Validation of an ICD-10-based algorithm to identify stillbirth in the Sentinel System.

PURPOSE: To develop and validate an International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify cases of stillbirth using electronic healthcare data. METHODS: We conducted a retrospective study using claims data from three Data Partners (healthcare systems and insurers) in the Sentinel Distributed Database. Algorithms were developed using ICD-10-CM diagnosis codes to identify potential stillbirths among females aged 12-55 years between July 2016 and June 2018. A random sample of medical charts (N = 169) was identified for chart abstraction and adjudication. Two physician adjudicators reviewed potential cases to determine whether a stillbirth event was definite/probable, the date of the event, and the gestational age at delivery. Positive predictive values (PPVs) were calculated for the algorithms. Among confirmed cases, agreement between the claims data and medical charts was determined for the outcome date and gestational age at stillbirth. RESULTS: Of the 110 potential cases identified, adjudicators determined that 54 were stillbirth events. Criteria for the algorithm with the highest PPV (82.5%; 95% CI, 70.9%-91.0%) included the presence of a diagnosis code indicating gestational age ≥20 weeks and occurrence of either >1 stillbirth-related code or no other pregnancy outcome code (i.e., livebirth, spontaneous abortion, induced abortion) recorded on the index date. We found ≥90% agreement within 7 days between the claims data and medical charts for both the outcome date and gestational age at stillbirth. CONCLUSIONS: Our results suggest that electronic healthcare data may be useful for signal detection of medical product exposures potentially associated with stillbirth.

Validation of an electronic algorithm for Hodgkin and non-Hodgkin lymphoma in ICD-10-CM.

PURPOSE: Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data. METHODS: We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g., biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated. RESULTS: We identified 8723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% confidence interval: 69%-84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL. CONCLUSIONS: Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.

Assessment of Quadrivalent Human Papillomavirus Vaccine Safety Using the Self-Controlled Tree-Temporal Scan Statistic Signal-Detection Method in the Sentinel System.

The self-controlled tree-temporal scan statistic-a new signal-detection method-can evaluate whether any of a wide variety of health outcomes are temporally associated with receipt of a specific vaccine, while adjusting for multiple testing. Neither health outcomes nor postvaccination potential periods of increased risk need be prespecified. Using US medical claims data in the Food and Drug Administration's Sentinel system, we employed the method to evaluate adverse events occurring after receipt of quadrivalent human papillomavirus vaccine (4vHPV). Incident outcomes recorded in emergency department or inpatient settings within 56 days after first doses of 4vHPV received by 9- through 26.9-year-olds in 2006-2014 were identified using International Classification of Diseases, Ninth Revision, diagnosis codes and analyzed by pairing the new method with a standard hierarchical classification of diagnoses. On scanning diagnoses of 1.9 million 4vHPV recipients, 2 statistically significant categories of adverse events were found: cellulitis on days 2-3 after vaccination and "other complications of surgical and medical procedures" on days 1-3 after vaccination. Cellulitis is a known adverse event. Clinically informed investigation of electronic claims records of the patients with "other complications" did not suggest any previously unknown vaccine safety problem. Considering that thousands of potential short-term adverse events and hundreds of potential risk intervals were evaluated, these findings add significantly to the growing safety record of 4vHPV.

Prospective influenza vaccine safety surveillance using fresh data in the Sentinel System.

PURPOSE: To develop the infrastructure to conduct timely active surveillance for safety of influenza vaccines and other medical countermeasures in the Sentinel System (formerly the Mini-Sentinel Pilot), a Food and Drug Administration-sponsored national surveillance system that typically relies on data that are mature, settled, and updated quarterly. METHODS: Three Data Partners provided their earliest available ("fresh") cumulative claims data on influenza vaccination and health outcomes 3-4 times on a staggered basis during the 2013-2014 influenza season, collectively producing 10 data updates. We monitored anaphylaxis in the entire population using a cohort design and seizures in children ≤4 years of age using both a self-controlled risk interval design (primary) and a cohort design (secondary). After each data update, we conducted sequential analysis for inactivated (IIV) and live (LAIV) influenza vaccines using the Maximized Sequential Probability Ratio Test, adjusting for data-lag. RESULTS: Most of the 10 sequential analyses were conducted within 6 weeks of the last care-date in the cumulative dataset. A total of 6 682 336 doses of IIV and 782 125 doses of LAIV were captured. The primary analyses did not identify any statistical signals following IIV or LAIV. In secondary analysis, the risk of seizures was higher following concomitant IIV and PCV13 than historically after IIV in 6- to 23-month-olds (relative risk = 2.7), which requires further investigation. CONCLUSIONS: The Sentinel System can implement a sequential analysis system that uses fresh data for medical product safety surveillance. Active surveillance using sequential analysis of fresh data holds promise for detecting clinically significant health risks early. Limitations of employing fresh data for surveillance include cost and the need for careful scrutiny of signals. © 2015 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

Febrile Seizures After 2010-2011 Trivalent Inactivated Influenza Vaccine.

OBJECTIVES: In the Post-Licensure Rapid Immunization Safety Monitoring Program, we examined risk of febrile seizures (FS) after trivalent inactivated influenza vaccine (TIV) and 13-valent pneumococcal conjugate vaccine (PCV13) during the 2010-2011 influenza season, adjusted for concomitant diphtheria tetanus acellular pertussis-containing vaccines (DTaP). Assuming children would receive both vaccines, we examined whether same-day TIV and PCV13 vaccination was associated with greater FS risk when compared with separate-day vaccination. METHODS: We used a self-controlled risk interval design, comparing the FS rate in a risk interval (0-1 days) versus control interval (14-20 days). Vaccinations were identified in claims and immunization registry data. FS were confirmed with medical records. RESULTS: No statistically significant TIV-FS associations were found in unadjusted or adjusted models (incidence rate ratio [IRR] adjusted for age, seasonality, and concomitant PCV13 and DTaP: 1.36, 95% confidence interval [CI] 0.78 to 2.39). Adjusted for age and seasonality, PCV13 was significantly associated with FS (IRR 1.74, 95% CI 1.06 to 2.86), but not when further adjusting for concomitant TIV and DTaP (IRR 1.61, 95% CI 0.91 to 2.82). Same-day TIV and PCV13 vaccination was not associated with excess risk of FS when compared with separate-day vaccination (1.08 fewer FS per 100 000 with same day administration, 95% CI -5.68 to 6.09). CONCLUSIONS: No statistically significant increased risk of FS was found for 2010-2011 TIV or PCV13, when adjusting for concomitant vaccines. Same-day TIV and PCV13 vaccination was not associated with more FS compared with separate-day vaccination.

Post-licensure rapid immunization safety monitoring program (PRISM) data characterization.

BACKGROUND: The Post-Licensure Rapid Immunization Safety Monitoring (PRISM) program is the immunization safety monitoring component of FDA's Mini-Sentinel project, a program to actively monitor the safety of medical products using electronic health information. FDA sought to assess the surveillance capabilities of this large claims-based distributed database for vaccine safety surveillance by characterizing the underlying data. METHODS: We characterized data available on vaccine exposures in PRISM, estimated how much additional data was gained by matching with select state and local immunization registries, and compared vaccination coverage estimates based on PRISM data with other available data sources. We generated rates of computerized codes representing potential health outcomes relevant to vaccine safety monitoring. Standardized algorithms including ICD-9 codes, number of codes required, exclusion criteria and location of the encounter were used to obtain the background rates. RESULTS: The majority of the vaccines routinely administered to infants, children, adolescents and adults were well captured by claims data. Immunization registry data in up to seven states comprised between 5% and 9% of data for all vaccine categories with the exception of 10% for hepatitis B and 3% and 4% for rotavirus and zoster respectively. Vaccination coverage estimates based on PRISM's computerized data were similar to but lower than coverage estimates from the National Immunization Survey and Healthcare Effectiveness Data and Information Set. For the 25 health outcomes of interest studied, the rates of potential outcomes based on ICD-9 codes were generally higher than rates described in the literature, which are typically clinically confirmed cases. CONCLUSION: PRISM program's data on vaccine exposures and health outcomes appear complete enough to support robust safety monitoring.