Coding diagnoses and procedures using a high-quality clinical database instead of a medical record review.
A discharge abstract must be completed for each hospitalization. The most time-consuming component of this task is a complete review of the doctors' progress notes to identify and code all diagnoses and procedures. We have developed a clinical database that creates hospital discharge summaries. To compare diagnostic and procedural coding from a clinical database vs. the standard chart review by health records analysts (HRA). All patients admitted and discharged from general medical and surgical services at a teaching hospital in Ontario, Canada. Diagnostic and procedural codes were identified by reviewing discharge summaries generated from a clinical database. Independently, codes were identified by hospital health records analysts using chart review alone. Codes were compared with a gold standard case review conducted by a health records analyst and a doctor. Coding accuracy (percentage of codes in gold standard review) and completeness (percentage of gold standard codes identified). The study included 124 patients (mean length of stay 5.5 days; 66.4% medical patients). The accuracy of the most responsible diagnosis was 68.5% and 62.9% for the database (D) and chart review (C), respectively (P = 0.18). Overall, the database significantly improved the accuracy (D = 78.9% vs. C = 74.5%; P = 0.02) and completeness (D = 63.9% vs. C = 36.7%; P < 0.0001) of diagnostic coding. Although completeness of procedural coding was similar (D = 5.4% vs. C = 64.2%; P = NS), accuracy decreased with the database (D = 70.3% vs. C = 92.2%; P < 0.0001). Mean resource intensity weightings calculated from the codes (D = 1.3 vs. C = 1.4; P = NS) were similar. Coding from a clinical database may circumvent the need for HRAs to review doctors' progress notes, while maintaining the quality of coding in the discharge abstract.
van Walraven
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Clinical Epidemiology Unit, Loeb Research Institute, Ottawa Hospital, Ottawa ON, Canada.
Demers
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D003628:Database Management Systems / Q000592:standards* / Q000706:statistics & numerical data*; D005260:Female; D005568:Forms and Records Control / Q000592:standards* / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008499:Medical Records / Q000592:standards* / Q000706:statistics & numerical data*; D016347:Medical Records Systems, Computerized / Q000592:standards / Q000706:statistics & numerical data; D008875:Middle Aged