RT Journal Article
SR Electronic
T1 Model-based methods for case definitions from administrative health data: application to rheumatoid arthritis
JF BMJ Open
JO BMJ Open
FD British Medical Journal Publishing Group
SP e016173
DO 10.1136/bmjopen-2017-016173
VO 7
IS 6
A1 Kristine Kroeker
A1 Jessica Widdifield
A1 Saman Muthukumarana
A1 Depeng Jiang
A1 Lisa M Lix
YR 2017
UL http://bmjopen.bmj.com/content/7/6/e016173.abstract
AB Objective This research proposes a model-based method to facilitate the selection of disease case definitions from validation studies for administrative health data. The method is demonstrated for a rheumatoid arthritis (RA) validation study.Study design and setting Data were from 148 definitions to ascertain cases of RA in hospital, physician and prescription medication administrative data. We considered: (A) separate univariate models for sensitivity and specificity, (B) univariate model for Youden’s summary index and (C) bivariate (ie, joint) mixed-effects model for sensitivity and specificity. Model covariates included the number of diagnoses in physician, hospital and emergency department records, physician diagnosis observation time, duration of time between physician diagnoses and number of RA-related prescription medication records.Results The most common case definition attributes were: 1+ hospital diagnosis (65%), 2+ physician diagnoses (43%), 1+ specialist physician diagnosis (51%) and 2+ years of physician diagnosis observation time (27%). Statistically significant improvements in sensitivity and/or specificity for separate univariate models were associated with (all p values <0.01): 2+ and 3+ physician diagnoses, unlimited physician diagnosis observation time, 1+ specialist physician diagnosis and 1+ RA-related prescription medication records (65+ years only). The bivariate model produced similar results. Youden’s index was associated with these same case definition criteria, except for the length of the physician diagnosis observation time.Conclusion A model-based method provides valuable empirical evidence to aid in selecting a definition(s) for ascertaining diagnosed disease cases from administrative health data. The choice between univariate and bivariate models depends on the goals of the validation study and number of case definitions.