Efficient management of operating room (OR) time is critical to optimizing healthcare delivery. This study, conducted at Cardarelli Hospital, aimed to determine the most reliable predictor of OR time by comparing International Classification of Diseases (ICD) codes, Diagnosis-Related Groups (DRGs), and Clinical Classification Software (CCS). Accuracy was measured by coefficient of variation (CV). Analysis of data from 19,430 procedures over 12 months, each paired with the classification system and surgical team involved, revealed varying levels of precision within different CV classes. For the ICD9-CM team, 3.4% of procedures had a CV < 0.25 and 59.7% had a CV < 0.5. CCS Level 1 team showed 0.1% and 12.1% for CV < 0.25 and CV < 0.5, respectively. The CCS Single Level team had 1.1% and 44.4%, and the DRG team had 0.9% and 41.5% for CV < 0.25 and CV < 0.5, respectively. ICD codes showed practical precision, while CCS classifications showed increased variability. DRGs provided a balance between simplicity and accuracy. Limitations include concerns about data quality, generalizability, and the impact of human factors in coding. These findings provide nuanced insights into predicting operative time to improve OR efficiency. Future studies should address these limitations and explore additional predictors for comprehensive analyses.

Precision and Management of Surgery Time Prediction: Comparative Analysis of ICD Codes, DRGs, and CCS Classifications in a Hospital Setting

Santalucia I.;
2024-01-01

Abstract

Efficient management of operating room (OR) time is critical to optimizing healthcare delivery. This study, conducted at Cardarelli Hospital, aimed to determine the most reliable predictor of OR time by comparing International Classification of Diseases (ICD) codes, Diagnosis-Related Groups (DRGs), and Clinical Classification Software (CCS). Accuracy was measured by coefficient of variation (CV). Analysis of data from 19,430 procedures over 12 months, each paired with the classification system and surgical team involved, revealed varying levels of precision within different CV classes. For the ICD9-CM team, 3.4% of procedures had a CV < 0.25 and 59.7% had a CV < 0.5. CCS Level 1 team showed 0.1% and 12.1% for CV < 0.25 and CV < 0.5, respectively. The CCS Single Level team had 1.1% and 44.4%, and the DRG team had 0.9% and 41.5% for CV < 0.25 and CV < 0.5, respectively. ICD codes showed practical precision, while CCS classifications showed increased variability. DRGs provided a balance between simplicity and accuracy. Limitations include concerns about data quality, generalizability, and the impact of human factors in coding. These findings provide nuanced insights into predicting operative time to improve OR efficiency. Future studies should address these limitations and explore additional predictors for comprehensive analyses.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1515296
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