Big Data Comes to Otolaryngology
Physicians draw data from a variety of sources. Understanding how to use it will improve clinical practice.
As otolaryngologists become more familiar with big data, they are finding new ways to use big data to transform practice and patient outcomes.
“The power of big data lies in its ability to look at something from a much higher level view with a much larger number of patients with a more representative sample,” said Nikhila Raol, MD, MPH, assistant professor of otolaryngology-head and neck surgery at
Emory University School of Medicine in Atlanta, Georgia. “Our single-center studies are too often plagued by bias that we simply can’t remove because numbers are too small. Big data lets you work across multiple geographic regions or multiple hospital types to give a more generalizable view of what is actually going on.”
The problem is size. Big data is too big for many clinicians to use easily, comfortably, or routinely.
“By their very nature, these large databases are increasingly becoming source data, which we base medical decisions,” added Jennifer J. Shin, MD, Deputy Editor of Otolaryngology–Head and Neck Surgery and OTO Open and associate professor of otolaryngology-head and neck surgery at Harvard Medical School in Boston, Massachusetts. “Understanding them is key.”
Dr. Raol and Dr. Shin will join colleagues to explore current applications of big data during a presentation available on demand titled, “Using Big Data in Otolaryngology.” The panel includes David Oliver Francis, MD, MPH, associate professor of otolaryngology-head & neck surgery and director of outcomes research at the University of Wisconsin School of Medicine of Public Health in Madison, Wisconsin. Derek J. Lam, MD, MPH, associate professor of otolaryngology-head and neck surgery at Oregon Health Sciences University in Portland, Oregon, will moderate.
Their program is available on-demand to registered AAO-HNSF 2021 Annual Meeting & OTO Experience attendees.
Otolaryngologists draw on multiple databases. Common sources include:
- NSQIP, the National Surgical Quality Improvement Program Pediatric, a nationally validated, risk-adjusted database tracking surgical complications and 30-day postoperative outcomes at the patient chart level.
- PHIS, Pediatric Health Information System and KID, Kids Inpatient Database, which draw on inpatient, ambulatory, and emergency department data from children’s hospitals nationwide.
- MarketScan, a national insurance claims database with individual-level claims data from employers, health plans and hospital inpatient, outpatient and emergency department settings.
- NAMCS, the National Ambulatory Care Medical Care Survey ,includes data sampled across U.S. populations based on surveys of individuals or households, providers, birth and death certificates and standardized medical records
- Reg-entSM, the American Academy of Otolaryngology–Head and Neck Surgery Foundation’s own otolaryngology-specific clinical data registry, focused on quality improvement and patient outcomes.
“Clinicians are becoming more aware of big data in otolaryngology because of the Academy’s own efforts with Reg-ent,” Dr. Shin said. “It now has about 20 million visits.
“For users, Reg-ent has become their practice’s avenue for quality reporting and quality performance metrics. There is also the goal of using Reg-ent for research as well.
A paper describing Reg-ent was published recently by Drs. Schmalbach [AAO-HNSF Coordinator for Research and Quality] and Denneny [AAO-HNS/F Executive Vice President and CEO], along with two of our excellent AAO-HNSF staff, which described diagnoses within the database,” Dr. Shin said. “There are substantial numbers of allergic rhinitis and sensorineural hearing loss, about 9% of patients each. That is practical and usable information, especially for our organization which has clinical practice guidelines and performance measures related to these topics.”
The literature includes a growing number of big data studies that affect practice, Dr. Raol added. That makes understanding how massive databases are populated, how they function, their strengths and their limitations an important part of reading and evaluating data studies.
“As a clinician, learning to understand and utilize findings from a big data study will help you provide better care for your patients,” she said.
This session is available on demand.
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