Pediatric Trigger Tool Research Articles

Development and Adjustment of an Algorithm for Identifying Drug-Related Hospital Admissions in Pediatrics.

Adverse drug events (ADEs) in the outpatient pediatric pharmacotherapy can be serious and lead to inpatient admissions. Recent research only focused on ADE identification during hospitalization. The aim of the present study was to develop an algorithm to identify drug-related hospital admissions in pediatrics. A systematic literature research was performed, and a pediatric trigger tool for identifying drug-related inpatient admissions was built. The initial version was tested in a sample of 292 patients admitted to a German university children's hospital. Subsequently, the tool was further improved by combining different modules as a novel approach. The obtained algorithm with 39 triggers in 5 modules identified drug-related inpatient admissions at a sensitivity of 95.5% (95% confidence interval [CI], 89.3%-100%) and a specificity of 16.5% (95% CI, 11.9%-21.2%), respectively. After modifications including trigger activation requiring a combination of different modules, specificity increased to 56.9% (95% CI, 50.7%-63.0%). Identifying 36 of 44 ADEs leading to admission, sensitivity remained high (81.8% [95% CI, 70.4%-93.2%]). The overall positive predictive value was 25.2% (95% CI, 18.1%-32.3%). The algorithm is the first trigger tool to identify ambulant acquired ADEs leading to hospital admission in pediatrics. However, the underlying patient sample is small.Using a larger population for refinement will allow further specifications and reduction in the total amount of triggers and thus signals.

Association between professional qualification and adverse events in neonatal and pediatric intensive treatment units.

to verify the association between the qualification of nursing professionals and the occurrence of adverse events in neonatal and pediatric intensive care units. Cross-sectional and evaluation study conducted in six intensive care units of five public hospitals in the state of Paraná, Brazil. Data was collected from April/2017 to January/2018 through the use of a questionnaire to be completed by 143 nursing professionals and retrospective analysis of 79 medical records using the Neonatal Trigger Tool and Pediatric Trigger Tool instruments. The prognostic factors were professional training and the existence, or not, of a continuing education service; analysis was performed by logistic regression. Detected 30 adverse events in 22 medical records analyzed. There was a prevalence of infection (n = 12; 40%) and skin damage (n = 9; 30%). Among the prognostic factors, continuing education was identified as a protective factor against adverse events (p≤0.05). Continuing education was associated with the prevention of adverse events in neonatal and pediatric intensive care units.

Establishment of a pediatric trigger tool based on Global Trigger Tool to identify adverse drug events of children: experience in a Chinese hospital

BackgroundThe Global Trigger Tool (GTT),which is a method using “triggers” to review medical record retrospectively to identify possible adverse events. Several studies showed that the GTT was effective. However, there were only a few localized trigger tools that had been established to detect pediatric adverse drug events (ADEs) in China. This study aimed to establish a pediatric trigger tool based on GTT, to examine the performance by detecting pediatric inpatients ADEs in a Chinese hospital (a retrospective review), and to investigate the factors associating with the occurrence of ADEs.MethodsThe triggers were established by three steps including literature search, triggers extraction and revision, and experts investigation. A retrospective cohort study was conducted to detect ADEs by using 200 pediatric inpatient records of Sichuan Provincial People’s Hospital.ResultsThirty-three preliminary triggers were established, and 2 rounds of experts investigation were conducted. Finally, 33 triggers were established. In the retrospective review, the positive trigger rate was 64.0%, while the positive predictive value (PPV) was 24.9%. The occurrence of inpatients with ADEs was 20.5%. ADEs/100 admissions were 49.0. ADEs/1000 patient days were 46.89. The most common ADE categories were leukocyte disorders, skin disorders and platelet disorders. The severity of 39 ADEs was grade 1, 55 ADEs was grade 2, 4 ADEs was grade 3. The highest frequency of ADE-related drugs was antineoplastic, followed by antibacterial. The length of stay and the leukemia in the diagnosed diseases were positively correlated with ADEs.ConclusionsThe 33 pediatric triggers may detect ADEs effectively, but still need to be optimized. This study may provide some references for further research in order to improve the rationality and safety of medication.

Smart triage: triage and management of sepsis in children using the point-of-care Pediatric Rapid Sepsis Trigger (PRST) tool

BackgroundSepsis is the leading cause of death and disability in children. Every hour of delay in treatment is associated with an escalating risk of morbidity and mortality. The burden of sepsis is greatest in low- and middle-income countries where timely treatment may not occur due to delays in diagnosis and prioritization of critically ill children. To circumvent these challenges, we propose the development and clinical evaluation of a digital triage tool that will identify high risk children and reduce time to treatment. We will also implement and clinically validate a Radio-Frequency Identification system to automate tracking of patients. The mobile platform (mobile device and dashboard) and automated patient tracking system will create a low cost, highly scalable solution for critically ill children, including those with sepsis.MethodsThis is pre-post intervention study consisting of three phases. Phase I will be a baseline period where data is collected on key predictors and outcomes before implementation of the digital triage tool. In Phase I, there will be no changes to healthcare delivery processes in place at the study hospitals. Phase II will involve model derivation, technology development, and usability testing. Phase III will be the intervention period where data is collected on key predictors and outcomes after implementation of the digital triage tool. The primary outcome, time to treatment initiation, will be compared to assess effectiveness of the digital health intervention.DiscussionSmart technology has the potential to overcome the barrier of limited clinical expertise in the identification of the child at risk. This mobile health platform, with sensors and data-driven applications, will provide real-time individualized risk prediction to rapidly triage patients and facilitate timely access to life-saving treatments for children in low- and middle-income countries, where specialists are not regularly available and deaths from sepsis are common.Trial registrationClinical Trials.gov Identifier: NCT04304235, Registered 11 March 2020.

Drug Use and Type of Adverse Drug Events-Identified by a Trigger Tool in Different Units in a Swedish Pediatric Hospital.

PurposeThe objectives of our study were to determine drug use, type and incidence of all adverse event associated with drug or drug-related processes (Adverse Drug Events, ADE) among pediatric inpatients in relation to hospital unit and length of stay.Patients and Methods600 pediatric (0–18 years) admissions at a Swedish university hospital during one year were included and stratified in blocks to 150 neonatal, surgical/orthopedic, medicine and emergency-medicine unit admissions, respectively. Adverse events were identified from medical records using a pediatric trigger tool. All triggers identifying an adverse event related to drugs and drug-related devices were included. Data on drug use were extracted from the hospital drug-data warehouse.ResultsIn total, 17794 daily drug orders were administrated to 486 (81.0% exposed) admissions. Parental nutrition, potassium salts and morphine constituted half of all high-risk drugs prescribed. Two-thirds of intravenous irritating drug doses consisted of vancomycin, esomeprazole and meropenem. In 129 (21.5%) admissions, at least one ADE was identified, out of which 21 ADE were classified as more severe (National Coordinating Council Medication Error Reporting Prevention-Index, NCCMERP≥F). The ADE incidence was 47.4 (95% confidence interval: 39.4–57.3) per 1000 admission days and varied by unit category. In neonatal units, 56.9 (49.5–65.4) ADEs/1000 admission days were detected, in surgery/orthopedic 54.2 (40.3–72.8), in medicine 44.1 (33.1–58.7), and in emergency-medicine 14.3 (7.7–26.7) ADEs/1000 admission days were found. The most common types of ADEs were identified by triggers that were not directly aiming at drugs including insufficiently treated pain (incidence peaking already in the first days), skin, tissue or vascular harm (peaking at the end of the first week) and hospital-acquired infections (peaking in later admission days).ConclusionAdverse drug events are common in pediatric patients. The incidence of ADEs and type of ADE varies by hospital unit and length of hospital stay.

Development of an electronic trigger tool at a children's hospital within an academic medical center.

To evaluate the validity and reliability of select recommended triggers, defined as flags found on review of the medical record that prompt further investigation to determine the presence or absence of an adverse drug event (ADE), selected from a list initially constructed based on severity, frequency, and detectability of triggers within a pediatric population. This was a single-center, retrospective cohort analysis of pediatric patients admitted to University of North Carolina (UNC) Children's Hospital who received trigger-associated medications between January 2015 and December 2016. Patient-care areas of the emergency department, operating rooms, and post-anesthesia care units were excluded. Trigger-detection encounters were evaluated by two reviewers using pre-established, consensus ADE criteria as determined by a panel of pediatric and medication safety specialists at UNC Medical Center. Events were categorized according to medication-related trigger and analyzed using descriptive statistics. A total of 3,836 positive triggers were included in this study. For the aggregate 12-part trigger tool package, 1,055 positive ADEs were identified, leading to a positive predictive value (PPV) of 27.5%. A 50% increase from baseline serum creatinine, resulting from co-administration of 2 or more nephrotoxic medications accounted for a total of 3,698/3,836 (96.4%). Incomplete documentation was the leading cause for event exclusion, 8/27 (30%). The triggers with the highest PPV included protamine 4/4 (100%), flumazenil 1/1 (100%), and vancomycin-related events 51/67 (76.1%), respectively. Phenytoin level >30 µg/mL or free level >2.5 µg/mL resulted in the lowest PPV, 1/12 (8.3%). This study lays the foundation for further studies to develop a robust pediatric trigger tool that may involve developing multi-element triggers, determining sensitivity and specificity of triggers, or mobilizing the trigger tool to an automated system. Trigger tools can be individualized to meet each institutions' needs and unique patient population.

Measurement of the incidence of care-associated adverse events at the Department of Pediatrics of a teaching hospital.

Adverse events may be detected using different screening tools. In the pediatric population, the Pediatric Trigger Tool looks for triggers in the medical record to detect preventable and non-preventable care-associated harm. To measure the incidence of adverse events at the Department of Pediatrics using this tool. To know the types of events and associated outcome measures. Longitudinal cohort study. A total of 318 patients were included; mean age: 2.99 years (range: 0-17); 164 (51.57 %) were girls. There were 11 % of events per 100 admissions, 15.5 events per 1000patient-days. The most common events were associated with medication use: 48.57 % (n = 17); bacteriology (infections): 42.85 % (n = 15); and care: 8.57 % (n = 3). Nineteen events were mild (54.28 %), 14 (40 %) extended the length of stay (moderate), and 2 (5.71 %) required vital support (severe). A total of 168 triggers were detected; 0.53 triggers per patient, 74.4 triggers per 1000 patient-days, and 4.8 triggers per adverse event. In the multivariate logistic regression analysis, the outcome measures associated with the development of adverse events were high-risk medications, female sex, weight, number of transfers within the hospital, and length of stay longer than 5 days. Using the Pediatric Trigger Tool helped to identify adverse events in hospitalized pediatric patients and guide improvement measures based on associated outcome measures.

Using a Pediatric Trigger Tool to Estimate Total Harm Burden Hospital-acquired Conditions Represent.

Introduction:To improve patient safety, the Centers for Medicare & Medicaid Services (CMS) has promoted systematically measuring and reporting harm due to patient care. The CMS’s Partnership for Patients program identified 9 hospital-acquired conditions (HACs) for reduction, to make care safer, more reliable, and less costly. However, the proportion of inpatient pediatric harm represented by these HACs is unknown.Methods:We conducted a retrospective review of 240 harms previously identified using the Pediatric All-Cause Harm Measurement Tool, a trigger tool that is applied to medical records to comprehensively identify harms. The original sample included 600 randomly selected patients from 6 children’s hospitals in February 2012. Patients with rehabilitation, obstetric, newborn nursery, and psychiatric admissions were excluded. The 240 identified harms were classified as a HAC if the event description potentially met the definition of 1 of the 9 CMS-defined HACs. HAC assessment was performed independently by 2 coauthors and compared using Cohen’s Kappa.Results:Two hundred forty harms across 6 children’s hospitals were identified in February 2012 using a pediatric global trigger tool. Agreement between the coauthors on HAC classification was high (Kappa = 0.77). After reconciling differences, of the 240 identified harms, 58 (24.2%; 95% confidence interval: 9.1–31.7%) were classified as a CMS-defined HAC.Conclusions:One-fourth of all harms detected by a pediatric-specific trigger tool are represented by HACs. Although substantial effort is focused on identifying and minimizing HACs, to better understand and ultimately mitigate harm, more comprehensive harm identification and quantification may be needed to address events unidentified using this approach.

A trigger tool to detect harm in pediatric inpatient settings.

An efficient and reliable process for measuring harm due to medical care is needed to advance pediatric patient safety. Several pediatric studies have assessed the use of trigger tools in varying inpatient environments. Using the Institute for Healthcare Improvement's adult-focused Global Trigger Tool as a model, we developed and pilot tested a trigger tool that would identify the most common causes of harm in pediatric inpatient environments. After formal training, 6 academic children's hospitals used this novel pediatric trigger tool to review 100 randomly selected inpatient records per site from patients discharged during the month of February 2012. From the 600 patient charts evaluated, 240 harmful events ("harms") were identified, resulting in a rate of 40 harms per 100 patients admitted and 54.9 harms per 1000 patient days across the 6 hospitals. At least 1 harm was identified in 146 patients (24.3% of patients). Of the 240 total events, 108 (45.0%) were assessed to have been potentially or definitely preventable. The most common patient harms were intravenous catheter infiltrations/burns, respiratory distress, constipation, pain, and surgical complications. Consistent with earlier rates of all-cause harm in adult hospitals, harm occurs at high rates in hospitalized children. Availability and use of an all-cause harm identification tool will establish the epidemiology of harm and will provide a consistent approach to assessing the effect of interventions on harms in hospitalized children.

Validation of triggers and development of a pediatric trigger tool to identify adverse events.

BackgroundLittle is known about adverse events (AEs) in pediatric patients. Record review is a common methodology for identifying AEs, but in pediatrics the record review tools generally have limited focus. The aim of the present study was to develop a broadly applicable record review tool to identify AEs in pediatric inpatients.MethodsUsing a broad literature review and expert opinion with a modified Delphi process, a pediatric trigger tool with 88 triggers, definitions, and descriptions including AE preventability decision support was developed and tested in a random sample of 600 hospitalized pediatric patients admitted in 2010 to a single university children’s hospital. Four registered nurse-physician teams performed complete two-stage retrospective reviews of 150 records each from either neonatal, surgical/orthopedic, medicine, or emergency medicine units.ResultsRegistered nurse review identified 296 of 600 records with triggers indicating potential AEs. Records (n = 121) with only false positive triggers not indicating any potential AEs were not forwarded to the next review stage. On subsequent physician review, 204 (34.0%) of patients were found to have had 563 AEs, range 1–27 AEs/patient. A total of 442 preventable AEs were found in 161 patients (26.8%), range 1–22. Overall, triggers were found 3,598 times in 417 (69.5%) records, with a mean of 6 (median 1, range 0–176) triggers per patient. The overall positive predictive value of the triggers was 22.9%, (range 0.0-100.0%). The final pediatric trigger tool, developed with a second Delphi round, required 29 triggers.ConclusionsAEs are common in pediatric patients and most are preventable. The main contributions of this study are to further develop and adapt trigger definitions, including AE preventability decision support, to introduce new triggers in pediatric care, as well as to apply pediatric triggers in different clinical specialties. Our findings resulted in a national pediatric trigger tool, and might also be adapted internationally. The pediatric trigger tool can help healthcare organizations to measure and analyze the AEs occurring in hospitalized children in order to improve patient safety.

Using a Trigger Tool to Assess Adverse Drug Events in a Children's Rehabilitation Hospital

Some of the most common actions after an adverse drug event (ADE) have been carefully listed, studied, and described as "triggers." Trigger-based tools for finding and evaluating ADEs have been validated in varied patient populations. A recent article described the frequency and severity of ADEs in hospitalized children in tertiary care children's hospitals. Our objective was to discover whether children in a pediatric rehabilitation setting are at higher risk for ADEs because of polypharmacy, or at a lower risk because of relative overall clinical stability. A pediatric inpatient trigger tool was used in 3 groups of children hospitalized in a pediatric rehabilitation setting. ADE frequencies and patient characteristics were compared with values from a multicenter study using the same tools in pediatric tertiary care hospitals. Changes in ADE frequency over time were assessed (2005, n=20; 2006, n=20; 2008, n=19). No serious ADEs were newly discovered using the trigger tool. Nearly all of the ADEs (16 of 17) discovered by the trigger tool had not been voluntarily reported to the hospital's event reporting program. ADE frequencies expressed per patient were higher than those seen in tertiary care children's hospitals. Longer lengths of stay resulted in lower ADE frequencies when expressed per day. ADE frequency increased in the institution over time, reflecting increases in the acuity and complexity of patients cared for at this facility. Many ADEs affected bowel frequency. Systematic chart review using a trigger tool discovered ADEs that had not been voluntarily reported or evaluated. ADEs in pediatric rehabilitation patients occurred less often than those in tertiary pediatric care when expressed as rates per day, but were more frequent when expressed per patient or per medication. Types and severity of ADEs in pediatric rehabilitation can guide monitoring and attention to specific areas of care.