Frank I Scott1,2, Ronac Mamtani2,3, Kevin Haynes2, David S Goldberg1,2, Najjia N Mahmoud4, James D Lewis1,2. 1. Division of Gastroenterology, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA. 2. Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. 3. Abramson Cancer Center, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA. 4. Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Abstract
PURPOSE: Epidemiological data on adhesion-related complications following intra-abdominal surgery are limited. We tested the accuracy of recording of these surgeries and complications within The Health Improvement Network (THIN), a primary care database within the UK. METHODS: Individuals within THIN from 1995 to 2011 with an incident intra-abdominal surgery and subsequent bowel obstruction (SBO) or adhesiolysis were identified using diagnostic codes. To compute positive predictive values (PPVs), requests were sent to treating physicians of patients with these diagnostic codes to confirm the surgery, SBO, or adhesiolysis code. Completeness of recording was estimated by comparing observed surgical rates within THIN to expected rates derived from the Hospital Episode Statistics dataset within England. Cumulative incidence rates of adhesion-related complications at 5 years were compared with a previously published cohort within Scotland. RESULTS: Two hundred seventeen of 245 (89%) questionnaires were returned (180 SBO and 37 adhesiolysis). The PPV of codes for surgery was 94.5% (95%CI: 91-97%). The 88.8% of procedure types were correctly coded. The PPV for SBO and adhesiolysis was 86.1% (95%CI: 80-91%) and 89.2% (95%CI: 75-97%), respectively. Colectomy, appendectomy, and cholecystectomy rates within THIN were 99%, 95%, and 84% of rates observed in national Hospital Episode Statistics data, respectively. Cumulative incidence rates of adhesion related complications following colectomy, appendectomy, and small bowel surgery were similar to those published previously. CONCLUSIONS: Surgical procedures, SBO, and adhesiolysis can be accurately identified within THIN using diagnostic codes. THIN represents a new tool for assessing patient-specific risk factors for adhesion-related complications and long-term outcomes.
PURPOSE: Epidemiological data on adhesion-related complications following intra-abdominal surgery are limited. We tested the accuracy of recording of these surgeries and complications within The Health Improvement Network (THIN), a primary care database within the UK. METHODS: Individuals within THIN from 1995 to 2011 with an incident intra-abdominal surgery and subsequent bowel obstruction (SBO) or adhesiolysis were identified using diagnostic codes. To compute positive predictive values (PPVs), requests were sent to treating physicians of patients with these diagnostic codes to confirm the surgery, SBO, or adhesiolysis code. Completeness of recording was estimated by comparing observed surgical rates within THIN to expected rates derived from the Hospital Episode Statistics dataset within England. Cumulative incidence rates of adhesion-related complications at 5 years were compared with a previously published cohort within Scotland. RESULTS: Two hundred seventeen of 245 (89%) questionnaires were returned (180 SBO and 37 adhesiolysis). The PPV of codes for surgery was 94.5% (95%CI: 91-97%). The 88.8% of procedure types were correctly coded. The PPV for SBO and adhesiolysis was 86.1% (95%CI: 80-91%) and 89.2% (95%CI: 75-97%), respectively. Colectomy, appendectomy, and cholecystectomy rates within THIN were 99%, 95%, and 84% of rates observed in national Hospital Episode Statistics data, respectively. Cumulative incidence rates of adhesion related complications following colectomy, appendectomy, and small bowel surgery were similar to those published previously. CONCLUSIONS: Surgical procedures, SBO, and adhesiolysis can be accurately identified within THIN using diagnostic codes. THIN represents a new tool for assessing patient-specific risk factors for adhesion-related complications and long-term outcomes.
Authors: Margaret Jean Hall; Carol J DeFrances; Sonja N Williams; Aleksandr Golosinskiy; Alexander Schwartzman Journal: Natl Health Stat Report Date: 2010-10-26
Authors: James D Lewis; Rita Schinnar; Warren B Bilker; Xingmei Wang; Brian L Strom Journal: Pharmacoepidemiol Drug Saf Date: 2007-04 Impact factor: 2.890
Authors: Ronac Mamtani; Kevin Haynes; Ben Boursi; Frank I Scott; David S Goldberg; Stephen M Keefe; David J Vaughn; S Bruce Malkowicz; James D Lewis Journal: Cancer Epidemiol Biomarkers Prev Date: 2014-11-11 Impact factor: 4.254
Authors: Kevin Haynes; Kimberly A Forde; Rita Schinnar; Patricia Wong; Brian L Strom; James D Lewis Journal: Pharmacoepidemiol Drug Saf Date: 2009-08 Impact factor: 2.890
Authors: Ronac Mamtani; Kevin Haynes; Brian S Finkelman; Frank I Scott; James D Lewis Journal: Pharmacoepidemiol Drug Saf Date: 2013-12-19 Impact factor: 2.890
Authors: Frank I Scott; Ravy K Vajravelu; Ronac Mamtani; Nicholas Bianchina; Najjia Mahmoud; Jason K Hou; Qufei Wu; Xingmei Wang; Kevin Haynes; James D Lewis Journal: JAMA Netw Open Date: 2021-02-01