Article Text

other Versions

PDF
Transnational research partnerships: leveraging big data to enhance US health
  1. Casey Crump1,
  2. Kristina Sundquist2,3,
  3. Marilyn A Winkleby3
  1. 1Department of Medicine, Stanford University, Stanford, California, USA
  2. 2Center for Primary Health Care Research, Lund University, Malmö, Sweden
  3. 3Stanford Prevention Research Center, Stanford University, Stanford, California, USA
  1. Correspondence to Dr Casey Crump, Department of Medicine, Stanford University, 211 Quarry Road, Suite 405, MC 5985, Palo Alto, CA 94304-1426, USA; kccrump{at}stanford.edu

Statistics from Altmetric.com

In the current era of big data and small research budgets, new strategies are needed for more cost-effective leveraging of big data to enhance our nation's health. One strategy is to promote transnational partnerships to tap into the rich, extensive databases available in other countries, particularly in Europe. The National Institutes of Health (NIH) has increasingly recognised that new collaborations that bring together multiple data sources will play a critical role in advancing our knowledge of disease causation, improving patient care, and promoting healthier communities. However, given cuts in research funding and fierce competition for US grants, some question whether US dollars should be diverted to fund ‘foreign’ studies. In this commentary, we argue that transnational research partnerships offer significant advantages for enhancing the health of the US population as well as the broader global community.

In the USA, the collection of population-wide health data has been hampered by the inherent difficulties in linking patients across many different healthcare delivery systems. As a result, the availability of big data for health research has been limited mainly to a few large organisations such as Kaiser Permanente, Group Health, the Mayo Clinic and VA hospitals. The data collected by such organisations are rich resources but have significant limitations. They include only a selected patient population, which is often a poor representative of the broader population in terms of socioeconomic, ethnic or health factors, thus limiting generalisability. Their patient populations also fluctuate over time …

View Full Text

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.