Detection of adverse drug events in e-prescribing and administrative health data: a validation study

Co-Designing a Consumer-Focused Digital Reporting Health Platform to Improve Adverse Medicine Event Reporting: Protocol for a Multimethod Research Project (the ReMedi Project)

BACKGROUND

Adverse medicine events (AMEs) are unintended effects that occur following administration of medicines. Up to 70% of AMEs are not reported to, and hence remain undetected by, health care professionals and only 6% of AMEs are reported to regulators. Increased reporting by consumers, health care professionals, and pharmaceutical companies to medicine regulatory authorities is needed to increase the safety of medicines.

OBJECTIVE

We describe a project that aims to co-design a digital reporting platform to improve detection and management of AMEs by consumers and health care professionals and improve reporting to regulators.

METHODS

The project will be conducted in 3 phases and uses a co-design methodology that prioritizes equity in designing with stakeholders. Our project is guided by the Consolidated Framework for Implementation Research. In phase 1, we will engage with 3 stakeholder groups-consumers, health care professionals, and regulators-to define digital platform development standards. We will conduct a series of individual interviews, focus group discussions, and co-design workshops with the stakeholder groups. In phase 2, we will work with a software developer and user interaction design experts to prototype, test, and develop the digital reporting platform based on findings from phase 1. In phase 3, we will implement and trial the digital reporting platform in South Australia through general practices and pharmacies. Consumers who have recently started using medicines new to them will be recruited to use the digital reporting platform to report any apparent, suspected, or possible AMEs since starting the new medicine. Process and outcome evaluations will be conducted to assess the implementation process and to determine whether the new platform has increased AME detection and reporting.

RESULTS

This project, initiated in 2023, will run until 2026. Phase 1 will result in persona profiles and user journey maps that define the standards for the user-friendly platform and interactive data visualization tool or dashboard that will be developed and further improved in phase 2. Finally, phase 3 will provide insights of the implemented platform regarding its impact on AME detection, management, and reporting. Findings will be published progressively as we complete the different phases of the project.

CONCLUSIONS

This project adopts a co-design methodology to develop a new digital reporting platform for AME detection and reporting, considering the perspectives and lived experience of stakeholders and addressing their requirements throughout the entire process. The overarching goal of the project is to leverage the potential of both consumers and technology to address the existing challenges of underdetection and underreporting of AMEs to health care professionals and regulators. The project potentially will improve individual patient safety and generate new data for regulatory purposes related to medicine safety and effectiveness.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/60084.

Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile-A Retrospective Population-Based Study in a Swedish Region

Adverse drug events (ADEs) occur frequently and are a common cause of suffering, hospitalizations, or death, and can be caused by harmful combinations of medications. One method used to prevent ADEs is by using clinical decision support systems (CDSSs). Janusmed Risk Profile is a CDSS evaluating the risk for nine common or serious ADEs resulting from combined pharmacodynamic effects. The aim of this study was to examine the prevalence of potential ADEs identified using CDSS algorithms from Janusmed Risk Profile. This retrospective, cross-sectional study covered the population of a Swedish region (n = 246,010 inhabitants in year 2020) using data on all medications dispensed and administered. More than 20% of patients had an increased risk of bleeding, constipation, orthostatism, or renal toxicity based on their medications. The proportion of patients with an increased risk varied from 3.5% to almost 30% across the nine categories of ADEs. A higher age was associated with an increased risk of potential ADEs and there were gender differences. A cluster analysis identified groups of patients with an increased risk for several categories of ADEs. This study shows that combinations of medications that could increase the risk of ADEs are common. Future studies should examine how this correlates with observed ADEs.

Sharing Adverse Drug Event Reports Between Hospitals and Community Pharmacists to Inform Re-dispensing: An Analysis of Reports and Process Outcomes

INTRODUCTION

Adverse drug events (ADEs) are a leading cause of unplanned hospital visits. We designed ActionADE, an online ADE reporting platform, and integrated it with PharmaNet, British Columbia's (BC's) provincial medication dispensing system, to overcome identified barriers in ADE reporting and communicate ADEs to community pharmacies. Our objectives were to characterise ADEs reported in ActionADE, explore associations between patients' age, sex and ADE characteristics, and estimate the re-dispensation rate of culprit medications in community pharmacies.

METHODS

We conducted a prospective observational study of ADE reporting in four BC hospitals between April 1, 2020 and October 31, 2022. We described the characteristics of ADEs reported into ActionADE, used logistic regression modelling to examine associations between age and sex and ADE characteristics, and calculated rates of avoided culprit drug re-dispensations using community pharmacists' responses to ActionADE alerts.

RESULTS

In total, 3591 ADE reports were initiated by hospital clinicians, 3174 of which were included in this analysis. Serious or life-threatening ADEs resulting in permanent disability, hospitalisation, extended hospitalisation, and/or death accounted for 28.5% (906/3174; 95% CI 27.0-30.1%) of reports. Males were more likely to have non-adherence reported compared to females and experienced life threatening ADEs at a younger age than females. Of 592 patients who had ≥ 1 adverse drug reaction or allergy report (a subset of ADEs) transmitted to community pharmacies, 200 subsequently attempted to re-fill the culprit or a same class drug. Community pharmacists responded to preventative alerts by avoiding re-dispensation in 33.0% (66/200; 95% CI 26.5-39.5%).

INTERPRETATION

ActionADE is the first interoperable system that communicates ADEs via a central medication database to community pharmacies. Every 10th ADE reported in ActionADE and shared to PharmaNet resulted in community pharmacists' avoiding one culprit or same class drug re-exposure. Further research is needed to understand ActionADE's impact on patient and health system outcomes.

A Narrative Review of Adverse Event Detection, Monitoring, and Prevention in Indian Hospitals

An adverse event is any abnormal clinical finding associated with the use of a therapy. Adverse events are classified by reporting an event's seriousness, expectedness, and relatedness. Monitoring patient safety is of utmost importance as more and more data becomes available. In reality, very low numbers of adverse events are reported via the official path. Chart review, voluntary reporting, computerized surveillance, and direct observation can detect adverse drug events. Medication errors are commonly seen in hospitals and need provider and system-based interventions to prevent them. The need of the hour in India is to develop and implement medication safety best practices to avoid adverse events. The utility of artificial intelligence techniques in adverse event detection remains unexplored, and their accuracy and precision need to be studied in a controlled setting. There is a need to develop predictive models to assess the likelihood of adverse reactions while testing novel pharmaceutical drugs.

Deprescribing Opportunities for Hospitalized Patients With End-Stage Kidney Disease on Hemodialysis: A Secondary Analysis of the MedSafer Cluster Randomized Controlled Trial

Background

End-stage kidney disease patients on dialysis have a substantial risk of polypharmacy due their propensity for comorbidity and contact with the health care system. MedSafer is an electronic decision support tool that integrates patient comorbidity and medication lists to generate personalized deprescribing reports focused on identifying potentially inappropriate medications (PIMs).

Objective

To conduct a secondary analysis of patients on regular hemodialysis included in the MedSafer randomized controlled trial to investigate the patterns of polypharmacy and evaluate the efficacy of the MedSafer deprescribing algorithms.

Design

Secondary analysis of a cluster randomized clinical trial.

Setting

Medical units in 11 acute care hospitals in Canada.

Patients

The MedSafer trial enrolled 5698 participants with an expected prognosis of >3 months, age 65 years and older, and on 5 or more daily home medications; 140 participants were receiving chronic hemodialysis.

Measurements

The primary outcome of the trial was 30-day adverse drug events (ADEs) post-hospital discharge, and a key secondary outcome was deprescribing.

Methods

Control patients received usual care (medication reconciliation), whereas clinicians caring for intervention patients received a MedSafer report that highlighted individualized opportunities for deprescribing.

Results

There were 70 patients in each of the control and intervention arms. The median number of home medications was 14 (compared with a median of 10 medications in the general trial population). The most frequent medications observed that were potentially inappropriate were proton pump inhibitors (potentially inappropriate in 55/76 users; 72.4%), diabetes medications in patients with a HBA1C <7.5% (36/65 users; 55.4%), docusate (27/27 users; 100%), gabapentinoids (27/36 users; 75%), and combination antiplatelet/anticoagulants (22/97 users; 22.7%). The proportion of PIMs deprescribed was higher during the intervention phase (28.8% vs 19.3%; absolute increase 9.4% [95% confidence interval 1.3%-17.6%]) compared with the control phase. There was no observed difference in ADEs at 30-day post-discharge between the control and the intervention groups. The most common ADE (n = 3) was gastrointestinal bleeding attributed to antiplatelet agents.

Limitations

This was a post hoc exploratory analysis, the original trial did not stratify by hemodialysis status, and the small sample size precludes drawing any definitive conclusions.

Conclusion

MedSafer facilitates deprescribing in hospitalized patients on hemodialysis. Larger-scale implementation of decision support software for deprescribing in dialysis and long-term follow-up are likely required to demonstrate an impact on ADEs.

The MedSafer Study-Electronic Decision Support for Deprescribing in Hospitalized Older Adults: A Cluster Randomized Clinical Trial

IMPORTANCE

Scalable deprescribing interventions may reduce polypharmacy and the use of potentially inappropriate medications (PIMs); however, few studies have been large enough to evaluate the impact that deprescribing may have on adverse drug events (ADEs).

OBJECTIVE

To evaluate the effect of an electronic deprescribing decision support tool on ADEs after hospital discharge among older adults with polypharmacy.

DESIGN, SETTING, AND PARTICIPANTS

This was a cluster randomized clinical trial of older (≥65 years) hospitalized patients with an expected survival of more than 3 months who were admitted to 1 of 11 acute care hospitals in Canada from August 22, 2017, to January 13, 2020. At admission, participants were taking 5 or more medications per day. Data analyses were performed from January 3, 2021, to September 23, 2021.

INTERVENTIONS

Personalized reports of deprescribing opportunities generated by MedSafer software to address usual home medications and measures of prognosis and frailty. Deprescribing reports provided to the treating team were compared with usual care (medication reconciliation).

MAIN OUTCOMES AND MEASURES

The primary outcome was a reduction of ADEs within the first 30 days postdischarge (including adverse drug withdrawal events) captured through structured telephone surveys and adjudicated blinded to intervention status. Secondary outcomes were the proportion of patients with 1 or more PIMs deprescribed at discharge and the proportion of patients with an adverse drug withdrawal event (ADWE).

RESULTS

A total of 5698 participants (median [range] age, 78 [72-85] years; 2858 [50.2%] women; race and ethnicity data were not collected) were enrolled in 3 clusters and were adjudicated for the primary outcome (control, 3204; intervention, 2494). Despite cluster randomization, there were group imbalances, eg, the participants in the intervention arm were older and had more PIMS prescribed at baseline. After hospital discharge, 4989 (87.6%) participants completed an ADE interview. There was no significant difference in ADEs within 30 days of discharge (138 [5.0%] of 2742 control vs 111 [4.9%] of 2247 intervention participants; adjusted risk difference [aRD] -0.8%; 95% CI, -2.9% to 1.3%). Deprescribing increased from 795 (29.8%) of 2667 control to 1249 (55.4%) of 2256 intervention participants [aRD, 22.2%; 95% CI, 16.9% to 27.4%]. There was no difference in ADWEs between groups. Several post hoc sensitivity analyses, including the use of a nonparametric test to address the low cluster number, group imbalances, and potential biases, did not alter study conclusions.

CONCLUSIONS AND RELEVANCE

This cluster randomized clinical trial showed that providing deprescribing clinical decision support during acute hospitalization had no demonstrable impact on ADEs, although the intervention was safe and led to improvements in deprescribing.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03272607.