METHODS: A quasi-experimental (before-after) study design was adopted. Pre-intervention data were collected over 7 months (January-July 2017). Subsequently, the workflow redesign (eaST system) was implemented and the effect of the intervention (August 2017-February 2018) was evaluated. Univariate analysis was used to compare the differences between pre-intervention and post-intervention of pharmacy waiting time and near-missed events. Significant factors affecting study outcomes were analysed using linear regression analysis.
KEY FINDINGS: A total of 210,530 prescriptions were analysed. The eaST system significantly increases the percentage of prescriptions dispensed within 30 min per day (median = 68 (interquartile range (IQR) = 41) vs. median = 93 (IQR = 33), P < 0.001) and reduced the mean percentage of near-missed events (mean = 50.71 (standard deviation (SD) = 23.95) vs. mean = 27.87 (SD = 12.23), P < 0.001). However, the eaST system's effects on related outcomes were conditional on a three-way interaction effect. The eaST system's effects on pharmacy waiting time were influenced by the number of prescriptions received and the number of PhIS server disruptions. Conversely, the eaST system's effects on near-missed events were influenced by the number of pharmacy personnel and number of controlled medications.
CONCLUSIONS: Overall, the eaST system improved the pharmacy waiting time and reduced near-missed events.
METHODS: A scoping review was carried out using the Arksey and O'Malley methodological framework. The search strategy was developed iteratively, with three main aspects: general practice/primary care contexts, risk assessment/decision support tools, and workload-related factors. Three databases were searched in 2019, and updated in 2021, covering articles published since 2009: Medline (Ovid), HMIC (Ovid) and Web of Science (TR). Double screening was completed by two reviewers, and data extracted from included articles were analysed.
RESULTS: The search resulted in 5,594 references, leading to 95 full articles, referring to 87 studies, after screening. Of these, 36 studies were based in the USA, 21 in the UK and 11 in Australia. A further 18 originated from Canada or Europe, with the remaining studies conducted in New Zealand, South Africa and Malaysia. Studies examined the use of eCDS tools and reported some findings related to their impact on workload, including on consultation duration. Most studies were qualitative and exploratory in nature, reporting health professionals' subjective perceptions of consultation duration as opposed to objectively-measured time spent using tools or consultation durations. Other workload-related findings included impacts on cognitive workload, "workflow" and dialogue with patients, and clinicians' experience of "alert fatigue".
CONCLUSIONS: The published literature on the impact of eCDS tools in general practice showed that limited efforts have focused on investigating the impact of such tools on workload and workflow. To gain an understanding of this area, further research, including quantitative measurement of consultation durations, would be useful to inform the future design and implementation of eCDS tools.
METHOD: A qualitative case study evaluation was conducted at a 620-bed public teaching hospital in Malaysia using interview, observation, and document analysis to investigate the features and functions of alert appropriateness and workflow-related issues in cardiological and dermatological settings. The current state map for medication prescribing process was also modelled to identify problems pertinent to CDS alert appropriateness.
RESULTS: The main findings showed that CDS was not well designed to fit into a clinician's workflow due to influencing factors such as technology (usability, alert content, and alert timing), human (training, perception, knowledge, and skills), organizational (rules and regulations, privacy, and security), and processes (documenting patient information, overriding default option, waste, and delay) impeding the use of CDS with its alert function. We illustrated how alert affect workflow in clinical processes using a Lean tool known as value stream mapping. This study also proposes how CDS alerts should be integrated into clinical workflows to optimize their potential to enhance patient safety.
CONCLUSION: The design and implementation of CDS alerts should be aligned with and incorporate socio-technical factors. Process improvement methods such as Lean can be used to enhance the appropriateness of CDS alerts by identifying inefficient clinical processes that impede the fit of these alerts into clinical workflow.
OBJECTIVE: This paper aimed to describe the development process of the COVID-19 Symptom Monitoring System (CoSMoS), which consists of a self-monitoring, algorithm-based Telegram bot and a teleconsultation system. We describe all the essential steps from the clinical perspective and our technical approach in designing, developing, and integrating the system into clinical practice during the COVID-19 pandemic as well as lessons learned from this development process.
METHODS: CoSMoS was developed in three phases: (1) requirement formation to identify clinical problems and to draft the clinical algorithm, (2) development testing iteration using the agile software development method, and (3) integration into clinical practice to design an effective clinical workflow using repeated simulations and role-playing.
RESULTS: We completed the development of CoSMoS in 19 days. In Phase 1 (ie, requirement formation), we identified three main functions: a daily automated reminder system for patients to self-check their symptoms, a safe patient risk assessment to guide patients in clinical decision making, and an active telemonitoring system with real-time phone consultations. The system architecture of CoSMoS involved five components: Telegram instant messaging, a clinician dashboard, system administration (ie, back end), a database, and development and operations infrastructure. The integration of CoSMoS into clinical practice involved the consideration of COVID-19 infectivity and patient safety.
CONCLUSIONS: This study demonstrated that developing a COVID-19 symptom monitoring system within a short time during a pandemic is feasible using the agile development method. Time factors and communication between the technical and clinical teams were the main challenges in the development process. The development process and lessons learned from this study can guide the future development of digital monitoring systems during the next pandemic, especially in developing countries.
METHODS: Three areas of priority were identified as follows: staff safety, patient movement, and possible clinical scenarios based on simulation principles in health care education. Staff was rostered and rotated through stations for rapid-cycle deliberate practice to learn donning and doffing of personal protective equipment (PPE) and powered air-purifying respirator (PAPR). For difficult airway management, Peyton's 4 steps for skills training and Harden's Three Circle model formed the structure in teaching the core skills. Several clinical scenarios used system probing to elicit inadequacies followed by formal debriefing to facilitate reflection. Finally, evaluation was both immediate and delayed with an online survey after 1 month to examine 4 levels of reaction, learning, behavior, and impact based on the Kirkpatrick Model. Frequency and thematic analysis were then conducted on the quantitative and qualitative data, respectively.
RESULTS: A total of 15 of 16 (93%) consultants, 16 (100%) specialists, and 81 (100%) medical officers in the department completed training within 2 consecutive weeks. Reaction and part of the learning were relayed immediately to trainers during training. In total, 42 (39%) trained staff responded to the survey. All were satisfied and agreed on the relevance of training. A total of 41 respondents (98%; 95% confidence interval [CI], 87-99) answered 16 of 20 questions correctly on identifying aerosol-generating procedures (AGP), indications for PPE, planning and preparation for airway management to achieve adequate learning. About 43% (95% CI, 27-59) and 52% (95% CI, 36-68) recalled donning and doffing steps correctly. A total of 92 responses from 33 respondents were analyzed in the thematic analysis. All respondents reported at least 1 behavioral change in intended outcomes for hand hygiene practice (20%), appropriate use of PPE (27%), and airway management (10%). The emerging outcomes were vigilance, physical distancing, planning, and team communication. Finally, the impact of training led to the establishment of institutional guidelines followed by all personnel.
CONCLUSIONS: Simulation-based training was a useful preparation tool for small institutions with limited time, resources, and manpower in developing nations. These recommendations represent the training experience to address issues of "when" and "how" to initiate urgent "medical education" during an outbreak.
Materials and Methods: The present systematic review was carried out according to PRISMA guidelines. The search was carried out on PubMed/MEDLINE, Cochrane collaboration, Science direct, and Scopus scientific engines using selected MeSH keywords. The articles fulfilling the predefined selection criteria based on the fit and accuracy of removable partial denture (RPD) frameworks constructed from digital workflow (CAD/CAM; rapid prototyping) and conventional techniques were included.
Results: Nine full-text articles comprising 6 in vitro and 3 in vivo studies were included in this review. The digital RPDs were fabricated in all articles by CAD/CAM selective laser sintering and selective laser melting techniques. The articles that have used CAD/CAM and rapid prototyping technique demonstrated better fit and accuracy as compared to the RPDs fabricated through conventional techniques. The least gaps between the framework and cast (41.677 ± 15.546 μm) were found in RPDs constructed through digital CAD/CAM systems.
Conclusion: A better accuracy was achieved using CAD/CAM and rapid prototyping techniques. The RPD frameworks fabricated by CAD/CAM and rapid prototyping techniques had clinically acceptable fit, superior precision, and better accuracy than conventionally fabricated RPD frameworks.
OBJECTIVE: In this study, we report a rapid method for the residue analysis of IND and its metabolites, viz., IND-carboxylic acid, diaminotriazine, and triazine indanone in a wide range of palm oil matrices using liquid chromatography-tandem mass spectrometry (LC-MS/MS).
METHOD: The optimized sample preparation workflows included two options: (1) acetonitrile extraction (QuEChERS workflow), followed by freezing at -80°C and (2) acetonitrile extraction, followed by cleanup through a C18 solid phase extraction (SPE) cartridge. The optimized LC runtime was 7 min. All these analytes were estimated by LC-MS/MS multiple reaction monitoring.
RESULTS: Both sample preparation methods provided similar method performance and acceptable results. The limit of quantification (LOQ) of IND, IND-carboxylic acid, and triazine indanone was 0.001 mg/kg. For diaminotriazine, the LOQ was 0.005 mg/kg. The method accuracy and precision complied with the SANTE/12682/2019 guidelines of analytical quality control.
CONCLUSIONS: The potentiality of the method lies in a high throughput analysis of IND and its metabolites in a single chromatographic run with high selectivity and sensitivity. Considering its fit-for-purpose performance, the method can be implemented in regulatory testing of IND residues in a wide range of palm oil matrices that are consumed and traded worldwide.
HIGHLIGHTS: This work has provided a validated method for simultaneous residue analysis of indaziflam and its metabolites in crude palm oil and its derived matrices with high sensitivity, selectivity, and throughput.