Project description:BackgroundSepsis is a common cause of serious illness and death. Sepsis management remains challenging and suboptimal. To support rapid sepsis diagnosis and treatment, screening tools have been embedded into hospital digital systems to appear as digital alerts. The implementation of digital alerts to improve the management of sepsis and deterioration is a complex intervention that has to fit with team workflow and the views and practices of hospital staff. Despite the importance of human decision-making and behavior in optimal implementation, there are limited qualitative studies that explore the views and experiences of health care professionals regarding digital alerts as sepsis or deterioration computerized clinician decision support systems (CCDSSs).ObjectiveThis study aims to explore the views and experiences of health care professionals on the use of sepsis or deterioration CCDSSs and to identify barriers and facilitators to their implementation and use in National Health Service (NHS) hospitals.MethodsWe conducted a qualitative, multisite study with unstructured observations and semistructured interviews with health care professionals from emergency departments, outreach teams, and intensive or acute units in 3 NHS hospital trusts in England. Data from both interviews and observations were analyzed together inductively using thematic analysis.ResultsA total of 22 health care professionals were interviewed, and 12 observation sessions were undertaken. A total of four themes regarding digital alerts were identified: (1) support decision-making as nested in electronic health records, but never substitute professionals' knowledge and experience; (2) remind to take action according to the context, such as the hospital unit and the job role; (3) improve the alerts and their introduction, by making them more accessible, easy to use, not intrusive, more accurate, as well as integrated across the whole health care system; and (4) contextual factors affecting views and use of alerts in the NHS trusts. Digital alerts are more optimally used in general hospital units with a lower senior decision maker:patient ratio and by health care professionals with experience of a similar technology. Better use of the alerts was associated with quality improvement initiatives and continuous sepsis training. The trusts' features, such as the presence of a 24/7 emergency outreach team, good technological resources, and staffing and teamwork, favored a more optimal use.ConclusionsTrust implementation of sepsis or deterioration CCDSSs requires support on multiple levels and at all phases of the intervention, starting from a prego-live analysis addressing organizational needs and readiness. Advancements toward minimally disruptive and smart digital alerts as sepsis or deterioration CCDSSs, which are more accurate and specific but at the same time scalable and accessible, require policy changes and investments in multidisciplinary research.

Project description:BackgroundMany medicine quality problems are detected after they arrive at health facilities. Thus, critically defective medicines that may pose health risks to patients need to be withheld or recalled.AimsTo investigate the withheld and recalled medicines in relation to the types of defects, their total numbers, therapeutic categories, pharmaceutical dosage forms, and country of manufacturer during the study period.MethodsA retrospective review was performed on withheld and recalled medicines published on the publicly available National Medicines Regulatory Authority (NMRA) official website in Sri Lanka between June 2018 and August 2021. Details on substandard medicines (SM) were extracted and documented. Each record of SM was individually reviewed to determine the type of defect, subsequent action taken by NMRA, therapeutic category, pharmaceutical dosage form, and country of manufacturer.ResultsA total of 163 defects were identified in 143 defective medicines, among which the most common types of defects were contamination (n = 59, 36.2%), stability defects (n = 41, 25.2%), packaging and labelling defects (n = 27, 16.6%) and active pharmaceutical ingredient defects (n = 26, 15.9%). Out of 143 total defective medicines identified, anti-infectives accounted for 41.9%, while parenteral preparations (44.0%) were found to be frequently defective. Nearly 70% of the recalled and withheld medicines were of Indian origin, and some manufacturers were identified to be repeatedly involved.ConclusionsThis study revealed that contamination was the most frequent cause of defective medicines, while parenteral preparations and anti-infectives were the most susceptible pharmaceutical dosage form and therapeutic category found to be substandard, respectively. In addition, the findings show that some manufacturers were accountable for repetitive withholdings and recalls, which reflects the ignorance of quality control measures and weak regulatory inspections as a violation of Good Manufacturing Practice (GMP).

Project description:Objectives A number of regulatory and accrediting bodies require the reporting of critical results on a timely basis (immediately or within the time frame established by the laboratory) to "the responsible, licensed caregiver" as timely notification of critical laboratory results can pivotally affect patient outcome. The aim of the study was to decrease the turnaround time (TAT) of critical result notification along with assurance of notification to the concerned caregiver or clinicians. The objectives was 30% reduction in the critical value notification TAT and identify factors associated with delayed reporting and root cause analysis for these factors by application of quality tools. Materials and Methods The study was conducted at the Institute of Human Behavior and Allied Sciences, Delhi, a tertiary center teaching Hospital, from April 2019 to June 2021. A value streamed Process Map of critical alert was prepared. The incidents related to failure were presented through Pareto chart. The possible causes were analyzed through the fishbone model. The failure mode prioritization was executed with Failure Mode and Effect Analysis (FMEA). Through extensive brainstorming, appropriate and feasible corrective actions were implemented. The effectiveness of the implemented plan was analyzed by reassessing the TAT of critical alert and feedback received by clinical caregivers. Results After implementation of corrective action plan using quality tools for 3 months, the average critical alert TAT was reduced to 21 minutes from 30 minutes (30% reduction). The median critical alert TAT for ICU, emergency, and IPD were reduced to 3 minutes (IQR: 1-7). During the pilot project, 156 critical value data were sent for feedback with treatment plan but was received only for 88 patients (56%). Conclusion Comprehensive utilization of quality tools has a potential role in patient safety by reducing the critical alert TAT as well as establishing an effective communication between laboratory personnel and clinicians.

Project description:IntroductionThe rapid expansion of the Internet and computing power in recent years has opened up the possibility of using social media for pharmacovigilance. While this general concept has been proposed by many, central questions remain as to whether social media can provide earlier warnings for rare and serious events than traditional signal detection from spontaneous report data.ObjectiveOur objective was to examine whether specific product-adverse event pairs were reported via social media before being reported to the US FDA Adverse Event Reporting System (FAERS).MethodsA retrospective analysis of public Facebook and Twitter data was conducted for 10 recent FDA postmarketing safety signals at the drug-event pair level with six negative controls. Social media data corresponding to two years prior to signal detection of each product-event pair were compiled. Automated classifiers were used to identify each 'post with resemblance to an adverse event' (Proto-AE), among English language posts. A custom dictionary was used to translate Internet vernacular into Medical Dictionary for Regulatory Activities (MedDRA®) Preferred Terms. Drug safety physicians conducted a manual review to determine causality using World Health Organization-Uppsala Monitoring Centre (WHO-UMC) assessment criteria. Cases were also compared with those reported in FAERS.FindingsA total of 935,246 posts were harvested from Facebook and Twitter, from March 2009 through October 2014. The automated classifier identified 98,252 Proto-AEs. Of these, 13 posts were selected for causality assessment of product-event pairs. Clinical assessment revealed that posts had sufficient information to warrant further investigation for two possible product-event associations: dronedarone-vasculitis and Banana Boat Sunscreen--skin burns. No product-event associations were found among the negative controls. In one of the positive cases, the first report occurred in social media prior to signal detection from FAERS, whereas the other case occurred first in FAERS.ConclusionsAn efficient semi-automated approach to social media monitoring may provide earlier insights into certain adverse events. More work is needed to elaborate additional uses for social media data in pharmacovigilance and to determine how they can be applied by regulatory agencies.

Project description:Study objectiveAlthough electronic behavioral alerts are placed as an alert flag in the electronic health record to notify staff of previous behavioral and/or violent incidents in emergency departments (EDs), they have the potential to reinforce negative perceptions of patients and contribute to bias. We provide characterization of ED electronic behavioral alerts using electronic health record data across a large, regional health care system.MethodsWe conducted a retrospective cross-sectional study of adult patients presenting to 10 adult EDs within a Northeastern United States health care system from 2013 to 2022. Electronic behavioral alerts were manually screened for safety concerns and then categorized by the type of concern. In our patient-level analyses, we included patient data at the time of the first ED visit where an electronic behavioral alert was triggered or, if a patient had no electronic behavioral alerts, the earliest visit in the study period. We performed a mixed-effects regression analysis to identify patient-level risk factors associated with safety-related electronic behavioral alert deployment.ResultsOf the 2,932,870 ED visits, 6,775 (0.2%) had associated electronic behavioral alerts across 789 unique patients and 1,364 unique electronic behavioral alerts. Of the encounters with electronic behavioral alerts, 5,945 (88%) were adjudicated as having a safety concern involving 653 patients. In our patient-level analysis, the median age for patients with safety-related electronic behavioral alerts was 44 years (interquartile range 33 to 55 years), 66% were men, and 37% were Black. Visits with safety-related electronic behavioral alerts had higher rates of discontinuance of care (7.8% vs 1.5% with no alert; P<.001) as defined by the patient-directed discharge, left-without-being-seen, or elopement-type dispositions. The most common topics in the electronic behavioral alerts were physical (41%) or verbal (36%) incidents with staff or other patients. In the mixed-effects logistic analysis, Black non-Hispanic patients (vs White non-Hispanic patients: adjusted odds ratio 2.60; 95% confidence interval [CI] 2.13 to 3.17), aged younger than 45 (vs aged 45-64 years: adjusted odds ratio 1.41; 95% CI 1.17 to 1.70), male (vs female: adjusted odds ratio 2.09; 95% CI 1.76 to 2.49), and publicly insured patients (Medicaid: adjusted odds ratio 6.18; 95% CI 4.58 to 8.36; Medicare: adjusted odds ratio 5.63; 95% CI 3.96 to 8.00 vs commercial) were associated with a higher risk of a patient having at least 1 safety-related electronic behavioral alert deployment during the study period.ConclusionIn our analysis, younger, Black non-Hispanic, publicly insured, and male patients were at a higher risk of having an ED electronic behavioral alert. Although our study is not designed to reflect causality, electronic behavioral alerts may disproportionately affect care delivery and medical decisions for historically marginalized populations presenting to the ED, contribute to structural racism, and perpetuate systemic inequities.

Project description:IntroductionRespiratory diseases encompass a diverse range of conditions that significantly impact global morbidity and mortality. While common diseases like asthma and COPD exhibit moderate symptoms, less prevalent conditions such as pulmonary hypertension and cystic fibrosis profoundly affect quality of life and mortality. The prevalence of these diseases has surged by approximately 40% over the past 3 decades. Despite advancements in pharmacotherapy, challenges in drug administration, adherence, and adverse effects persist. This study aimed to develop and perform an interim validation of a Capacity-Motivation-Opportunity (CMO) model tailored for respiratory outpatients to enhance pharmaceutical care, which is the direct, responsible provision of medication-related care for the purpose of achieving definite outcomes that improve a patient's quality of life, and overall wellbeing.MethodologyThis cross-sectional, multicenter study was conducted from March 2022 to March 2023. It comprised four phases: 1) forming an expert panel of 15 hospital pharmacists, 2) selecting respiratory pathologies based on prevalence and severity, 3) developing the CMO model's pillars, and 4) integrating and conducting an interim validation of the model. The Capacity pillar focused on patient stratification and personalized care; the Motivation pillar aligned therapeutic goals through motivational interviewing; and the Opportunity pillar promoted the use of information and communication technologies (ICTs) for telemedicine.ResultsThe model included eight respiratory diseases based on expert assessment. For the Capacity pillar, 22 variables were defined for patient stratification, leading to three priority levels for personalized pharmaceutical care. In a preliminary test involving 201 patients across six hospitals, the stratification tool effectively classified patients according to their needs. The Motivation pillar adapted motivational interviewing techniques to support patient adherence and behavior change. The Opportunity pillar established teleconsultation protocols and ICT tools to enhance patient monitoring and care coordination.ConclusionThe CMO model, tailored for respiratory patients, provides a comprehensive framework for improving pharmaceutical care. By focusing on patient-centered care, aligning therapeutic goals, and leveraging technology, this model addresses the multifaceted needs of individuals with respiratory conditions. Future studies are necessary to validate this model in other healthcare systems and ensure its broad applicability.

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Trusts ignoring safety alerts should be named, says CMO

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