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Mira Y Friedman,1,2 Maya Leventer-Roberts,3 Joseph Rosenblum,4 Nir Zigman,4 Iris Goren,4 Vered Mourad,4 Natan Lederman,5 Nurit Cohen,5 Eran Matz,6 Doron Z Dushnitzky,6 Nirit Borovsky,6 Moshe B Hoshen,3 Gili Focht,1 Malka Avitzour,1 Yael Shachar,1 Yehuda Chowers,7 Rami Eliakim,8 Shomron Ben-Horin,8 Shmuel Odes,9 Doron Schwartz,9 Iris Dotan,10 Eran Israeli,11 Zohar Levi,10 Eric I Benchimol,12–14 Ran D Balicer,3 Dan Turner1 On behalf of the Israeli IBD Research Nucleus (IIRN) 1The Juliet Keidan Institute of Pediatric Gastroenterology and Nutrition, Shaare Zedek Medical Center, The Hebrew University of Jerusalem, Jerusalem, Israel; 2Braun School of Public and Community Medicine, The Hebrew University– Hadassah Medical Center, Jerusalem, Israel; 3Clalit Research Institute, Chief’s Office, Clalit Health Services, Tel Aviv, Israel; 4Maccabi Healthcare Services, Tel Aviv, Israel; 5Meuhedet Health Services, Tel Aviv, Israel; 6Leumit Health Services, Tel Aviv, Israel; 7Department of Gastroenterology, Rambam Health Care Campus, Bruce Rappaport School of Medicine, Technion Israel Institute of Technology, Haifa, Israel; 8Department of Gastroenterology, Chaim Sheba Medical Center, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel; 9Department of Gastroenterology and Hepatology, Soroka Medical Center, Ben-Gurion University of the Negev, Beer Sheva, Israel; 10Division of Gastroenterology, Rabin Medical Center, Petah Tikva, Israel; 11Institute of Gastroenterology and Liver Diseases, Hadassah Medical Center, Hebrew University, Jerusalem, Israel; 12CHEO Inflammatory Bowel Disease Centre, Children’s Hospital of Eastern Ontario, Ottawa, ON, Canada; 13Department of Pediatrics and School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, ON, Canada; 14Institute for Clinical Evaluative Sciences, Ottawa, ON, Canada Background: Before embarking on administrative research, validated case ascertainment algorithms must be developed. We aimed at developing algorithms for identifying inflammatory bowel disease (IBD) patients, date of disease onset, and IBD type (Crohn’s disease [CD] vs ulcerative colitis [UC]) in the databases of the four Israeli Health Maintenance Organizations (HMOs) covering 98% of the population. Methods: Algorithms were developed on 5,131 IBD patients and 2,072 controls, following independent chart review (60% CD and 39% UC). We reviewed 942 different combinations of clinical parameters aided by mathematical modeling. The algorithms were validated on an independent cohort of 160,000 random subjects. Results: The combination of the following variables achieved the highest diagnostic accuracy: IBD-related codes, alone if more than five to six codes or combined with purchases of IBD-related medications (at least three purchases or ≥3 months from the first to last purchase) (sensitivity 89%, specificity 99%, positive predictive value [PPV] 92%, negative predictive value [NPV] 99%). A look-back period of 2–5 years (depending on the HMO) without IBD-related codes or medications best determined the date of diagnosis (sensitivity 83%, specificity 68%, PPV 82%, NPV 70%). IBD type was determined by the majority of CD/UC codes of the three recent contacts or the most recent when less than three contacts were recorded (sensitivity 92%, specificity 97%, PPV 97%, NPV 92%). Applying these algorithms, a total of 38,291 IBD patients were residing in Israel, corresponding to a prevalence rate of 459/100,000 (0.46%). Conclusion: The application of the validated algorithms to Israel’s administrative databases will now create a large and accurate ongoing population-based cohort of IBD patients for future administrative studies. Keywords: inflammatory bowel diseases, Crohn’s disease, ulcerative colitis, search algorithms, validation, case ascertainment, Israel, administrative database research

Background This was a diagnostic accuracy study to develop an algorithm based on administrative database codes that identifies patients with Chronic Rhinosinusitis (CRS) who have endoscopic sinus surgery (ESS). Methods From January 1st, 2011 to December 31st, 2012, a chart review was performed for all hospital-identified ESS surgical encounters. The reference standard was developed as follows: cases were assigned to encounters in which ESS was performed for Otolaryngologist-diagnosed CRS; all other chart review encounters, and all other hospital surgical encounters during the timeframe were controls. Algorithm development was based on International Classification of Diseases, version 10 (ICD-10) diagnostic codes and Canadian Classification of Health Interventions (CCI) procedural codes. Internal model validation was performed with a similar chart review for all model-identified cases and 200 randomly selected controls during the following year. Results During the study period, 347 cases and 185,007 controls were identified. The predictive model assigned cases to all encounters that contained at least one CRS ICD-10 diagnostic code and at least one ESS CCI procedural code. Compared to the reference standard, the algorithm was very accurate: sensitivity 96.0% (95%CI 93.2–97.7), specificity 100% (95% CI 99.9–100), and positive predictive value 95.4% (95%CI 92.5–97.3). Internal validation using chart review for the following year revealed similar accuracy: sensitivity 98.9% (95%CI 95.8–99.8), specificity 97.1% (95%CI 93.4–98.8), and positive predictive value 96.9% (95%CI 93.0–99.8). Conclusion A simple model based on administrative database codes accurately identified ESS-CRS encounters. This model can be used in population-based cohorts to study longitudinal outcomes for the ESS-CRS population.

Background Administrative database research is widely applied in the field of epidemiology. However, the results of the studies depend on the type of database used and the algorithms applied for case ascertainment. The optimal methodology for identifying patients with rheumatic diseases from administrative databases is yet not known. Our aim was to describe an administrative database as a source for estimation of epidemiological characteristics on an example of systemic lupus erythematosus (SLE, ICD-10 code M32) prevalence assessment in the database of the Estonian Health Insurance Fund (EHIF). Methods Code M32 billing episodes were extracted from the EHIF database 2006–2010. For all cases where M32 was assigned by a rheumatologist less than four times during the study period, diagnosis verification process using health care providers’ (HCP) databases was applied. For M32 cases assigned by a rheumatologist four times or more, diagnoses were verified for a randomly selected sample. Results From 677 persons with code M32 assigned in EHIF database, 404 were demonstrated having “true SLE”. The code M32 positive predictive value (PPV) for the whole EHIF database was 60%; PPV varies remarkably by specialty of a physician and repetition of the code assignment. The false positive M32 codes were predominantly initial diagnoses which were not confirmed afterwards; in many cases, a rheumatic condition other than SLE was later diagnosed. Conclusions False positive codes due to tentative diagnoses may be characteristic for conditions with a complicated diagnosis process like SLE and need to be taken into account when performing administrative database research.

Asta Linauskas,1,2 Kim Overvad,3 Martin Berg Johansen,4 Kristian Stengaard-Pedersen,1,5 Annette de Thurah1,5 1Department of Rheumatology, Aarhus University Hospital, Aarhus, Denmark; 2Department of Rheumatology, North Denmark Regional Hospital, Hjoerring, Denmark; 3Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark; 4Unit of Clinical Biostatistics, Aalborg University Hospital, Aalborg, Denmark; 5Department of Clinical Medicine, Aarhus University, Aarhus, Denmark Purposes: To assess whether the positive predictive value (PPV) of first-time rheumatoid arthritis (RA) diagnosis registration in the Danish National Patient Registry increases when data are linked to the RA treatment codes and to assess the PPV of first-time RA diagnoses according to RA serological subtypes.Methods: Participants from the Danish Diet, Cancer, and Health cohort with at least one RA diagnosis, registered at one of the Central Denmark Region hospitals in the Danish National Patient Registry during the period 1977–2016, were identified. Register-based RA diagnoses were verified by scrutinizing medical records against RA classification criteria or clinical case RA. PPVs for overall RA, seropositive RA, and other RA were calculated for two models: first-time RA diagnosis registration ever in the Danish National Patient Registry and first-time RA diagnosis registration ever where subsequently a prescription had been redeemed for a synthetic disease-modifying antirheumatic drug.Results: Overall, 205 of 311 first-time register-based RA diagnoses were verified (PPV: 61.9%; 95% CI: 56.9–67.0). Regarding RA serological subtypes, 93 of 150 register-based seropositive RA (PPV: 62.0; 95% CI: 53.9–69.5) and 36 of 144 other RA (PPV: 25.0; 95% CI: 18.5–32.8) were confirmed. When register-based RA diagnosis codes were linked to RA treatment codes, the PPVs increased substantially: the PPV for overall RA was 87.7% (95% CI: 82.5–91.5), the PPV for seropositive RA was 80.2% (95% CI: 71.6–86.7), and the PPV for other RA was 41.1% (95% CI: 30.2–52.9).Conclusion: The first-time RA diagnoses in the Danish National Patient Registry should be used with caution in epidemiology research. However, linking registry-based RA diagnoses to the subsequent RA treatment codes increases the probability of identifying true RA diagnoses, especially overall RA and seropositive RA. Keywords: administrative database research, Danish National Prescription Registry, Anatomical Therapeutic Chemical codes, seropositive rheumatoid arthritis, Denmark

International audience; he accuracy of French medico-administrative data concerning amyotrophic lateral sclerosis (ALS) is to date unknown. We aimed to assess the validity of hospital discharge data (HDD) and health insurance data (HID) related to ALS. A retrospective population-based study was performed. The French register of ALS in Limousin (FRALim) was used as gold standard (2000–2013 period). All patients discharged from the regional hospitals with a ‘G12.2’ code in their HDD (according to the International Classification of Disease-10th version) or having a G12 HID code were considered. In the study period, the register included a total of 322 incident ALS patients. Among 451 subjects identified through HDD, 290 were true incident ALS cases, corresponding to 90.1% (95% CI 86.3–93.1) sensitivity and 64.3% (95% CI 59.7–68.7) positive predictive value (PPV). A total of 184 subjects were identified through HID, 142 of which were true ALS cases. This corresponded to 44.1% (95% CI 38.6–49.7) sensitivity and 75.5% (95% CI 68.7–81.5) PPV. The combination of both HDD and HID led to 93.8% (95% CI 90.6–96.2) sensitivity and 60.8% (95% CI 56.3–65.1) PPV. This study shows that French HDD and HID, even if combined, are not per se suitable for accurate and exhaustive direct identification of ALS cases.

This conference report describes six presentations that were given during a Canadian Institutes for Health Research-funded workshop. The goal of the workshop was to discuss key knowledge gaps in the study of outcomes in mothers with rheumatic diseases and their offspring. Presentations focused on epidemiological and methodological issues associated with the reproductive and perinatal health of women with rheumatic diseases. Discussions of relevant recent research allowed for discovery of potential data sources that could facilitate interdisciplinary research and created the opportunity for future collaborations.