Sunday, May 1, 2016

Shoulder arthroplasty - a minimal set of data to assess outcomes - a big step forward

Is it feasible to merge data from national shoulder registries? A new collaboration within the Nordic Arthroplasty Register Association.


A group of surgeons from Denmark, Norway, and Sweden have explored the feasibility of merging data from their national shoulder registries by defining a common minimal data set. They  agreed on a data set containing patient-related data (age, gender, and diagnosis), operative data (date, arthroplasty type and brand), and data in case of revision (date, reason for revision, and new arthroplasty brand).

From 2004 to 2013, there were 19,857 primary arthroplasties reported. The most common indications were osteoarthritis (35%) and acute fracture (34%). The number of arthroplasties and especially the number of arthroplasties for osteoarthritis have increased in the study period. The most common arthroplasty type was total shoulder arthroplasty (34%) for osteoarthritis and stemmed hemiarthroplasty (90%) for acute fractures.

The minimal set of data and key definitions are shown below.



 Comment: By creating a set of data that are common to all three registries, the surgeons can carry out analyses on trends in implant type (such as the growth in reverses and the diminution in resurfacing shown below)

and the revision rate by prosthesis type) shown below.



What is important is that the minimal set of data are collected for each patient, and that the data for all patients are made available for analysis. This is in marked contrast to the usual type of Level IV study in which summary statistics are presented for an individual case series. Congratulations to these Nordic surgeons for showing an example that all countries should follow.



In a prior post we pointed to an article that proposed a minimal data set for cuff surgery:

"The authors suggest that future clinical studies of cuff repairs need to include the following minimal dataset on each patient in an accessible appendix so that the data can be used in further systematic reviews and meta analyses:

•Patient (age, gender, smoking)
•Shoulder (tear size, fatty infiltration, preoperative clinical scores)
•Procedure (treatment method, rehabilitation protocol)
•Results (repair integrity, postoperative clinical scores, duration of followup)"