This post comes from Fred Nelson, MD, an orthopaedic surgeon in the Department of Orthopedics at Henry Ford Hospital and a clinical associate professor at Wayne State Medical School. Some of Dr. Nelson’s tips go out weekly to more than 3,000 members of the Orthopaedic Research Society (ORS), and all are distributed to more than 30 orthopaedic residency programs. Those not sent to the ORS are periodically reposted in OrthoBuzz with the permission of Dr. Nelson.
The broad term “big data,” when applied to health care, refers to the mining of large databases to find information that might predict and improve clinical outcomes on a national scale. A recent article in AAOSNow cites one example of the merging of big data with artificial intelligence (AI) as the 10-year partnership between the Mayo Clinic and Google to leverage cloud technologies, machine learning, and AI to accelerate change in healthcare delivery. The American Joint Replacement Registry (AJRR) is also using big data to help hospitals make more efficient supply-chain decisions and lower costs.
However, there are limitations and potential flaws in the use of big data. One is the high cost, making it unaffordable for some institutions. In addition, variations in how the data is collected and reported may lead to flawed analyses. Also, data collection may vary in completeness by region, which makes nationwide registries with consistent data collection so important. Big data can also be contaminated by bias. Even large datasets may over- or underrepresent certain groups of people, thereby skewing any analysis made with those data.
There are several solutions to improve the use of big data in orthopaedics. One is the development of registries with uniform and consistent data collection methods to ensure equity. Participation in registries by orthopaedic surgeons is critical. The authors of the AAOSNow article also emphasize that if patient data were linked longitudinally, researchers would have a powerful tool with which to study health outcomes and monitor public health trends. However, current HIPAA rules prevent clearinghouses from linking data that way. To update the law to match our data-driven reality, in 2017 US Rep. Cathy McMorris Rodgers (D-Ore.) introduced the Ensuring Patient Access to Health Records Act (H.R. 4613), which would allow greater access to big data for the purpose of research, public health, and personal patient use. The bill has been tied up in committee since December 15, 2017. The ultimate objective of using big data in medicine is to provide health care that is “predictive, preventive, personalized, and participatory,” conclude the authors.