Surveillance of non-communicable diseases (NCD) has evolved in the wake of data outbursts and the development of data analytics and other cutting-edge technologies, according to a recent perspective article in Health Data Science, a Science Partner Journal.
Based on an overview of the latest evidence, the article intends to provide ideas on improving the practice and broaden the view of NCD surveillance, says Pengfei Li, author and researcher with the Advanced Institute of Information Technology, Peking University.
Surveillance is crucial in tracking and monitoring NCD. A periodic population-based survey is standard in traditional surveillance systems. However, a large consumer of labor, time, and other resources, the existing surveillance systems have functioned with defects, including data accuracy, quality, and standardization. Further, such methods are often insufficient to identify the influence of rapid changes in significant events, such as the coronavirus disease 2019 (COVID-19) outbreak.
On the other hand, NCD surveillance faces tremendous opportunities and unprecedented solutions thanks to the widespread use of electronic health records and the accumulation of national administrative data, insurance claim data, and other datasets. Practice-based and longitudinally generated, these data sources contained information, including risk factors, interventions, and outcomes. Also, such data generated in real-time have a higher sensitivity to the changing landscape of health care and risk behaviors, overcoming the delay in representing changes common to the survey-based surveillance systems. Health systems can identify emerging problems and facilitate swift intervention with time-sensitive information.
“Integrating real-world data from the health care system and survey data from the existing public health monitoring system provides a great opportunity for NCD surveillance and management,” says Li. “The novel, hybrid surveillance program may provide enriched, timely information, at lower costs, in supporting chronic disease control, particularly valuable in low- and middle-income countries with limited resources and varied capacities.”
For example, chronic kidney disease (CKD), defined only in 2002, is not ubiquitously included in the traditional NCD surveillance systems. However, the CKD Surveillance System in the United States and the China Kidney Disease Network (CK-NET) in China, established in 2006 and 2014, respectively, use comprehensive data sources and continuously provide detailed information to support CKD control.
In addition, NCD surveillance can be incorporated with data from other technologies, such as home-based or wearable wireless devices, mobile apps, virtual care platforms, and Internet-of-Things. Proven practicable and effective in preventing and caring for COVID-19, these technologies are readily applicable for NCD surveillance.
NCD surveillance can also include community data as health is inherent in the interwoven social, behavioral, and environmental systems. Insights gained from such analysis could yield population-based health measures. Borrowing tools from other sectors, such as spatial analyses and geographical systems, NCD surveillance may help elucidate health disparities, accessibility, and other aspects of care. Increased sophistication of the collected data and the information retrieved may provide hints of innovative approaches to NCD problems.
The big data era and advanced data-based analytics have brought enormous opportunities to NCD surveillance. However, further efforts are warranted in addressing the legal, ethical, and technical challenges and seeking multidisciplinary collaboration.
- This press release was provided by Health Data Science