TY - JOUR
T1 - Concordance between clinical diagnosis and medicare claims of depression among older primary care patients
AU - Hwang, Seungyoung
AU - Jayadevappa, Ravishankar
AU - Zee, Jarcy
AU - Zivin, Kara
AU - Bogner, Hillary R.
AU - Raue, Patrick J.
AU - Bruce, Martha L.
AU - Reynolds, Charles F.
AU - Gallo, Joseph J.
N1 - Funding Information:
Supported by grants from the National Institute of Mental Health, United States ( R01 MH065539 and K24MH070407 to J.G.; R21 MH094940 to H.B.; P30MH085943 to M.B. and P.R.; P30MH090333 to C.R.; and T32MH065218 to J.Z.).
Publisher Copyright:
© 2015 American Association for Geriatric Psychiatry.
PY - 2015
Y1 - 2015
N2 - Objective: To identify patient characteristics associated with concordance of Medicare claims with clinically identified depression. Methods: The authors studied a cohort of 742 older primary care patients linked to Medicare claims data using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition major depressive disorder and clinically significant minor depression. Results: Among 474 patients with depression, 198 patients had a Medicare claim for depression (sensitivity: 42%; 95% confidence interval [CI]: 37%e46%). Among 268 patients who did not meet criteria for depression, 235 patients did not have a Medicare claim for depression (specificity: 88%; 95% CI: 83%e91%). After adjustment for demographic and clinical characteristics, non-white participants were nearly twice as likely not to have Medicare claims for depression among patients who met criteria for depression ("false negatives"). Smoking status, depression severity (Hamilton Depression Rating Scale), cardiovascular disease, and more primary care physician office visits were also significantly associated with decreased odds to be false negatives. In contrast, after covariate adjustment, white race and chronic pulmonary disease were associated with increased odds of a Medicare claim for depression among patients who did not meet criteria for depression ("false positives"). Using weights based on the screened sample, the positive predictive value of a Medicare claim for depression was 66% (95% CI [63%, 69%]), whereas the negative predictive value was 77% (95% CI [76%, 78%]). Conclusion: Investigators using Medicare data to study depression must recognize that diagnoses of depression from Medicare data may be biased by patient ethnicity and the presence of medical comorbidity.
AB - Objective: To identify patient characteristics associated with concordance of Medicare claims with clinically identified depression. Methods: The authors studied a cohort of 742 older primary care patients linked to Medicare claims data using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition major depressive disorder and clinically significant minor depression. Results: Among 474 patients with depression, 198 patients had a Medicare claim for depression (sensitivity: 42%; 95% confidence interval [CI]: 37%e46%). Among 268 patients who did not meet criteria for depression, 235 patients did not have a Medicare claim for depression (specificity: 88%; 95% CI: 83%e91%). After adjustment for demographic and clinical characteristics, non-white participants were nearly twice as likely not to have Medicare claims for depression among patients who met criteria for depression ("false negatives"). Smoking status, depression severity (Hamilton Depression Rating Scale), cardiovascular disease, and more primary care physician office visits were also significantly associated with decreased odds to be false negatives. In contrast, after covariate adjustment, white race and chronic pulmonary disease were associated with increased odds of a Medicare claim for depression among patients who did not meet criteria for depression ("false positives"). Using weights based on the screened sample, the positive predictive value of a Medicare claim for depression was 66% (95% CI [63%, 69%]), whereas the negative predictive value was 77% (95% CI [76%, 78%]). Conclusion: Investigators using Medicare data to study depression must recognize that diagnoses of depression from Medicare data may be biased by patient ethnicity and the presence of medical comorbidity.
KW - Claims analysis
KW - Depression
KW - Medicare
KW - Primary healthcare
UR - http://www.scopus.com/inward/record.url?scp=84942797822&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84942797822&partnerID=8YFLogxK
U2 - 10.1016/j.jagp.2014.08.009
DO - 10.1016/j.jagp.2014.08.009
M3 - Article
C2 - 25256215
AN - SCOPUS:84942797822
SN - 1064-7481
VL - 23
SP - 726
EP - 734
JO - American Journal of Geriatric Psychiatry
JF - American Journal of Geriatric Psychiatry
IS - 7
ER -