Prioritization Of Patients Research Articles

Healthcare professionals' attitudes concerning prioritisation decisions: a quali-quantitative analysis in Angola

Bedside rationing decisions are a necessary evil in the context of resource scarcity. The ethical values inherent in decisions about who to treat make interprofessional collaboration between health professionals essential. We evaluate and compare the attitudes of Angolan physicians and nurses towards patient's prioritisation decisions and the rationing principles supported. Faced with rationing scenarios comprising of four-patient respondents should: 1) select the only patient to treat, explaining their choice; 2) establish a patient care sequential order. Non-parametric tests and multinomial logistic regressions were performed to compare patient's choice between both groups and explore relations between socio-demographic, health and health-related behaviours and patient top priority assigned. Content analysis was used to explore the reasons for patients' selection. Findings suggest that physicians and nurses share similar views, suggesting no tensions regarding patient's prioritisation. Respondents support health maximisation, severity and fair-innings as rationing principles while waiting time and health-related behaviours were undervalued.

Prioritization of Patients in ICU: Composite Approach of Multiple-Criteria Decision-Making and Discrete Event Simulation

Goal: This article aims to present a systematic approach to improve the resource allocation and human queues prioritization patterns.
 Design / Methodology / Approach: To achieve such a purpose, effective criteria using a fuzzy-Delphi method, and subject-related researchers’ views were obtained. Utilizing the Analytic Network Process method, the weights of each criterion was measured. Then, considering the established weights and using a fuzzy-TOPSIS method, a prioritization system via Discrete Event Simulation was developed.
 Results: Results indicate that the established approach properly improved the performance of the prioritization system in terms of resources and facilities allocation in neurology’s ICUs.
 Limitations of the investigation: A drawback of this research can be in states of emergency which limits the options at hand and the criteria proposed may set a drawback on the aim of the study.
 Practical implications: The results show that the proposed model can modify patient entry based on multiple criteria in terms of productivity and social justice in the patient queuing strategy.
 Originality / Value: The contribution of this research is threefold: the literature has been reviewed to conclude the criteria concerning decisions around ICUs, the concluded criteria filtered through an expert panel which can be relied based on the method, a real application of the steps proposed is presented which allows comparing the accuracy and efficiency of the decisions made in the hospitals.

Latin American ophthalmology practitioner's perception on current COVID-19 pandemic.

To assess the perception of Latin American ophthalmology practitioners regarding coronavirus disease 2019 (COVID-19) exposure risk, knowledge about personal protection measures, and prioritization of patients. Self-administered voluntary anonymous survey (Google Drive forms) was distributed via text message to ophthalmology practitioners from May 01 to May 05, 2020. Three hundred seventy-one practitioners (45% response rate) comprising 118 (27.6%) residents, 111 (40.5%) ophthalmologists, and 142 (32.8%) sub-specialists completed the survey. Among them, 106 (32.6%) thought that they were at a high risk of acquiring COVID-19 during the course of work. Furthermore, 273 (69.1%) believed that the current guidelines were insufficient to identify COVID-19 patients. The survey also revealed that 265 (59.5%) were not trained to use personal protective equipment (PPE), and even with its correct use, 341 (91.5%) still felt that they were at risk of acquiring COVID-19. Moreover, 80% of the respondents were of the view that staff members were not knowledgeable about national protocols for attending COVID-19 patients. However, only 9 (2%) considered changing their profession to ameliorate COVID-19 contagion risk. This survey has revealed the issues faced by ophthalmology practitioners in Latin America during their routine practice. These concerns and anxiety about COVID- 19 pandemic seem to be the same worldwide. It is important to reinforce the confidence of ophthalmology practitioners on current guidelines for attending COVID-19 patients. It is also necessary to conduct training programs on PPE usage and ensure that PPE items are available at all times to enhance the quality of care and minimize the spread of the disease.

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

ObjectivesWe 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 designWe 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. MethodsWe 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. ResultsThe 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. ConclusionDecision science can provide useful analytical tools for designing efficient public policies that can excel in terms of quantitative health performance indicators.

Can Post-Transplant Outcomes Predicted at the Time of Liver Graft Allocation?

Introduction: Liver grafts are a scarce resource. Both medical urgency and expected post-transplant outcomes should be considered when allocating livers for transplantation. For allocation decisions, it is important to identify variables known at the time of liver allocation that may affect transplant outcomes. Method: Recipient and donor data from the Australia and New Zealand Liver Transplant Registry from January 1998 to May 2019 were used. All interactions between donor and recipient variables were included. The outcome was graft failure, including patient death. Penalised regression with elastic net analysis was performed to select variables for the final multivariable Cox model. The c-statistic was used to assess score discrimination. Results: 3734 patients were included, with 636 graft failures. 714 recipient, donor and interaction variables were considered, with 35 variables selected using elastic net for the multivariable Cox model. Variables with the largest hazard ratios were transplant for liver tumour other than hepatocellular cancer (HR 2.47, 95% CI 1.33-4.61) , retransplant with a donation after cardiac death donor (HR 2.08, CI 1.38-3.13) and split-liver graft (HR 1.5, CI 1.11-1.95). Internal validation on the same data used for model creation resulted in a c-statistic of 0.72. Conclusions: Prediction of post-transplant outcomes from only variables known at the time of liver allocation is challenging. Further improvements are needed in the context of the prioritisation of patients for transplantation.

Is MELD Score the Best Method of Predicting Waiting List Mortality in the Australian and New Zealand Liver Transplant Population?

Introduction: Model for end-stage liver disease (MELD) score is a reproducible, validated and widely accepted method for prioritisation of patients for liver transplantation, although there are some limitations. The aim was to create an Australian and New Zealand (ANZ) population-derived waiting list mortality score, and to compare the discriminative ability of this score to MELD and MELD-Na scores. Method: All transplants from January 1998 to May 2019 were included, using data from the ANZ Liver Transplant Registry. The outcome considered was patient death prior to transplantation. The ANZ-derived waiting list mortality score was created by randomly splitting the data into training and test datasets (70:30). Elastic net regularisation was used to select variables to create the multivariable Cox model. Discrimination of MELD, MELD-Na and the ANZ scores was compared using the c-statistic. Results: 4886 listings were included, with a total of 534 waiting list deaths. 30 of 39 variables were selected for the ANZ score Cox model, with the highest hazard ratios for patients who were ventilated at time of listing (HR 4.4, 95% CI 2.22-8.68) and patients listed from 2006 to 2011 (HR 2.54, CI 1.69-3.82). The c-statistic for MELD and MELD-Na score was 0.76 and 0.77 respectively. The c-statistic for the ANZ score was 0.8. Conclusion: The discriminative ability of all 3 scores was similar, despite a large number of variables included in the ANZ score. Both MELD and MELD-Na are simple to calculate and performed well in predicting waiting list mortality in the ANZ transplant population.

Simulation of “North Carolina Protocol for Allocating Scarce Inpatient Critical Care Resources in a Pandemic” in a Multi-hospital Health Care System

BACKGROUND An integrated nonprofit health care system with 13 North Carolina medical centers conducted a time-pressured quality improvement simulation of its plan to implement the "North Carolina Protocol for Allocating Scarce Inpatient Critical Care Resources in a Pandemic" attendant to pandemic scenario planning. Simulation objectives included assessing the plan in terms of a) efficiency and effectiveness; b) comorbidity scoring validity; c) impact by race/ethnicity, gender, age, and payer status; and d) simulation participant impressions of potential impact on clinicians.METHOD The simulation scenario involved scoring 14 patients with the constraint that only 10 could be afforded critical care resources. Also included were independent scoring validation by four clinicians, structured debriefs with simulation participants and observers, and tracking patient outcomes for 30 days.RESULTS Triage scoring was identical among four triage teams. Lack of concordance in clinician comorbidity scoring did not alter patient prioritization for withdrawal of treatment in this small cohort. Protocol scoring was not correlated with resource utilization or near-term mortality.LIMITATIONS The simulation sample was small and selected when COVID-19 census was temporarily waning. No protocol for pediatric patients was tested.CONCLUSIONS The simulation yielded resource allocation concordance using comorbidity scoring by attending physicians, which significantly accelerated triage team decision-making and did not result in notable disparities by race/ethnicity, gender, or advanced age. Qualitative findings surfaced tensions in balancing de-identified data with individualized assessment and in trusting the clinical judgments of other physicians. Additional research is needed to validate the protocol's predictive value related to patient outcomes.

Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies

IntroductionEarly identification of children at risk of severe febrile illness can optimise referral, admission and treatment decisions, particularly in resource-limited settings. We aimed to identify prognostic clinical and laboratory factors...

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.

Identification of Criteria for Patient Prioritization in Two Specialized Rehabilitation Programs: A Consensus-Seeking Method

Patient prioritization, which is the process of ranking in a certain order based on various criteria, might be a good strategy to help manage access to healthcare services in a fair and equitable manner. It implies a decision-making process about prioritization criteria, and diverges substantially across programs. This process should thus be performed using a rigorous process that considers the various needs of the patients and evaluates them in a valid and reliable manner using prioritization tools carefully designed.

Identification of Criteria for Patient Prioritization in Two Specialized Rehabilitation Programs: A Consensus-Seeking Method

Identification of Criteria for Patient Prioritization in Two Specialized Rehabilitation Programs: A Consensus-Seeking Method

Improving ED Emergency Severity Index Acuity Assignment Using Machine Learning and Clinical Natural Language Processing

IntroductionTriage is critical to mitigating the effect of increased volume by determining patient acuity, need for resources, and establishing acuity-based patient prioritization. The purpose of this retrospective study was to determine whether historical EHR data can be used with clinical natural language processing and machine learning algorithms (KATE) to produce accurate ESI predictive models. MethodsThe KATE triage model was developed using 166,175 patient encounters from two participating hospitals. The model was tested against a random sample of encounters that were correctly assigned an acuity by study clinicians using the Emergency Severity Index (ESI) standard as a guide. ResultsAt the study sites, KATE predicted accurate ESI acuity assignments 75.7% of the time compared with nurses (59.8%) and the average of individual study clinicians (75.3%). KATE’s accuracy was 26.9% higher than the average nurse accuracy (P <.001). On the boundary between ESI 2 and ESI 3 acuity assignments, which relates to the risk of decompensation, KATE’s accuracy was 93.2% higher, with 80% accuracy compared with triage nurses 41.4% accuracy (P <.001). DiscussionKATE provides a triage acuity assignment more accurate than the triage nurses in this study sample. KATE operates independently of contextual factors, unaffected by the external pressures that can cause under triage and may mitigate biases that can negatively affect triage accuracy. Future research should focus on the impact of KATE providing feedback to triage nurses in real time, on mortality and morbidity, ED throughput, resource optimization, and nursing outcomes.

Liver Transplantation Outcomes in a U.S. Multicenter Cohort of 789 Patients With Hepatocellular Carcinoma Presenting Beyond Milan Criteria.

The Organ Procurement and Transplantation Network recently approved liver transplant (LT) prioritization for patients with hepatocellular carcinoma (HCC) beyond Milan Criteria (MC) who are down-staged (DS) with locoregional therapy (LRT). We evaluated post-LT outcomes, predictors of down-staging, and the impact of LRT in patients with beyond-MC HCC from the U.S. Multicenter HCC Transplant Consortium (20 centers, 2002-2013). Clinicopathologic characteristics, overall survival (OS), recurrence-free survival (RFS), and HCC recurrence (HCC-R) were compared between patients within MC (n=3,570) and beyond MC (n=789) who were down-staged (DS, n=465), treated with LRT and not down-staged (LRT-NoDS, n=242), or untreated (NoLRT-NoDS, n=82). Five-year post-LT OS and RFS was higher in MC (71.3% and 68.2%) compared with DS (64.3% and 59.5%) and was lowest in NoDS (n=324; 60.2% and 53.8%; overall P<0.001). DS patients had superior RFS (60% vs. 54%, P=0.043) and lower 5-year HCC-R (18% vs. 32%, P<0.001) compared with NoDS, with further stratification by maximum radiologic tumor diameter (5-year HCC-R of 15.5% in DS/<5cm and 39.1% in NoDS/>5cm, P<0.001). Multivariate predictors of down-staging included alpha-fetoprotein response to LRT, pathologic tumor number and size, and wait time >12months. LRT-NoDS had greater HCC-R compared with NoLRT-NoDS (34.1% vs. 26.1%, P<0.001), even after controlling for clinicopathologic variables (hazard ratio [HR]=2.33, P<0.001) and inverse probability of treatment-weighted propensity matching (HR=1.82, P<0.001). In LT recipients with HCC presenting beyond MC, successful down-staging is predicted by wait time, alpha-fetoprotein response to LRT, and tumor burden and results in excellent post-LT outcomes, justifying expansion of LT criteria. In LRT-NoDS patients, higher HCC-R compared with NoLRT-NoDS cannot be explained by clinicopathologic differences, suggesting a potentially aggravating role of LRT in patients with poor tumor biology that warrants further investigation.

Patient prioritisation for hospital pharmacy services: current approaches in the UK

ObjectivesTo survey and explore current approaches to deployment of pharmaceutical care prioritisation tools in acute hospitals in the UK.MethodsA national online survey was circulated electronically to chief pharmacists of hospitals...

PNS126 Simpli – a Capacity Simulator for Evaluating Measures to Reduce the Backlog of Hospital Services after the COVID-19 Pandemic

In Portugal, due to the COVID-19 pandemic, almost 1.4 million hospital consultations were not conducted at public hospitals and the number of surgeries was reduced by 40% in comparison with 2019. Local safety measures applied by hospitals reduced hospital capacity by 1/3. SimPLI - Simulating Capacity Performance Leading to Impact, a capacity simulator to test the effectiveness of measures to reduce the hospital backlog within capacity constraints, is hereby introduced. A proof of concept was presented for a hospital ophthalmology service. A spreadsheet-based simulator was developed for testing measures to accelerate the realization of delayed external consultations and outpatient surgeries. Inputs include the number of rooms and operation times, waiting room capacity, and allocation of healthcare professionals (HCP) to multiple roles. The impact of several measures was simulated namely the reorganization of HCP schedules and hiring, patient prioritization criteria, the specific allocation of rooms, and increasing teleconsultations. The baseline backlog is represented by the number of delayed procedures. The time to eliminate this backlog was calculated and compared with the output for scenarios where one or more measures were implemented. The implementation of telemedicine for subsequent ophthalmology consultations and the reduction in 10 minutes in the time of face to face consultations would allow eliminating the consultations backlog in 9.3 months vs 16.7 months without any measures. Pertaining to surgeries, allocating an additional room for ophthalmology outpatient surgery and hiring a medical doctor were predicted to reduce the time to perform all backlog surgeries by four months (7.6 vs 11.3 months). SimPLI is invaluable for planning the investment in efficient actions towards optimization of hospital capacity in a post-COVID era in Portugal. The proof of concept demonstrates that the proposed measures could bring significant savings to the hospital by lowering the number of outsourced surgeries.

Prioritizing the Surgical Waiting List-Cosine Consistency Index: An Optimized Framework for Prioritizing Surgical Waiting List

This paper aims to examine patient prioritization challenges faced by surgeons attending to patients awaiting surgery and proposes a decision-making framework named PSWL-CCI to prioritize patients in the surgical waiting list. The proposed framework deals with two critical issues: One, to prioritize patients from the surgical waiting list. Two, to refine and optimize cosine consistency index (CCI) of inconsistent pairwise comparison matrix (PCM) and obtain consistent priorities. The judgment of surgeons on identified parameters in the term of rating helps in determining priorities from the surgical waiting list. The cosine maximization method (CM), along with the analytic hierarchy process (AHP), is used to evaluate the resulting priority. To improve inconsistent pairwise comparison matrix (PCM), a novel hybrid algorithm HMWCA (Hybrid modified water cycle algorithm), is proposed and incorporated in PSWL-CCI. The proposed algorithm exploits the feature of three traditional algorithms, namely the evaporation-based water cycle algorithm (ER-WCA), genetic algorithm, and 2-opt heuristic. In this paper, the concept of salt concentration and absorption introduced into the evaporation rate (ER) that extends ER-WCA to a modified water cycle algorithm (MWCA). MWCA iteratively modifies the entries in PCM until PCM is optimized. The genetic algorithm helps MWCA to determine the evaporation rate and enhance the rate of convergence. The 2-OPT algorithm improvises the optimal solution. The proposed algorithm is tested with different datasets, and the improved CCI values are validated through paired sample t-test. Finally, the proposed PSWL-CCI framework is validated through a case study of a real patient dataset from an orthopedic surgery department of a multispecialty hospital in India. The experimental results obtained in this study reveal that the proposed methodology and algorithms significantly improve the CCI values, thus generating optimum priorities for the patients of the surgical waiting list.

PCV38 The IMPACT on Clinical an Economic VALUE of Patient Prioritization According to Risk: Evolocumab in Patients with Myocardial Infarction in Sweden

PCV38 The IMPACT on Clinical an Economic VALUE of Patient Prioritization According to Risk: Evolocumab in Patients with Myocardial Infarction in Sweden

Design and Evaluation of a Novel Mobile Phone Application to Improve Palliative Home-Care in Resource-Limited Settings

ContextMobile health (mHealth) provides an opportunity to use internet coverage in low- and middle-income countries to improve palliative care access and quality. ObjectivesThis study aimed to design a mobile phone application (app) to enable or improve communication between family caregivers, community caregivers, and palliative care teams; to evaluate its acceptability, processes, and mechanisms of action; and to propose refinements. MethodsA codesign process entailed collaboration between a Project Advisory Group and collaborators in India, Uganda, and Zimbabwe. We then trained community and family caregivers to use an app to communicate patient-reported outcomes to their palliative care providers each week on a data dashboard. App activity was monitored, and qualitative in-depth interviews explored experience with the app and its mechanisms and impact. ResultsN = 149 caregivers participated and uploaded n = 837 assessments of patient-reported outcomes. These data were displayed to the palliative care team on an outcomes dashboard on n = 355 occasions. Qualitative data identified: 1) high acceptability and data usage; 2) improved understanding by team members of patient symptoms and concerns; 3) a need for better feedback to caregivers, for better prioritisation of patients according to need, for enhanced training and support to use the app, and for user-led recommendations for ongoing improvement. ConclusionAn outcomes-focused app and data dashboard are acceptable to caregivers and health-care professionals. They are beneficial in identifying, monitoring, and communicating patient outcomes and in allocating staff resource to those most in need.

Liver Transplantation in Acute-on-chronic Liver Failure.

Liver transplantation (LT) has revolutionized outcomes for cirrhotic patients. Current liver allocation policies dictate patients with highest short-term mortality receive the highest priority, thus, several patients become increasingly ill on the waitlist. Given cirrhosis is a progressive disease, it can be complicated by the occurrence of acute-on-chronic liver failure (ACLF), a syndrome defined by an acute deterioration of liver function associated with extrahepatic organ failures requiring intensive care support and a high short-term mortality. Successfully bridging to transplant includes accurate prognostication and prioritization of ACLF patients awaiting LT, optimizing intensive care support pre-LT, and tailoring immunosuppressive and anti-infective therapies post-LT. Furthermore, predicting futility (too sick to undergo LT) in ACLF is challenging. In this review, we summarize the role of LT in ACLF specifically highlighting (a) current prognostic scores in ACLF, (b) critical care management of the ACLF patient awaiting LT, (c) donor issues to consider in transplant in ACLF, and (d) exploring of recent post-LT outcomes in ACLF and potential opportunities to improve outcomes including current care gaps and unmet research needs.

The experience of UK patients with bladder cancer during the COVID-19 pandemic: a survey-based snapshot.

The COVID-19 pandemic has placed unprecedented strain on healthcare systems worldwide with the requirement to treat large influxes of infected patients, many of whom require respiratory support. Healthcare systems have had to redirect resources and redeploy staff away from routine diagnostic, treatment and follow-up services. The UK's National Health Service (NHS) is no different and cancer services have undergone significant disruption to create the emergency capacity to tackle the pandemic. As a charity that endeavours to support bladder cancer (BC) patients and improve outcomes, Action Bladder Cancer UK (ABCUK, Tetbury, UK) designed and administered an online survey to investigate the prevalence of such disruption.