Minimizing population health loss due to scarcity in OR capacity: validation of quality of life input.

OBJECTIVES: A previously developed decision model to prioritize surgical procedures in times of scarce surgical capacity used quality of life (QoL) primarily derived from experts in one center. These estimates are key input of the model, and might be more context-dependent than the other input parameters (age, survival). The aim of this study was to validate our model by replicating these QoL estimates. METHODS: The original study estimated QoL of patients in need of commonly performed procedures in live expert-panel meetings. This study replicated this procedure using a web-based Delphi approach in a different hospital. The new QoL scores were compared with the original scores using mixed effects linear regression. The ranking of surgical procedures based on combined QoL values from the validation and original study was compared to the ranking based solely on the original QoL values. RESULTS: The overall mean difference in QoL estimates between the validation study and the original study was - 0.11 (95% CI: -0.12 - -0.10). The model output (DALY/month delay) based on QoL data from both studies was similar to the model output based on the original data only: The Spearman's correlation coefficient between the ranking of all procedures before and after including the new QoL estimates was 0.988. DISCUSSION: Even though the new QoL estimates were systematically lower than the values from the original study, the ranking for urgency based on health loss per unit of time delay of procedures was consistent. This underscores the robustness and generalizability of the decision model for prioritization of surgical procedures.

US and Dutch Perspectives on the Use of COVID-19 Clinical Prediction Models: Findings from a Qualitative Analysis.

INTRODUCTION: Clinical prediction models (CPMs) for coronavirus disease 2019 (COVID-19) may support clinical decision making, treatment, and communication. However, attitudes about using CPMs for COVID-19 decision making are unknown. METHODS: Online focus groups and interviews were conducted among health care providers, survivors of COVID-19, and surrogates (i.e., loved ones/surrogate decision makers) in the United States and the Netherlands. Semistructured questions explored experiences about clinical decision making in COVID-19 care and facilitators and barriers for implementing CPMs. RESULTS: In the United States, we conducted 4 online focus groups with 1) providers and 2) surrogates and survivors of COVID-19 between January 2021 and July 2021. In the Netherlands, we conducted 3 focus groups and 4 individual interviews with 1) providers and 2) surrogates and survivors of COVID-19 between May 2021 and July 2021. Providers expressed concern about CPM validity and the belief that patients may interpret CPM predictions as absolute. They described CPMs as potentially useful for resource allocation, triaging, education, and research. Several surrogates and people who had COVID-19 were not given prognostic estimates but believed this information would have supported and influenced their decision making. A limited number of participants felt the data would not have applied to them and that they or their loved ones may not have survived, as poor prognosis may have suggested withdrawal of treatment. CONCLUSIONS: Many providers had reservations about using CPMs for people with COVID-19 due to concerns about CPM validity and patient-level interpretation of the outcome predictions. However, several people who survived COVID-19 and their surrogates indicated that they would have found this information useful for decision making. Therefore, information provision may be needed to improve provider-level comfort and patient and surrogate understanding of CPMs. HIGHLIGHTS: While clinical prediction models (CPMs) may provide an objective means of assessing COVID-19 prognosis, provider concerns about CPM validity and the interpretation of CPM predictions may limit their clinical use.Providers felt that CPMs may be most useful for resource allocation, triage, research, or educational purposes for COVID-19.Several survivors of COVID-19 and their surrogates felt that CPMs would have been informative and may have aided them in making COVID-19 treatment decisions, while others felt the data would not have applied to them.

Prognostic models for COVID-19 needed updating to warrant transportability over time and space.

BACKGROUND: Supporting decisions for patients who present to the emergency department (ED) with COVID-19 requires accurate prognostication. We aimed to evaluate prognostic models for predicting outcomes in hospitalized patients with COVID-19, in different locations and across time. METHODS: We included patients who presented to the ED with suspected COVID-19 and were admitted to 12 hospitals in the New York City (NYC) area and 4 large Dutch hospitals. We used second-wave patients who presented between September and December 2020 (2137 and 3252 in NYC and the Netherlands, respectively) to evaluate models that were developed on first-wave patients who presented between March and August 2020 (12,163 and 5831). We evaluated two prognostic models for in-hospital death: The Northwell COVID-19 Survival (NOCOS) model was developed on NYC data and the COVID Outcome Prediction in the Emergency Department (COPE) model was developed on Dutch data. These models were validated on subsequent second-wave data at the same site (temporal validation) and at the other site (geographic validation). We assessed model performance by the Area Under the receiver operating characteristic Curve (AUC), by the E-statistic, and by net benefit. RESULTS: Twenty-eight-day mortality was considerably higher in the NYC first-wave data (21.0%), compared to the second-wave (10.1%) and the Dutch data (first wave 10.8%; second wave 10.0%). COPE discriminated well at temporal validation (AUC 0.82), with excellent calibration (E-statistic 0.8%). At geographic validation, discrimination was satisfactory (AUC 0.78), but with moderate over-prediction of mortality risk, particularly in higher-risk patients (E-statistic 2.9%). While discrimination was adequate when NOCOS was tested on second-wave NYC data (AUC 0.77), NOCOS systematically overestimated the mortality risk (E-statistic 5.1%). Discrimination in the Dutch data was good (AUC 0.81), but with over-prediction of risk, particularly in lower-risk patients (E-statistic 4.0%). Recalibration of COPE and NOCOS led to limited net benefit improvement in Dutch data, but to substantial net benefit improvement in NYC data. CONCLUSIONS: NOCOS performed moderately worse than COPE, probably reflecting unique aspects of the early pandemic in NYC. Frequent updating of prognostic models is likely to be required for transportability over time and space during a dynamic pandemic.

Minimising population health loss in times of scarce surgical capacity: a modelling study for surgical procedures performed in nonacademic hospitals.

BACKGROUND: The burden of the COVID-19 pandemic resulted in a reduction of available health care capacity for regular care. To guide prioritisation of semielective surgery in times of scarcity, we previously developed a decision model to quantify the expected health loss due to delay of surgery, in an academic hospital setting. The aim of this study is to validate our decision model in a nonacademic setting and include additional elective surgical procedures. METHODS: In this study, we used the previously published three-state cohort state-transition model, to evaluate the health effects of surgery postponement for 28 surgical procedures commonly performed in nonacademic hospitals. Scientific literature and national registries yielded nearly all input parameters, except for the quality of life (QoL) estimates which were obtained from experts using the Delphi method. Two expert panels, one from a single nonacademic hospital and one from different nonacademic hospitals in the Netherlands, were invited to estimate QoL weights. We compared estimated model results (disability adjusted life years (DALY)/month of surgical delay) based on the QoL estimates from the two panels by calculating the mean difference and the correlation between the ranks of the different surgical procedures. The eventual model was based on the combined QoL estimates from both panels. RESULTS: Pacemaker implantation was associated with the most DALY/month of surgical delay (0.054 DALY/month, 95% CI: 0.025-0.103) and hemithyreoidectomy with the least DALY/month (0.006 DALY/month, 95% CI: 0.002-0.009). The overall mean difference of QoL estimates between the two panels was 0.005 (95% CI -0.014-0.004). The correlation between ranks was 0.983 (p < 0.001). CONCLUSIONS: Our study provides an overview of incurred health loss due to surgical delay for surgeries frequently performed in nonacademic hospitals. The quality of life estimates currently used in our model are robust and validate towards a different group of experts. These results enrich our earlier published results on academic surgeries and contribute to prioritising a more complete set of surgeries.

Randomized Evaluation of Surgery in Elderly with Traumatic Acute SubDural Hematoma (RESET-ASDH trial): study protocol for a pragmatic randomized controlled trial with multicenter parallel group design.

BACKGROUND: The rapidly increasing number of elderly (≥ 65 years old) with TBI is accompanied by substantial medical and economic consequences. An ASDH is the most common injury in elderly with TBI and the surgical versus conservative treatment of this patient group remains an important clinical dilemma. Current BTF guidelines are not based on high-quality evidence and compliance is low, allowing for large international treatment variation. The RESET-ASDH trial is an international multicenter RCT on the (cost-)effectiveness of early neurosurgical hematoma evacuation versus initial conservative treatment in elderly with a t-ASDH METHODS: In total, 300 patients will be recruited from 17 Belgian and Dutch trauma centers. Patients ≥ 65 years with at first presentation a GCS ≥ 9 and a t-ASDH > 10 mm or a t-ASDH < 10 mm and a midline shift > 5 mm, or a GCS < 9 with a traumatic ASDH < 10 mm and a midline shift < 5 mm without extracranial explanation for the comatose state, for whom clinical equipoise exists will be randomized to early surgical hematoma evacuation or initial conservative management with the possibility of delayed secondary surgery. When possible, patients or their legal representatives will be asked for consent before inclusion. When obtaining patient or proxy consent is impossible within the therapeutic time window, patients are enrolled using the deferred consent procedure. Medical-ethical approval was obtained in the Netherlands and Belgium. The choice of neurosurgical techniques will be left to the discretion of the neurosurgeon. Patients will be analyzed according to an intention-to-treat design. The primary endpoint will be functional outcome on the GOS-E after 1 year. Patient recruitment starts in 2022 with the exact timing depending on the current COVID-19 crisis and is expected to end in 2024. DISCUSSION: The study results will be implemented after publication and presented on international conferences. Depending on the trial results, the current Brain Trauma Foundation guidelines will either be substantiated by high-quality evidence or will have to be altered. TRIAL REGISTRATION: Nederlands Trial Register (NTR), Trial NL9012 . CLINICALTRIALS: gov, Trial NCT04648436 .

Changes in the quality of cancer care as assessed through performance indicators during the first wave of the COVID-19 pandemic in 2020: a scoping review.

BACKGROUND: Cancer comprises a high burden on health systems. Performance indicators monitoring cancer outcomes are routinely used in OECD countries. However, the development of process and cancer-pathway based information is essential to guide health care delivery, allowing for better monitoring of changes in the quality of care provided. Assessing the changes in the quality of cancer care during the COVID-19 pandemic requires a structured approach considering the high volume of publications. This study aims to summarize performance indicators used in the literature to evaluate the impact of the COVID-19 pandemic on cancer care (January-June 2020) in OECD countries and to assess changes in the quality of care as reported via selected indicators. METHODS: Search conducted in MEDLINE and Embase databases. Performance indicators and their trends were collated according to the cancer care pathway. RESULTS: This study included 135 articles, from which 1013 indicators were retrieved. Indicators assessing the diagnostic process showed a decreasing trend: from 33 indicators reporting on screening, 30 (91%) signalled a decrease during the pandemic (n = 30 indicators, 91%). A reduction was also observed in the number of diagnostic procedures (n = 64, 58%) and diagnoses (n = 130, 89%). The proportion of diagnoses in the emergency setting and waiting times showed increasing trends (n = 8, 89% and n = 14, 56%, respectively). A decreasing trend in the proportion of earliest stage cancers was reported by 63% of indicators (n = 9), and 70% (n = 43) of indicators showed an increasing trend in the proportion of advanced-stage cancers. Indicators reflecting the treatment process signalled a reduction in the number of procedures: 79%(n = 82) of indicators concerning surgeries, 72%(n = 41) of indicators assessing radiotherapy, and 93%(n = 40) of indicators related to systemic therapies. Modifications in cancer treatment were frequently reported: 64%(n = 195) of indicators revealed changes in treatment. CONCLUSIONS: This study provides a summary of performance indicators used in the literature to assess the cancer care pathway from January 2020 to June 2020 in OECD countries, and the changes in the quality of care signalled by these indicators. The trends reported inform on potential bottlenecks of the cancer care pathway. Monitoring this information closely could contribute to identifying moments for intervention during crises.

International Validation of the Erasmus Guillain-Barré Syndrome Respiratory Insufficiency Score.

OBJECTIVE: This study aimed to validate the Erasmus Guillain-Barré Syndrome Respiratory Insufficiency Score in the International Guillain-Barré Syndrome Outcome Study cohort, and to improve its performance and region-specificity. METHODS: We examined data from the first 1,500 included patients, aged ≥6 years and not ventilated prior to study entry. Patients with a clinical variant or mild symptoms were also included. Outcome was mechanical ventilation within the first week from study entry. Model performance was assessed regarding the discriminative ability (area under the receiver operating characteristic curve) and the calibration (observed vs predicted probability of mechanical ventilation), in the full cohort and in Europe/North America and Asia separately. We recalibrated the model to improve its performance and region-specificity. RESULTS: In the group of 1,023 eligible patients (Europe/North America n = 842, Asia n = 104, other n = 77), 104 (10%) required mechanical ventilation within the first week from study entry. Area under the curve values were ≥0.80 for all validation subgroups. Mean observed proportions of mechanical ventilation were lower than predicted risks: full cohort 10% versus 21%, Europe/North America 9% versus 21%, and Asia 17% versus 23%. After recalibration, predicted risks for the full cohort and Europe/North America corresponded to observed proportions. INTERPRETATION: This prospective, international cohort study validated the Erasmus Guillain-Barré Syndrome Respiratory Insufficiency Score, and showed that the model can be used in the full spectrum of Guillain-Barré syndrome patients. In addition, a more accurate, region-specific version of the model was developed for patients from Europe/North America. ANN NEUROL 2022;91:521-531.

The Impact of the COVID-19 Pandemic on Hospital Services for Patients with Cardiac Diseases: A Scoping Review.

This study aims to assess the impact of the COVID-19 pandemic on hospital cardiac care, as assessed by performance indicators. Scoping review methodology: performance indicators were extracted to inform on changes in care during January-June 2020. Database searches yielded 6277 articles, of which 838 met the inclusion criteria. After full-text screening, 94 articles were included and 1637 indicators were retrieved. Most of the indicators that provided information on changes in the number of admissions (n = 118, 88%) signaled a decrease in admissions; 88% (n = 15) of the indicators showed patients' delayed presentation and 40% (n = 54) showed patients in a worse clinical condition. A reduction in diagnostic and treatment procedures was signaled by 95% (n = 18) and 81% (n = 64) of the indicators, respectively. Length of stay decreased in 58% (n = 21) of the indicators, acute coronary syndromes treatment times increased in 61% (n = 65) of the indicators, and outpatient activity decreased in 94% (n = 17) of the indicators related to outpatient care. Telehealth utilization increased in 100% (n = 6). Outcomes worsened in 40% (n = 35) of the indicators, and mortality rates increased in 52% (n = 31). All phases of the pathway were affected. This information could support the planning of care during the ongoing pandemic and in future events.

Minimizing Population Health Loss in Times of Scarce Surgical Capacity During the Coronavirus Disease 2019 Crisis and Beyond: A Modeling Study.

OBJECTIVES: Coronavirus disease 2019 has put unprecedented pressure on healthcare systems worldwide, leading to a reduction of the available healthcare capacity. Our objective was to develop a decision model to estimate the impact of postponing semielective surgical procedures on health, to support prioritization of care from a utilitarian perspective. METHODS: A cohort state-transition model was developed and applied to 43 semielective nonpediatric surgical procedures commonly performed in academic hospitals. Scenarios of delaying surgery from 2 weeks were compared with delaying up to 1 year and no surgery at all. Model parameters were based on registries, scientific literature, and the World Health Organization Global Burden of Disease study. For each surgical procedure, the model estimated the average expected disability-adjusted life-years (DALYs) per month of delay. RESULTS: Given the best available evidence, the 2 surgical procedures associated with most DALYs owing to delay were bypass surgery for Fontaine III/IV peripheral arterial disease (0.23 DALY/month, 95% confidence interval [CI]: 0.13-0.36) and transaortic valve implantation (0.15 DALY/month, 95% CI: 0.09-0.24). The 2 surgical procedures with the least DALYs were placing a shunt for dialysis (0.01, 95% CI: 0.005-0.01) and thyroid carcinoma resection (0.01, 95% CI: 0.01-0.02). CONCLUSION: Expected health loss owing to surgical delay can be objectively calculated with our decision model based on best available evidence, which can guide prioritization of surgical procedures to minimize population health loss in times of scarcity. The model results should be placed in the context of different ethical perspectives and combined with capacity management tools to facilitate large-scale implementation.