To measure the prevalence and intensity of pain in hospitalized patients and to assess the quality of pain management, an exhaustive cross-sectional study was conducted in every department in a university hospital. Patients hospitalized for 24 hours or more completed an anonymous self-report questionnaire. Among the 1,475 inpatients, 998 completed the questionnaire. During the 24-hour period prior to our survey, 55% experienced pain. On 100 mm pain intensity measures, the median maximum pain experienced in the 24 preceding hours was 60 mm and the median pain intensity at the time of the survey was 30 mm. Although pain measured at the time of survey disappeared in only 16% of patients, 79% were satisfied with pain management. Despite a high satisfaction level, the prevalence and intensity of pain were very high. This study provided baseline data on pain in a French hospital and led to the implementation of a program for improving pain management.

To estimate the prevalence of pain in adult patients attending an emergency department (ED) and to identify risk markers for insufficient pain relief, a cross-sectional survey was conducted for 16 days, 24 hours each day, in the ED of a Paris university hospital. A structured questionnaire was used to collect characteristics of pain and its management from patients. Pain intensity was evaluated both on arrival and before discharge using two scales (a numerical descriptor scale or a verbal pain intensity scale). On arrival, 78% of the patients complained of pain; among them, 54% complained of intense pain and 47% suffered procedural pain. Insufficient pain relief was assessed in 289 (77%) patients. We identified the following risk markers for insufficient pain relief: moderate or low pain intensity, no intervention in the ED before the medical examination, and no use of medication before arrival.

Introduction and ObjectiveSocial media has been proposed as a possibly useful data source for pharmacovigilance signal detection. This study primarily aimed to evaluate the performance of established statistical signal detection algorithms in Twitter/Facebook for a broad range of drugs and adverse events.MethodsPerformance was assessed using a reference set by Harpaz et al., consisting of 62 US Food and Drug Administration labelling changes, and an internal WEB-RADR reference set consisting of 200 validated safety signals. In total, 75 drugs were studied. Twitter/Facebook posts were retrieved for the period March 2012 to March 2015, and drugs/events were extracted from the posts. We retrieved 4.3 million and 2.0 million posts for the WEB-RADR and Harpaz drugs, respectively. Individual case reports were extracted from VigiBase for the same period. Disproportionality algorithms based on the Information Component or the Proportional Reporting Ratio and crude post/report counting were applied in Twitter/Facebook and VigiBase. Receiver operating characteristic curves were generated, and the relative timing of alerting was analysed.ResultsAcross all algorithms, the area under the receiver operating characteristic curve for Twitter/Facebook varied between 0.47 and 0.53 for the WEB-RADR reference set and between 0.48 and 0.53 for the Harpaz reference set. For VigiBase, the ranges were 0.64–0.69 and 0.55–0.67, respectively. In Twitter/Facebook, at best, 31 (16%) and four (6%) positive controls were detected prior to their index dates in the WEB-RADR and Harpaz references, respectively. In VigiBase, the corresponding numbers were 66 (33%) and 17 (27%).ConclusionsOur results clearly suggest that broad-ranging statistical signal detection in Twitter and Facebook, using currently available methods for adverse event recognition, performs poorly and cannot be recommended at the expense of other pharmacovigilance activities.Electronic supplementary materialThe online version of this article (10.1007/s40264-018-0699-2) contains supplementary material, which is available to authorized users.

Purpose To assess the impact of a variety of methodological parameters on the association between six drug classes and five key adverse events in multiple databases. Methods The selection of Drug-Adverse Event pairs was based on public health impact, regulatory relevance, and the possibility to study a broad range of methodological issues. Common protocols and data analytical specifications were jointly developed and independently and blindly executed in different databases in Europe with replications in the same and different databases. Results The association between antibiotics and acute liver injury, benzodiazepines and hip fracture, antidepressants and hip fracture, inhaled long-acting beta2-agonists and acute myocardial infarction was consistent in direction across multiple designs, databases and methods to control for confounding. Some variation in magnitude of the associations was observed depending on design, exposure and outcome definitions, but none of the differences were statistically significant. The association between anti-epileptics and suicidality was inconsistent across the UK CPRD, Danish National registries and the French PGRx system. Calcium channel blockers were not associated with the risk of cancer in the UK CPRD, and this was consistent across different classes of calcium channel blockers, cumulative durations of use up to >10 years and different types of cancer. Conclusions A network for observational drug effect studies allowing the execution of common protocols in multiple databases was created. Increased consistency of findings across multiple designs and databases in different countries will increase confidence in findings from observational drug research and benefit/risk assessment of medicines.