Literature DB >> 15135837

Assessing accuracy of diagnosis-type indicators for flagging complications in administrative data.

Hude Quan1, Gerry A Parsons, William A Ghali.   

Abstract

OBJECTIVE: Canadian administrative hospital discharge data contain a diagnosis-type indicator for each coded diagnosis that allows researchers to distinguish complications from pre-existing diagnoses. Given that the validity of diagnosis-type indicators is unknown, we conducted a detailed chart review to evaluate the accuracy of diagnosis-type indicators for flagging complications. STUDY DESIGN AND
SETTING: We obtained administrative hospital discharge data for 1,200 randomly selected adult inpatient separations in Calgary, Alberta, occurring between April 1, 1996 and March 31, 1997. Each discharge record contains up to 16 diagnoses and 16 corresponding diagnosis-type indicators (value of "2"=complication). The corresponding medical charts were reviewed for evidence of diagnoses and complications. A complication was defined as a new diagnosis arising after the start of hospitalization. We determined the extent to which the diagnosis-type indicator in the administrative data agreed with the chart reviewer's assessment (criterion standard) of whether a diagnosis was a complication or not.
RESULTS: The agreement for complications between the two databases varied greatly across 12 conditions studied (kappa range: 0-0.72) and was often low (kappa <0.20 for six conditions). Sensitivity ranged from 0 to 57.1% (higher than 50% for only two conditions), indicating a tendency for complications to often be miscoded as baseline comorbidities. In contrast, specificity was generally high (range: 99.0-100%), suggesting that pre-existing conditions were usually appropriately coded as such in the administrative data.
CONCLUSION: The validity of diagnosis-type indicators in Canadian administrative discharge data appears to be poor for some types of complications. This is likely to be of greatest concern in studies that rely solely on diagnosis-type indicators to define complications as outcomes.

Mesh:

Year:  2004        PMID: 15135837     DOI: 10.1016/j.jclinepi.2003.01.002

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  36 in total

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