Measuring Diagnoses: ICD Code Accuracy

Abstract

Objective. To examine potential sources of errors at each step of the described inpatient International Classification of Diseases (ICD) coding process. Data Sources/Study Setting. The use of disease codes from the ICD has expanded from classifying morbidity and mortality information for statistical purposes to diverse sets of applications in research, health care policy, and health care finance. By describing a brief history of ICD coding, detailing the process for assigning codes, identifying where errors can be introduced into the process, and reviewing methods for examining code accuracy, we help code users more systematically evaluate code accuracy for their particular applications. Study Design/Methods. We summarize the inpatient ICD diagnostic coding process from patient admission to diagnostic code assignment. We examine potential sources of errors at each step and offer code users a tool for systematically evaluating code accuracy. Principle Findings. Main error sources along the ''patient trajectory'' include amount and quality of information at admission, communication among patients and providers, the clinician's knowledge and experience with the illness, and the clinician's attention to detail. Main error sources along the ''paper trail'' include variance in the electronic and written records, coder training and experience, facility quality-control efforts, and unintentional and intentional coder errors, such as misspecification, unbundling, and upcoding. Conclusions. By clearly specifying the code assignment process and heightening their awareness of potential error sources, code users can better evaluate the applicability and limitations of codes for their particular situations. ICD codes can then be used in the most appropriate ways.

Who Gets Testosterone? Patient Characteristics Associated with Testosterone Prescribing in the Veteran Affairs System: A Cross-Sectional Study

“…3,4 Though these codes have played a significant role in advancing research and policymaking in general, underreporting of chronic conditions with these codes is common. 3 As reported in the limitations section of our paper, we addressed this concern by requiring two ICD-9 codes for confirming the condition.…”

Diagnosis-based emergency department alcohol harm surveillance: What can it tell us about acute alcohol harms at the population level?

“…This would entail grouping all acute alcohol intoxication classification codes assigned by the treating physician in the back‐end of the surveillance system and excluding codes related to chronic alcohol problems. Creating a more specific sub‐syndrome risks reducing the accuracy of the grouping due to known variability in coding practices within EDs 32. Post‐hoc analysis showed promising results, with general agreement between the classification based on manual review of the triage notes and the ED diagnosis code assigned for each presentation (Table S3).…”

“…For this group, it is possible that while the triage nurse did not assess alcohol to be involved or did not document alcohol involvement, the ED clinician assessed alcohol to be a primary presenting factor and coded the presentation as such. Miscoding is also possible, with previous studies reporting the validity of coded ED data to be susceptible to the unpredictable ED environment, varying staff coding competence, unintentional and intentional misclassification and patient–clinician communication problems 15, 31, 32. This group was included in the chronic harm group as they continue to be included in the routine operation of the system, and this ensures a more conservative analysis.…”

Use of State Administrative Data Sources to Study Adolescents and Young Adults with Rare Conditions

“…While there have been no specific reviews of ICD-9 code accuracy regarding FXS, SB, or MD in the United States, broader reviews of the literature reveal that unintentional coder errors caused by the limits of the clinician's knowledge and experience with the condition, misinterpreted information from the clinical record, and data entry mistakes lead to inaccuracy in ICD coding. [29][30][31] To control for miscoding, our inclusion criteria required two or more diagnoses of FXS, SB, or MD. The specification of at least two occurrences of a diagnosis was used in a Canadian study, which linked two surveillance systems; for spina bifida, they found an agreement rate of 64.1 %.…”