Automation in signal management in pharmacovigilance—an insight

2020 ◽  
Author(s):  
Diksha Wadhwa ◽  
Keshav Kumar ◽  
Sonali Batra ◽  
Sumit Sharma
Keyword(s):  
Health Care ◽  
Signal Detection ◽  
Adverse Drug Events ◽  
Data Extraction ◽  
Modern Society ◽  
Individual Case ◽  
Optimal Decision ◽  
Therapeutic Effects ◽  
Quality Of Data ◽  
Ideal System

Abstract Drugs are the imperial part of modern society, but along with their therapeutic effects, drugs can also cause adverse effects, which can be mild to morbid. Pharmacovigilance is the process of collection, detection, assessment, monitoring and prevention of adverse drug events in both clinical trials as well as in the post-marketing phase. The recent trends in increasing unknown adverse events, known as signals, have raised the need to develop an ideal system for monitoring and detecting the potential signals timely. The process of signal management comprises of techniques to identify individual case safety reports systematically. Automated signal detection is highly based upon the data mining of the spontaneous reporting system such as reports from health care professional, observational studies, medical literature or from social media. If a signal is not managed properly, it can become an identical risk associated with the drug which can be hazardous for the patient safety and may have fatal outcomes which may impact health care system adversely. Once a signal is detected quantitatively, it can be further processed by the signal management team for the qualitative analysis and further evaluations. The main components of automated signal detection are data extraction, data acquisition, data selection, and data analysis and data evaluation. This system must be developed in the correct format and context, which eventually emphasizes the quality of data collected and leads to the optimal decision-making based upon the scientific evaluation.

A Brief Primer on Automated Signal Detection

2003 ◽  
Vol 37 (7-8) ◽  
pp. 1117-1123 ◽  
Author(s):  
Manfred Hauben
Keyword(s):  
Signal Detection ◽  
Adverse Drug Events ◽  
Data Extraction ◽  
Performance Characteristics ◽  
Data Sources ◽  
Drug Event ◽  
Computer Assisted ◽  
Statistical Independence ◽  
Medline Search ◽  
Advantages And Disadvantages

BACKGROUND: Statistical techniques have traditionally been underused in spontaneous reporting systems used for postmarketing surveillance of adverse drug events. Regulatory agencies, pharmaceutical companies, and drug monitoring centers have recently devoted considerable efforts to develop and implement computer-assisted automated signal detection methodologies that employ statistical theory to enhance screening efforts of expert clinical reviewers. OBJECTIVE: To provide a concise state-of-the-art review of the most commonly used automated signal detection procedures, including the underlying statistical concepts, performance characteristics, and outstanding limitations, and issues to be resolved. DATA SOURCES: Primary articles were identified by MEDLINE search (1965–December 2002) and through secondary sources. STUDY SELECTION AND DATA EXTRACTION: All of the articles identified from the data sources were evaluated and all information deemed relevant was included in this review. DATA SYNTHESIS: Commonly used methods of automated signal detection are self-contained and involve screening large databases of spontaneous adverse event reports in search of interestingly large disproportionalities or dependencies between significant variables, usually single drug–event pairs, based on an underlying model of statistical independence. The models vary according to the underlying model of statistical independence and whether additional mathematical modeling using Bayesian analysis is applied to the crude measures of disproportionality. There are many potential advantages and disadvantages of these methods, as well as significant unresolved issues related to the application of these techniques, including lack of comprehensive head-to-head comparisons in a single large transnational database, lack of prospective evaluations, and the lack of gold standard of signal detection. CONCLUSIONS: Current methods of automated signal detection are nonclinical and only highlight deviations from independence without explaining whether these deviations are due to a causal linkage or numerous potential confounders. They therefore cannot replace expert clinical reviewers, but can help them to focus attention when confronted with the difficult task of screening huge numbers of drug–event combinations for potential signals. Important questions remain to be answered about the performance characteristics of these methods. Pharmacovigilance professionals should take the time to learn the underlying mathematical concepts in order to critically evaluate accumulating experience pertaining to the relative performance characteristics of these methods that are incompletely defined.

scholarly journals Drug Safety Report Generator

2021 ◽  
pp. 38-49
Author(s):  
Sudhir Dubey ◽  
Pruthviraj Bhamre ◽  
Akshay Patil ◽  
Rahul Kumar
Keyword(s):  
Drug Safety ◽  
Adverse Drug Events ◽  
Digital Health ◽  
Data Extraction ◽  
Individual Case ◽  
Free Text ◽  
Electronic Patient Records ◽  
Health Records ◽  
Signature Test

This document provides an overview on identifying ICSR (Individual case safety reports) & Drug Safety Classification of Adverse Drug Events from free Text Electronic Patient Records and Information. As a remarkable rise is observed in the usage of digital health records the potential for extensive clinical data extraction has drawn much attention. We intend to separate the causes and effects of unfriendly drugs from the records. We have therefore promoted a machine learning-based framework for the planned signature test of hostile drugs or safe phrases in the event of a report. In addition, the framework also uses named substance recognition based on word references to identify drugs and diseases that are present at the same time. The framework evaluation of physical comments in the corpus and a context-related analysis of consumption, which was carried out on preselected drugs, showed convincing results.

scholarly journals Pharmacological Management of Steroid-Induced Psychosis: A Review of Patient Cases

2020 ◽  
pp. 875512252097853
Author(s):  
Grace Huynh ◽  
Justin P. Reinert
Keyword(s):  
Adverse Drug Events ◽  
Data Extraction ◽  
Management Strategies ◽  
Pharmacological Intervention ◽  
Symptom Presentation ◽  
Pharmacological Management ◽  
Diagnostic And Statistical Manual ◽  
Study Selection ◽  
Cord Injury ◽  
Male Patients

Objective: To review the efficacy and safety of medications used in the management of steroid-induced psychosis. Data Sources: A comprehensive literature search was conducted using PubMed, MEDLINE, ProQuest, and Scopus between May and October 2020 using the following search terminology: “steroid-induced psychosis” OR “corticosteroid-induced psychosis.” Study Selection and Data Extraction: Definitive cases, as defined by the Diagnostic and Statistical Manual of Mental Disorders, 5th edition, were included in this review. Geriatric patients >65 years of age, those with a confounding neurological condition such as a traumatic brain or spinal cord injury, or those with active malignancy were excluded. Data Synthesis: A total of 13 patient cases were included in this review, representing 8 male patients and 5 female patients. The mean age at symptom presentation was 42.5 years. Six patients presented with delusions, 5 presented with hallucinations, and 2 presented with both manifestations; 12 patients were managed with an antipsychotic, with haloperidol being the most commonly prescribed, followed by risperidone. One patient was managed with lithium and clonazepam alone. All patients returned to their psychological baseline upon the discontinuation or decreased dose of steroids in combination with Pharmacological intervention, though the time to resolution of symptoms varied significantly. No notable adverse drug events associated with treatments were reported. Conclusions: Steroid-induced psychosis is a serious adverse effect of corticosteroid therapy; however, management strategies that combine a dose reduction or elimination of steroids, in combination with an antipsychotic medication, are effective in resolving this syndrome.

Bezlotoxumab: Could This be the Answer for Clostridium difficile Recurrence?

2017 ◽  
Vol 51 (9) ◽  
pp. 804-810 ◽  
Author(s):  
Ryan W. Chapin ◽  
Tiffany Lee ◽  
Christopher McCoy ◽  
Carolyn D. Alonso ◽  
Monica V. Mahoney
Keyword(s):  
Monoclonal Antibody ◽  
Clostridium Difficile ◽  
English Language ◽  
Adverse Drug Events ◽  
Data Extraction ◽  
Standard Of Care ◽  
Phase Iii ◽  
Relative Reduction ◽  
Two Phase ◽  
Mesh Terms

Objective: To review the pharmacology, pharmacokinetics, efficacy, safety, and place in therapy of bezlotoxumab (BEZ), a novel monoclonal antibody against Clostridium difficile toxin B. Data Sources: A PubMed search was conducted for data between 1946 and April 2017 using MeSH terms bezlotoxumab, MK-6072, or MDX-1388 alone and the terms Clostridium difficile combined with monoclonal antibody or antitoxin. Study Selection and Data Extraction: The literature search was limited to English-language studies that described clinical efficacy, safety, and pharmacokinetics in humans and animals. Abstracts featuring prepublished data were also evaluated for inclusion. Data Synthesis: BEZ is indicated for adult patients receiving standard-of-care (SoC) antibiotics for C difficile infection (CDI) to prevent future recurrence. Two phase III trials—MODIFY I (n = 1452) and MODIFY II (n = 1203)—demonstrated a 40% relative reduction in recurrent CDI (rCDI) with BEZ compared with placebo (16.5% vs 26.6%, P < 0.0001). The most common adverse drug events associated with BEZ were mild to moderate infusion-related reactions (10.3%). Conclusions: In patients treated with SoC antibiotics, BEZ is effective in decreasing rCDI. BEZ has no apparent effect on treatment of an initial CDI episode. In light of increasing rates of CDI, BEZ is a promising option for preventing recurrent episodes. The greatest benefit has been demonstrated in high-risk patients, though the targeted patient population is yet to be defined.

Wrist Wearable Physiological Signal Detection Equipment with Biochemical Materials

2012 ◽  
Vol 459 ◽  
pp. 293-297 ◽  
Author(s):  
Xing Chen ◽  
Hong Lun Hou ◽  
Ming Hui Wu ◽  
Mei Mei Huo
Keyword(s):  
Health Care ◽  
Oxygen Saturation ◽  
Signal Detection ◽  
Human Body ◽  
Family Health ◽  
Medical Field ◽  
Physiological Signal ◽  
Potential Value ◽  
Care Field ◽  
Physiological Information

This paper designed a wrist Device which can detect physiological information and save the information data. The information got by device is including Oxygen saturation of blood, Pulse rate and steps. And the device even can distinguish the state of human body between fall and normal activities with 3-axis accelerometer. The equipment designed for family health care and remote healthy care field. The operation of device is so easy to be mastered that the device might have a potential value for the future medical field

Preaching with Their Lives

2020 ◽  
Keyword(s):  
United States ◽  
Health Care ◽  
Social Services ◽  
Fine Arts ◽  
Modern Society ◽  
The United States ◽  
Economic Justice ◽  
Epidemic Disease ◽  
Music Drama ◽  
The Arts

This volume tells the little-known story of the Dominican Family—priests, sisters, brothers, contemplative nuns, and lay people—and integrates it into the history of the United States. Starting after the Civil War, the book takes a thematic approach through twelve essays examining Dominican contributions to the making of the modern United States by exploring parish ministry, preaching, health care, education, social and economic justice, liturgical renewal and the arts, missionary outreach and contemplative prayer, ongoing internal formation and renewal, and models of sanctity. It charts the effects of the United States on Dominican life as well as the Dominican contribution to the larger U.S. history. When the country was engulfed by wave after wave of immigrants and cities experienced unchecked growth, Dominicans provided educational institutions; community, social, and religious centers; and health care and social services. When epidemic disease hit various locales, Dominicans responded with nursing care and spiritual sustenance. As the United States became more complex and social inequities appeared, Dominicans cried out for social and economic justice. Amidst the ugliness and social dislocation of modern society, Dominicans offered beauty through the liturgical arts, the fine arts, music, drama, and film, all designed to enrich the culture. Through it all, the Dominicans cultivated their own identity as well, undergoing regular self-examination and renewal.

Prevention and Control of Trichotomy Infection in the Elderly Surgical Patient: An Umbrella Review

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Teresa Ferreira ◽  
Filipe Orfao ◽  
Cesar Fonseca ◽  
Lara Guedes de Pinho
Keyword(s):  
Health Care ◽  
Narrative Analysis ◽  
Data Extraction ◽  
Elderly Person ◽  
The Elderly ◽  
World Health ◽  
Surgical Patient ◽  
Risk Of Infection ◽  
Umbrella Review ◽  
And Control

Introduction: The World Health Organization creates norms and guidelines for the adoption of good practices in health care that are provided to the surgical patient. In order to prevent and control infections associated with health care, the nurse must follow the guidelines for preparing the surgical patient for success. These infections can be particularly harmful to the elderly person given their vulnerability. The preoperative preparation, includes the trichotomy as one of the interventions to be performed, however, is one of the most controversial interventions that has caused in clinical practice, by the potential risk of infection in the surgical patient. Aim: To investigate the need for trichotomy, or removal of hair, in the preparation of the skin of the surgical patient, clarifying which is the most appropriate technique in the prevention of infection. Methodology: we conducted an umbrella review. The documentary research followed the consultation of bibliographic sources in the Cumulative Index to Nursing & Allied Health (CINAHL) and Public/Publisher Medline (PubMed) databases. The researched articles were grouped in a time horizon between 2011 and 2020. Afer data extraction, a narrative analysis was performed. Results: We found 40 articles from which 8 were selected. Conclusion: Trichotomy should be avoided by increasing the risk of infection of the surgical site. Innovative haircut and vacuum technologies can help in hair removal, mitigating the risk of contaminating the surgical incision. The timing of the trichotomy is not consensual among researchers.

scholarly journals Methodological Development of Mathematical Modeling Techniques in Health Care

2020 ◽  
Vol 9 (3) ◽  
pp. 3339-3342
Keyword(s):  
Mathematical Modeling ◽  
Health Care ◽  
Decision Making ◽  
Health Economics ◽  
Service Planning ◽  
Optimal Decision ◽  
Optimal Decision Making ◽  
The Individual ◽  
Specific Modeling ◽  
Health Care Application

The advancement of mathematical model has utilized for simulating the output of medical is a development area over medicine whereas the modeling can be mentioned with several activities namely simulation or decision analysis and predictive modeling. However, the traditional modeling technique utilized in planning of health service, assessment reports and its efficiency, financing about health care and assessment in budget impact, assessment in health economics, surveillance of infectious disease and other health care application. Therefore, the mathematical modelling is performed as a frequent and timely benefit in order to make rapid decision making while facing investigation with several issues like time elapsing, unusual and unethical particularly projected for future. This paper focused in applying the mathematical modeling to accomplish an optimal decision making in healthcare whereas this study discuss about the specific modeling concepts namely decision tree and fuzzified rule tables on evaluation of health economics and better service planning that my replicate the individual experience or patients cohorts.

Quality Issues in Personalized E-Health, Mobile Health and E-Health Grids

2011 ◽  
pp. 118-131 ◽  
Author(s):  
Anastasia N. Kastania ◽  
Sophia Kossida
Keyword(s):  
Health Care ◽  
Integrated Circuits ◽  
Health Management ◽  
Low Cost ◽  
Modern Society ◽  
Public Health Care ◽  
Smart Sensors ◽  
Grid Middleware ◽  
Rigorous Testing ◽  
Personalized Health

The electronic healthcare in the modern society has the possibility of converting the practice of delivery of health care. Currently, chaos of information is characterizing the public health care, which leads to inferior decision-making, increasing expenses and even loss of lives. Technological progress in the sensors, integrated circuits, and the wireless communications have allowed designing low cost, microscopic, light, and smart sensors. These smart sensors are able to feel, transport one or more vital signals, and they can be incorporated in wireless personal or body networks for remote health monitoring. Sensor networks promise to drive innovation in health care allowing cheap, continuous, mobile and personalized health management of electronic health records with the Internet. The e-health applications imply an exciting set of requirements for Grid middleware and provide a rigorous testing ground for Grid. In the chapter, the authors present an overview of the current technological achievements in the electronic healthcare world combined with an outline of the quality dimensions in healthcare.

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