Economic burden of adverse drug reactions and potential for pharmacogenomic testing in Singaporean adults

A review of real-world evidence on preemptive pharmacogenomic testing for preventing adverse drug reactions: a reality for future health care

Adverse drug reactions (ADRs) are a significant public health concern and a leading cause of hospitalization; they are estimated to be the fourth leading cause of death and increasing healthcare costs worldwide. Carrying a genetic variant could alter the efficacy and increase the risk of ADRs associated with a drug in a target population for commonly prescribed drugs. The use of pre-emptive pharmacogenetic/omic (PGx) testing can improve drug therapeutic efficacy, safety, and compliance by guiding the selection of drugs and/or dosages. In the present narrative review, we examined the current evidence of pre-emptive PGx testing-based treatment for the prevention of ADRs incidence and hospitalization or emergency department visits due to serious ADRs, thus improving patient safety. We then shared our perspective on the importance of preemptive PGx testing in clinical practice for the safe use of medicines and decreasing healthcare costs.

Knowledge, attitude and practice of physicians and nurses at the cape coast teaching hospital in the Central Region of Ghana on spontaneous adverse drug reaction reporting

Ghana's rate of reporting adverse drug reaction (ADRs) over the past years has consistently been below the WHO standard despite utilizing the spontaneous or voluntary reporting system. While underreporting undermines the pharmacovigilance system and poses a huge threat to public health safety, there is limited information on the perspectives of healthcare workers directly involved in drug administration. The present study investigated the knowledge, attitude and practice of physicians and nurses at the Cape Coast Teaching Hospital (CCTH) towards spontaneous reporting of ADRs (SR-ADRs). A descriptive cross-sectional survey was employed in the study. Pre-tested (Cronbach's alpha value of 0.72) and validated questionnaires comprising 37 open-ended and close-ended questions were administered to 44 doctors and 116 nurses at the CCTH who had been practicing for at least six months prior to study. Out of the 160 administered questionnaires, 86 was administered face-to-face and the remaining via e-mails. Descriptive analysis was performed and the results were presented in simple frequencies and percentages. Binary logistic regression model was used to test association of the independent variables with SR-ADRs. With a response rate of 86.4% for physicians and 59.5% for nurses, 38 (35.5%) physicians and 69 (64.5%) nurses completed the questionnaires and returned same. Majority (82.3%, 88) of the respondents knew that it is their responsibility to report ADRs although their knowledge levels was found to be inadequate (that is ≤80%) in majority (66.7%) of the text items that assessed knowledge levels. On the attitude of respondents, it was found that 57% (61) of them agreed that under-reporting was due to complacency whereas 80.4% (86) of them agreed that it was due the lack of adequate training. On the issues of practice, the prevalence of encountering, assisting in the management, and reporting of ADRs were 26.1% (28), 17.8% (19) and 7.5% (8) respectively. Also, nurses were 1.22 times more likely to encounter a patient with ADRs and twice more likely to fill and forward ADR form than doctors during management. Respondents with more than six months but less than one year of practice experience were more likely (AOR = 1.38, 95% CI: 2.72-7.3) to encounter a patient with ADRs as compared to those with just six months of practice experience. Furthermore, male respondents were more likely (AOR = 2.42, 95% CI: 1-5.85) to encounter patients with ADRs but less likely (AOR = 0.49, 95% CI: 0.91-2.6) to fill and forward ADR form compared to their female counterparts. In conclusion, doctors and nurses at the CCTH had inadequate knowledge about ADRs and its existing pharmacovigilance systems, thus accounting for the low spontaneous ADRs reporting in the facility.

Combining Machine Learning with a Rule-Based Algorithm to Detect and Identify Related Entities of Documented Adverse Drug Reactions on Hospital Discharge Summaries

INTRODUCTION

Discharge summaries contain valuable information about adverse drug reactions, but their unstructured nature makes them challenging to analyse and use as a signal source for pharmacovigilance. Machine learning has shown promise in identifying discharge summaries that contain related drug-adverse event pairs but has fared relatively poorer in entity extraction.

METHODS

A hybrid model is developed combining rule-based and machine learning algorithms using discharge summaries with the aim of maximising capture of related drug-adverse event pairs. The rule first identifies segments containing adverse event entities within a 100-character distance from a drug term; machine learning subsequently estimates the relatedness of the drug and adverse event entities contained. The approach is validated on four independent datasets that are temporally and geographically separated from model development data. The impact of restricted drug-adverse event pair detection on recall is evaluated by using two of the four validation datasets that do not impose rule-based restrictions to annotations.

RESULTS

The hybrid model achieves a recall of 0.80 (fivefold cross validation), 0.80 (temporal) and 0.76 (geographical) on validation using datasets containing only pre-identified target text segments that fulfil the rule-based algorithm criteria. When tested on datasets that additionally contained drug-adverse event pairs not restricted by the rule-based criteria, recall of the model declines to 0.68 and 0.62 on temporally and geographically separated datasets, respectively.

CONCLUSIONS

The proposed hybrid model demonstrates reasonable generalisability on external validation. Rule-based restriction of the detection space results in an approximately 12-14% reduction in recall but improves identification of the related drug and adverse event terms.

Access to Telepharmacy Services May Reduce Hospital Admissions in Outpatient Populations During the COVID-19 Pandemic

Introduction:

Avoidable hospital admissions put increased pressure on already strained health care resources, causing emotional and financial distress for patients and their families while taxing the health system. Pharmacist involvement in patient care has been shown to improve health care outcomes. Telepharmacy allows for personalized interaction and access to pharmacy services in a flexible format. The primary aim of this report is to explore the impact that access to a personalized telepharmacy service has on the hospital admission rate in an outpatient population before and during the COVID-19 pandemic.

Materials and Methods:

A retrospective, double-arm cohort study was performed. Hospital admission rates were analyzed in two similarly aged groups; one group (n = 2,242) had access to telepharmacy services through their primary care provider and another group did not (n = 1,540), from 2019 to 2020. Statistical analysis was performed to explore hospitalization rates in both groups.

Results:

An increase in hospitalization rates was observed in both groups of patients from 2019 to 2020. The patient group that had access to the telepharmacy service demonstrated a reduced rise in hospitalization rates versus the group without access to the telepharmacy service (access group +12.9% vs. nonaccess group +40.2%, p < 0.05, Student's t-test).

Discussion:

The patient group with access to telepharmacy services demonstrated a reduced increase in hospitalizations versus the group without access in 2020. While this represents a preliminary investigation into the potential impacts of telepharmacy on hospitalization rates, telepharmacy services may have a role in improving patient outcomes and cost savings.

Self-Efficacy, Social Activity, and Spirituality in the Care of Elderly Patients with Polypharmacy in Germany-A Multicentric Cross-Sectional Study within the HoPES3 Trial

About one third of Europe’s elderly population takes ≥5 drugs. Polypharmacy increases their risk of adverse drug reactions. To ensure drug safety, innovative approaches are needed. The aim of this cross-sectional study was to explore the relationship between psychosocial factors and medication-related beliefs and behaviors. Medication lists of 297 patients were recorded according to the ATC classification. Correlations between the dependent variables, Medication Adherence (MARS) and Beliefs about Medicines (BMQ), and independent variables, General Self-Efficacy (GSE), self-efficacy for managing chronic diseases (SES6G), spiritual needs (SpNQ), patient activity (PAM), loneliness (DJG), and social networks (LSNS), were measured. Patients with higher self-efficacy (OR: 1.113; 95% CI [1.056–1.174]; p < 0.001) or self-confidence in managing their chronic condition (OR: 1.188; 95% CI [1.048–1.346]; p < 0.007) also showed higher adherence. Lonely patients (OR: 0.420; 95% CI [0.267–0.660]; p < 0.001) and those with a need for inner peace (OR: 0.613; 95% CI [0.444–0.846], p = 0.003) were more likely nonadherent. Stronger positive beliefs about medications’ usefulness weakly correlated with higher scores on the SES6G (ρ = 0.178, p = 0.003) and GSES scale (ρ = 0.121, p = 0.042), patient activity (ρ = 0.155, p = 0.010) and functioning social networks scale (ρ = 0.159, p = 0.008). A weak positive correlation was found between loneliness and the belief that drugs were harmful (ρ = 0.194, p = 0.001). Furthermore, interesting correlations were detected regarding the number of medications and overuse beliefs. Psychosocial factors, such as self-efficacy, loneliness, and spiritual needs and medication-related beliefs and behaviors seem to interrelate. Addressing these factors may improve medication management and drug safety.

Health outcomes and policy in pharmay curricula among Arab countries: An evaluation of 191 academic institutions

INTRODUCTION

Health outcomes and policies is a growing areas that is needed in the healthcare culture. This study aimed to examine the availability, extent and type of teaching curricula (pharmacoeconomics, pharmacoepidemiology, pharmacovigilance, patient safety) in Arab countries.

METHODS

A retrospective observational study was conducted during the period of November 2019 to January 2020. The collection strategy was performed by listing of pharmacy colleges in each country and then reviewing the institutions' websites that met the inclusion criteria. Five criteria were utilized to assess the availability of these courses: full-time mandatory, full-time elective, partial mandatory, partial elective, and not offered.

RESULTS

One hundred ninety-one academic institutions were screened during the study period. Of those, 151 (79.1%) institutions were included in the study and their curricular descriptions were retrieved from their electronic websites. Pharmacoeconomics was the most taught subject among the four subjects. It was offered in 89/151 of the colleges among Arab countries. Among these 89 colleges that offered pharmacoeconomics, 74/89 offered it as a mandatory. While, Pharmacoepidemiology was offered in 51 colleges, with 44/51 offering the subject as a mandatory, and 6 out of those 44 list it as a full-time mandatory, while 38 out of those 44 offer it as a partially mandatory. Only 22 of the colleges offered pharmacovigilance, with 14/22 offering the subject as a mandatory. Finally, there was only one institution that offers the subject of patient safety. Moreover, most of the four courses investigated are only taught in the final two years of study.

CONCLUSIONS

The study found a clear shortcoming in the teaching pharmaceutical outcomes. More efforts are needed by academic institutions to adopt and teach these subjects to ensure they meet the work needs and advanced pharmacy practice transformation.

Genetics of Severe Cutaneous Adverse Reactions

Severe cutaneous adverse reactions (SCARs) including Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), and drug rash with eosinophilia and systemic symptoms (DRESS) are T cells-mediated life-threatening immune reactions, most commonly induced by drug. The last decade has seen significant progress in SCARs research. Recent studies have unveiled the pathogenesis of SCARs involved in susceptible genes, including human leukocyte antigens (HLA) and drugs-T cell receptor (TCR) interaction that may trigger T cell activation with downstream immune signaling of cytokines/chemokines and specific cytotoxic proteins releases. Advances in identification of multiple genetic alleles associated with specific drugs related SCARS in different populations is an important breakthrough in recent years for prevention of SCARs. This article summarized the findings on genetic factors related to SJS/TEN, especially for HLA.

Pharmacogenetics in primary care

The use of pharmacogenetic information is becoming mainstream with insurance companies and others starting to pay for widescale implementation of this new technology starting with patients who have anxiety and depression. It has been introduced in response to the unpredictability of medication, the high number of adverse drug events, and lack of drug effectiveness. Greater than one-third of patients are identified as having one or more pharmacogenetic variants. Each pharmacogenetic variant may affect the metabolism of several medications used in primary care, in addition to the antidepressant and anti-anxiolytic medications. Pharmacogenetic information is evolving with major international working groups providing continuous updates. It is challenging to incorporate this new information along with all the other variables needed to identify safe and effective drug options within a normal consultation. Medication decision support software is one solution that can help address this.

Detecting adverse drug reactions in discharge summaries of electronic medical records using Readpeer

BACKGROUND

Hospital discharge summaries offer a potentially rich resource to enhance pharmacovigilance efforts to evaluate drug safety in real-world clinical practice. However, it is infeasible for experts to read through all discharge summaries to find cases of drug-adverse event (AE) relations.

PURPOSE

The objective of this paper is to develop a natural language processing (NLP) framework to detect drug-AE relations from unstructured hospital discharge summaries.

BASIC PROCEDURES

An NLP algorithm was designed using customized dictionaries of drugs, adverse event (AE) terms, and rules based on trigger phrases, negations, fuzzy logic and word distances to recognize drug, AE terms and to detect drug-AE relations. Furthermore, a customized annotation tool was developed to facilitate expert review of discharge summaries from a tertiary hospital in Singapore in 2011.

MAIN FINDINGS

A total of 33 trial sets with 50 to 100 records per set were evaluated (1620 discharge summaries) by our algorithm and reviewed by pharmacovigilance experts. After every 6 trial sets, drug and AE dictionaries were updated, and rules were modified to improve the system. Excellent performance was achieved for drug and AE entity recognition with over 92% precision and recall. On the final 6 sets of discharge summaries (600 records), our algorithm achieved 75% precision and 59% recall for identification of valid drug-AE relations.

PRINCIPAL CONCLUSIONS

Adverse drug reactions are a significant contributor to health care costs and utilization. Our algorithm is not restricted to particular drugs, drug classes or specific medical specialties, which is an important attribute for a national regulatory authority to carry out comprehensive safety monitoring of drug products. Drug and AE dictionaries may be updated periodically to ensure that the tool remains relevant for performing surveillance activities. The development of the algorithm, and the ease of reviewing and correcting the results of the algorithm as part of an iterative machine learning process, is an important step towards use of hospital discharge summaries for an active pharmacovigilance program.