Goudge J.; Kabudula C.; Limbani F.; Masilela N.; Myakayaka N.; Gómez-Olivé F.X.; Thorogood M.; Arabshahi S.; Evans R.; Mahal A.; Oldenburg B.; Srikanth V.; Heritier S.; Kalyanram K.; Kartik K.; Suresh O.; Maulik P.; Salam A.; Sudhir T.; Thankappan K.; Thirunavukkarasu S.; Thomas N.; Clifford G.; Prabhakaran D.; Thom S.; Shivashankar R.; Mohan S.; Reddy K.S.; Krishnan A.; Faletoese S.; Ieremia M.; Ulberg C.; Viali S.; Pillay A.; Sukhu A.; Schultz J.; Siitia J.; Snowdon W.; Cárdenas M.K.; Gilman R.H.; Miranda J.J.; Diez-Canseco F.; Ponce-Lucero V.; Sacksteder K.; Gyamfi J.; Ogedegbe O.; Apusiga K.; Cooper R.; Ntim M.; Plange-Rhule J.; Rotich J.; Binanay C.; Finkelstein E.; Bloomfield G.; DeLong A.; Hogan J.; Inui T.; Naanyu V.; Fuster V.; Horowitz C.; Kimaiyo S.; Kofler C.; Menya D.; Kamano J.H.; Vedanthan R.; Velazquez E.; Were M.; Dolan J.; Irazola V.; Krousel-Wood M.; Augustovski F.; Beratarrechea A.; Chen J.; He J.; Mills K.; Poggio R.; Rubinstein A.; Shi L.; Webber L.; Akinyemi R.; Arulogun O.; Hurst S.; Waddy S.; Warth S.; Gebregziabher M.; Uvere E.
title Developing consensus measures for global programs: Lessons from the Global Alliance for Chronic Diseases Hypertension research program
title_short Developing consensus measures for global programs: Lessons from the Global Alliance for Chronic Diseases Hypertension research program
title_full Developing consensus measures for global programs: Lessons from the Global Alliance for Chronic Diseases Hypertension research program
title_fullStr Developing consensus measures for global programs: Lessons from the Global Alliance for Chronic Diseases Hypertension research program
title_full_unstemmed Developing consensus measures for global programs: Lessons from the Global Alliance for Chronic Diseases Hypertension research program
title_sort Developing consensus measures for global programs: Lessons from the Global Alliance for Chronic Diseases Hypertension research program
publishDate 2017
container_title Globalization and Health
container_volume 13
container_issue 1
doi_str_mv 10.1186/s12992-017-0242-8
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015260273&doi=10.1186%2fs12992-017-0242-8&partnerID=40&md5=7c1790c09fb595d0c6e6662dfa08963d
description 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. © 2017 The Author(s).
publisher BioMed Central Ltd
issn 17448603
language English
format Article
accesstype All Open Access; Gold Open Access
record_format scopus
collection Scopus
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