Objective: This study aimed to explore the impact of the COVID-19 pandemic on hospital-based clinical pharmacists working in Malaysia and the implications on how clinical pharmacy is perceived as a health care service.
Methods: A qualitative study was designed to meet the research objectives. Nineteen hospital-based clinical pharmacists consented and participated in one-on-one, semi-structured interviews. The interviews were transcribed and analyzed using an iterative thematic analysis approach.
Results: The experiences and views of the participants were reported. Three main themes were developed: 'Reassignment and other changes in clinical pharmacist roles', 'Adapting clinical pharmacy services to COVID-19', and 'The need for clinical pharmacists in the ward'. The findings indicate that in many cases, clinical pharmacy services were fully or partially withdrawn from the ward to reduce the risk of infection and to conserve the usage of personal protective equipment. Despite this, clinical pharmacists continued to support patient care in hospitals through the use of technology. The withdrawal of clinical pharmacy services, however, raises concern that the role of clinical pharmacists is still poorly recognized.
Conclusion: Clinical pharmacists in hospitals continue to support patient care despite the disruption caused by the COVID-19 pandemic. Greater support and recognition of their role is required in order to empower and enhance their ability to deliver pharmaceutical care.This article is protected by copyright. All rights reserved.
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.
METHODS: Forty-eight hospital departments were recruited via open call and stratified by country. Departments were assigned to the operational program (intervention) or usual routine (control group). Data for analyses included 36 of these departments and their 5285 patients (median 147 per department; range 29-201), 2529 staff members (70; 10-393), 1750 medical records (50; 50-50), and standards compliance assessments. Follow-up was measured after 1 year. The outcomes were health status, service delivery, and standards compliance.
RESULTS: No health differences between groups were found, but the intervention group had higher identification of lifestyle risk (81% versus 60%, p health effects, the bias, and the limitations should be considered in implementation efforts and further studies.
TRIAL REGISTRATION: ClinicalTrials.gov : NCT01563575. Registered 27 March 2012. https://clinicaltrials.gov/ct2/show/NCT01563575.
METHODS: This bibliometric work investigated the academic publication trends in medical image segmentation technology. These data were collected from the Web of Science (WoS) Core Collection and the Scopus. In the quantitative analysis stage, important visual maps were produced to show publication trends from five different perspectives including annual publications, countries, top authors, publication sources, and keywords. In the qualitative analysis stage, the frequently used methods and research trends in the medical image segmentation field were analyzed from 49 publications with the top annual citation rates.
RESULTS: The analysis results showed that the number of publications had increased rapidly by year. The top related countries include the Chinese mainland, the United States, and India. Most of these publications were conference papers, besides there are also some top journals. The research hotspot in this field was deep learning-based medical image segmentation algorithms based on keyword analysis. These publications were divided into three categories: reviews, segmentation algorithm publications, and other relevant publications. Among these three categories, segmentation algorithm publications occupied the vast majority, and deep learning neural network-based algorithm was the research hotspots and frontiers.
CONCLUSIONS: Through this bibliometric research work, the research hotspot in the medical image segmentation field is uncovered and can point to future research in the field. It can be expected that more researchers will focus their work on deep learning neural network-based medical image segmentation.
METHODS: A mixed survey questionnaire with open- and closed-ended questions relating to HTA governance, HTA infrastructure, supply and demand of HTA and global HTA networking opportunities in each country was administered electronically to representatives of HTA nodal agencies of all ASEAN members. In-person meetings or email correspondence were used to clarify or validate any unclear responses. Results were collated and presented quantitatively.
RESULTS: Responses from eight out of ten member countries were analysed. The results illustrate that countries in the ASEAN region are at different stages of HTA institutionalization. While Malaysia, Singapore and Thailand have well-established processes and methods for priority setting through HTA, other countries, such as Cambodia, Indonesia, Lao PDR, Myanmar, the Philippines and Vietnam, have begun to develop HTA systems in their countries by establishing nodal agencies or conducting ad-hoc activities.
DISCUSSION AND CONCLUSION: The study provides a general overview of the HTA landscape in ASEAN countries. Systematic efforts to mitigate the gaps between the demand and supply of HTA in each country are required while ensuring adequate participation from stakeholders so that decisions for resource allocation are made in a fair, legitimate and transparent manner and are relevant to each local context.