"Concordance between comorbidity data from patient self-report interviews and medical record documentation".
BACKGROUND
Comorbidity is an important adjustment measure in research focusing on outcomes such as health status and mortality. One recurrent methodological issue concerns the concordance of comorbidity data obtained from different reporting sources. The purpose of these prospectively planned analyses was to examine the concordance of comorbidity data obtained from patient self-report survey interviews and hospital medical record documentation.


METHODS
Comorbidity data were obtained using survey interviews and medical record entries from 525 hospitalized Acute Coronary Syndrome patients. Frequencies and descriptive statistics of individual and composite comorbidity data from both sources were completed. Individual item agreement was evaluated with simple and weighted kappas, Spearman Rho coefficients for composite scores.


RESULTS
On average, patients reported more comorbidities during their patient survey interviews (mean = 1.78, SD = 1.99) than providers had documented in medical records (mean = 1.27, SD = 1.43). Higher proportions of positive responses were obtained from self-reports compared to medical records for all conditions except congestive heart failure and renal disease. Older age and higher depressive symptom levels were significantly associated with poorer levels of data concordance.


CONCLUSIONS
These results demonstrate that survey comorbidity data from ACS patients may not be entirely concordat with medical record documentation. In the absence of a gold standard, it is possible that hospital records did not include all pre-admission comorbidities and these patient survey interview methods may need to be refined. Self-report methods to facilitate some patients' complete recall of comorbid conditions may need to be refined by health services researchers.


BACKGROUND
ClinicalTrials.gov NCT00416026.
Corser
William
W
College of Nursing, Michigan State University, B500A West Fee Hall,, East Lansing, Michigan 48824, USA. bill.corser@ht.msu.edu
Sikorskii
Alla
A
Olomu
Ade
A
Stommel
Manfred
M
Proden
Camille
C
Holmes-Rovner
Margaret
M
D000368:Aged; D015897:Comorbidity; D003625:Data Collection; D005260:Female; D006801:Humans; D007407:Interviews as Topic; D016015:Logistic Models; D008297:Male; D008499:Medical Records; D008875:Middle Aged; D016017:Odds Ratio; D012959:Socioeconomic Factors