scholarly journals Countering Hesitancy and Misinformation on Side Effects to Complete the Course of COVID Vaccination

2021 ◽  
Vol 8 ◽  
pp. 237437352110673
Author(s):  
Nabarun Dasgupta
Keyword(s):  
Primary Care ◽  
Decision Making ◽  
Adverse Event ◽  
Side Effects ◽  
Family Medicine ◽  
Decision Making Process ◽  
Event Data ◽  
Post Vaccination ◽  
Adverse Event Data ◽  
To Receive

It has been well-documented that concerns about side effects prevent many from soliciting immunization. And family medicine providers play a key role in addressing concerns about COVID vaccines. However, there are few documented examples of the decision-making process regarding second shots after the emergence of a concerning and previously unknown side effect. Therefore, we present a case where a primary care provider and patient worked together to analyze real-time adverse event data on post-vaccination shingles to decide whether to receive the second dose.

Adverse Event Data for Years 2018 to 2020 for Diabetes Devices

2021 ◽  
pp. 193229682110116
Author(s):  
Jan S. Krouwer
Keyword(s):  
Adverse Event ◽  
Blood Glucose ◽  
Adverse Events ◽  
Performance Evaluations ◽  
Routine Analysis ◽  
Event Data ◽  
Adverse Event Data ◽  
Continuous Glucose Monitors ◽  
Device Use ◽  
Test Result

Unlike performance evaluations, which are often conducted under ideal conditions, adverse events occur during actual device use for people with diabetes. This report summarizes the number of adverse events for the years 2018 to 2020 for the 3 diabetes devices: blood glucose meters (BG), continuous glucose monitors (CGM), and insulin pumps. A text example of a CGM injury is provided. Possible reasons are suggested for trends. Whereas the rate per test result (events/usage) is exceedingly small, the rate per patient (events/people with diabetes that use insulin) is of concern. Hence, it is important to determine event causes and provide corrective actions. The first step is to put in place routine analysis of adverse event data for diabetes devices.

scholarly journals A Bayesian meta-analytic approach for safety signal detection in randomized clinical trials

2017 ◽  
Vol 14 (2) ◽  
pp. 192-200 ◽  
Author(s):  
Motoi Odani ◽  
Satoru Fukimbara ◽  
Tosiya Sato
Keyword(s):  
Clinical Trials ◽  
Adverse Event ◽  
Adverse Events ◽  
Hierarchical Structure ◽  
Meta Analysis ◽  
Event Data ◽  
Analysis Model ◽  
Exact Test ◽  
Adverse Event Data ◽  
Fisher’S Exact Test

Background/Aim: Meta-analyses are frequently performed on adverse event data and are primarily used for improving statistical power to detect safety signals. However, in the evaluation of drug safety for New Drug Applications, simple pooling of adverse event data from multiple clinical trials is still commonly used. We sought to propose a new Bayesian hierarchical meta-analytic approach based on consideration of a hierarchical structure of reported individual adverse event data from multiple randomized clinical trials. Methods: To develop our meta-analysis model, we extended an existing three-stage Bayesian hierarchical model by including an additional stage of the clinical trial level in the hierarchical model; this generated a four-stage Bayesian hierarchical model. We applied the proposed Bayesian meta-analysis models to published adverse event data from three premarketing randomized clinical trials of tadalafil and to a simulation study motivated by the case example to evaluate the characteristics of three alternative models. Results: Comparison of the results from the Bayesian meta-analysis model with those from Fisher’s exact test after simple pooling showed that 6 out of 10 adverse events were the same within a top 10 ranking of individual adverse events with regard to association with treatment. However, more individual adverse events were detected in the Bayesian meta-analysis model than in Fisher’s exact test under the body system “Musculoskeletal and connective tissue disorders.” Moreover, comparison of the overall trend of estimates between the Bayesian model and the standard approach (odds ratios after simple pooling methods) revealed that the posterior median odds ratios for the Bayesian model for most adverse events shrank toward values for no association. Based on the simulation results, the Bayesian meta-analysis model could balance the false detection rate and power to a better extent than Fisher’s exact test. For example, when the threshold value of the posterior probability for signal detection was set to 0.8, the false detection rate was 41% and power was 88% in the Bayesian meta-analysis model, whereas the false detection rate was 56% and power was 86% in Fisher’s exact test. Limitations: Adverse events under the same body system were not necessarily positively related when we used “system organ class” and “preferred term” in the Medical Dictionary for Regulatory Activities as a hierarchical structure of adverse events. For the Bayesian meta-analysis models to be effective, the validity of the hierarchical structure of adverse events and the grouping of adverse events are critical. Conclusion: Our proposed meta-analysis models considered trial effects to avoid confounding by trial and borrowed strength from both within and across body systems to obtain reasonable and stable estimates of an effect measure by considering a hierarchical structure of adverse events.

Depressed Latinx Older Adults’ Shared Decision-Making Preferences

2021 ◽  
Author(s):  
Sara Romero ◽  
Patrick Raue ◽  
Andrew Rasmussen
Keyword(s):  
Primary Care ◽  
Decision Making ◽  
Puerto Rican ◽  
Shared Decision Making ◽  
Decision Making Process ◽  
Shared Decision ◽  
Medical Conditions ◽  
Depression Severity ◽  
Related Information ◽  
Health Related

The shared decision-making (SDM) model is the optimal patient-centered approach to reduce racial and ethnic health disparities in primary care settings. This study examined decision-making preferences and the desire to be knowledgeable of health-related information of a multiheritage group of depressed older Latinx primary care patients. The primary aim was to determine differences in treatment preferences for both general medical conditions and depression and desire to be knowledgeable of health-related information between older Puerto Rican adults compared to older non-Puerto Rican Latinx adults. We also examined whether depression severity moderated those relationships. A sample of 178 older Latinx patients were assessed on measures of decision-making preferences, information-seeking desires, and depression severity. Regression models indicated depression severity moderated the relationship between Latinx heritage and decision-making preferences that relate to general medical decisions, but not depression treatment. Specifically, Puerto Ricans with high levels of depression preferred to be more active in making decisions related to general medical conditions compared to non-Puerto Rican patients who preferred less active involvement. There was no difference between groups at low levels of depression as both groups preferred to be similarly active in the decision-making process. This investigation adds to the literature by indicating between-group differences within a Latinx older adult sample regarding decision-making preferences and the desire to be informed of health-related information. Future research is needed to identify other sociocultural characteristics that contribute to this disparity between Latinx heritage groups in their desires to participate in the decision-making process with their primary care provider.

The Decision Making Process of Older Adults Who Elect to Receive ECT

2008 ◽  
Vol 46 (5) ◽  
pp. 45-52 ◽  
Author(s):  
Jody Amazon ◽  
Elizabeth McNeely ◽  
Sally Lehr ◽  
Martha G. Marquardt
Keyword(s):  
Older Adults ◽  
Decision Making ◽  
Decision Making Process ◽  
To Receive

Confirmation of in vitro and clinical safety assessment of behentrimonium chloride-containing leave-on body lotions using post-marketing adverse event data

2013 ◽  
Vol 27 (8) ◽  
pp. 2203-2212 ◽  
Author(s):  
D.M. Cameron ◽  
D.A. Donahue ◽  
G.-E. Costin ◽  
L.E. Kaufman ◽  
J. Avalos ◽  
...  
Keyword(s):  
Adverse Event ◽  
Safety Assessment ◽  
Event Data ◽  
Clinical Safety ◽  
Adverse Event Data ◽  
Post Marketing

scholarly journals General practitioners referring patients to specialists in tertiary healthcare: a qualitative study

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Konstantinos Tzartzas ◽  
Pierre-Nicolas Oberhauser ◽  
Régis Marion-Veyron ◽  
Céline Bourquin ◽  
Nicolas Senn ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Making ◽  
General Practitioners ◽  
Care Center ◽  
Decision Making Process ◽  
Primary Care Center ◽  
Feedback Group ◽  
Clear Cut ◽  
Tertiary Healthcare ◽  
Complex Cases

Abstract Background There is a large and unexplained variation in referral rates to specialists by general practitioners, which calls for investigations regarding general practitioners’ perceptions and expectations during the referral process. Our objective was to describe the decision-making process underlying referral of patients to specialists by general practitioners working in a university outpatient primary care center. Methods Two focus groups were conducted among general practitioners (10 residents and 8 chief residents) working in the Center for Primary Care and Public Health (Unisanté) of the University of Lausanne, in Switzerland. Focus group data were analyzed with thematic content analysis. A feedback group of general practitioners validated the results. Results Participating general practitioners distinguished two kinds of situations regarding referral: a) “clear-cut situations”, in which the decision to refer or not seems obvious and b) “complex cases”, in which they hesitate to refer or not. Regarding the “complex cases”, they reported various types of concerns: a) about the treatment, b) about the patient and the doctor-patient relationship and c) about themselves. General practitioners evoked numerous reasons for referring, including non-medical factors such as influencing patients’ emotions, earning specialists’ esteem or sharing responsibility. They also explained that they seek validation by colleagues and postpone referral so as to relieve some of the decision-related distress. Conclusions General practitioners’ referral of patients to specialists cannot be explained in biomedical terms only. It seems necessary to take into account the fact that referral is a sensitive topic for general practitioners, involving emotionally charged interactions and relationships with patients, colleagues, specialists and supervisors. The decision to refer or not is influenced by multiple contextual, personal and clinical factors that dynamically interact and shape the decision-making process.

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