Accuracy of coding for possible warfarin complications in hospital discharge abstracts
Introduction
Warfarin is a commonly used anticoagulant that has many clinical indications. Although warfarin is effective, there is also considerable risk associated with its use including bleeding and treatment failures. The annual risks are estimated to be between 2–8% for bleeding and 1–3% for treatment failures [1]. Estimating risk of bleeding and treatment failure for a particular patient is an important consideration when deciding to initiate or continue anticoagulant therapy.
Most data regarding bleeding and treatment risks with warfarin come from clinical trials or specialized warfarin clinics. Such patients are often at low risk for complications because they tend to be carefully selected and are assessed at a greater frequency. The paucity of studies measuring community-based risks could be due to prohibitive costs of following large cohorts of patients. Administrative databases could address this issue if they are truly population-based. With administrative databases, warfarin-treated patients could be identified with pharmacy claims and bleeding or thromobembolism outcomes data could be identified from diagnoses within hospital discharge abstracts.
Databases of pharmacy claims are reliable since their creation requires relatively minimal human input. This is because many pharmacies can automatically create a claim for a medication when it is dispensed to a patient. However, diagnostic coding in discharge abstracts requires extensive human input. Getting a diagnostic code into the discharge abstract typically requires the physician to identify and document the diagnosis, the health records analyst to recognize and correctly interpret the physician's documentation, determine the appropriate code for that diagnosis, and then correctly input the code into the discharge abstract. Given the multiple steps involved in this process, one should expect that the accuracy of diagnostic codes in the discharge abstract is suboptimal.
The accuracy of diagnostic coding in the discharge abstract coding varies considerably between diagnoses. For example, the positive predictive value for acute myocardial infarction is 96.9% [2] while that for pelvic inflammatory disease it is only 18.1% [3]. Some data are available for potential warfarin complications such as upper gastrointestinal tract bleeding [4], [5], [6]. There are also some data for potential warfarin failures such as venous thromboembolism [7] and stroke [8], [9], [10], [11] However, we are unaware of any published study describing coding accuracy for a wide range of bleeding or clotting outcomes.
We performed this study to determine the accuracy of bleeding and thromboembolic diagnostic codes in the hospital discharge abstract. We reasoned that if such codes were sufficiently accurate, we could use administrative data to study patient outcomes related to warfarin treatment.
Section snippets
Design summary
This is a retrospective chart re-abstraction study in a 500-bed, university-associated teaching hospital in Ottawa, Canada. Health records analysts performed the original chart abstraction as part of the routine administrative tasks required for billing purposes. A second, gold-standard chart abstraction was performed by a single trained chart abstractor to determine whether a bleeding or clotting events had occurred. The gold-standard abstraction was performed independent of the primary
Results
Table 1 describes the overall population and our random sample by bleeding or thromboembolism category. There were 1964 patients discharged from the Ottawa Hospital during the study period with a bleeding code, a thromboembolic code, or both. We randomly sampled the records of 622 of these hospitalizations and six records were unavailable. Thus, our sample includes 616 hospital discharges. There were 361 patients with bleeding codes and 291 patients with thromboembolism codes in our sample. 36
Discussion
We determined that a set of ICD-9CM codes could be used to identify bleeding episodes with reasonable accuracy. We also found that most categories of bleeding are coded precisely, with the exception of hematuria. We found that when the bleeding code was listed as the ‘most responsible diagnosis’ or the ‘admitting diagnosis’, a true bleeding event occurred 96% of the time. These results indicate that these codes could be used to identify bleeding complications related to anticoagulants within
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