Prioritization Of Patients Research Articles

TRIF-IFN-I pathway in Helicobacter-induced gastric cancer in an accelerated murine disease model and patient biopsies

Helicobacter pylori (H.pylori) infection is a known cause of many digestive diseases, including gastritis, peptic ulcers, and gastric cancer. However, the underlying mechanisms by which H.pylori infection triggers these disorders are still not clearly understood. Gastric cancer is a slow progressing disease, which makes it difficult to study. We have developed an accelerated disease progression mouse model, which leverages mice deficient in the myeloid differentiation primary response 88 gene (Myd88-/-) infected with Helicobacter felis (H.felis). Using this model and gastric biopsy samples from patients, we report that activation of the Toll/interleukin-1 receptor (TIR)-domain-containing adaptor inducing interferon-β (TRIF)-type I interferon (IFN-I) signaling pathway promotes Helicobacter-induced disease progression toward severe gastric pathology and gastric cancer development. Further, results implicated downstream targets of this pathway in disease pathogenesis. These findings may facilitate stratification of Helicobacter-infected patients and thus enable treatment prioritization of patients.

The Pandemic of Invisible Victims in American Mental Health.

Although considerable attention has been devoted to the concepts of "visible" and "invisible" victims in general medical practice, especially in relation to resource allocation, far less consideration has been devoted to these concepts in behavioral health. Distinctive features of mental health care in the United States help explain this gap. This essay explores three specific ways in which the American mental health care system protects potentially "visible" individuals at the expense of "invisible victims" and otherwise fails to meet the needs of great numbers of people with serious psychiatric conditions: prioritization of the wrong patients, incentivization of excessive caution among providers, and a narrow definition of psychiatry's purview. While each of these practices has been discussed elsewhere in the literature, they are rarely considered as part of an interrelated and systemic problem. Reconceptualizing these three issues as aspects of the larger conflict between the interests of "visible" and "invisible" victims may prove a path toward reform.

A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing.

Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein-based subtypes. However, if and how these findings extend to UTUC remains unclear. Artificial intelligence-based approaches could help elucidate UTUC's biology and extend access to targeted treatments to a wider patient audience. Here, UTUC protein-based subtypes were identified, and a deep-learning (DL) workflow was developed to predict them directly from routine histopathological H&E slides. Protein-based subtypes in a retrospective cohort of 163 invasive tumors were assigned by hierarchical clustering of the immunohistochemical expression of three luminal (FOXA1, GATA3, and CK20) and three basal (CD44, CK5, and CK14) markers. Cluster analysis identified distinctive luminal (N = 80) and basal (N = 42) subtypes. The luminal subtype mostly included pushing, papillary tumors, whereas the basal subtype diffusely infiltrating, non-papillary tumors. DL model building relied on a transfer-learning approach by fine-tuning a pre-trained ResNet50. Classification performance was measured via three-fold repeated cross-validation. A mean area under the receiver operating characteristic curve of 0.83 (95% CI: 0.67-0.99), 0.8 (95% CI: 0.62-0.99), and 0.81 (95% CI: 0.65-0.96) was reached in the three repetitions. High-confidence DL-based predicted subtypes showed significant associations (p < 0.001) with morphological features, i.e. tumor type, histological subtypes, and infiltration type. Furthermore, a significant association was found with programmed cell death ligand 1 (PD-L1) combined positive score (p < 0.001) and FGFR3 mutational status (p = 0.002), with high-confidence basal predictions containing a higher proportion of PD-L1 positive samples and high-confidence luminal predictions a higher proportion of FGFR3-mutated samples. Testing of the DL model on an independent cohort highlighted the importance to accommodate histological subtypes. Taken together, our DL workflow can predict protein-based UTUC subtypes, associated with the presence of targetable alterations, directly from H&E slides.

Patient prioritisation of items to develop the Patient-Reported Impact of Dermatological Diseases measure: A global Delphi study.

The Global Research on the Impact of Dermatological Diseases (GRIDD) project is developing the new Patient-Reported Impact of Dermatological Diseases (PRIDD) measure. PRIDD measures the impact of dermatological conditions on the patient's life. This study aimed to seek consensus from patients on which items to prioritize for inclusion in PRIDD. A modified, two-round Delphi study was conducted. Adults (≥18 years) with dermatological conditions were recruited. The survey consisted of a demographic's questionnaire and 263 potential impact items in six languages. Quantitative data used Likert-type ranking scales and analysed against consensus criteria. Qualitative data collected free text responses for additional feedback and a framework analysis was conducted. 1154 people representing 90 dermatological conditions from 66 countries participated. Items were either removed (n = 79), edited (n = 179) or added (n = 2), based on consensus thresholds and qualitative feedback. Results generated the first draft of PRIDD with 27 items across five impact domains. This Delphi study resulted in the draft version of PRIDD, ready for psychometric testing. The triangulated data helped refine the existing conceptual framework of impact. PRIDD has since been pilot tested with patients and is currently undergoing psychometric testing.

Transcatheter Aortic Valve Implantation Wait-Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T).

Transcatheter aortic valve implantation (TAVI) has seen indication expansion and thus exponential growth in demand over the past decade. In many jurisdictions, the growing demand has outpaced capacity, increasing wait times and preprocedural adverse events. In this study, we derived prediction models that estimate the risk of adverse events on the waitlist and developed a triage tool to identify patients who should be prioritized for TAVI. We included adult patients in Ontario, Canada referred for TAVI and followed up until one of the following events first occurred: death, TAVI procedure, removal from waitlist, or end of the observation period. We used subdistribution hazards models to find significant predictors for each of the following outcomes: (1) all-cause death while on the waitlist; (2) all-cause hospitalization while on the waitlist; (3) receipt of urgent TAVI; and (4) a composite outcome. The median predicted risk at 12 weeks was chosen as a threshold for a maximum acceptable risk while on the waitlist and incorporated in the triage tool to recommend individualized wait times. Of 13 128 patients, 586 died while on the waitlist, and 4343 had at least 1 hospitalization. A total of 6854 TAVIs were completed, of which 1135 were urgent procedures. We were able to create parsimonious models for each outcome that included clinically relevant predictors. The Canadian TAVI Triage Tool (CAN3T) is a triage tool to assist clinicians in the prioritization of patients who should have timely access to TAVI. We anticipate that the CAN3T will be a valuable tool as it may improve equity in access to care, reduce preventable adverse events, and improve system efficiency.

Ethical dilemmas in prioritizing patients for scarce radiotherapy resources

BackgroundRadiotherapy is an essential component of cancer treatment, yet many countries do not have adequate capacity to serve all patients who would benefit from it. Allocation systems are needed to guide patient prioritization for radiotherapy in resource-limited contexts. These systems should be informed by allocation principles deemed relevant to stakeholders. This study explores the ethical dilemmas and views of decision-makers engaged in real-world prioritization of scarce radiotherapy resources at a cancer center in Rwanda in order to identify relevant principles.MethodsSemi-structured interviews were conducted with a purposive sample of 22 oncology clinicians, program leaders, and clinical advisors. Interviews explored the factors considered by decision-makers when prioritizing patients for radiotherapy. The framework method of thematic analysis was used to characterize these factors. Bioethical analysis was then applied to determine their underlying normative principles.ResultsParticipants considered both clinical and non-clinical factors relevant to patient prioritization for radiotherapy. They widely agreed that disease curability should be the primary overarching driver of prioritization, with the goal of saving the most lives. However, they described tension between curability and competing factors including age, palliative benefit, and waiting time. They were divided about the role that non-clinical factors such as social value should play, and agreed that poverty should not be a barrier.ConclusionsMultiple competing principles create tension with the agreed upon overarching goal of maximizing lives saved, including another utilitarian approach of maximizing life-years saved as well as non-utilitarian principles, such as egalitarianism, prioritarianism, and deontology. Clinical guidelines for patient prioritization for radiotherapy can combine multiple principles into a single allocation system to a significant extent. However, conflicting views about the role that social factors should play, and the dynamic nature of resource availability, highlight the need for ongoing work to evaluate and refine priority setting systems based on stakeholder views.

Examining medical urgent and patient precedence within the telemedicine landscape with its infrastructure and policies: A comprehensive review

Medical facilities are confronted with grave issues, including a population that is aging and a physician shortage. In an effort to address these issues, telehealth and remote health monitoring systems (RHMS) aim to reduce hospital visits by a small amount. RHMS lessens the workload for primary care patients and enhances inter-unit communication, which lessens the strain on emergency rooms. Due to significant advancements in mobile information transfer and processing of signal technologies, some healthcare researchers have made efforts to employ RHMS in place of hospital visits to provide triage and prioritization for individuals. Prioritization is a strategy for giving people urgent medical care in an attempt to save their lives, while clinical examination determines the severity of a sickness or damage. To emphasize the disadvantages of the present patient screening and prioritization system over the telehealth environment, a crucial inquiry is needed. Based on two crucial axes, an in-depth examination of patient prioritization and medical crisis assessment in a videoconferencing setting was provided in this research. First, a collection, analysis, and classification of earlier research on triage of patients and prioritization in this kind of setting was done. Second, a variety of priorities and standards, as well as various approaches and procedures for prioritization, were provided and examined. The subsequent outcomes were attained: The shortcomings and issues with the current patient prioritization and assessment methods were highlighted. The assessment and priority for individuals who have cardiac conditions were not presented. In the years to come, a structure based on the theory of evidence, as well as the incorporation of a multiple-layer analytical hierarchy approach and method for ranking preference due to resemblance to perfect solutions, can be used to prioritize the care of several patients with ongoing cardiovascular disease by triaging them based on various emergencies dimensions.

Setting Up a Just and Fair ICU Triage Process during a Pandemic: A Systematic Review.

Triage is a dynamic and complex decision-making process to determine fair access to medical care in mass casualty situations. Triage takes place through healthcare settings including Intensive Care Units (ICUs). Triage governing principles have been subject to ethical debates for a long time specifically with the recent global pandemic of COVID-19. This study aims to revisit the ethical principles guiding patient prioritisation during recent COVID-19 disaster triage in the Indian subcontinent and attempts to look for principles with consideration of social justice. Key electronic databases such as WHO, EMBASE, and DOAJ were used to access published literature relating to ICU triage in the Indian subcontinent. Literature on and from 2015-2022 were included in this study. The SPICE framework was used to identify the literature. The Inclusion criteria were as follows: Literature with ethical connotations focusing on India and neighbouring countries, and in an ICU setting during pandemics. The Exclusion criteria were as follows: Literature focusing on other countries, without ethical foundations, hospital admissions, and non-COVID-19 ICU admissions. The PRISMA standard was applied to screen the appropriate literature. The BOOLEAN operator "OR" was used to enhance the literature search. Finally, six papers were found suitable for this study and thus were included in the literature review. Additionally, for the second time, the frequency of certain ethical phrases was reassessed in the plans and guidelines to check the changed awareness of ethical pandemic planning, if any. A thematic analysis was applied to analyse the data and generate findings and new knowledge. The findings highlight gaps in knowledge around ICU triaging in the region which indicates the scope of better ethical pandemic preparation at the regional level. The findings show that there is a debate between researchers on prioritisation from available resources and ethical perspectives and principles associated with fair access to healthcare even during pandemic times. The literature also highlights enhancing the regional capacity and building equitable approaches to reduce existing health inequities and the need of the social justice framework for ICU triaging during a pandemic. ICU triaging in five South Asian neighbour nations was studied for the presence of a guided ethical framework. Additionally, for the second time, certain ethical phrases were reassessed in the plans and guidelines; however, usage of those terms was found to be significantly low. The discussion shows that the plans and guidelines have the scope to improve ethical ICU triaging in these countries and in the specific region. After analysing different ethical guidelines, this study emphasises that there is a need for a just and fair framework, specifically a social justice framework in ICU triage in the subcontinent to address the underlying health inequities.

Novel ways of applying artificial intelligence in emergency medicine - literature review

Artificial intelligence (AI) holds immense promise for revolutionizing emergency medicine, expediting diagnosis and treatment decisions. This review explores AI’s wide-ranging applications in emergency care, ranging from managing out-of-hospital cardiac arrest (OHCA) to diagnosing fractures, spine injuries, stroke, and pulmonary embolisms, and even assisting in search and rescue missions with snake robots. In OHCA cases, AI aids in early detection, survival prediction, and ECG waveform classification, bolstering prehospital care efficiency. AI-powered digital assistants like the AI4EMS platform optimize diagnosis and patient prioritization, reducing overlooked cases of cardiac arrest and improving response times. Furthermore, AI algorithms enhance the diagnosis of conditions such as pneumothorax, pulmonary emphysema, and fractures by analysing medical images with exceptional accuracy, often outperforming human experts. In stroke and pulmonary embolism, AI expedites diagnosis through automated imaging analysis, enabling swift treatment. AI may enhance triage methods with independent systems, improving patient sharing and treatment quality while minimizing infection risks, especially during pandemics. Medical professionals generally welcome AI triage systems, acknowledging their potential to enhance healthcare efficiency. It is important to understand the scope of development of AI in order to make its application beneficial.

Optimizing the Hospital Discharge Process: Perspectives of the Health Care Team.

Prior research capturing pharmacists' perspectives on the discharge process has shown that their involvement is essential. Given the multidisciplinary nature of the hospital environment, it is important to understand the perspectives of nonpharmacist health care providers. To explore the perspectives of nonpharmacist health care providers concerning current discharge practices, components of an effective discharge plan, and perceived barriers to an optimal discharge, and to explore their expectations of pharmacists at discharge. This qualitative study used key informant interviews of allied health professionals and prescribers at Vancouver General Hospital and North Island Hospital Comox Valley (British Columbia). Participants primarily working on general medicine, family practice, or hospitalist wards were invited to participate. A total of 16 health care providers participated, consisting of 12 allied health professionals and 4 prescribers. Thematic analysis of the interview transcripts revealed 5 themes for each group. The following 3 themes were common to both groups: systems-related barriers to an optimal discharge; patient- and community-related barriers to an optimal discharge; and patient involvement and education. For allied health professionals, themes of prioritization of patients for discharge and direct communication/teamwork were also key for an optimal discharge. Prescriber-specific themes were limitations related to technology infrastructure and inefficiency of existing collaborative processes. Key responsibilities expected of the pharmacist at discharge included preparing the discharge medication reconciliation and prescriptions, addressing medication-related cost concerns, organizing adherence aids/tools, and providing medication counselling. Further studies are warranted to investigate optimization of the discharge process through implementation of standardized discharge protocols and electronic health record-related tools. The primary responsibilities of the pharmacist at discharge, as perceived by study participants, were consistent with previous literature.

Nurses’ Perception on the Hindrances of Triage System in Emergency Unit

Background: Despite the fact that several triage tools have been implemented globally, emergency care, including the triage system, is often one of the weakest parts of the health system in developing countries, as compared to developed countries. Moreover, emergency centers in African countries are very busy, often flooded by high load of trauma patients, chronic medical conditions, acute medical emergencies, and HIV‐related conditions. These disease conditions precipitate the reasons for the prioritization of patients. In South Africa, studies conducted on the use of triage by nurses revealed that most patients are satisfied with the Nurse‐led triage service provided in emergency departments (EDs). At the same time, some Nurses also see the South African Triage Scale (SATS) as one of the easiest Nurse‐led triage tools.Aim: The study aimed at identifying the factors hindering the effective process of triage during care provision at a selected public hospital in KwaZulu‐Natal (KZN).Methods: This study utilized a cross‐sectional survey, employing a nonprobability convenience sampling to recruit its respondents. The recognition primed decision model formed the framework of the study. Ethical clearance was obtained from the University of KwaZulu‐Natal Ethics Review Board, and ethics principles were carefully observed throughout the study.Results: Out of the 100 respondents, 89% (89) of the respondents perceived that various factors still impede the progress of triage, while 11% (11) of the respondents perceived that no factor impedes the progress of triage.Conclusion: The study indicates that several factors still hinder the effective process of triage. Based on the findings of the study, factors like overcrowding, Nurses waiting for doctors when they know what to do, lack of continuous professional development on triage system, inadequate experience, lack of confidence, and lack of adequate training on triage still impede the efficient triage system.

The ADEM project: implementation of ‘Good medicines use conversation’ for COPD-patients, embedded in multidisciplinary context.

COPD is a chronic, progressive disease, for which a multidisciplinary approach is crucial. Appropriate follow-up is crucial to improve the quality of life of COPD-patients and reduce associated healthcare costs. &#x0D; A ‘Good medicines use conversation’ COPD is a pharmaceutical care intervention, conducted by the community pharmacist, consisting of a tailored-made education of the COPD-patient on the disease and its treatment. Scientific research (PHARMACOP-trial) has shown that this intervention significantly improves therapy adherence and inhalation technique and reduces exacerbation rates and associated hospitalizations. &#x0D; The aim of the ADEM implementation project was to investigate the needs for a sustainable implementation of this intervention.&#x0D; The ADEM project was conducted in Flemish-Brabant (Belgium), with the integrated care region ‘Leuven Cares’ as a separate entity. &#x0D; All participating pharmacies (9 in region Flemish-Brabant and 8 in region ‘Leuven Cares’) received a support package consisting of: 1) a three-part online training about COPD and a visual COPD-atlas; 2) a population management-tool (a query to identify COPD-patients in the pharmacy, resulting in a list of COPD-patients with a ‘score’ per patient as an initial proxy for patient prioritization); and 3) local interdisciplinary meetings (LIM) to discuss and promote the intervention. Pharmacist of the region Caring Leuven additionally received individual care plans, providing an overview of the healthcare status of each COPD-patient, and an individual coaching session.&#x0D; Semi-structured interviews were conducted with 8 participating pharmacists (4 region Flemish-Brabant, 4 region ‘Leuven Cares’). Thematic analysis was performed.&#x0D; &#x0D; All elements of the support package were positively evaluated by the participating pharmacists. The population management tool seemed to support pharmacists in planning, interpreting and prioritizing care for COPD-patients. A follow-up study is needed to further investigate the tool and to what extent population management contributes to a more qualitative and effective pharmaceutical care. &#x0D; COVID-19, lack of personnel, lack of reimbursement and lack of time were identified as limiting factors for the implementation of the protocol-based COPD-intervention. Cooperation with the GP was indicated by the majority as minimal and insufficient. Therefore, LIM’s were evaluated as very important to inform GP’s about the pharmaceutical intervention and make local agreements about the multidisciplinary approach of COPD.&#x0D; The findings of this study are in line with the available evidence on the implementation of new services in pharmacies. Many pharmacists have the intrinsic motivation to offer extended pharmaceutical care, but current practices often do not allow this. Population management appeared to be a major factor that can be used to facilitate the implementation. By considering the needs of the local population, pharmacists can work in a more targeted way and prioritize the pharmaceutical services they offer. Given the group of chronically ill people in Belgium is expected to grow in the coming years due to the increasing ageing of the population, there will be an increasing demand for specialized interventions and advice from the pharmacist. It is therefore necessary to provide a sufficient framework for these services, bearing in mind the needs of the local population and the requirement for a pragmatic approach in the pharmacy. &#x0D;

COVID-19- related work, managerial factors and exhaustion among general practitioners in Sweden: a cross-sectional study

IntroductionA significant number of international studies show that general practitioners (GPs) suffered from burnout when working during the COVID-19 pandemic. A Swedish study found that more than 16% of GPs had exhaustion in spring 2021. Exhaustion can be regarded as an initial stage of burnout. A knowledge gap remains on GPs´ working conditions, the impact of management during the pandemic and how it was associated with exhaustion. This study aims to explore the association between severe symptoms of exhaustion and COVID-19 pandemic-related work and managerial factors among Swedish GPs and whether managerial factors have an impact on the association between exhaustion and COVID-19-related work factors.MethodsCross-sectional data was drawn from the Longitudinal Occupational Health survey in Health Care Sweden (LOHHCS), which included a representative sample of practicing doctors in Sweden. The sample consisted of 6699 doctors with a response rate of 41.2%. This study constitutes a sample of doctors who reported working in primary care facilities at the time of data collection, i.e. 1013 GPs. The Burnout Assessment Tool (BAT) was used to assess severe symptoms of exhaustion. Questions were also asked about pandemic-related work and managerial factors. The data was analysed using descriptive statistics and multivariate logistic regression to identify the association between exhaustion, work and managerial factors.ResultsThe multivariate analysis showed that GPs who managed COVID-19 patients were about twice as likely to report severe symptoms of exhaustion. Further, GPs who reported that management was unsupportive, provided unsatisfactory working conditions and unsatisfactory policies for patient prioritisation were between two and four times more likely to report severe symptoms of exhaustion.ConclusionsCOVID-19-related work and managerial factors had a significant impact on the mental health of GPs. Furthermore, the potentially protective effect that satisfactory management actions had on mental health was limited. In the aftermath of the COVID-19 pandemic and in preparation for future major crises that have a high impact on healthcare, there is a need to investigate the measures that can be taken to enable GPs to carry out their work, while maintaining their wellbeing.

Clinical Deployment of Machine Learning Tools in Transplant Medicine: What Does the Future Hold?

Medical applications of machine learning (ML) have shown promise in analyzing patient data to support clinical decision-making and provide patient-specific outcomes. In transplantation, several applications of ML exist which include pretransplant: patient prioritization, donor-recipient matching, organ allocation, and posttransplant outcomes. Numerous studies have shown the development and utility of ML models, which have the potential to augment transplant medicine. Despite increasing efforts to develop robust ML models for clinical use, very few of these tools are deployed in the healthcare setting. Here, we summarize the current applications of ML in transplant and discuss a potential clinical deployment framework using examples in organ transplantation. We identified that creating an interdisciplinary team, curating a reliable dataset, addressing the barriers to implementation, and understanding current clinical evaluation models could help in deploying ML models into the transplant clinic setting.

Using discrete-event simulation to assess an AHP-based dynamic patient prioritisation policy for elective surgery

ABSTRACTPatient prioritisation in elective surgery is a critical multi-criteria decision-making issue. Elective patients should be ranked on the waiting list based on various criteria related to their health conditions and their evolution over time. This study suggests a dynamic prioritisation where elective patients are ranked considering their evolving health conditions, waiting time, and patient loss, i.e., the likelihood of patients abandoning the waiting list. We proposed deploying the Analytic Hierarchy Process (AHP) to weigh prioritisation criteria. The AHP-derived weights are integrated into a discrete-event simulation model, which periodically ranks patients considering their health status, waiting time, and patient loss. The proposed dynamic prioritisation is compared with the first-come, first-served (FCFS) policy and the static prioritisation, which ranks patients according to their initial priority. Results showed that dynamic prioritisation outperforms the FCFS and static prioritisation policies in preventing health deterioration, reducing weighted waiting time, and reducing the ratio of lost patients.

Exploring current patient prioritisation approaches used by UK mental health inpatient pharmacy teams

Abstract Introduction Clinical pharmacy services play a key role in reducing drug related problems and improving patient outcomes1. Prioritising patients for clinical pharmacy services is a relatively new approach that has been reported to have a positive impact on patients and pharmacy service delivery2. Although patient prioritisation for clinical pharmacy services have been studied in UK acute care settings, such approaches in UK mental health secondary care remain unexplored. Aim To explore current patient prioritisation systems used by UK mental health inpatient pharmacy teams. Methods This multi-method research comprised a survey, document analysis and semi-structured remote video interviews. A national survey was first distributed to all mental health UK organisations to understand the prevalence of patient prioritisation approaches. This was followed by pharmacy staff interviews and document analysis to learn more about existing patient prioritisation systems. Interviews and prioritisation documents were thematically analysed following Braun and Clark’s thematic analysis approach3. Ethical approval was obtained from the University of Manchester Ethics Committee (No. 13973). Results A total of 73 mental health trusts/boards were invited to take part in the survey between July 2022 and January 2023. Responses were received from 55 organisations achieving a 75.3% response rate, with 38.2% (n=21/55) of these reporting use of a patient prioritisation system for clinical pharmacy services. Survey respondents not using any patient prioritisation system reported in free text responses prioritising by reactive approaches, acuity, or prioritising new admissions or specific wards only. Additionally, over 70% of these organisations reported considering using a prioritisation system in the future with reported challenges to adoption being limited funding, staff shortage, lack of a standardised prioritisation system, and competing priorities. Organisations using patient prioritisation systems were then invited for follow up interviews and to share their patient prioritisation documents. Fifteen staff interviews were conducted between August and December 2022 and 11 prioritisation documents were analysed. Patient prioritisation approaches used in these organisations were either described as (a) guidance within their pharmacy standard operating procedures (n=3), (b) prioritisation criteria/space within handover tools between pharmacy staff (n=3), or (c) reports/tools designed specifically to guide patient prioritisation (n=9). Of the patient prioritisation report/tools (n=9), four were reports that guided pharmacy staff in prioritising through emailing a list of patients with a specific high-risk indicator whereas five were tools that categorised patients based on a pre-set criteria using a traffic light system (red, amber, and green) (n=3), numerical levels (1- 4) (n=1), or one high-risk category (n=1). All prioritisation tools depended on pharmacy staff categorising patients except one that was completely automatic. These approaches were perceived to be valuable in managing limited resources and optimising pharmacy services. Nevertheless, these benefits came with some reported challenges such us balancing between standardisation of services and use of clinical judgement. Discussion/Conclusion This research highlights the opportunities and limitations associated with highly variable patient prioritisation approaches used by UK mental health pharmacy teams. Future research could focus on developing a standardised evidence- and consensus- based patient prioritisation system for use by UK mental health inpatient pharmacy teams.

HPB O08 Championing benign biliary patients in Emergency General Surgery: A 3 year quality improvement project

Abstract Background A biliary quality improvement project (QuIP) was established in 2019 following 3 audit cycles highlighting delays to laparoscopic cholecystectomy (Lap-C) in patients with gallstone pancreatitis. Limited theatre space and other urgent care priorities hindered efforts to meet other biliary key performance indicator targets between 2015 and 2019. The last phase of the QuIP has introduced a dedicated consultant lead biliary service, a live biliary patient tracking system, increased in-patient Lap-C, implementation of ambulatory pathways and a patient centred integrated care approach. Methods Prospectively collected data from a live biliary tracking system was compared with retrospective audit data from 2015-2019. Key performance indicators were; average time to Lap-C, rate of Lap-C with-in 2 weeks following pancreatitis, inpatient Lap-C rate and out-patient appointments saved. Results 523 patients were managed through inpatient and ambulatory biliary pathways from November 2021-June 2023. 2 week Lap-C post pancreatitis improved from 27% to 79% (43% as inpatients) with average time to Lap-C improving from 68 days to 13 days. 191 outpatient appointments were saved by counselling and pre-assessing patients for Lap-C as inpatients, saving £22920 in outpatient costs. In-patient Lap-C rate improved from 2% to 19% for fit and consenting patients. Conclusions A higher quality of care can be achieved for biliary patients through; effective patient prioritisation, increasing inpatient Lap-C, the establishment of ambulatory pathways and a robust outpatient tracking system.

Access to healthcare services for people with non-communicable diseases during the COVID-19 pandemic in Ibadan, Nigeria: a qualitative study

BackgroundDesirable outcomes for people with non-communicable diseases (NCDs) are achieved when they access routine monitoring and care services. Expectedly, the COVID-19 pandemic severely impacted access to healthcare services, leading to poor health outcomes among people with NCDs. We aimed to [1] explore the delays in accessing healthcare services and [2] understand alternative actions adopted by people with NCDs to overcome these delays.MethodsWe conducted an exploratory qualitative research guided by the “Three Delays” model to unpack the barriers to healthcare access for people living with NCDs in Ibadan, Nigeria. The “Three Delays” model conceptualizes the reasons for negative/adverse healthcare outcomes related to the patient’s decision-making to seek healthcare, reaching an appropriate healthcare facility, and receiving adequate care at the healthcare facility. Twenty-five (25) people with NCDs were purposively selected from the University College Hospital’s medical outpatient department to participate in in-depth interviews. Interview recordings were transcribed verbatim and analyzed using a deductive-inductive hybrid thematic analysis.ResultsAt the level of individual decision-making, delays were related to fear of contracting COVID-19 in the hospital (considered a hotspot of the COVID-19 pandemic). Regarding reaching an appropriate healthcare facility, delays were mainly attributed to the intra- and inter-city lockdowns, limiting the movements of persons. For those who successfully arrived at the healthcare facilities, delays were related to the unavailability of healthcare professionals, prioritization of COVID-19 patients, and mandatory adherence to COVID-19 protocols, including COVID-19 testing. To overcome the delays mentioned above, people with NCDs resorted to (i) using private healthcare facilities, which were more costly, (ii) using virtual consultation through mobile phone Apps and (iii) self-management, usually by repeating previously prescribed prescriptions to obtain medication.ConclusionPandemic conditions provide unique challenges to people with chronic illnesses. Recognizing the need for continuous access to monitoring and care services under such conditions remains critical. Alternative health service provision approaches should be considered in pandemic situations, including remote healthcare services such as Mobile health apps (mHealth) that can help manage and prevent NCDs.

Prioritization of surgical patients during the COVID-19 pandemic and beyond: A qualitative exploration of patients' perspectives.

During the COVID-19 pandemic, prioritizing certain surgical patients became inevitable due to limited surgical capacity. This study aims to identify which factors patients value in priority setting, and to evaluate their perspective on a decision model for surgical prioritization. We enacted a qualitative exploratory study and conducted semi-structured interviews with N = 15 patients. Vignettes were used as guidance. The interviews were transcribed and iteratively analyzed using thematic analysis. We unraveled three themes: 1) general attitude towards surgical prioritization: patients showed understanding for the difficult decisions to be made, but demanded greater transparency and objectivity; 2) patient-related factors that some participants considered should, or should not, influence the prioritization: age, physical functioning, cognitive functioning, behavior, waiting time, impact on survival and quality of life, emotional consequences, and resource usage; and 3) patients' perspective on a decision model: usage of such a model for prioritization decisions is favorable if the model is simple, uses trustworthy data, and its output is supervised by physicians. The model could also be used as a communication tool to explain prioritization dilemmas to patients. Support for the various factors and use of a decision model varied among patients. Therefore, it seems unrealistic to immediately incorporate these factors in decision models. Instead, this study calls for more research to identify feasible avenues and seek consensus.

Abstract 12022: Transcatheter Aortic Valve Implantation Wait-Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T)

Introduction: Transcatheter aortic valve implantation (TAVI) for patients with aortic stenosis has seen indication expansion and exponential growth in demand over the last decade. In many jurisdictions the growing demand outpaced capacity, increasing wait-times and pre-procedural adverse events. Objective: To derive prediction models that estimate the risk of adverse events on the waitlist that would inform the development of a triage tool for use by clinicians to identify patients who should be prioritized for TAVI. Methods: We conducted an observational retrospective cohort study using population-based administrative data from Ontario, Canada. Adult patients referred for TAVI from April 1 st , 2012 to March 31 st , 2020 were included and followed-up to the first of: death, TAVI procedure, removal from waitlist, or end of the observation period. We used competing risk subdistributions hazards models to find significant predictors for each of the following outcomes: (1) all-cause death while on the waitlist, (2) all-cause hospitalization while on the waitlist, (3) receipt of urgent TAVI, and (4) a composite of outcomes 1-3. The median predicted risk in our population at 12 weeks was chosen as a threshold for a maximum acceptable risk while on the waitlist, and was incorporated in the triage tool to recommend individualized wait-times. Results: We included 13,128 patients in the analyses. 586 (4.46%) patients died on the waitlist, and 4,343 (33.08%) had at least one all-cause hospitalization. 6,854 TAVIs were completed, of which 1,135 (16.56%) were urgent procedures. We were able to create parsimonious models for each outcome that included clinically relevant predictors. Optimism-corrected C-statistics varied from 0.63 to 0.75, optimism-corrected Brier scores from 0.03 to 0.19, and the calibration slopes from 0.79 to 0.99. Conclusions: We developed the Canadian TAVI Triage Tool (CAN3T), a triage tool to assist clinicians in the prioritization of patients who should have timely access to TAVI. We anticipate that the CAN3T will be a valuable support tool for patients and clinicians, with the potential of bringing meaningful changes to the health system as it may improve equity in access to care, reduce preventable adverse events and improve system efficiency.