Validating a Trigger Tool for Detecting Adverse Drug Events in Elderly Patients With Multimorbidity (TRIGGER-CHRON)

Development and validation of trigger tools in primary care: A scoping review

In primary care, trigger tools have been utilized to evaluate and identify patient safety events. The use of trigger tools could help clinicians and patients detect adverse events in a patient's medical record. Due to a lack of research on the process development of trigger tools in primary care, the purpose of this scoping review is to investigate the trigger development and validation process in primary care settings. A scoping review methodology was used to map the published literature using the Joanna Briggs Methodology of performing scoping review. We considered only studies published in English in the last five years and included both qualitative and quantitative study designs. The final review included five articles. The primary care and combined primary-secondary care studies are included to gain more knowledge in the process development and validation of trigger tools. The trigger tool development process begins with clearly defining the triggers, which are then programmed into a combined computerized algorithm. The validation process was then carried out in two steps by both physician and non-physician experts for content and concurrent validity. The sensitivity, specificity, and positive predictive value (PPV) of the final algorithm were critical in determining the validity of each trigger. This study provided a comprehensive guide to developing trigger tools, emphasizing the importance of precisely defining triggers through a thorough literature review and dual validation process. There were similarities in the development and validation of trigger tools across primary care and hospital settings, allowing primary care to learn from hospital settings.

Machine learning to predict adverse drug events based on electronic health records: a systematic review and meta-analysis

OBJECTIVE

This systematic review aimed to provide a comprehensive overview of the application of machine learning (ML) in predicting multiple adverse drug events (ADEs) using electronic health record (EHR) data.

METHODS

Systematic searches were conducted using PubMed, Web of Science, Embase, and IEEE Xplore from database inception until 21 November 2023. Studies that developed ML models for predicting multiple ADEs based on EHR data were included.

RESULTS

Ten studies met the inclusion criteria. Twenty ML methods were reported, most commonly random forest (RF, n = 9), followed by AdaBoost (n = 4), eXtreme Gradient Boosting (n = 3), and support vector machine (n = 3). The mean area under the summary receiver operator characteristics curve (AUC) was 0.76 (95% confidence interval [CI] = 0.26-0.95). RF combined with resampling-based approaches achieved high AUCs (0.9448-0.9457). The common risk factors of ADEs included the length of hospital stay, number of prescribed drugs, and admission type. The pooled estimated AUC was 0.72 (95% CI = 0.68-0.75).

CONCLUSIONS

Future studies should adhere to more rigorous reporting standards and consider new ML methods to facilitate the application of ML models in clinical practice.

Performance of triggers in detecting hospitalizations related to drug-induced respiratory disorders in older adults: A pilot cross-sectional study

BACKGROUND

There is no gold-standard trigger for detecting drug-induced respiratory disorders, a type of Adverse Drug Event (ADE) with high morbimortality, particularly in older people.

OBJECTIVE

To propose and evaluate the performance of triggers for detecting hospitalizations related to drug-induced respiratory disorders in older people.

METHODS

A pilot cross-sectional study was conducted with older people (age ≥ 60) admitted to a Brazilian hospital. Electronic chart documentation was screened using ICD-10 codes; Global Trigger Tool (GTT); and drugs potentially associated with respiratory disorders. A chart and medication review were conducted to perform the causality assessment using the instrument developed by the World Health Organization. The performance of triggers was evaluated by the Positive Predictive Value (PPV), with values ≥ 0.20 indicating good performance.

RESULTS

Among 221 older people, 72 were eligible. Potential drug-induced dyspnea and/or cough were detected in six older people (6/72), corresponding to a prevalence of 8.3 %. The overall PPV of the triggers was 0.14, with abrupt medication stop (PPV = 1.00), codeine (PPV = 1.00), captopril (PPV = 0.33), and carvedilol (PPV = 0.33) showing good performance. Two triggers were proposed for detecting therapeutic ineffectiveness associated with respiratory disorders: furosemide (PPV = 0.23) and prednisone (PPV = 0.20).

CONCLUSION

The triggers enabled the identification that one in 12 hospitalizations was related to drug-induced respiratory. Although good performance was observed in the application of triggers, additional investigations are needed to assess the feasibility of incorporating them into clinical practice for the screening, detection, management, and reporting of these ADEs, which are considered to be underreported and difficult to detect.

Application of trigger tools for detecting adverse drug events in older people: A systematic review and meta-analysis

OBJECTIVE

To identify trigger tools applied to detect adverse drug events (ADEs) in older people and describe their utility and performance.

METHODS

A systematic review was conducted in the PubMed, Lilacs, and Scopus databases (January 2024). Studies that developed, applied, or validated trigger tools and evaluated their utility and/or performance for detecting ADEs in older people were considered. Direct proportion meta-analyses using the inverse-variance method were performed for prevalence of ADEs and positive predictive value (PPV).

RESULTS

Twenty-four studies (25 publications) were included. Twelve trigger tools were identified, of which six were developed for detecting ADEs in older population, four developed for general population and modified for older people, and two developed for general population. No tools for detecting ADEs in older people receiving palliative care or hospitalized in intensive or surgical care units were found. The performance of triggers was presented through PPV (11.5-71%), negative predictive values (83.3%), and sensitivity (30-94.8%). The overall PPV was 33.3% (95%CI: 32.5-34.2%). Triggers with good performance were changes in plasma levels of digoxin, glucose, and potassium; changes in international normalized ratio; abrupt medication stop; hypotension; and constipation. The prevalence of ADEs ranged from 2.8 to 66%, with overall prevalence of ADEs of 20% (95%CI: 19.3-20.8%). Preventability ranged from 8.4 to 94.4%. Metabolic or electrolyte disturbances induced by diuretics, constipation induced by opioids, and falls and delirium induced by benzodiazepines were the most prevalent ADEs.

CONCLUSION

The trigger tools are flexible and easy to apply, and they can contribute to the detection of ADEs, their associated risk factors, the level of harm, and preventability in different health settings. However, there is no consensus on good or poor values of PPV, which indicate the performance of triggers. Furthermore, there is limited evidence regarding the evaluation of performance through negative predictive value, sensitivity, and specificity.

PROSPERO

CRD42022379893.

Active monitoring of antifungal adverse events in hospitalized patients based on Global Trigger Tool method

Background

The increasing prevalence of fungal infections necessitates broader use of antifungal medications. However, the prevalence of adverse drug events (ADEs) restricts their clinical application. This study aimed to develop a reliable ADEs trigger for antifungals to enable proactive ADEs monitoring, serving as a reference for ADEs prevention and control.

Methods

This investigation comprises two phases. Initially, the trigger was established via a literature review, extraction of relevant items, and refinement through Delphi expert consultation. Subsequently, the validity of the trigger was assessed by analyzing hospital records of antifungal drug users from 1 January 2019 to 31 December 2020. The correlation between each trigger signal and ADEs occurrence was examined, and the sensitivity and specificity of the trigger were evaluated through the spontaneous reporting system (SRS) and Global Trigger Tool (GTT). Additionally, risk factors contributing to adverse drug events (ADEs) resulting from antifungal use were analyzed. Results: Twenty-one preliminary triggers were refined into 21 final triggers after one expert round. In the retrospective analysis, the positive trigger rate was 65.83%, with a positive predictive value (PPV) of 28.75%. The incidence of ADEs in inpatients was 28.75%, equating to 44.58 ADEs per 100 admissions and 33.04 ADEs per 1,000 patient days. Predominant ADEs categories included metabolic disturbances, gastrointestinal damage, and skin rashes. ADEs severity was classified into 36 cases at grade 1, 160 at grade 2, and 18 at grade 3. The likelihood of ADEs increased with longer stays, more positive triggers, and greater comorbidity counts.

Conclusion

This study underscores the effectiveness of the GTT in enhancing ADEs detection during antifungal medication use, thereby confirming its value as a monitoring tool.

Establishing a trigger tool based on global trigger tools to identify adverse drug events in obstetric inpatients in China

BACKGROUND

Pregnant women belong to the special population of drug therapy, and their physiological state, pharmacokinetics and pharmacodynamics are significantly different from the general population. Drug safety during pregnancy involves two generations, which is a hot issue widely concerned in the whole society. Global Trigger Tool (GTT) of the Institute for Healthcare Improvement (IHI) has been wildly used as a patient safety measurement strategy by several institutions and national programs, and the effectiveness had been demonstrated. But only one study reports the use of GTT in obstetric delivery until now. The aim of the study is to establish triggers detecting adverse drug events (ADEs) suitable for obstetric inpatients on the basis of the GTT, to examine the performance of the obstetric triggers in detecting ADEs experienced by obstetric units compared with the spontaneous reporting system and GTT, and to assess the utility and value of the obstetric trigger tool in identifying ADEs of obstetric inpatients.

METHODS

Based on a literature review searched in PubMed and CNKI from January of 1997 to October of 2023, retrospective local obstetric ADEs investigations, relevant obstetric guidelines and the common adverse reactions of obstetric therapeutic drugs were involved to establish the initial obstetric triggers. According to the Delphi method, two rounds of expert questionnaire survey were conducted among 16 obstetric and neonatological physicians and pharmacists until an agreement was reached. A retrospective study was conducted to identity ADEs in 300 obstetric inpatient records at the Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital from June 1 to September 30, 2018. Two trained junior pharmacists analyzed the first eligible records independently, and the included records reviewed by trained pharmacist and physician to identify ADEs. Sensitivity and specificity of the established obstetric triggers were assessed by the number of ADEs/100 patients and positive predictive value with the spontaneous reporting system (SRS) and GTT. Excel 2010 and SPSS22 were used for data analysis.

RESULTS

Through two rounds of expert investigation, 39 preliminary triggers were established that comprised four modules (12 laboratory tests, 9 medications, 14 symptoms, and 4 outcomes). A total of 300 medical records were reviewed through the obstetric triggers, of which 48 cases of ADEs were detected, with an incidence of ADEs of 16%. Among the 39 obstetric triggers, 22 (56.41%) were positive and 11 of them detected ADEs. The positive predictive value (PPV) was 36.36%, and the number of ADEs/100 patients was 16.33 (95% CI, 4.19-17.81). The ADE detection rate, positive trigger rate, and PPV for the obstetric triggers were significantly augmented, confirming that the obstetric triggers were more specific and sensitive than SRS and GTT.

CONCLUSION

The obstetric triggers were proven to be sensitive and specific in the active monitoring of ADE for obstetric inpatients, which might serve as a reference for ADE detection of obstetric inpatients at medical institutions.

Validation of a Reduced Set of High-Performance Triggers for Identifying Patient Safety Incidents with Harm in Primary Care: TriggerPrim Project

OBJECTIVE

The aim of the study was to construct and validate a reduced set of high-performance triggers for identifying adverse events (AEs) via electronic medical records (EMRs) review in primary care (PC).

METHODS

This was a cross-sectional descriptive study for validating a diagnostic test. The study included all 262 PC centers of Madrid region (Spain). Patients were older than 18 years who attended their PC center over the last quarter of 2018. The randomized sample was n = 1797. Main measurements were as follows: ( a ) presence of each of 19 specific computer-identified triggers in the EMR and ( b ) occurrence of an AE. To collect data, EMR review was conducted by 3 doctor-nurse teams. Triggers with statistically significant odds ratios for identifying AEs were selected for the final set after adjusting for age and sex using logistic regression.

RESULTS

The sensitivity (SS) and specificity (SP) for the selected triggers were: ≥3 appointments in a week at the PC center (SS = 32.3% [95% confidence interval {CI}, 22.8%-41.8%]; SP = 92.8% [95% CI, 91.6%-94.0%]); hospital admission (SS = 19.4% [95% CI, 11.4%-27.4%]; SP = 97.2% [95% CI, 96.4%-98.0%]); hospital emergency department visit (SS = 31.2% [95% CI, 21.8%-40.6%]; SP = 90.8% [95% CI, 89.4%-92.2%]); major opioids prescription (SS = 2.2% [95% CI, 0.0%-5.2%]; SP = 99.8% [95% CI, 99.6%-100%]); and chronic benzodiazepine treatment in patients 75 years or older (SS = 14.0% [95% CI, 6.9%-21.1%]; SP = 95.5% [95% CI, 94.5%-96.5%]).The following values were obtained in the validation of this trigger set (the occurrence of at least one of these triggers in the EMR): SS = 60.2% (95% CI, 50.2%-70.1%), SP = 80.8% (95% CI, 78.8%-82.6%), positive predictive value = 14.6% (95% CI, 11.0%-18.1%), negative predictive value = 97.4% (95% CI, 96.5%-98.2%), positive likelihood ratio = 3.13 (95% CI, 2.3-4.2), and negative likelihood ratio = 0.49 (95% CI, 0.3-0.7).

CONCLUSIONS

The set containing the 5 selected triggers almost triples the efficiency of EMR review in detecting AEs. This suggests that this set is easily implementable and of great utility in risk-management practice.

Adverse drug events in Chinese elder inpatients: a retrospective review for evaluating the efficiency of the Global Trigger Tool

Background

Elderly patients frequently experience a high incidence of adverse drug events (ADEs) due to the coexistence of multiple diseases, the combination of various medications, poor medication compliance, and other factors. Global Trigger Tool (GTT) is a new method for identifying ADEs, introducing the concept of a trigger, that is, clues including abnormal laboratory values, reversal drugs, and clinical symptoms that may suggest ADEs, and specifically locating information related to ADEs in the medical record to identify ADEs. The aim of this study was to establish a GTT-based trigger tool for adverse medication events in elderly patients and to investigate the risk variables associated with such events.

Methods

The triggers were identified by reviewing the frequency of ADEs in elderly patients in Sichuan, China, retrieving relevant literature, and consulting experts. A retrospective analysis was carried out to identify adverse medication occurrences among 480 elderly inpatients in Sichuan People's Hospital.

Results

A total of 56 ADEs were detected in 51 patients (10.62%), 13.04 per 1,000 patient days, and 11.67 per 100 admissions. The overall positive predictive value (PPV) of the triggers was 23.84, and 94.64% of ADEs caused temporary injury. Gastrointestinal system injury (27.87%) and metabolic and nutritional disorders (24.53%) were the primary organ-systems affected by ADEs. The majority of ADEs were caused by drugs used to treat cardiovascular diseases. 71.43% of ADE occurred within 2 days of administration and the risk factor analysis of ADE revealed that the number of medicines had a significant correlation.

Conclusion

This study demonstrated GTT's value as a tool for ADEs detection in elderly inpatients in China. It enhances the level of medication management and comprehensively reflects the situation of ADE of the elderly.

Impact of suspected adverse drug reactions on mortality and length of hospital stay in the hospitalised patients: a meta-analysis

PURPOSE

To estimate the risk of mortality and length of stay in hospitalised patients who have experienced suspected adverse drug reactions (ADRs) as compared to patients who did not experience suspected ADRs.

METHODS

A systematic literature search was conducted on databases for observational and randomised controlled studies conducted in any inpatient setting that reported deaths and/or length of hospital stay in patients who had suspected ADRs and did not have suspected ADRs during hospitalisation. PRISMA guidelines were strictly followed during the review. The methodological quality of included studies was assessed using a tool designed by Smyth et al. for the studies of adverse drug reactions. The meta-analytic summary of all-cause mortality was estimated using odds ratio-OR (95% CI) and length of stay using mean difference-MD (95% CI). Both outcomes were pooled using a random effect model (DerSimonian and Laird method). Subgroup and meta-regression were performed based on study variables: study design, age group, study ward, study region, types of suspected ADRs (ADRAd-suspected ADRs that lead to hospitalisation and ADRIn-suspected ADRs that occur following hospitalisation), study duration, sample size and study period. The statistical analysis was conducted through the 'Review manager software version 5.4.1 and JASP (Version 0.14.1)'.

RESULTS

After screening 475 relevant articles, 55 studies were included in this meta-analysis. Patients having suspected ADRs had reported significantly higher odds of all-cause mortality [OR: 1.50 (95% CI: 1.21-1.86; I2 = 100%) than those patients who did not have suspected ADRs during hospitalisation. Study wards, types of suspected ADRs and sample size were observed as significant predictors of all-cause mortality (p < 0.05). Patients having suspected ADRs had reported significantly higher mean difference in hospital stay [MD: 3.98 (95% CI: 2.91, 5.05; I2 = 99%) than those patients who did not have suspected ADRs during hospitalisation. Types of suspected ADRs and study periods were observed as significant predictors of length of stay (p < 0.05).

CONCLUSION

Suspected ADRs significantly increase the risk of mortality and length of stay in hospitalised patients.

SYSTEMATIC REVIEW REGISTRATION

CRD42020176320.

Performance of a trigger tool for detecting adverse drug reactions in patients with polypharmacy acutely admitted to the geriatric ward

Aim

To investigate the performance of an adverse drug reaction (ADR) trigger tool in patients with polypharmacy acutely admitted to our geriatric ward.

Findings

The ADR trigger tool had a positive predictive value (PPV) of 41.8%. Usual care recognised 83.5% of ADRs considered as possible, probable or certain, increasing to 97.1% when restricted to probable and certain ADRs.

Message

It is unlikely that implementation of the ADR trigger tool will improve detection of unrecognised ADRs in older patients acutely admitted to our geriatric ward.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41999-022-00649-x.

Purpose

Adverse drug reactions (ADRs) account for 10% of acute hospital admissions in older people, often under-recognised by physicians. The Dutch geriatric guideline recommends screening all acutely admitted older patients with polypharmacy with an ADR trigger tool comprising ten triggers and associated drugs frequently causing ADRs. This study investigated the performance of this tool and the recognition by usual care of ADRs detected with the tool.

Methods

A cross-sectional study was performed in patients ≥ 70 years with polypharmacy acutely admitted to the geriatric ward of the University Medical Centre Utrecht. Electronic health records (EHRs) were screened for trigger–drug combinations listed in the ADR trigger tool. Two independent appraisers assessed causal probability with the WHO-UMC algorithm and screened EHRs for recognition of ADRs by attending physicians. Performance of the tool was defined as the positive predictive value (PPV) for ADRs with a possible, probable or certain causal relation.

Results

In total, 941 trigger–drug combinations were present in 73% (n = 253/345) of the patients. The triggers fall, delirium, renal insufficiency and hyponatraemia covered 86% (n = 810/941) of all trigger–drug combinations. The overall PPV was 41.8% (n = 393/941), but the PPV for individual triggers was highly variable ranging from 0 to 100%. Usual care recognised the majority of ADRs (83.5%), increasing to 97.1% when restricted to possible and certain ADRs.

Conclusion

The ADR trigger tool has predictive value; however, its implementation is unlikely to improve the detection of unrecognised ADRs in older patients acutely admitted to our geriatric ward. Future research is needed to investigate the tool’s clinical value when applied to older patients acutely admitted to non-geriatric wards.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41999-022-00649-x.

Chronic-pharma: New Platform for Chronic Patients Pharmacotherapy Optimization

We describe the technological development of a web platform named CHRONIC-PHARMA that integrates three prescription support tools for patients with chronic diseases: Anticholinergic Burden Calculator (ABC), LESS-CHRON criteria and TRIGGER-CHRON. They focus on the optimization and evaluation of pharmacotherapy in patients with chronic diseases, resulting in a useful, single platform that can facilitate the review of pharmacotherapy and improve the safety of chronically ill patients. This is achieved by estimating and reducing the anticholinergic risk (ABC), detecting opportunities for deprescribing drugs and monitoring its success (LESS-CHRON criteria), as well as calculating the risk of adverse drug events (TRIGGER-CHRON). The platform is freely accessible online (https://chronic-pharma.com/) as well as through a mobile application, and therefore easily accessible among the healthcare community.

Predictive Power of the "Trigger Tool" for the detection of adverse events in general surgery: a multicenter observational validation study

BACKGROUND

In spite of the global implementation of standardized surgical safety checklists and evidence-based practices, general surgery remains associated with a high residual risk of preventable perioperative complications and adverse events. This study was designed to validate the hypothesis that a new "Trigger Tool" represents a sensitive predictor of adverse events in general surgery.

METHODS

An observational multicenter validation study was performed among 31 hospitals in Spain. The previously described "Trigger Tool" based on 40 specific triggers was applied to validate the predictive power of predicting adverse events in the perioperative care of surgical patients. A prediction model was used by means of a binary logistic regression analysis.

RESULTS

The prevalence of adverse events among a total of 1,132 surgical cases included in this study was 31.53%. The "Trigger Tool" had a sensitivity and specificity of 86.27% and 79.55% respectively for predicting these adverse events. A total of 12 selected triggers of overall 40 triggers were identified for optimizing the predictive power of the "Trigger Tool".

CONCLUSIONS

The "Trigger Tool" has a high predictive capacity for predicting adverse events in surgical procedures. We recommend a revision of the original 40 triggers to 12 selected triggers to optimize the predictive power of this tool, which will have to be validated in future studies.

Performance of a trigger tool for detecting drug-related hospital admissions in older people: analysis from the OPERAM trial

BACKGROUND

identifying drug-related hospital admissions (DRAs) in older people is difficult. A standardised chart review procedure has recently been developed. It includes an adjudication team (physician and pharmacist) screening using 26 triggers and then performing causality assessment to determine whether an adverse drug event (ADE) occurred (secondary to an adverse drug reaction, overuse, misuse or underuse) and whether the ADE contributed to hospital admission (DRA).

OBJECTIVE

to assess the performance of those triggers in detecting DRA.

DESIGN

retrospective study using data from the OPERAM (OPtimising thERapy to prevent Avoidable hospital admissions in Multimorbid older people) trial.

SETTINGS

four European medical centres.

SUBJECTS

multimorbid (≥ 3 chronic medical conditions) older (≥ 70 years) inpatients with polypharmacy (≥ 5 chronic medications) were enrolled in the OPERAM trial (N = 2,008) and followed for 12 months. We included patients with ≥1 adjudicated hospitalisation during the follow-up.

METHODS

the positive predictive value (PPV; number of DRAs identified by trigger/number of triggers) was calculated for each trigger and for the tool as a whole.

RESULTS

of 1,235 hospitalisations adjudicated for 832 patients, 716 (58%) had at least one trigger; an ADE was identified in 673 (54%) and 518 (42%) were adjudicated as DRAs. The overall PPV of the trigger tool for detecting DRAs was 0.66 [0.62-0.69].

CONCLUSIONS

this tool performs well for identifying DRAs in older people. Based on our results, a revised version of the tool was proposed but will require external validation before it can be incorporated into research and clinical practice.

Translation, Cross-Cultural Adaptation, and Measurement Properties of the Portuguese Version of the Global Trigger Tool for Adverse Events

Purpose

To adapt and validate the Global Trigger Tool (IHI-GTT), which identifies and analyzes adverse events (AE) in hospitalized patients and their measurement properties in the Portuguese context.

Methods

A retrospective cross-sectional study was based on a random sample of 90 medical records. The stages of translation and cross-cultural adaptation of the IHI-GTT were based on the Cross-Cultural Adaptation Protocol that originated from the Portuguese version, GTT-PT, for the hospital context in medical-surgical departments. Internal consistency, reliability, reproducibility, diagnostic tests, and discriminatory predictive value were investigated.

Results

The final phase of the GTT-PT showed insignificant inconsistencies. The pre-test phase confirmed translation accuracy, easy administration, effectiveness in identifying AEs, and relevance of integrating it into hospital risk management. It had a sensitivity of 97.8% and specificity of 74.8%, with a cutoff point of 0.5, an accuracy of 83%, and a positive predictive value of 69.8% and a negative predictive value of 0.98%.

Conclusion

The GTT-PT is a reliable, accurate, and valid tool to identify AE, with robust measurement properties.

Utility of a trigger tool (TRIGGER-CHRON) to detect adverse events associated with high-alert medications in patients with multimorbidity

OBJECTIVE

To determine the utility of a tool (TRIGGER-CHRON) for identifying adverse drug events (ADEs) associated with the administration of high-alert medications in elderly patients with multimorbidity and to determine the medications most frequently implicated.

METHODS

A retrospective observational study was conducted at 12 Spanish hospitals. A random sample of five medical records from each hospital was selected weekly for review over a 12-week period. We included patients aged 65 and over with multimorbidities, hospitalised for >48 hours. ADEs detected by the 32 TRIGGER-CHRON signals and caused by high-alert medications included on the Spanish HAMC list for chronic patients were selected for analysis. Triggers identified and ADEs detected were recorded. The severity and preventability of the ADEs were evaluated. The positive predictive value (PPV) of each trigger was calculated.

RESULTS

On 720 charts reviewed, 908 positive triggers were identified that led to the detection of 158 ADEs caused by at least one high-alert medication on the HAMC list. These ADEs occurred in 139 patients (prevalence 19.3/100 admissions). The majority of ADEs were mild and 59.5% were deemed preventable. The drugs most frequently associated with ADEs were corticosteroids, loop diuretics, opioid analgesics and oral anticoagulants. Fifteen triggers had PPVs ≥20%. Six triggers (serum glucose >110 mg/dL, abrupt cessation of medication, oversedation/lethargy, hypotension, adverse reaction recorded and constipation) accounted for 69.8% of the ADEs identified.

CONCLUSIONS

Applying the TRIGGER-CHRON to hospitalised patients with multimorbidity in 12 Spanish centres allowed detection of one adverse event caused by a high-alert drug for every four patients, which were preventable in a large proportion of patients. This confirms the need to establish interventions that reduce harm with these medications. We believe that TRIGGER-CHRON can be a useful tool to measure this harm and to determine the effects of medication safety improvement programmes as they are implemented.

Validating the Chinese geriatric trigger tool and analyzing adverse drug event associated risk factors in elderly Chinese patients: A retrospective review

Objective

The aim was to evaluate the performance of the initial Chinese geriatric trigger tool to detect adverse drug events (ADEs) in Chinese older patients, to attempt to shorten this list for improving the efficiency of the trigger tool, and to study the incidence and characteristics of ADEs in this population.

Methods

A sample of 25 cases was randomly selected per half a month from eligible patients who aged 60 years and older, hospitalized more than 24 hours, and discharged or died between January 1, 2015 and December 31, 2017 in West China hospital. A two-stage retrospective chart review of the included inpatients were conducted. ADEs were detected using a list of 42 triggers previously selected by an expert panel by means of a Delphi method. The number of triggers identified and ADEs detected were recorded and the positive predictive value (PPV) of each trigger was calculated to select the most efficient triggers. Several variables were recorded, including age, sex, number of diseases, length of hospital stay and so on, to analyze the risk factor of ADEs.

Results

Among 1800 patients, 1646 positive triggers and 296 ADEs were detected in 234 (13.00%) patients. Older patients who were younger, had more medications, longer stays or more admission, and did not experience surgical operation more likely experienced ADEs. Triggers with PPV less than 5% were eliminated, which resulted in the upgraded version of Chinese geriatric trigger tool of 20 triggers with a PPV of 28.50%. This upgraded tool accounted for 99.66% of all ADEs detected.

Conclusions

The upgraded version of Chinese geriatric trigger tool was an efficient tool for identifying ADEs in Chinese older patients. Future, the trigger tool could be incorporated into routine screen systems to provide real-time identification of ADEs, thereby enabling timely clinical interventions.

Developing a cancer-specific trigger tool to identify treatment-related adverse events using administrative data

Background

As there are few validated tools to identify treatment‐related adverse events across cancer care settings, we sought to develop oncology‐specific “triggers” to flag potential adverse events among cancer patients using claims data.

Methods

322 887 adult patients undergoing an initial course of cancer‐directed therapy for breast, colorectal, lung, or prostate cancer from 2008 to 2014 were drawn from a large commercial claims database. We defined 16 oncology‐specific triggers using diagnosis and procedure codes. To distinguish treatment‐related complications from comorbidities, we required a logical and temporal relationship between a treatment and the associated trigger. We tabulated the prevalence of triggers by cancer type and metastatic status during 1‐year of follow‐up, and examined cancer trigger risk factors.

Results

Cancer‐specific trigger events affected 19% of patients over the initial treatment year. The trigger burden varied by disease and metastatic status, from 6% of patients with nonmetastatic prostate cancer to 41% and 50% of those with metastatic colorectal and lung cancers, respectively. The most prevalent triggers were abnormal serum bicarbonate, blood transfusion, non‐contrast chest CT scan following radiation therapy, and hypoxemia. Among patients with metastatic disease, 10% had one trigger event and 29% had two or more. Triggers were more common among older patients, women, non‐whites, patients with low family incomes, and those without a college education.

Conclusions

Oncology‐specific triggers offer a promising method for identifying potential patient safety events among patients across cancer care settings.