Leveraging the Strengths of Large Databases to Study Patterns of Hip Surgery and Outcomes at the Population Level

Large databases play an increasingly important role in studying patterns of care and outcomes at the population level. In this special issue of Journal of Hip Surgery, we present studies using such data, and illustrating the many applications of these data resources in orthopaedics-related health services research.

In the article by Schwartzkopf et al, the authors examined time trends in computer-assisted surgery (CAS) to perform total hip arthroplasty (THA) and compared outcomes with conventional techniques, using 2008 to 2015 data from the American College of Surgeons' National Surgical Quality Improvement Program (NSQIP). The findings indicated an increasing trend in the use of CAS THA, though the percent of CAS THA relative to the overall THAs remained very small. Compared with conventional THAs, CAS THA was associated with lower rates of transfusion and superficial wound infections, as well as shorter length of stay. However, no advantages could be attributed to CAS THA relative to operative time, overall infection rates, early return to the operating room, or early readmissions.

In another NSQIP-based study, Kouk et al compared mortality and 30-day complication rates for patients undergoing fixation versus revision arthroplasty after periprosthetic fractures of the hip and knee. The findings showed no difference in mortality or complications rates between the two groups, suggesting that patients with periprosthetic fractures can be effectively managed with either surgical approach.

In a third study, Brigati et al used data from the 1998 to 2013 National Inpatient Sample of the Healthcare Cost and Utilization Project to study annual utilization of primary THA among patients 18 to 99 years of age, and examine trends in primary diagnoses, as well as comorbidity burden. The authors documented rapidly increasing utilization trends among patients in the 55 to 64 and 45 to 54 age groups. With regard to primary diagnosis, the authors observed increasing trends in osteoarthritis, but decreasing trends in avascular necrosis and trauma. In addition, the comorbidity burden among patients undergoing THA increased over time. These findings suggest heightened risks of revision in the years to come.

Using the national 2010 to 2015 Medicare data, Kurtz et al analyzed unplanned readmissions among patients undergoing THA with known bearing types (ceramic-on-polyethylene [C-PE], ceramic-on-ceramic [COC], and metal-on-polyethylene [M-PE]). They hypothesized that readmissions, which are caused by infections and dislocation, may be reduced by ceramic bearing usage. Consistent with the authors' hypothesis, the findings showed reduced readmissions for C-PE, while redmissions were comparable for COC and M-PE.

Finally, we highlight the article by Haynes and Grauer documenting the results of a systematic review of the literature to identify strengths, weaknesses, and conclusions from large database studies comparing THA and hemiarthroplasty for geriatric hip fractures. In addition to reporting the study findings, the authors provide a detailed description of a number of population-based databases from which these studies originated. As such, this is a highly informative and useful article to which one can refer whether in planning—or interpreting findings from—a large database study in orthopaedics-related health services and outcomes research.

While we highlight the many potential uses of these databases to study patterns of surgical care and outcomes, we remind the reader of additional databases and areas of research that have remained underexplored. Specifically, we note the dearth of studies in the literature on functional outcomes in patients undergoing orthopaedic surgery, and the impact of functional restoration on physical and emotional well-being. We recommend that the next generation of population-based studies embrace this holistic approach in future research.