Brief surgical procedure code lists for outcomes measurement and quality improvement in resource-limited settings

Background: The lack of a classification system for surgical procedures in resource-limited settings hinders outcomes measurement and reporting. Existing procedure coding systems are prohibitively large and expensive to implement. We describe the creation and prospective validation of 3 brief procedure code lists applicable in low-resource settings, based on analysis of surgical procedures performed at Mbarara Regional Referral Hospital, Uganda's second largest public hospital.

Methods: We reviewed operating room logbooks to identify all surgical operations performed at Mbarara Regional Referral Hospital during 2014. Based on the documented indication for surgery and procedure(s) performed, we assigned each operation up to 4 procedure codes from the International Classification of Diseases, 9th Revision, Clinical Modification. Coding of procedures was performed by 2 investigators, and a random 20% of procedures were coded by both investigators. These codes were aggregated to generate procedure code lists.

Results: During 2014, 6,464 surgical procedures were performed at Mbarara Regional Referral Hospital, to which we assigned 435 unique procedure codes. Substantial inter-rater reliability was achieved (κ = 0.7037). The 111 most common procedure codes accounted for 90% of all codes assigned, 180 accounted for 95%, and 278 accounted for 98%. We considered these sets of codes as 3 procedure code lists. In a prospective validation, we found that these lists described 83.2%, 89.2%, and 92.6% of surgical procedures performed at Mbarara Regional Referral Hospital during August to September of 2015, respectively.

Conclusion: Empirically generated brief procedure code lists based on International Classification of Diseases, 9th Revision, Clinical Modification can be used to classify almost all surgical procedures performed at a Ugandan referral hospital. Such a standardized procedure coding system may enable better surgical data collection for administration, research, and quality improvement in resource-limited settings.