Avoiding Redundancy in Coronavirus Research

September 17, 2020

A health data analytics expert describes how repeat or low-value studies can arise amid the rush to publish pandemic research.

MediFind CEO and health data analytics expert Patrick Howie describes how repeat or low-value studies can arise amid the rush to publish pandemic research.

Howie used to lead Merck's Global Analytics team. After his brother's encounter with a rare disease, and subsequent search for new medical options, Howie now uses his health analytics experience to help patients connect with expert second opinion via MediFind.

Key Quotes:

“The areas of research most negatively affected by COVID-19 include other infectious diseases, many types of cancer and neurological diseases. The impact is potentially dire in all categories, but in somewhat different ways." “Failing to make advances against infectious diseases could have a global impact in the future, given their ability to spread quickly and indiscriminately. Slowdowns in research here may severely limit our ability to counteract outbreaks of both known infectious diseases and novel ones, given the fact that learnings are often relevant across different vectors of disease. “Unfortunately, the way our medical research system is structured means there are limited resources, and thus clear winners and losers in the face of crisis. Progress against COVID-19 comes at the expense of many other important diseases, with implications that could last years. A researcher diverting their focus to COVID-19 may have a difficult time regaining funding, employees and resources when the time comes. Patients who were candidates for a clinical trial that was delayed due to the pandemic may have pursued other options that could later disqualify them, or faced even more dire consequences of these delays. With clinical trials unable to proceed as normal, and recruitment and retention becoming problematic, the delays in new research may be far-reaching and long-lasting. “COVID-19 was an unprecedented challenge and call-to-arms for the global medical research community. The speed and size of the response has been stunning, serving as evidence of our ability to scale up global collaboration in record time, across borders and boundaries. The response stands as a monument to the work we can do together when necessary. This reality offers hope not only for future pandemics, but also points to possibilities for more purposeful and progressive collaboration in the thousands of other diseases that rely on continued research. Disease isn’t limited by geopolitical boundaries, and our response can’t be either. “COVID-19 has also put a new spotlight on the numerous issues in the healthcare system, including technological barriers like limited data interoperability. It’s become clear that no single person (or even group) can conduct research on the scale required for a challenge like COVID-19. To succeed, we desperately need to accelerate our ability to use tools like artificial intelligence and machine learning to amplify human effort. “COVID-19, like SARS and MERS before it, has naturally relied heavily on the talents of infectious disease specialists. In all cases, these experts had to divert their attention, time, energy and perhaps even funding, given that they were best equipped to tackle these new threats. What’s different about COVID-19 is the scale of the impact. COVID-19 has impacted the entire world in dramatic numbers, leaving no country unscathed. The scale of increase in coronavirus research, and the related scale of decrease in all other research, is novel.”