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Coding diagnoses and procedures using a high‐quality clinical database instead of a medical record review
Author(s) -
Walraven Carl van,
Demers Sylvie V.
Publication year - 2001
Publication title -
journal of evaluation in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 73
eISSN - 1365-2753
pISSN - 1356-1294
DOI - 10.1046/j.1365-2753.2001.00305.x
Subject(s) - medical diagnosis , gold standard (test) , coding (social sciences) , diagnosis code , medicine , chart , medical record , database , pediatrics , computer science , statistics , surgery , mathematics , pathology , population , environmental health
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.