An international team from Queen Mary University of London, Chiang Mai University, the Ministry of Public Health in Thailand, and the London School of Hygiene & Tropical Medicine has been awarded a £2.2 million grant to pilot an intervention to empower doctors in Thailand to improve outcomes for their patients.
International programme team meeting at Chiang Mai University, Thailand.
The programme has been awarded £2.2 million from the National Institute for Health and Care Research (NIHR) Global Health Research Groups programme, and additional support from the British Council.
The UK-Thai team will pilot a ‘Learning Health System’ approach in Thailand, which uses patient record data to help primary care doctors identify people who are at high risk of diabetes, kidney disease, or high blood pressure (hypertension), and inform their care. Queen Mary’s Clinical Effectiveness Group (CEG) has been implementing this approach over the past 30 years, with NHS North East London, and this opportunity will allow them to share their expertise with others across the world.
The programme has life-saving potential: Analysis by the World Health Organization estimates that effective control of hypertension in Thailand over five years can prevent more than 14,000 deaths, 27,000 strokes, and 18,000 heart attacks. Software tools, performance dashboards, training and facilitation will support doctors to work proactively with their patients to manage controllable risk factors and prevent diseases from developing or getting worse. The team will pilot the approach in 16 primary care practices in Thailand and evaluate the impact before rolling it out across the country.
The leading causes of death in Thailand are long-term conditions, including diabetes and chronic kidney disease, which are affected by lifestyle factors and high blood pressure. Of an estimated 13.2 million people with hypertension in Thailand, fewer than one-third have their blood pressure under control. The intervention will drive quality improvement in these disease areas specifically.
In a Learning Health System, the data that is generated during routine patient care is used to drive iterative improvements in population health. Queen Mary’s Clinical Effectiveness Group (CEG) and NHS North East London have implemented and honed the approach over the past 30 years - the region is among the best performing in England for key metrics relating to managing heart disease and preventing heart attacks and strokes. The model uses templates to standardise the way practitioners record data in the patient record (including information on diagnoses, test results and medications), software tools and dashboards that display data for cohorts of people with a particular condition, and a team of facilitators who support GP practices to use the resources and act on the insight.
In Thailand, data from electronic health records are already used by the Ministry of Public Health to understand how regions deliver care. But the insight is not available to frontline health workers in a format that is easy to use for improving population health. The Learning Health System intervention will close the loop and make it possible to use routinely collected data for the benefit of patients.
The project begins with a series of workshops with healthcare providers, researchers and the public in Thailand, to identify challenges around improving care for people with hypertension, diabetes, and kidney disease. ‘Community champions’ – including professionals and members of the public – will be involved in every stage of designing, delivering and improving the Learning Health System.
The programme team will train local PhD students, researchers and healthcare teams to lead the Learning Health System, creating a sustainable model that can continue to support life-saving care and improve population health. The findings from the pilot will be shared globally through collaborations with the Thai Ministry of Public Health and the World Health Organization. If the intervention is successful, Learning Health Systems will be implemented widely across Thailand, and could be adopted by other countries in the South East Asia region.
Rohini Mathur, Epidemiologist and Professor of Health Data Science at Queen Mary, says:
“The programme combines CEG’s experience in delivering Learning Health Systems with the local leadership and expertise of our partners in Thailand. Together we will target specific disease areas where we know an intervention can make a huge difference to health equity and outcomes for the Thai population. “Thailand has invested heavily in its primary health care system and the technologies to capture data about clinical care. We are excited to be working with colleagues in Thailand to close the loop and use health data for the benefit of patients.”
Chaisiri Angkurawaranon, Associate Professor and Head of the Global Health Research Centre at Chiang Mai University says:
“Collaborating with international experts allows us to leverage global knowledge and tailor it to our local context. This partnership will not only enhance our capacity to address chronic diseases like hypertension and diabetes but also improve the overall health system in Thailand.
“We are committed to making a tangible impact on patient outcomes through data-driven interventions. This collaboration represents a significant step towards using health data effectively to benefit patients.”
Dorothea Nitsch, Professor of Clinical Epidemiology at the London School of Hygiene & Tropical Medicine says:
“I am absolutely delighted that we can do this exciting work together, and test whether a CEG style learning health system is something that can be used around the world to address hypertension, diabetes and chronic kidney disease.
“As a kidney doctor looking after people just before they need to start dialysis, I see some patients who over the previous 10-20 year period had missed opportunities to improve their kidney and cardiovascular health. I always wondered whether a learning health system approach could protect a population against the consequences of chronic kidney disease. This study will provide data in the longer term as to whether that is the case or not.”