DOS Kongressen 2014 ·
91
Completeness and data validity in the Danish Achilles
Tendon Rupture Database
Michael Bilde Kuhlman, Anders Troelsen, Kristoffer Barfod
Orthopaedic surgery, Clinical Orthopaedic Research Hvidovre, Copenhagen
University Hospital, Hvidovre, Denmark
Background:
Orthopaedic surgeons treat acute Achilles tendon rupture (ATR)
differently as there is currently no consensus on the preferred treatment. Data
from the Danish Achilles Tendon Rupture Database (DADB) can, for the first
time, offer quality monitoring of treatment and may shed light on outcomes of
different treatments provided that data are complete and valid.
Purpose / Aim of Study:
The aim of this study was to test the completeness
and validity of data in DADB.
Materials and Methods:
DADB was established in April 2012. Currently, five
Danish Orthopaedic Departments enter data such as general patient demo-
graphics and acute ATR treatment and outcome specifics. The study period
was 1st of October 2012 to 30th of September 2013. Two primary outcome
parameters were assessed: 1) Completeness of data was assessed using data
generated at one institution. Data from DADB was compared to medical re-
cords. The proportion of patients with acute ATR registered in DADB was as-
sessed. Eighty percent completeness was considered satisfactory. 2) Validity of
data entered in to DADB was performed on the same dataset. Data from DADB
was compared to medical records. Only complete (100%) agreement between
DADB and medical records were considered valid.
Findings / Results:
Eighty-five patients were registered in DADB. Of these,
73 (86%) were males. Median age was 40.3 years (25-75% IQR: 35.0-51.9).
Overall, 87.1% of data from DADB was consistent with medical records. The va-
lidity (consistency with medical records) of the individual parameters assessed
range from 50.6-92.9%. Data completeness in DADB was 82.5%.
Conclusions:
In conclusion, this study shows that DADB offer satisfactory
data completeness and validity for future purposes of quality monitoring and
research. Improved data validity can be achieved through clarifying data param-
eter definitions.
38.
