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Big data is rewriting the medical future of millions of people

Big data is rewriting the medical future of millions of people

Strokes – sudden interruptions to the brain’s blood supply – are the leading cause of death in China and the second leading cause of death globally. While strokes are the top killer in China, stroke care in the country is suboptimal. Patients in China suffering from acute ischemic stroke, when arteries leading to the brain are blocked, have traditionally not experienced excellent clinical outcomes. Battling this disease has been a long-term battle for physicians working in the country’s overcrowded under-resourced public hospitals. However, improvements in healthcare analytics is throwing these doctors a lifeline, allowing them to incorporate more precise care guidelines into their routines and introduce targeted interventions to improve patient outcomes.

Professor Haipeng Shen, Patrick S C Poon Professor in Analytics and Innovation at HKU Business School, has been working to change this situation by collaborating with top physicians and embracing the power of big data. Their work uses big data to increase the dimensions and the sample size of stroke research by analysing vast amounts of clinical data like patient demographics, lab reports, diagnoses, and medical histories. 

The analysis of vast amounts of clinical data is enabled by healthcare analytics

Professor Shen has been the lead statistician on several high-level empirical and clinical research projects that use healthcare analytics to demonstrate how adherence to evidence-based clinical guidelines improves stroke patient outcomes. 

In one project, the Golden Bridge-Acute Ischemic Stroke randomised clinical trial, which Professor Shen and his colleagues from neurology, science and medicine performed for the China National Network of Stroke Research, the research team worked with 40 hospitals across China. Twenty hospitals followed a targeted quality improvement intervention regime, sticking closely to evidence-based clinical guidelines; while the other 20 formed the control group, providing the “usual” stroke care regimen.

Continuous Quality Improvement of Stroke Care Model

The results? The quality improvement interventions led directly to enhanced quality of care and significantly better patient outcomes. New stroke events were significantly reduced in the intervention group at three, six and 12 months. Based on a 2013 estimate of 2.4 million new stroke events per year nationwide, the reduction corresponds to 33,600 fewer strokes at three months, 36,000 at six months, and 64,800 at 12 months. 

Their findings suggest that quality improvement interventions are both feasible and successful despite the resource limitations and overcrowded conditions which exist at many hospitals. What’s more, the interventions did not require expensive technology or complex medical procedures and did not put any unrealistic burdens on the hospitals or physicians.

Ultimately, the Golden Bridge study concluded that a continuous stroke quality improvement programme should be developed as a national priority for China. This has now happened: the China Stroke Association “incorporated this successful model in its 2019 China Neurological Disease Clinical Guideline, and implemented it in the Chinese Stroke Centre Alliance, with over 2,600 hospitals that provide stroke care across China.” An editorial in the Journal of the American Medical Association praised the study, saying, “Trials like this one leave a lasting legacy because the coaching and follow-up and the demonstration that data collection can lead to better outcomes with practice change [which] will leave each of the intervention hospitals with a platform of good quality stroke care and a mechanism to keep improving.”

Professor Shen and colleagues’ work is still on-going, and has evolved from clinical trials to the development of a mobile clinical support app called StrokePro, aimed at stroke patients and their caregivers in Hong Kong, Macau, and parts of Shenzhen, China. The app incorporates the intervention procedures and several risk factors identified in Professor Shen’s earlier publications. 

Today, the future is full of uncertainty and the pressure on healthcare systems around the world is set to increase dramatically. This calls for even closer interdisciplinary collaboration between healthcare professionals and data scientists, so that together we can pursue constant improvements in data quality and healthcare analytics. This will enhance data-driven decision making and efficiency, and the quality of healthcare services – ensuring better outcomes for every patient.


Professor Haipeng Shen

Professor Haipeng Shen is the Associate Dean (Executive Education), Patrick S C Poon Professor in Analytics and Innovation, Professor of Innovation and Information Management, HKU Business School. His research revolves around data-driven decision making in the face of uncertainty, including methodological research about analytical challenges imposed by big data and artificial intelligence, as well as interdisciplinary research in healthcare. His joint-authored research about artificial intelligence in healthcare earned him the Most Influential Publication Award from the China Stroke Association in 2018.



[1] Wang, Y., Li, Z., Zhao, X., Wang, C., Wang, X., Wang, D., Liang, L., Liu, L., Wang, C., Li, H., Shen, H., Bettger, J., Pan, Y., Jiang, Y., Yang, X., Zhang, C., Han, X., Meng, X., Yang, X., Kang, H., Yuan, W., Fonarow, G.C., Peterson, E.D., Schwamm, L.H., Xian, Y. and Wang, Y. (2018) ‘Effect of a Multifaceted Quality Improvement Intervention on Hospital Personnel Adherence to Performance Measures in Patients With Acute Ischemic Stroke in China A Randomized Clinical Trial’, The Journal of the American Medical Association (JAMA), 320(3), 245-254.

[2] Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H. and Wang, Y. (2017) ‘Artificial Intelligence in Healthcare: Past, Present, and Future’, Stroke and Vascular Neurology, 2: e000101, 230-243.

[3] Li, Z., Wang, C., Zhao, X., Liu, L., Wang, C., Li, H., Shen, H., Liang, L., Bettger, J., Yang, Q., Wang, D., Wang, A., Pan, Y., Jiang, Y., Yang, X., Zhang, C., Fonarow, G.C., Schwamm, L.H., Hu, B., Peterson, E.D., Xian, Y., Wang, Y. and Wang, Y. (2016) ‘Substantial Progress Yet Significant Opportunity for Improvement in Stroke Care in China’, Stroke, 47, 2843-2849.

[4] Wang, Y., Li, Z., Xian, Y., Zhao, X., Li, H., Shen, H., Wang, C., Liu, L., Wang, C., Pan, Y.,  Wang, D., Bettger, J.P., Fonarow, G.C., Schwamm, L.H., Smith, S.C., Peterson, E.D. and Wang, Y. (2015) ‘Rationale and Design of a Cluster-Randomized Multifaceted Intervention Trial to Improve Stroke Care Quality in China: The GOLDEN BRIDGE-AIS’, American Heart Journal, 169, 767-774.