Dataset Information

Evaluating the risk of patient re-identification from adverse drug event reports.

ABSTRACT: Our objective was to develop a model for measuring re-identification risk that more closely mimics the behaviour of an adversary by accounting for repeated attempts at matching and verification of matches, and apply it to evaluate the risk of re-identification for Canada's post-marketing adverse drug event database (ADE).Re-identification is only demonstrably plausible for deaths in ADE. A matching experiment between ADE records and virtual obituaries constructed from Statistics Canada vital statistics was simulated. A new re-identification risk is considered, it assumes that after gathering all the potential matches for a patient record (all records in the obituaries that are potential matches for an ADE record), an adversary tries to verify these potential matches. Two adversary scenarios were considered: (a) a mildly motivated adversary who will stop after one verification attempt, and (b) a highly motivated adversary who will attempt to verify all the potential matches and is only limited by practical or financial considerations.The mean percentage of records in ADE that had a high probability of being re-identified was computed.Under scenario (a), the risk of re-identification from disclosing the province, age at death, gender, and exact date of the report is quite high, but the removal of province brings down the risk significantly. By only generalizing the date of reporting to month and year and including all other variables, the risk is always low. All ADE records have a high risk of re-identification under scenario (b), but the plausibility of that scenario is limited because of the financial and practical deterrent even for highly motivated adversaries.It is possible to disclose Canada's adverse drug event database while ensuring that plausible re-identification risks are acceptably low. Our new re-identification risk model is suitable for such risk assessments.

SUBMITTER: El Emam K

PROVIDER: S-EPMC4137558 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Evaluating the risk of patient re-identification from adverse drug event reports.

El Emam Khaled K Dankar Fida K FK Neisa Angelica A Jonker Elizabeth E

BMC medical informatics and decision making 20131005

<h4>Background</h4>Our objective was to develop a model for measuring re-identification risk that more closely mimics the behaviour of an adversary by accounting for repeated attempts at matching and verification of matches, and apply it to evaluate the risk of re-identification for Canada's post-marketing adverse drug event database (ADE).Re-identification is only demonstrably plausible for deaths in ADE. A matching experiment between ADE records and virtual obituaries constructed from Statisti ...[more]

PMID: 24094134

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Project description:IntroductionAdverse 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.MethodsWe 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.ResultsIn 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%).InterpretationActionADE 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.

Project description:BackgroundAntipsychotics (APs) have been associated with risk of torsade de Pointes (TdP). This has important public health implications. Therefore, (a) we exploited the public FDA Adverse Event Reporting System (FAERS) to characterize their torsadogenic profile; (b) we collected drug utilization data from 12 European Countries to assess the population exposure over the 2005-2010 period.MethodsFAERS data (2004-2010) were analyzed based on the following criteria: (1) ? 4 cases of TdP/QT abnormalities; (2) Significant Reporting Odds Ratio, ROR [Lower Limit of the 95% confidence interval>1], for TdP/QT abnormalities, adjusted and stratified (Arizona CERT drugs as effect modifiers); (3) ? 4 cases of ventricular arrhythmia/sudden cardiac death (VA/SCD); (4) Significant ROR for VA/SCD; (5) Significant ROR, combined by aggregating TdP/QT abnormalities with VA and SCD. Torsadogenic signals were characterized in terms of signal strength: from Group A (very strong torsadogenic signal: all criteria fulfilled) to group E (unclear/uncertain signal: only 2/5 criteria). Consumption data were retrieved from 12 European Countries and expressed as defined daily doses per 1,000 inhabitants per day (DID).ResultsThirty-five antipsychotics met at least one criterium: 9 agents were classified in Group A (amisulpride, chlorpromazine, clozapine, cyamemazine, haloperidol, olanzapine, quetiapine, risperidone, ziprasidone). In 2010, the overall exposure to antipsychotics varied from 5.94 DID (Estonia) to 13.99 (France, 2009). Considerable increment of Group A agents was found in several Countries (+3.47 in France): the exposure to olanzapine increased across all Countries (+1.84 in France) and peaked 2.96 in Norway; cyamemazine was typically used only in France (2.81 in 2009). Among Group B drugs, levomepromazine peaked 3.78 (Serbia); fluphenazine 1.61 (Slovenia).ConclusionsThis parallel approach through spontaneous reporting and drug utilization analyses highlighted drug- and Country-specific scenarios requiring potential regulatory consideration: levomepromazine (Serbia), fluphenazine (Slovenia), olanzapine (across Europe), cyamemazine (France). This synergy should be encouraged to support future pharmacovigilance activities.

Project description:BackgroundThere is a high degree of variability in assessing the preventability of adverse drug events, limiting the ability to compare rates of preventable adverse drug events across different studies. We compared three methods for determining preventability of adverse drug events in emergency department patients and explored their strengths and weaknesses.MethodsThis mixed-methods study enrolled emergency department patients diagnosed with at least one adverse drug event from three prior prospective studies. A clinical pharmacist and physician reviewed the medical and research records of all patients, and independently rated each event's preventability using a "best practice-based" approach, an "error-based" approach, and an "algorithm-based" approach. Raters discussed discordant ratings until reaching consensus. We assessed the inter-rater agreement between clinicians using the same assessment method, and between different assessment methods using Cohen's kappa with 95% confidence intervals (95% CI). Qualitative researchers observed discussions, took field notes, and reviewed free text comments made by clinicians in a "comment" box in the data collection form. We developed a coding structure and iteratively analyzed qualitative data for emerging themes regarding the application of each preventability assessment method using NVivo.ResultsAmong 1356 adverse drug events, a best practice-based approach rated 64.1% (95% CI: 61.5-66.6%) of events as preventable, an error-based approach rated 64.3% (95% CI: 61.8-66.9%) of events as preventable, and an algorithm-based approach rated 68.8% (95% CI: 66.1-71.1%) of events as preventable. When applying the same method, the inter-rater agreement between clinicians was 0.53 (95% CI: 0.48-0.59), 0.55 (95%CI: 0.50-0.60) and 0.55 (95% CI: 0.49-0.55) for the best practice-, error-, and algorithm-based approaches, respectively. The inter-rater agreement between different assessment methods using consensus ratings for each ranged between 0.88 (95% CI 0.85-0.91) and 0.99 (95% CI 0.98-1.00). Compared to a best practice-based assessment, clinicians believed the algorithm-based assessment was too rigid. It did not account for the complexities of and variations in clinical practice, and frequently was too definitive when assigning preventability ratings.ConclusionThere was good agreement between all three methods of determining the preventability of adverse drug events. However, clinicians found the algorithmic approach constraining, and preferred a best practice-based assessment method.

Dataset Information

Evaluating the risk of patient re-identification from adverse drug event reports.

Publications

Evaluating the risk of patient re-identification from adverse drug event reports.

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