Impact of Share 35 liver transplantation allocation in Australia and New Zealand.

Patients with high model for end-stage liver disease (MELD) scores waiting for liver transplantation in Australia and New Zealand (ANZ) have had limited access to deceased donor livers and therefore binational sharing of livers, for patients with a MELD score ≥35 was introduced in February 2016. Waiting list mortality, post-transplant outcomes and intention-to-treat survival were compared between patients whose MELD score reached 35 on the waiting list between October 2013 and April 2015 (Pre-Share 35 group, n = 23) and patients who were Share 35 listed between February 2016 and May 2022 (Share 35 group, n = 112). There was significantly reduced waiting list mortality in share 35 listed patients in comparison to the pre-Share 35 group (11.7% vs. 52.2%, OR .120 95% CI .044-.328, P < .001). Post-transplant patient and graft survival were not significantly different between the groups (5-year patient survival 82% vs. 84%, P = .991, 5-year graft survival 82% vs. 76%, P = .543). Intention-to-treat survival was superior in the Share 35 group (HR .302, 95% CI .149-.614, P < .001). Introduction of Share 35 in ANZ resulted in a 78% risk reduction in waiting list mortality, equivalent post-transplant survival and an improvement in intention-to-treat survival.

Surgical waiting lists and queue management in a Brazilian tertiary public hospital.

BACKGROUND: Centralized management of queues helps to reduce the surgical waiting time in the publicly funded healthcare system, but this is not a reality in the Brazilian Unified Healthcare System (BUHS). We describe the implementation of the "Patients with Surgical Indication" (PSI) in a Brazilian public tertiary hospital, the impact on waiting time, and its use in rationing oncological surgeries during the COVID-19 Pandemic. METHODS: Retrospective observational study of elective surgical requests (2016-2022) in a Brazilian general, public, tertiary university hospital. We recovered information regarding the inflows (indications), outflows and their reasons, the number of patients, and waiting time in queue. RESULTS: We enrolled 82,844 indications in the PSI (2016-2022). The waiting time (median and interquartile range) in days decreased from 98(48;168) in 2016 to 14(3;152) in 2022 (p < 0.01). The same occurred with the backlog that ranged from 6,884 in 2016 to 844 in 2022 (p < 001). During the Pandemic, there was a reduction in the number of non-oncological surgeries per month (95% confidence interval) of -10.9(-18.0;-3.8) during Phase I (January 2019-March 2020), maintenance in Phase II (April 2020-August 2021) 0.1(-10.0;10.4) and increment in Phase III (September 2021-December 2022) of 23.0(15.3;30.8). In the oncological conditions, these numbers were 0.6(-2.1;3.3) for Phase I, an increase of 3.2(0.7;5.6) in Phase II and 3.9(1,4;6,4) in Phase III. CONCLUSION: Implementing a centralized list of surgical indications and developing queue management principles proved feasible, with effective rationing. It unprecedentedly demonstrated the decrease in the median waiting time in Brazil.

Availability and Accessibility of Mental Health Services for Youth: A Descriptive Survey of Safety-Net Health Centers During the COVID-19 Pandemic.

Community Mental Health Centers (CMHCs) and Federally Qualified Health Centers (FQHCs) are critical access points for families with adolescents needing mental health care, especially those enrolled in Medicaid. However, barriers exist which may reduce their accessibility. This study aims to describe the availability and accessibility of outpatient mental health services for children and adolescents at safety-net health centers in a large metropolitan county. Approximately one year after the COVID-19 pandemic began in the U.S., a comprehensive sample of 117 CMHCs and 117 FQHCs were called and administered a 5-minute survey. Approximately 10% of health centers were closed, and 20% (28.2% of FQHCs and 7.7% of CMHCs) reported not offering outpatient mental health services. Despite CMHCs having 5.4 more clinicians on staff on average, reported wait times were longer at CMHCs than FQHCs. These findings indicate that online directories intended to be a comprehensive and accessible resource, such as the SAMHSA Treatment Locator, are often inaccurate or out-of-date.

Impact of newly diagnosed prostate cancer at time of evaluation for renal transplantation.

Systematic screening for prostate cancer is widely recommended in candidates for renal transplant at the time of listing. There are concerns that overdiagnosis of low-risk prostate cancer may result in reducing access to transplant without demonstrated oncological benefits. The objective of the study was to assess the outcome of newly diagnosed prostate cancer in candidates for transplant at the time of listing, and its impact on transplant access and transplant outcomes according to treatment options. This retrospective study was conducted over 10 years in 12 French transplant centers. Patients included were candidates for renal transplant at the time of prostate cancer diagnosis. Demographical and clinical data regarding renal disease, prostate cancer, and transplant surgery were collected. The primary outcome of the study was the interval between prostate cancer diagnosis and active listing according to treatment options. Overall median time from prostate cancer diagnosis to active listing was 25.0 months [16.4-40.2], with statistically significant differences in median time between the radiotherapy and the active surveillance groups (p = .03). Prostate cancer treatment modalities had limited impact on access and outcome of renal transplantation. Active surveillance in low-risk patients does not seem to compromise access to renal transplantation, nor does it impact oncological outcomes.

"I would not want the mechanic to direct me to an engine repair manual": a qualitative analysis of provider perspectives on low-intensity treatments for patients on waiting lists.

BACKGROUND: Low-intensity treatments (LITs), such as bibliotherapy or online self-help, have the potential to reach more individuals than traditional face-to-face care by circumventing many of the common barriers to mental health treatment. Despite substantial research evidence supporting their usability and efficacy across several clinical presentations, prior work suggests that mental health providers rarely recommend LITs for patients waiting for treatment. METHODS: The present study analyzed provider open responses to a prompt asking about perceived barriers, thoughts, and comments related to additional treatment resources for patients on treatment waiting lists. We surveyed 141 practicing mental health providers, 65 of whom responded to an open text box with additional thoughts on using LITs for patients on treatment waiting lists. Responses were qualitatively coded using a thematic coding process. RESULTS: Qualitative outcomes yielded 11 codes: patient appropriateness, research evidence, feasibility, patient barriers, liability, patient personal contact, additional resources, positive attitudes, trust in programs, systemic problems, and downplaying distress. CONCLUSIONS: Results suggest providers are predominantly concerned about the potential of suggesting a LIT that would be ultimately inappropriate for their patient due to a lack of assessment of the patient's needs. Furthermore, providers noted ambiguity around the legal and ethical liability of recommending a LIT to someone who may not yet be a patient. Guidelines and standards for recommending LITs to patients on treatment waiting lists may help address ambiguity regarding their use in routine care.

The impacts of waiting for surgical correction of Adolescent Idiopathic Scoliosis and its repercussions for publicly funded health systems: systematic review.

PURPOSE: To investigate, through a systematic review, the impact of the waiting time for Adolescent Idiopathic Scoliosis (AIS) surgical correction from the point of view of deformity evolution, treatment cost, and quality of life. METHODS: PubMed, Embase, LILACS, SciELO, Scopus, Web of Science, LIVIVO, and Cochrane Library databases were searched by two researchers to select the articles. The eligibility criteria were: Patients diagnosed with AIS with indication for surgical correction and submitted to waiting lists until treatment. The risks of bias were evaluated using the Risk Of Bias In Non-randomized Studies-Interventions (ROBINS-I) tool, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was used to classify the level of the evidence for each outcome. The summary of the available evidence is presented in a narrative synthesis. RESULTS: Six observational studies were included. In a Canadian study, the primary outcome was the need for additional spine surgery in patients who had to wait more than three months due to spine deformity progression. American researchers presented a sample of premenarcheal and skeletally immature patients with AIS showing increased Cobb angle and attributed this to a six-month waiting for the surgical treatment. Another study included 177 patients with AIS with a mean waiting time of 225.7 days. There was a worsening average of 7.7° ± 8.6° in Cobb angle, and there was a change in surgical plan in 28 patients, which increased surgical time. Studies that evaluated the treatment cost showed significantly higher mean costs in those who waited longer than six months. Regarding the quality of life, while waiting for surgery, a retrospective study found that patients who underwent surgery earlier showed better results in a questionnaire that assessed their quality of life compared to those who were still waiting. CONCLUSION: Observational studies show that, in individuals who are on waiting lists for AIS surgery, there is a worsening of the spinal deformity (substantial evidence), an increasing cost of treatment (moderate evidence) and it may negatively impact patients' quality of life (insufficient evidence). Performing better methodological quality studies to investigate these outcomes can violate good research practices since randomized clinical trials on this subject have ethical limitations to be carried out. TRIAL REGISTRATION: The authors declare that the systematic review protocol was registered at the international prospective register of systematic reviews (PROSPERO), CRD42020212134, and it was accepted for publication.

Reducing the neurosurgical waiting list burden: is it a futile endeavour?

BACKGROUND: Cancellation of elective operations during the COVID-19 pandemic has led to a significant increase in the number of patients waiting for treatment. In neurosurgery, treatment for spinal diseases, in particular, has been disproportionately delayed. We aim to describe the waiting list burden at our institution and forecast the time and theatre capacity required to return to pre-pandemic levels. METHODS: A retrospective evaluation of the waiting list records (both cranial and spinal), from January 2015-October 2022, inclusive, was conducted at a high-volume neurosciences centre. The average monthly decrease in the waiting list was calculated for the months since the waiting list was noted to fall consistently during or after the pandemic, as applicable. Five different scenarios were modelled to identify the time required to reduce the waiting list to the pre-pandemic level of December 2019. Data collection and analyses were performed on Excel (Microsoft). RESULTS: At the pre-pandemic threshold (December 2019), 782 patients were on the waiting list. Between January 2015-January 2020, inclusive, an average of 673 patients were on the waiting list but this has doubled over the subsequent months to a peak of 1388 patients in December 2021. Between December 2021-October 2022, on average, the waiting list reduced by 18 per month. At the current rate of change, the waiting list would fall to the pre-pandemic level by October 2024, an interval of 24 months. A seven-day service would require 18 months to clear the backlog. Doubling or tripling the current rate of change would require 12 months and 8 months, respectively. CONCLUSIONS: Pre-existing, pandemic-related, and new NHS-wide challenges continue to have negative influences on reducing the backlog. Proposals for surgical hubs to tackle this carry the risks of removing staff from hospitals which cannot avoid emergency/urgent operating thereby further reducing those institutions' capacity to undertake elective work.

The effect of treatment timing on clinical and psychological outcomes with Twin Block therapy: A multicentre two-arm parallel randomised controlled trial.

OBJECTIVE: To evaluate whether delaying treatment with a twin block appliance affects treatment outcomes, in terms of skeletal and dental change and psychological disadvantage. DESIGN: Multicentre, two-arm parallel randomised controlled trial. SETTING: Three UK hospital orthodontic units. METHODS: A total of 75 participants were randomly allocated into an Immediate Treatment Group (ITG) (n= 41) and an 18-month delayed Later Treatment Group (LTG) (n=34). OUTCOMES: Dentofacial changes were recorded from lateral cephalograms and study models, psychological impact was measured using a child perception questionnaire (CPQ11-14) and an Oral Aesthetic Subjective Impact Score (OASIS) at registration (DC1), 18 months (DC2) and 3 years (DC3). RESULTS: The ITG initial effect was a mean ANB reduction was 1.6° (P<0.001) (95% confidence interval [CI] = 0.89-2.29), and an overjet reduction of 5.06 mm (P<0.001) (95% CI = 3.96-6.16) (boys: aged 12 years 8 months; girls: aged 11 years 8 months). There were no statistically significant differences between the ITG and LTG for twin block treatment outcomes, but the ITG active treatment time was longer (P=0.004) (ITG: 13.1 months; LTG: 9.8 months). There was insufficient evidence to state that patients were psychologically disadvantaged by waiting 18 months for active twin block treatment (P>0.05). CONCLUSION: Participants achieved similar clinical and psychological outcomes irrespective of whether they started their twin block at the age of referral (ITG) or 18 months later (LTG). This suggests that boys aged 12 years 8 months and girls aged 11 years 8 months, on average, are not disadvantaged by waiting 18 months for active twin block treatment.

The use of clinical photography to aid in the triage of ENT patient referrals.

Waiting lists for Ear, Nose and Throat (ENT) outpatient appointments are currently the longest that they have ever been. The Aneurin Bevan University Health Board has adopted a unique Clinical Photography ENT triage service to tackle this. General Practitioner referrals are triaged by ENT consultants, to identify those patients in whom otoscopic imaging could be used to detect a serious otological condition or to enable virtual management. They are triaged to Clinical Photography, to undergo digital imaging which is reviewed in a virtual clinic alongside the initial referral. 72 patients have completed the pathway, with 51.3% discharged without requirement for face-to-face consultant appointment. 9.7% were upgraded to urgent or 2 week waits. This intervention is predicted to help identify patients on the waiting list with potentially serious disease so that they do not wait excessively, and to reduce waiting times for outpatient appointments in ENT.

Associations between social determinants of health and abdominal solid organ transplant wait-lists in the United States.

BACKGROUND: Societal factors that influence wait-listing for transplantation are complex and poorly understood. Social determinants of health (SDOH) affect rates of and outcomes after transplantation. METHODS: This cross-sectional study investigated the impact of SDOH on additions to state-level, 2017-2018 kidney and liver wait-lists. Principal components analysis, starting with 127 variables among 3142 counties, was used to derive novel, comprehensive state-level composites, designated (1) health/economics and (2) community capital/urbanicity. Stepwise multivariate linear regression with backwards elimination (n = 51; 50 states and DC) tested the effects of these composites, Medicaid expansion, and center density on adult disease burden-adjusted wait-list additions. RESULTS: SDOH related to increased community capital/urbanicity were independently associated with wait-listing (starting models: B = .40, P = .010 Kidney; B = .36, P = .038 Liver) (final models: B = .31, P = .027 Kidney, B = .34, P = .015 Liver). In contrast and surprisingly, no other covariates were associated with wait-listing (P ≥ .122). CONCLUSIONS: These results suggest that deficits in community resources are important contributors to disparities in wait-list access. Our composite SDOH metrics may help identify at-risk communities, which can be the focus of local and national policy initiatives to improve access to organ transplantation.

Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England.

OBJECTIVES: A significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In England's National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7 million by August 2021. The objective of this study was to estimate the trajectory of future waiting list size and waiting times up to December 2025. METHODS: A scenario analysis was performed using computer simulation and publicly available data as of November 2021. Future demand assumed a phased return of various proportions (0%, 25%, 50%, and 75%) of the estimated 7.1 million referrals "missed" during the pandemic. Future capacity assumed 90%, 100%, and 110% of that provided in the 12 months immediately before the pandemic. RESULTS: As a worst-case scenario, the waiting list would reach 13.6 million (95% confidence interval 12.4-15.6 million) by Autumn 2022, if 75% of missed referrals returned and only 90% of prepandemic capacity could be achieved. The proportion of patients waiting under 18 weeks would reduce from 67.6% in August 2021 to 42.2% (37.4%-46.2%) with the number waiting over 52 weeks reaching 1.6 million (0.8-3.1 million) by Summer 2023. At this time, 29.0% (21.3%-36.8%) of patients would be leaving the waiting list before treatment. Waiting lists would remain pressured under even the most optimistic of scenarios considered, with 18-week performance struggling to maintain 60%. CONCLUSIONS: This study reveals the long-term challenge for the National Health Service in recovering elective waiting lists and potential implications for patient outcomes and experience.

Pre-Outpatient Group Education and Assessment in Chronic Pain: A Systematic Review.

BACKGROUND: Pre-outpatient interventions in chronic pain have the potential to improve patient self-management earlier in primary or secondary care, which may minimize pain chronicity and negative health outcomes. The literature for this is sparse, and there are no existing systematic reviews on this topic. METHODS: The purpose of this systematic review is to examine the evidence for pre-outpatient group interventions in chronic pain. RESULTS: We identified four studies that looked at this: two randomized control trials, one prospective observational study, and one descriptive study. We identified high-quality evidence that a pre-outpatient group intervention reduces waiting times, moderate-quality evidence that it results in reduced costs per patient, very low-quality evidence that it reduces health care utilization, and very low-quality evidence that it improves service throughput. There were moderate-to-low levels of participant engagement with the initiative, which varied across the included studies. For patient outcome measures, we found no evidence that a pre-outpatient group intervention improves pain intensity, very low-quality evidence that it improves pain-related interference, low-quality evidence that it increases use of pain management strategies and produces high satisfaction levels, low-quality evidence that it improves pain self-efficacy, and no evidence that it improves psychological distress. CONCLUSIONS: Group interventions before individual appointments have the potential to provide important improvements in service delivery, including improvements in waiting times and cost per patient. Benefits for patient outcome measures are less clear. Clinical heterogeneity and high levels of bias existed in the included studies. Further research is required so that meaningful conclusions can be made about these interventions.

"It's messing with my physical health. It's messing with my sex life": Women's perspectives about, and impact of, pelvic health issues whilst awaiting specialist care.

INTRODUCTION AND HYPOTHESIS: Pelvic health conditions are a common health complaint among women worldwide, and conservative management is recognised as first-line treatment. There is often a time lag between referral from general practitioners to specialist consultation and conservative therapy. Therefore, the aim of this research was to explore perspectives from women with pelvic health conditions while they wait for specialist input, specifically about their understanding of their condition and its impact. METHODS: This research was underpinned by a qualitative descriptive methodology. Individual semi-structured interviews were conducted with women with pelvic health conditions who were waiting for specialist gynaecology consultation. RESULTS: A total of 11 women shared their perspectives about, and their understanding of, their condition and its impact. Thematic analysis of the interview data identified a variety of experiences and perspectives of women waiting to see the gynaecologist. These perspectives were categorised into four different themes: drivers to seek help, understanding the condition, experience/feeling being on the waiting list and expectations from the gynaecology team. CONCLUSION: This study identified the main drivers for seeking help were worsening and/or persistent symptoms. Participants were able to articulate their symptoms, identify possible causes and describe various treatment options, and amenable to alternate treatment options. This research sheds light on the devastating impact of pelvic health conditions on women, which may be amplified while waiting to seek specialist input. There appears to be a need for health services to better support these women during this time of waiting.

Supporting COVID-19 elective recovery through scalable wait list modelling: Specialty-level application to all hospitals in England.

The recovery of elective waiting lists represents a major challenge and priority for the health services of many countries. In England's National Health Service (NHS), the waiting list has increased by 45% in the two years since the COVID-19 pandemic was declared in March 2020. Long waits associate with worse patient outcomes and can deepen inequalities and lead to additional demands on healthcare resources. Modelling the waiting list can be valuable for both estimating future trajectories and considering alternative capacity allocation strategies. However, there is a deficit within the current literature of scalable solutions that can provide managers and clinicians with hospital and specialty level projections on a routine basis. In this paper, a model representing the key dynamics of the waiting list problem is presented alongside its differential equation based solution. Versatility of the model is demonstrated through its calibration to routine publicly available NHS data. The model has since been used to produce regular monthly projections of the waiting list for every hospital trust and specialty in England.

The Waiting Game - How Cooperation Between Public and Private Hospitals Can Help Reduce Waiting Lists.

Prolonged waiting to access health care is a primary concern for nations aiming for comprehensive effective care, due to its adverse effects on mortality, quality of life, and government approval. Here, we propose two novel bargaining frameworks to reduce waiting lists in two-tier health care systems with local and regional actors. In particular, we assess the impact of 1) trading patients on waiting lists among hospitals, the 2) introduction of the role of private hospitals in capturing unfulfilled demand, and the 3) hospitals' willingness to share capacity on the system performance. We calibrated our models with 2008-2018 Chilean waiting list data. If hospitals trade unattended patients, our game-theoretic models indicate a potential reduction of waiting lists of up to 37%. However, when private hospitals are introduced into the system, we found a possible reduction of waiting lists of up to 60%. Further analyses revealed a trade-off between diagnosing unserved demand and the additional expense of using private hospitals as a back-up system. In summary, our game-theoretic frameworks of waiting list management in two-tier health systems suggest that public-private cooperation can be an effective mechanism to reduce waiting lists. Further empirical and prospective evaluations are needed.

A Delphi study to explore clinician and lived experience perspectives on setting priorities in eating disorder services.

BACKGROUND: Due to scarce resources and high demand, priority setting in mental health services is necessary and inevitable. To date, no study has examined priority setting in eating disorder (ED) services specifically. Here, we evaluate the level of consensus and perceived relative importance of factors used to determine patient prioritisation in ED services, amongst clinicians and individuals with lived experience (LE) of an ED. METHODS: A three round Delphi study and a ranking task were used to determine the level of consensus and importance. Consensus was defined as > 80% agreement or disagreement. Items that reached consensus for agreement were ranked in order of importance from most to least important. Participants were 50 ED clinicians and 60 LE individuals. Participant retention across rounds 2, 3, and 4 were 92%, 85%, and 79%, respectively. RESULTS: Over three iterative rounds, a total of 87 statements about patient prioritisation were rated on a 5-point Likert-scale of agreement. Twenty-three items reached consensus in the clinician panel and 20 items reached consensus in the LE panel. The pattern of responding was broadly similar across the panels. The three most important items in both panels were medical risk, overall severity, and physical health deteriorating quickly. Clinicians tended to place greater emphasis on physical risk and early intervention whereas the LE panel focused more on mental health and quality of life. CONCLUSIONS: Eating disorder services tend to prioritise patients based upon medical risk and severity, and then by the order in which patients are referred. Our findings align in some respects with what is observed in services, but diverge in others (e.g., prioritising on quality of life), providing important novel insights into clinician and LE opinions on waiting list prioritisation in EDs. More research is warranted to validate these findings using multi-criterion decision techniques and observational methods. We hope these findings provide a foundation for future research and encourage evidence-based conversations around priority setting in ED services.

Initiatives to reduce the waiting time to initiate oncological treatment: a scoping literature review.

Objective: To identify the managerial actions proposed and employed to reduce the waiting time to initiate oncological treatments in the public health system and its application in Latin America. Method: We searched seven databases in December 2020. Search terms were conceptualized into three groups: waiting time, cancer, and terms related to public sector. The eligibility criteria included theoretical or empirical academic articles written in English, Spanish, or Portuguese, that focused on managerial solutions to face oncological healthcare queues' dilemma. Results: The search returned 1 255 articles, and 20 were selected and analysed in this review. Results show that most of the proposals are related to the process and people dimensions. The actions related to the process dimension were mainly associated with programming new treatment pathways and integrating cancer systems. People's dimension initiatives referred mostly to task forces and groups of specialists. Some initiatives were related to implementing technological solutions and the technology dimension, mainly concerning radiotherapy devices' acquisition. Conclusion: Few studies focus on analysing actions to minimize waiting time to initiate oncological treatments. The prevalence of conceptual and illustrative case studies indicates the lack of research maturity on this theme. Future studies should focus on setting the field's theoretical foundations, considering the existing paradigms, or developing new ones. There is a need for empirical studies applying a multidisciplinary approach to face the oncological treatment waiting time challenge and proposing new and innovative initiatives.

Uterine prolapse: impact of the condition and practical advice.

Pelvic-organ prolapse is where organs such as the uterus move out of place; in some cases, they can protrude out of the body. It occurs when muscles extending from the pubic bone to the coccyx or the levator ani muscles become weak or are injured. Although it is not life-threatening, the condition can be life limiting, adversely affecting physiological processes, function and quality of life, with patients reporting years of pain, discomfort, humiliation and embarrassment. Uterine prolapse is often under-reported as women may feel resigned to a condition that is viewed as part of getting old or the menopause, or a consequence of childbirth; they may also feel embarrassed. Gynaecology has the fastest growing waiting lists of any NHS specialty, and women may wait a long time for treatment. This article focuses on uterine prolapse, management of symptoms from conservative self-help to surgical options, and includes a case study of a successful laparoscopic hysteropexy with bifurcated polypropylene mesh apical support procedure carried out by a skilled surgeon.

Heart transplantation in Mexico. 2006-2019 productivity analysis and Pan American and Iberian comparison.

INTRODUCTION: In Mexico, heart transplants (HTs) have been performed since 1988. OBJECTIVE: To review Mexican productivity in terms of HT between 2006 and 2019 and compare it with that of American and Iberian Peninsula countries. METHODS: Mexican information was collected from HT waiting lists (WL) and from the HTs carried out annually in the period, and was expressed as rates per million population (pmp); 2019 information was compared with that reported at the Pan American and Iberian levels. RESULTS: In the studied period, the rate of HTs in Mexico went from 0.12 pmp in 2006 to 0.25 pmp in 2019, with HTs accounting for between 1 and 2% of all solid organ transplants. Among 13 countries, in 2019 Mexico ranked 12th in the HT rate pmp and 11th in the rate of patients registered for the first time in the WL for a heart (0.42 pmp). Between 2016 and 2019, only one authorized Mexican center reached a volume higher than 10 HT/year. CONCLUSIONS: Given the low figures in the main indicators related to HT in Mexico, it is urgent to rethink health policies in heart failure and HT.

INTRODUCCIÓN: En México se realizan trasplantes de corazón (TC) desde 1988. OBJETIVO: Revisar la productividad mexicana en TC entre 2006 y 2019 y compararla con la de otros países americanos y de la península ibérica. MÉTODOS: Se recabó la información mexicana de las listas de espera (LE) de TC y de los TC realizados anualmente en el periodo, que se expresaron como tasas por millón de pobladores (pmp); la información de 2019 se comparó con la reportada en América y la península ibérica. RESULTADOS: En el periodo estudiado, los TC en México pasaron de 0.12 pmp en 2006 a 0.25 pmp en 2019 y representaron entre 1 y 2 % de todos los trasplantes de órganos sólidos. Entre 13 países, en 2019 México ocupó el 12° lugar en cuanto a la tasa de TC pmp y el 11° lugar en cuanto a la tasa del número de pacientes registrados por primera vez en la LE para un corazón (0.42 pmp). Entre 2016 y 2019, solo un centro mexicano autorizado alcanzó un volumen superior a 10 TC/año. CONCLUSIONES: Debido a las bajas cifras en los principales indicadores relacionados con el TC, en México urge replantear las políticas de salud en insuficiencia cardiaca y TC.

Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation.

OBJECTIVE: The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTATs) for critical findings in chest radiographs (CXRs). Furthermore, we investigate a method to counteract the effect of false negative predictions by AI-resulting in an extremely and dangerously long RTAT, as CXRs are sorted to the end of the worklist. METHODS: We developed a simulation framework that models the current workflow at a university hospital by incorporating hospital-specific CXR generation rates and reporting rates and pathology distribution. Using this, we simulated the standard worklist processing "first-in, first-out" (FIFO) and compared it with a worklist prioritization based on urgency. Examination prioritization was performed by the AI, classifying eight different pathological findings ranked in descending order of urgency: pneumothorax, pleural effusion, infiltrate, congestion, atelectasis, cardiomegaly, mass, and foreign object. Furthermore, we introduced an upper limit for the maximum waiting time, after which the highest urgency is assigned to the examination. RESULTS: The average RTAT for all critical findings was significantly reduced in all prioritization simulations compared to the FIFO simulation (e.g., pneumothorax: 35.6 min vs. 80.1 min; p < 0.0001), while the maximum RTAT for most findings increased at the same time (e.g., pneumothorax: 1293 min vs 890 min; p < 0.0001). Our "upper limit" substantially reduced the maximum RTAT in all classes (e.g., pneumothorax: 979 min vs. 1293 min/1178 min; p < 0.0001). CONCLUSION: Our simulations demonstrate that smart worklist prioritization by AI can reduce the average RTAT for critical findings in CXRs while maintaining a small maximum RTAT as FIFO. KEY POINTS: • Development of a realistic clinical workflow simulator based on empirical data from a hospital allowed precise assessment of smart worklist prioritization using artificial intelligence. • Employing a smart worklist prioritization without a threshold for maximum waiting time runs the risk of false negative predictions of the artificial intelligence greatly increasing the report turnaround time. • Use of a state-of-the-art convolution neural network can reduce the average report turnaround time almost to the upper limit of a perfect classification algorithm (e.g., pneumothorax: 35.6 min vs. 30.4 min).