Public perceptions related to healthcare preparedness to anti-amyloid therapies for Alzheimer's Disease in Japan.

BACKGROUND: The approval of lecanemab, an anti-amyloid therapy for Alzheimer's disease (AD), necessitates addressing healthcare preparedness for disease-modifying treatment (DMT) to ensure appropriate, safe, and sustainable drug administration. Understanding public perceptions on this matter is crucial. We aimed to assess discrepancies and similarities in the perceptions of Japanese trial-ready cohort study ('J-TRC webstudy') participants and clinical specialists in the fields of dementia treatment and radiology, concerning affairs related to challenges in DMT preparedness. METHODS: This was a cross-sectional prospective observational study conducted in November-December 2023. The J-TRC webstudy participants were invited to participate in an online survey using Google Forms, and clinical specialists were invited to complete a mail-based survey. Main questionnaire items had been designed to be common in both surveys, and their responses were analyzed for participant attributes, interests, attitudes, expectations, and concerns about DMTs without specifying lecanemab. RESULTS: Responses were obtained from n = 2,050 J-TRC webstudy participants and n = 1,518 clinical specialists. Compared to specialists, more J-TRC respondents perceived the eligible proportion for DMT as smaller (59.1% versus 30.7%), perceived the eligible severity for DMT as more limited (58.0% versus 24.5%), and perceived the efficacy of DMT as slightly more encouraging (29.3% versus 34.8%). In terms of treatment prioritization, both J-TRC respondents and specialist respondents exhibited similar levels of acceptance for prioritizing patients to treat: e.g., approximately two-thirds endorsed patient prioritization under hypothetical resource constraints or other reasons. A medical rationale emerged as the most compelling reason for acceptance of patient prioritization across the surveys. In contrast, the need to address vulnerable populations was the reason that led to the least acceptance of prioritization, followed by economic considerations. CONCLUSIONS: Our findings offer valuable insights into the discrepancies in knowledge and perception between patients and healthcare providers. This could enhance the delivery of patient information in clinical settings and inform the discussion surrounding patient prioritization strategies.

Randomized controlled open-label trial to evaluate prioritization software for the secondary triage of patients in the pediatric emergency department.

BACKGROUND: The continual increase in patient attendance at the emergency department (ED) is a worldwide health issue. The aim of this study was to determine whether the use of a secondary prioritization software reduces the patients' median length of stay (LOS) in the pediatric ED. METHODS: A randomized, controlled, open-label trial was conducted over a 30-day period between March 15th and April 23rd 2021 at Lille University Hospital. Work days were randomized to use the patient prioritization software or the pediatric ED's standard dashboard. All time intervals between admission and discharge were recorded prospectively by a physician not involved in patient care during the study period. The study's primary endpoint was the LOS in the pediatric ED, which was expected to be 15 min shorter in the intervention group than in the control group. The secondary endpoints were specific time intervals during the stay in the pediatric ED and levels of staff satisfaction. RESULTS: 1599 patients were included: 798 in the intervention group and 801 in the control group. The median [interquartile range] LOS was 172 min [113-255] in the intervention group and 167 min [108-254) in the control group (p = 0.46). In the intervention group, the time interval between admission to the first medical evaluation for high-priority patients and the time interval between the senior physician's final evaluation and patient discharge were shorter (p < 0.01). The median satisfaction score was 68 [55-80] (average). CONCLUSION: The patients' total LOS was not significantly shorter on days of intervention. However, use of the electronic patient prioritization tool was associated with significant decreases in some important time intervals during care in the pediatric ED. CLINICALTRIALS: gov: NCT05994196 Trial registration number: NCT05994196. Date of registration: August 16th, 2023.

Surgical Preparedness Index in Orthopaedics During the Coronavirus Disease 2019 (COVID-19) Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has increased the vulnerability of routine surgical procedures and elective surgery preparedness all over the world, with the suspension of most elective surgeries during the pandemic and the backlog of patients currently on waiting lists, especially in publicly funded healthcare systems. On average, at the beginning of the year 2022, about 200 million patients awaited surgery all over the world. By enhancing the strength of surgical preparedness, there is a better chance of strengthening elective surgical systems against shocks such as future pandemics or climate emergencies. We explore the implications, challenges, and strategies of the concept of surgical preparedness to maintain sustainability in the global healthcare system, especially in low- and middle-income countries (LMICs), with the experiences gained during the COVID-19 pandemic.

A Machine Learning Model for Week-Ahead Hypoglycemia Prediction From Continuous Glucose Monitoring Data.

BACKGROUND: Remote patient monitoring (RPM) programs augment type 1 diabetes (T1D) care based on retrospective continuous glucose monitoring (CGM) data. Few methods are available to estimate the likelihood of a patient experiencing clinically significant hypoglycemia within one week. METHODS: We developed a machine learning model to estimate the probability that a patient will experience a clinically significant hypoglycemic event, defined as CGM readings below 54 mg/dL for at least 15 consecutive minutes, within one week. The model takes as input the patient's CGM time series over a given week, and outputs the predicted probability of a clinically significant hypoglycemic event the following week. We used 10-fold cross-validation and external validation (testing on cohorts different from the training cohort) to evaluate performance. We used CGM data from three different cohorts of patients with T1D: REPLACE-BG (226 patients), Juvenile Diabetes Research Foundation (JDRF; 355 patients) and Tidepool (120 patients). RESULTS: In 10-fold cross-validation, the average area under the receiver operating characteristic curve (ROC-AUC) was 0.77 (standard deviation [SD]: 0.0233) on the REPLACE-BG cohort, 0.74 (SD: 0.0188) on the JDRF cohort, and 0.76 (SD: 0.02) on the Tidepool cohort. In external validation, the average ROC-AUC across the three cohorts was 0.74 (SD: 0.0262). CONCLUSIONS: We developed a machine learning algorithm to estimate the probability of a clinically significant hypoglycemic event within one week. Predictive algorithms may provide diabetes care providers using RPM with additional context when prioritizing T1D patients for review.

Going Beyond Waitlists in Mental Healthcare.

Managing waitlists for outpatient mental health services particularly in community health settings is difficult to standardize, poses an administrative burden, and are barriers rather than gateways to access to care particularly for low-income communities. While telehealth has initially expanded access to mental healthcare at the onset of the COVID-19 pandemic, it has not resolved the challenges associated with the increasing demand for services and the shortage of available providers. This commentary explores the intricate interconnections between wait times, readiness for and appropriateness of therapy, and engagement in treatment. Drawing on insights from waiting line theory to question the attachment to and utility of waitlists for non-emergency, outpatient mental healthcare, this commentary questions the utility and efficacy of waitlists. Alternative solutions that capitalize on community resources and collaboration and harness patients' agency for change are discussed.

Who needs clinician attention first? A qualitative study of critical care clinicians' needs that enable the prioritization of care for populations of acutely ill patients.

BACKGROUND: To adequately care for groups of acutely ill patients, clinicians maintain situational awareness to identify the most acute needs within the entire intensive care unit (ICU) population through constant reappraisal of patient data from electronic medical record and other information sources. Our objective was to understand the information and process requirements of clinicians caring for multiple ICU patients and how this information is used to support their prioritization of care among populations of acutely ill patients. Additionally, we wanted to gather insights on the organization of an Acute care multi-patient viewer (AMP) dashboard. METHODS: We conducted and audio-recorded semi-structured interviews of ICU clinicians who had worked with the AMP in three quaternary care hospitals. The transcripts were analyzed with open, axial, and selective coding. Data was managed using NVivo 12 software. RESULTS: We interviewed 20 clinicians and identified 5 main themes following data analysis: (1) strategies used to enable patient prioritization, (2) strategies used for optimizing task organization, (3) information and factors helpful for situational awareness within the ICU, (4) unrecognized or missed critical events and information, and (5) suggestions for AMP organization and content. Prioritization of critical care was largely determined by severity of illness and trajectory of patient clinical status. Important sources of information were communication with colleagues from the previous shift, bedside nurses, and patients, data from the electronic medical record and AMP, and physical presence and availability in the ICU. CONCLUSIONS: This qualitative study explored ICU clinicians' information and process requirements to enable the prioritization of care among populations of acutely ill patients. Timely recognition of patients who need priority attention and intervention provides opportunities for improvement of critical care and for preventing catastrophic events in the ICU.

Clinical information predicting severe obstructive sleep apnea: A cross-sectional study of patients waiting for sleep diagnostics.

INTRODUCTION: Obstructive sleep apnea (OSA) is highly prevalent with serious health consequences. Demand for diagnostic studies is high, in many countries exceeding capacity. PURPOSE: The objective of this cross-sectional study was to identify predictors of severe OSA among patients on waiting lists for sleep studies, to better prioritize time to examinations. METHODS: The sample comprised 3646 patients (30.3% women) referred to a university clinic in Western Norway with suspected OSA. All patients underwent respiratory polygraphy. Severe OSA was defined by an apnea-hypopnea index ≥30. Information on symptoms (snoring, breathing cessations, daytime sleepiness) and medical history was collected with questionnaires, including prior diagnosis of angina, myocardial infarction, stroke, hypertension, depression or diabetes. Blood pressure was measured with thresholds of 90 and 140 mmHg defining diastolic and systolic hypertension. RESULTS: 15.7% had severe OSA. In multivariate logistic regression analysis, factors positively associated with severe OSA were increasing age, male sex, snoring, breathing cessations, BMI ≥30, diastolic hypertension, self-reported history of hypertension, and self-reported myocardial infarction. A prediction score (range 0-5) devised from 5 of these items (age ≥50, snoring, breathing cessations, BMI ≥30, and self-reported hypertension) had a sensitivity of 96.2% and a negative predictive value of 97.1% for severe OSA, when a score ≥2 was set as cut-off. CONCLUSIONS: Based on a prediction score derived from simple, easily available data, patients unlikely to suffer from severe OSA can be identified, and thus facilitate more urgent consideration of patients more likely to have severe OSA.

Prioritization, patient selection, and multimodal perioperative management of colorectal cancer facing health-care system saturation.

OBJECTIVE: The aim is to analyze the usefulness of pre-operative COVID-19 screening to detect asymptomatic patients, the capability of our patient selection algorithm to detect patients with more advanced tumors and the results of colorectal cancer surgery managed with a multimodal approach. We propose the use of a preoperative patient selection algorithm to prioritize the surgical treatment of patients with worse oncological prognosis and lower perioperative risk in situations of health system saturation. MATERIAL AND METHODS: Prospective descriptive study including 71 patients operated on for colorectal cancer during COVID-19's high incidence period. A division was made into two periods of time that were later compared with the aim of assessing whether the scale used identified those patients with lower surgical risk and higher oncological priority for their priority scheduling. RESULTS: Post-operative severe acute respiratory syndrome coronavirus 2 infection occurred in one patient (1.4%). Pre-operative polymerase chain reaction detected one asymptomatic patient (3%). Tumor stage was ≥ IIIA in 39% and node positive in 39% of patients in the first period, while 26% and 21% in the second period, respectively (p = 0.320; p = 0.179), without increasing the surgical stay or complications. Median hospital stay was 5 days. Grades III and IV morbidity were 4.4% and 1.4%. CONCLUSION: The use of an algorithm and Patient Selection Scale can detect patients with more advanced tumors to be operated before. Multimodal management/ERAS have a role in achieving short stay and low morbidity.

OBJETIVO: El retraso terapéutico derivado de la saturación del Sistema sanitario conlleva un peor pronóstico oncológico y un aumento de complicaciones en el cáncer colorrectal. Proponemos el usode un algoritmo de selección de pacientes de forma preoperatoria para priorizar el tratamiento quirúrgico de los pacientes con peor pronóstico oncológico y menor riesgo perioperatorio. MATERIAL Y MÉTODOS: Realizamos un estudio descriptivo prospectivo de 71 pacientes intervenidos por cáncer colorrectal durante el periodo de máxima incidencia por COVID. Se realizó una división en dos periodos de tiempo que fueron comparados posteriormente con el objetivo de valorar si la escala utilizada conseguía identificar aquellos pacientes con menor riesgo quirúrgico y mayor prioridad oncológica para su programación prioritaria. RESULTADOS: Utilizando la escala de priorización de pacientes (PSS) observamos que el estadio tumoral fue mayor de IIIA en un 39% de los pacientes con un 39% de ganglios positivos en un primer periodo, frente a un 26% y 21% en un segundo periodo (p = 0.320; p = 0.179) de tiempo, sin aumentar la estancia operatoria ni las complicaciones. Se realizaron dos métodos de cribado de COVID-19 en dos periodos de tiempo, detectando un 3% de pacientes asintomáticos de forma preoperatoria con PCR, y documentando un 1.4% de infección por COVID postoperatoria. CONCLUSIONES: Ante la saturación del sistema sanitario, la utilización de protocolos y algoritmos para selección de pacientes con cáncer colorrectal puede ayudar a dar preferencia quirúrgica a aquellos casos que no deben ser demorados.

Directives of general surgical practice during the COVID-19 pandemic: A systematic review.

The coronavirus disease 2019 (COVID-19) is a serious global pandemic that has extremely affected health-care systems. This article aimed to review the perspectives of general surgical practice during the COVID-19 pandemic. A systematic review of the literature addressing modification to general surgical practice during the COVID-19 pandemic indexed in PubMed, Scopus, Google, and Google scholar was carried out on June 19-20, 2020. The literature review yielded 577 articles. The exclusion of duplication, articles not in English, and specialized ones in various surgical disciplines precluded 398 articles. Finally, following checking for relevance and publication status, 114 papers were included. Recommendations for surgical practice during the COVID-19 pandemic revolved around mitigation of the risk of virus transmission to patients and health-care workers. The emerging themes of safety precautions were related to patient prioritization and testing, mindful consideration of the operative strategy, optimum use of personal protective equipment, operative room setup, and departmental organization. However, those recommendations were often diverging and bore on a dearth of evidence and personal opinions. Multidisciplinary work and cooperation among surgical specialties are required to establish and validate the protocols for safe surgical practice during the pandemic and perhaps similar crises in future. The COVID-19 pandemic has brought several challenges to the field of medicine, including the surgical specialty. The centrality of safety precautions emerging in this crisis requires surgeons to adopt the new roles and work standards and translate them into practice during the pandemic and perhaps longer.

Patient prioritization and management during the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) pandemic affected the healthcare system in a major way generally. Healthcare re-organization of resources and manpower, establishing management protocols and specific patients' pathways are all evolving with the continuously changing situation. Neuro-vascular management and its re-organization are part of these global measures to cope with this pandemic in a way to establish less risky patients' pathways, help in patients' triage, protecting the staff by introducing training and applying safety measures and to manage neuro-vascular emergencies and elective activity. We here describe the situation of the pandemic affecting neuro-vascular interventions and propose our recommendations for patients' triage, resources management and organization, remote solutions and preparations for any future waves.

Perceptions on principle of priority setting in disaster triage: A Q-method study.

INTRODUCTION: An ethical plan is required to make decisions regarding setting the priority for assisting injured patients through triage. The aim of this study was to explore the measures used to sort patients for ethical decision-making in disaster triage. METHOD: The participants were 54 clinicians and non-clinicians among the Iranian experts. Q-statements were selected from a literature review and face-to-face interviews. Data were analyzed by principal components factor analysis (PCA), Varimax, and hand-rotation techniques. RESULTS: Distinct perspectives included: Saving patients with greater medical needs, survivability of patients and the community, providing effective treatment based on available capacity, maximizing health gain, supporting the human generation and productive and independent lives. Approximately 61% of the variance in decision is explained by these factors. CONCLUSION: A combination of saving more people and more positive outcomes has been accepted to make an ethical decision in triage. Public engagement needs to reach a more acceptable view of patients' prioritizing factors in a scarce-resource situation.

The challenges of administering a new treatment: the case of direct-acting antivirals for hepatitis C virus.

OBJECTIVES: We develop a patient prioritization scheme for treating patients infected with hepatitis C virus (HCV) and study under which scenarios it outperforms the current practices in Spain and Chile. STUDY DESIGN: We use simulation to evaluate the performance of prioritization rules under two HCV patient cohorts, constructed using secondary data of public records from Chile and Spain, during 2015-2016. METHODS: We use the results of a mathematical model, which determines individual optimal HCV treatment policies as an input for constructing a patient prioritization rule, when limited resources are present. The prioritization is based on marginal analysis on cost increases and health-outcome gains. We construct the Chilean and Spanish case studies and used Monte Carlo simulation to evaluate the performance of our methodology in these two scenarios. RESULTS: The resulting prioritizations for the Chilean and Spanish patients are similar, despite the significant differences of both countries, in terms of epidemiological profiles and cost structures. Furthermore, when resources are scarce compared with the number of patients in need of the new drug, our prioritization significantly outperforms current practices of treating sicker patients first, both in terms of cost and healthcare indicators: for the Chilean case, we have an increase in the quality-adjusted life years (QALYs) of 0.83 with a cost reduction of 8176 euros per patient, with a budget covering 2.5% of the patients in the cohort. This difference slowly decreases when increasing the available resources, converging to the performance indicators obtained when all patients are treated immediately: for the Spanish case, we have a decrease in the QALYs of 0.17 with a cost reduction of 1134 euros per patient, with a budget covering 20% of the patients in the cohort. CONCLUSION: Decision science can provide useful analytical tools for designing efficient public policies that can excel in terms of quantitative health performance indicators.

Individuals with common diseases but with a low polygenic risk score could be prioritized for rare variant screening.

PURPOSE: Identifying rare genetic causes of common diseases can improve diagnostic and treatment strategies, but incurs high costs. We tested whether individuals with common disease and low polygenic risk score (PRS) for that disease generated from less expensive genome-wide genotyping data are more likely to carry rare pathogenic variants. METHODS: We identified patients with one of five common complex diseases among 44,550 individuals who underwent exome sequencing in the UK Biobank. We derived PRS for these five diseases, and identified pathogenic rare variant heterozygotes. We tested whether individuals with disease and low PRS were more likely to carry rare pathogenic variants. RESULTS: While rare pathogenic variants conferred, at most, 5.18-fold (95% confidence interval [CI]: 2.32-10.13) increased odds of disease, a standard deviation increase in PRS, at most, increased the odds of disease by 5.25-fold (95% CI: 5.06-5.45). Among diseased patients, a standard deviation decrease in the PRS was associated with, at most, 2.82-fold (95% CI: 1.14-7.46) increased odds of identifying rare variant heterozygotes. CONCLUSION: Rare pathogenic variants were more prevalent among affected patients with a low PRS. Therefore, prioritizing individuals for sequencing who have disease but low PRS may increase the yield of sequencing studies to identify rare variant heterozygotes.

Coupling Wearable Devices and Decision Theory in the United States Emergency Department Triage Process: A Narrative Review.

This research was motivated by the nurses' decision-making process in the current emergency department (ED) triage process in the United States. It explores how continuous vital signs monitoring can be integrated into the ED. The article presents four shortcomings on current ED triage systems and proposes a new conceptual clinical decision support model that exploits the benefits of combining wireless wearable devices with Multi-Attribute Utility Theory to address those shortcomings. A literature review was conducted using various engineering and medical research databases, analyzing current practices and identifying potential improvement opportunities. The results from the literature review show that advancements in wireless wearable devices provide opportunities to enhance current ED processes by monitoring patients while they wait after triage and, therefore, reduce the risk of an adverse event. A dynamic mathematical decision support model to prioritize patients is presented, creating a feedback loop in the ED. The coupling of wearable devices (to collect data) with decision theory (to synthesize and organize the information) can assist in reducing sources of uncertainty inherent to ED systems. The authors also address the feasibility of the proposed conceptual model.

A systematic review of patient prioritization tools in non-emergency healthcare services.

BACKGROUND: Patient prioritization is a strategy used to manage access to healthcare services. Patient prioritization tools (PPT) contribute to supporting the prioritization decision process, and to its transparency and fairness. Patient prioritization tools can take various forms and are highly dependent on the particular context of application. Consequently, the sets of criteria change from one context to another, especially when used in non-emergency settings. This paper systematically synthesizes and analyzes the published evidence concerning the development and challenges related to the validation and implementation of PPTs in non-emergency settings. METHODS: We conducted a systematic mixed studies review. We searched evidence in five databases to select articles based on eligibility criteria, and information of included articles was extracted using an extraction grid. The methodological quality of the studies was assessed by using the Mixed Methods Appraisal Tool. The article selection process, data extraction, and quality appraisal were performed by at least two reviewers independently. RESULTS: We included 48 studies listing 34 different patient prioritization tools. Most of them are designed for managing access to elective surgeries in hospital settings. Two-thirds of the tools were investigated based on reliability or validity. Inconclusive results were found regarding the impact of PPTs on patient waiting times. Advantages associated with PPT use were found mostly in relationship to acceptability of the tools by clinicians and increased transparency and equity for patients. CONCLUSIONS: This review describes the development and validation processes of PPTs used in non-urgent healthcare settings. Despite the large number of PPTs studied, implementation into clinical practice seems to be an open challenge. Based on the findings of this review, recommendations are proposed to develop, validate, and implement such tools in clinical settings. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018107205.

Prioritization of Proton Patients in the COVID-19 Pandemic: Recommendations from The New York Proton Center.

It has been well documented from the early days of the 2019 novel coronavirus (COVID-19) pandemic that patients with a diagnosis of cancer are not only at higher risks of contracting a COVID-19 infection but also at higher risks of suffering severe, and possibly fatal, outcomes from the infection. Given that the United States has the greatest number of positive coronavirus cases, it is likely that many, if not all, radiation oncology clinics will be faced with the challenge of safely balancing a patient's risk of contracting COVID-19, while under active radiation treatment, against their risk of cancer progression if treatment is delayed. To address this challenge, the New York Proton Center established an internal algorithm that considers treatment-related, tumor-related, and patient-related characteristics. Despite having suffered staff shortages due to illness, this algorithm has allowed the center to maintain patient treatment volumes while keeping the rate of COVID-19 infection low.

Serum lysophosphatidylcholines to phosphatidylcholines ratio is associated with symptomatic responders to symptomatic drugs in knee osteoarthritis patients.

BACKGROUND: Identification of the optimal treatment for a given patient is of paramount importance. This is of particular relevance in osteoarthritis (OA) because of the high prevalence of the disease, extensive heterogeneity of the disease, and need for long-term treatment. The aim of the study was to examine whether serum lysophosphatidylcholines (lysoPCs) to phosphatidylcholines (PCs) ratio can predict clinical response to licofelone and naproxen treatments in symptomatic knee OA patients. METHODS: One hundred fifty-eight OA patients who completed the study according to protocol (ATP) of a previous 24-month clinical trial cohort comparing the effect of licofelone vs. naproxen in symptomatic knee OA patients were included. Symptomatic responses to either treatments were classified according to the OARSI-OMERACT criteria based on the WOMAC scores at 24 months. Total concentrations of PCs and lysoPCs were measured in the serum samples collected before the initiation of the treatments, and the lysoPCs to PCs ratio was calculated. Student's t test was utilized to compare the difference in the ratio of lysoPCs to PCs between the symptomatic responders and non-responders. Logistic regression was utilized to adjust for the potential confounders. Receiver operating characteristic (ROC) analysis was performed to identify the optimal cutoff of the ratio for prediction. RESULTS: Data showed that 61.4% of the patients symptomatically responded to licofelone and naproxen and 38.6% were deemed as therapeutic failures (non-responders). There was no difference in responders between licofelone and naproxen (p = 0.87). Responders had a significantly higher lysoPCs to PCs ratio than non-responders (0.097 ± 0.003 vs. 0.085 ± 0.003; p = 0.006). Patients with a ratio greater than the optimal cutoff of 0.088 had 2.93 times more likely to respond to licofelone and naproxen (p = 0.002). CONCLUSIONS: Serum lysoPCs to PCs ratio is a marker for response to licofelone and naproxen and may aid in the personalized treatment to knee OA.

Lessons Learned from Implementing a Patient Prioritization Tool Designed with End-Users in a Pediatric Emergency Ward.

INTRODUCTION: Overcrowding is a common problem in emergency departments. This is true for adult and pediatric emergency department (PED) and issues are potentially important (e.g. quality of care, financial, social, ethical). Optimum is one among several solutions implemented to fight this phenomenon. It is an electronic patient prioritization tool for PED devoted to non-vital emergencies. First usage assessments reported the tool was not used by the PED staffs despite their strong involvement during the development. AIM: This paper aims at understanding why the PED staff did not use the Optimum system that has been designed with them and for them, through a user-centered design process. METHOD: PED staffs answered answer a short survey about their usage of Optimum. Depending on their answer (user vs. non-user), they either underwent an individual semi-structured interview or an unstructured one. Interviews were audio-recorded and transcribed and, from each interview, meaningful semantic units representing the reasons for using/non-using Optimum were extracted and organized iteratively following a grounded approach by three ergonomics experts till a consensus was reached. RESULTS: 12 interviews have been performed with 6 physicians, 5 nurses and 1 auxiliary nurse. Overall, the prioritization tool Optimum have received a mixed response from the PED staff: Optimum display is neither understood nor trusted by users. Moreover, it is mainly used to estimate the PED attendance rate and not to prioritize patients. DISCUSSION: This study shows how much it is difficult to implement new tool in wards despite a user-centered development and without being included in the daily used patient management tool.

Patient prioritization tools and their effectiveness in non-emergency healthcare services: a systematic review protocol.

BACKGROUND: Waiting lists should be managed as fairly as possible to ensure that patients with greater or more urgent needs receive services first. Patient prioritization refers to the process of ranking referrals in a certain order based on various criteria with the aim of improving fairness and equity in the delivery of care. Despite the widespread use of patient prioritization tools (PPTs) in healthcare services, the existing literature on this subject has mainly focused on emergency settings. Evidence has not been synthesized with respect to all the non-emergency services. METHODS: This review aims to perform a systematic synthesis of published evidence concerning (1) prioritization tools' characteristics, (2) their metrological properties, and (3) their effect measures across non-emergency services. Five electronic databases will be searched (Cochrane Library, Ovid/MEDLINE, Embase, Web of Science, and CINAHL). Eligibility criteria guiding data selection will be (1) qualitative, quantitative, or mixed methods empirical studies; (2) patient prioritization in any non-emergency setting; and (3) discussing characteristic, metrological properties, or effect measures. Data will be sought to report tool's format, description, population, setting, purpose, criteria, developer, metrological properties, and outcome measures. Two reviewers will independently screen, select, and extract data. Data will be synthesized with sequential exploratory design method. We will use the Mixed Methods Appraisal Tool (MMAT) to assess the quality of articles included in the review. DISCUSSION: This systematic review will provide much-needed knowledge regarding patient prioritization tools. The results will benefit clinicians, decision-makers, and researchers by giving them a better understanding of the methods used to prioritize patients in clinical settings. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018107205.

Population Health and Cost-Effectiveness Implications of a "Treat All" Recommendation for HCV: A Review of the Model-Based Evidence.

The World Health Organization HCV Guideline Development Group is considering a "treat all" recommendation for persons infected with hepatitis C virus (HCV). We reviewed the model-based evidence of cost-effectiveness and population health impacts comparing expanded treatment policies to more limited treatment access policies, focusing primarily on evaluations of all-oral directly acting antivirals published after 2012. Searching PubMed, we identified 2,917 unique titles. Sequentially reviewing titles and abstracts identified 226 potentially relevant articles for full-text review. Sixty-nine articles met all inclusion criteria-42 cost-effectiveness analyses and 30 models of population-health impacts, with 3 articles presenting both types of analysis. Cost-effectiveness studies for many countries concluded that expanding treatment to people with mild liver fibrosis, who inject drugs (PWID), or who are incarcerated is generally cost-effective compared to more restrictive treatment access policies at country-specific prices. For certain patient subpopulations in some countries-for example, elderly individuals without fibrosis-treatment is only cost-effective at lower prices. A frequent limitation is the omission of benefits and consequences of HCV transmission (i.e., treatment as prevention; risks of reinfection), which may underestimate or overestimate the cost-effectiveness of a "treat all" policy. Epidemiologic modeling studies project that through a combination of prevention, aggressive screening and diagnosis, and prompt treatment for all fibrosis stages, it may be possible to virtually eliminate HCV in many countries. Studies show that if resources are not available to diagnose and treat all HCV-infected individuals, treatment prioritization may be needed, with alternative prioritization strategies resulting in tradeoffs between reducing mortality or reducing incidence. Notably, because most new HCV infections are among PWID in many settings, HCV elimination requires unrestricted treatment access combined with injection transmission disruption strategies. The model-based evidence suggests that a properly constructed strategy that substantially expands HCV treatment could achieve cost-effective improvements in population health in many countries.