Purpose: To assess the general public awareness and perception about Adverse Drug Reactions (ADRs) reporting and pharmacovigilance. Method: A cross-sectional study conducted on June 2012 during awareness campaign held in two malls in Riyadh city for two days. A self-administered questionnaire consisting of three parts was distributed to the attendees who accepted to participate in the study. Results: A total of 204 questionnaires were collected with a response rate of 68%. Twenty-three percent could correctly define ADRs. Only 13(15.7%) of responders were familiar with the term “Pharmacovigilance” and only 78.6% were aware about the Saudi Pharmacovigilance Center. Sixty-seventy percent indicated that their physicians or pharmacists don't actively encourage them to report ADRs that may occur when they take their medications. The majority of responders (73.2%) believed that the medical team, rather than consumers, should report ADRs. When asked why patients do not report ADRs, 19.1(48.5%) believed that patients do not know whether the ADR is from the medication or not, 18.1(46.1%) stated that the reason was because patients don't know about the Pharmacovigilance Center, 16(40.7%) think that patients don't know about the importance of ADRs reporting, and 14(36.3%) responded that patients probably don't know how to report ADRs. Conclusion: The general public in Saudi Arabia are not aware about ADRs reporting and the pharmacovigilance system. The Saudi Food and Drug Authorities (FDA) need to put more efforts to increasing public awareness about the importance of ADRs reporting process and the importance of pharmacovigilance system in promoting patient safety.

Background: Before October 2015, pregnancy cohorts assembled from US health insurance claims have relied on medical encounters with International Classification of Diseases-ninth revision-clinical modification (ICD-9-CM) codes. We aimed to extend existing pregnancy identification algorithms into the ICD-10-CM era and evaluate performance. Methods: We used national private insurance claims data (2005-2018) to develop and test a pregnancy identification algorithm. We considered validated ICD-9-CM diagnosis and procedure codes that identify medical encounters for live birth, stillbirth, ectopic pregnancy, abortions, and prenatal screening to identify pregnancies. We then mapped these codes to the ICD-10-CM system using general equivalent mapping tools and reconciled outputs with literature and expert opinion. Both versions were applied to the respective coding period to identify pregnancies. We required 45 weeks of health plan enrollment from estimated conception to ensure the capture of all pregnancy endpoints. Results: We identified 7,060,675 pregnancy episodes, of which 50.1% met insurance enrollment requirements. Live-born deliveries comprised the majority (76.5%) of episodes, followed by abortions (20.3%). The annual prevalence for all pregnancy types was stable across the ICD transition period except for postterm pregnancies, which increased from 0.5% to 3.4%. We observed that ICD codes indicating gestational age were available for 86.8% of live-born deliveries in the ICD-10 era compared to 23.5% in the ICD-9 era. Patterns of prenatal tests remained stable across the transition period. Conclusion: Translation of existing ICD-9-CM pregnancy algorithms into ICD-10-CM codes provided reasonable consistency in identifying pregnancy episodes across the ICD transition period. New codes for gestational age can potentially improve the precision of conception estimates and minimize measurement biases.

Purpose: Accurate ascertainment of gestational age (GA) has been a challenge in perinatal epidemiologic research. To date, no study has validated GA algorithms in Medicaid Analytic eXtract (MAX). Methods: We linked livebirths of mothers enrolled in Medicaid ≥30 days after delivery in 1999-2010 MAX to state birth certificates. We used clinical/obstetric estimate of gestation on the birth certificates as gold standard to validate claims-based GA algorithms. We calculated the proportions of deliveries with algorithm-estimated GA within 1−/2-weeks of the gold standard, the sensitivity, specificity, and positive/negative predictive value (PPV/NPV) of exposure to select medications during specific gestation windows, and quantified the impact of exposure misclassification on hypothetical relative risk (RR) estimates. Results: We linked 1 336 495 eligible deliveries. Within 1-week agreement was 77%-80% overall and 47%-56% for preterm deliveries. The trimester-specific drug exposure status had high sensitivities and PPVs (88.5%-98.5%), and specificities and NPVs (>99.0%). Assuming a hypothetical RR of 2.0, bias associated with exposure misclassification during first trimester ranged from 10% to 40% under non-differential/differential misclassification assumptions. Conclusions: Claims-based GA algorithms had good agreement with the gold standard overall, but lower agreement among preterm deliveries, potentially resulting in biased risk estimated for pregnancy exposure evaluations.

OBJECTIVE Emerging data from animal and human pilot studies suggest potential benefits of glucagon-like peptide 1 receptor agonists (GLP-1RA) on lung function. We aimed to assess the association of GLP-1RA and chronic lower respiratory disease (CLRD) exacerbation in a population with comorbid type 2 diabetes (T2D) and CLRD. RESEARCH DESIGN AND METHODS A new-user active-comparator analysis was conducted with use of a national claims database of beneficiaries with employer-sponsored health insurance spanning 2005–2017. We included adults with T2D and CLRD who initiated GLP-1RA or dipeptidyl peptidase 4 inhibitors (DPP-4I) as an add-on therapy to their antidiabetes regimen. The primary outcome was time to first hospital admission for CLRD. The secondary outcome was a count of any CLRD exacerbation associated with an inpatient or outpatient visit. We estimated incidence rates using inverse probability of treatment weighting for each study group and compared via risk ratios. RESULTS The study sample consisted of 4,150 GLP-1RA and 12,540 DPP-4I new users with comorbid T2D and CLRD. The adjusted incidence rate of first CLRD admission during follow-up was 10.7 and 20.3 per 1,000 person-years for GLP-1RA and DPP-4I users, respectively, resulting in an adjusted hazard ratio of 0.52 (95% CI 0.32–0.85). For the secondary outcome, the adjusted incidence rate ratio was 0.70 (95% CI 0.57–0.87). CONCLUSIONS GLP-1RA users had fewer CLRD exacerbations in comparison with DPP-4I users. Considering both plausible mechanistic pathways and this real-world evidence, potential beneficial effects of GLP-1RA may be considered in selection of an antidiabetes treatment regimen. Randomized clinical trials are warranted to confirm our findings.