Abstract

To determine the baseline accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of routinely collected co-morbidity data in patients undergoing abdominal wall hernia repair. All patients aged>18 who underwent umbilical, para-umbilical, inguinal or incisional hernia repair between 1 January 2015 and 1 November 2016 were identified. All parts of the clinical notes were searched for co-morbidities by two authors independently. The following co-morbidities were considered: hypertension, ischaemic heart disease (IHD), diabetes, asthma, chronic obstructive pulmonary disease (COPD), cerebrovascular disease (CVD), chronic kidney disease (CKD), hypercholesterolemia, obesity and smoking. The co-morbidities data from clinical notes were compared with corresponding data in hospital episode statistics (HES) database to calculate accuracy, sensitivity, specificity, PPV and NPV of HES codes for co-morbidities. To assess the agreement between clinical notes and HES data, we also calculated Cohen's Kappa index value as a more robust measure of agreement. Overall, 346 patients comprising 3460 co-morbidity codes were included in the study. The overall accuracy of HES codes for all co-morbidities was 77% (Kappa: 0.13). When calculated separately for each co-morbidity, the accuracy was 72% (Kappa: 0.113) for hypertension, 82% (Kappa: 0.232) for IHD, 85% (Kappa: 0.203) for diabetes, 86% (Kappa: 0.287) for asthma, 91% (Kappa: 0.339) for COPD, 92% (Kappa: 0.374) for CVD, 94% (Kappa: 0.424) for CKD, 74% (Kappa: 0.074) for hypercholesterolemia, 71% (Kappa: 0.66) for obesity and 24% (Kappa: 0.005) for smoking. The overall sensitivity, specificity, PPV and NPV of HES codes were 9, 100, 100, and 77%, respectively. The results were consistent when individual co-morbidities were analyzed separately. Our results demonstrated that HES co-morbidity codes in patients undergoing abdominal wall hernia repair are specific with good positive predictive value; however, they have substandard accuracy, sensitivity, and negative predictive value. The presence of a relatively large number of false negative or missed cases in HES database explains our findings. Better documentation of co-morbidities in admission clerking proforma may help to improve the quality of source documents for coders, which in turn may improve the accuracy of coding.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.