Search

Aims: We aimed to confirm that three-dimensional echocardiography–derived right ventricular ejection fraction (RVEF) is better associated with adverse cardiopulmonary outcomes than the conventional echocardiographic parameters. Methods: We performed a meta-analysis of studies reporting the impact of unit change of RVEF, tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), and free-wall longitudinal strain (FWLS) on clinical outcomes (all-cause mortality and/or adverse cardiopulmonary outcomes). Hazard ratios (HRs) were rescaled by the within-study SDs to represent standardized changes. Within each study, we calculated the ratio of HRs related to a 1 SD reduction in RVEF versus TAPSE, or FAC, or FWLS, to quantify the association of RVEF with adverse outcomes relative to the other metrics. These ratios of HRs were pooled using random-effects models. Results: Ten independent studies were identified as suitable, including data on 1,928 patients with various cardiopulmonary conditions. Overall, a 1 SD reduction in RVEF was robustly associated with adverse outcomes (HR = 2.64 [95% CI, 2.18-3.20], P < .001; heterogeneity: I 2 = 65%, P = .002). In studies reporting HRs for RVEF and TAPSE, or RVEF and FAC, or RVEF and FWLS in the same cohort, head-to-head comparison revealed that RVEF showed significantly stronger association with adverse outcomes per SD reduction versus the other 3 parameters (vs TAPSE, HR = 1.54 [95% CI, 1.04-2.28], P = .031; vs FAC, HR = 1.45 [95% CI, 1.15-1.81], P = .001; vs FWLS, HR = 1.44 [95% CI, 1.07-1.95], P = .018). Conclusion: Reduction in three-dimensional echocardiography–derived RVEF shows stronger association with adverse clinical outcomes than conventional right ventricular functional indices; therefore, it might further refine the risk stratification of patients with cardiopulmonary diseases.

OBJECTIVE: To estimate the risk of an avoidable adverse event for high‐need patients in England and Germany and the causal impact that has on outcomes. DATA SOURCES: We use administrative, secondary data for all hospital inpatients in 2018. Patient records for the English National Health Service are provided by the Hospital Episode Statistics database and for the German health care system accessed through the Research Data Center of the Federal Statistical Office. STUDY DESIGN: We calculated rates of three hospital‐acquired adverse events and their causal impact on mortality and length of stay through propensity score matching and estimation of average treatment effects. DATA COLLECTION/EXTRACTION METHODS: Patients were identified based on diagnoses codes and translated Patient Safety Indicators developed by the Agency for Healthcare Research and Quality. PRINCIPAL FINDINGS: For the average hospital stay, the risk of an adverse event was 5.37% in the English National Health Service and 3.26% in the German health care system. High‐need patients are more likely to experience an adverse event, driven by hospital‐acquired infections (2.06%–4.45%), adverse drug reactions (2.37%–2.49%), and pressure ulcers (2.25%–0.45%). Adverse event risk is particularly high for patients with advancing illnesses (10.50%–27.11%) and the frail elderly (17.75%–28.19%). Compared to the counterfactual, high‐need patients with an adverse event are more likely to die during their hospital stay and experience a longer length of stay. CONCLUSIONS: High‐need patients are particularly vulnerable with an adverse event risking further deterioration of health status and adding resource use. Our results indicate the need to assess the costs and benefits of a hospital stay, particularly when care could be provided in settings considered less hazardous.

AimsWe aimed to confirm that three-dimensional echocardiography (3DE)-derived right ventricular (RV) ejection fraction (EF) is a more robust predictor of adverse cardiopulmonary outcomes than the conventional echocardiographic parameters.Methods and ResultsWe performed a meta-analysis of studies reporting the impact of unit change of RVEF, tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), and free-wall longitudinal strain (FWLS) on clinical outcomes (all-cause mortality and/or adverse cardiopulmonary outcomes). Hazard ratios (HR) were rescaled by the within-study standard deviations (SD) to represent standardized changes. Within each study, we calculated the ratio of HRs related to 1 SD reduction in RVEF versus TAPSE, or FAC, or FWLS, to quantify the predictive value of RVEF relative to the other metrics. These ratios of HRs were pooled using random-effects models.Ten independent studies were identified as suitable, including data on 1,928 patients with various cardiopulmonary conditions. Overall, 1 SD reduction in RVEF was robustly associated with adverse outcomes (HR: 2.64 [95% CI: 2.18 to 3.20], p2=65%, p=0.002). In studies reporting HRs for RVEF and TAPSE, FAC, or FWLS in the same cohort, RVEF had superior predictive value per SD reduction versus the other three parameters (vs. TAPSE, HR: 1.54 [95% CI: 1.04 to 2.28], p=0.031; vs. FAC, HR: 1.45 [95% CI: 1.15 to 1.81], p=0.001; vs. FWLS, HR: 1.44 [95% CI: 1.07 to 1.95], p=0.018).Conclusion3DE-derived RVEF has superior prognostic value compared with conventional RV indices, therefore, it might further refine the risk stratification of patients with cardiopulmonary diseases.Graphical AbstractAdded predictive value of three-dimensional (3D) echocardiography-derived right ventricular ejection fraction (RVEF) versus conventional metrics of RV systolic function on clinical outcomes: a meta-analysis of 10 studies. FAC: fractional area change, FWLS: free-wall longitudinal strain, HR: hazard ratio, SD: standard deviation, TAPSE: tricuspid annular plane systolic excursion

Opioid abuse has become a public health concern among many developed countries, with policymakers searching for strategies to mitigate adverse effects on population health and the wider economy. The United Kingdom has seen dramatic increases in opioid-related mortality following the financial crises in 2008. We examine the impact of spending cuts resulting from government prescribed austerity measures on opioid-related hospitalisations and mortality, thereby expanding on existing evidence suggesting a countercyclical relationship with macroeconomic performance. We take advantage of the variation in spending cuts passed down from central government to local authorities since 2010, with reductions in budgets of up to fifty percent in some areas resulting in the rescaling of vital public services. Longitudinal panel data methods are used to analyse a comprehensive, linked dataset that combines information from spending records, official death registry data and large administrative health care data for 152 local authorities (i.e., unitary authorities and county councils) in England between April 2010 and March 2017. A total of 280,827 people experienced a hospital admission in the English National Health Service because of an opioid overdose and 14,700 people died from opioids across the study period. Local authorities that experienced largest spending cuts also saw largest increases in opioid abuse. Interactions between changes in unemployment and spending items for welfare programmes show evidence about the importance for governments to protect populations from social-risk effects at times of deteriorating macroeconomic performance. Our study carries important lessons for countries aiming to address high rates of opioid abuse, including the United States, Canada and Sweden.

Opposition to Universal Basic Income (UBI) is encapsulated by Martinelli’s claim that ‘an affordable basic income would be inadequate, and an adequate basic income would be unaffordable’. In this article, we present a model of health impact that transforms that assumption. We argue that UBI can affect higher level social determinants of health down to individual determinants of health and on to improvements in public health that lead to a number of economic returns on investment. Given that no trial has been designed and deployed with that impact in mind, we present a methodological framework for assessing prospective costs and returns on investment through modelling to make the case for that trial. We begin by outlining the pathways to health in our model of change in order to present criteria for establishing the size of transfer capable of promoting health. We then consider approaches to calculating cost in a UK context to estimate budgetary burdens that need to be met by the state. Next, we suggest means of modelling the prospective impact of UBI on health before asserting means of costing that impact, using a microsimulation approach. We then outline a set of fiscal options for funding any shortfall in returns. Finally, we suggest that fiscal strategy can be designed specifically with health impact in mind by modelling the impact of reform on health and feeding that data cyclically back into tax transfer module of the microsimulation.

Background Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. Methods In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. Findings Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. Interpretation Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Funding British Heart Foundation Data Science Centre, led by Health Data Research UK.

Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): National Institute for Health Research (NIHR) Biomedical Research Centre at St Bartholomew"s Hospital London. Irish Cardiac Society OnBehalf European Association of Cardiovascular Imaging (EACVI) -Task Force for Cost Effectiveness. Background Acute presentations with myocardial injury that occur despite culprit-free coronary angiography were first reported over 70 years ago, with a prevalence between 5-9%. 1-3 There is increasing evidence that a more accurate diagnosis is available and that CMR is a key tool to determine the underlying pathology. This is reflected with the most recent international guidelines advocating for the use of CMR in the diagnostic pathways of this heterogeneous population. However, to date there is no formal assessment of the financial implications of adopting these new guidelines. Purpose To determine the financial impact of implementing cardiac magnetic resonance imaging in the diagnostic pathway of a population with unexplained acute myocardial injury and normal coronary angiography in comparison to existing clinical practice. Methods We performed a focused cost-benefit analysis using a hypothetical population of 2,000 patients with unexplained acute myocardial injury and normal coronary angiography. The population was split evenly into two groups of either standard, or CMR guided management, and extrapolated over a ten-year period. Standard management was defined as 66% of the population receiving dual antiplatelet therapy (ticagrelor and aspirin) for one year followed by aspirin for life, and the remaining 34% of the population receiving aspirin for life. CMR guided management determined antiplatelet therapy according to the imaging findings. This analysis focused on CMR’s ability to accurately identify those patients who may have had an MI and facilitate tailored treatment with evidence based dual antiplatelet therapy. Costs and rates were defined in Table 1. A one-way sensitivity analysis was also performed to determine the variables with largest impact on the costs. Each variable was varied by +/- 20% and the change in cost determined at year 10. Results Using CMR in the diagnostic pathway resulted in an increased cost of £72,656 in the first year. After year 7, CMR guided practice becomes cost neutral, resulting in cost saving of £24,054 over a ten-year period in a population of 1000 patients. Figure 1. Utilizing CMR in this population also resulted in 7 fewer myocardial infarctions and 14 fewer major bleeding events over a ten-year time horizon. The three most sensitive variables were, in decreasing order, the cost of CMR, the cost of ticagrelor and the percentage of the population with MI requiring DAPT. A 20% change from baseline resulted in a 320%, 247% and 162% change in costs at 10 years, respectively. Conclusion Utilizing CMR in this population may be associated with reduced costs in the medium to long term. The initial increased cost of CMR is offset over time, by delivering a more personalised, higher quality level of care to patients.

Background Global budget payments (GBP) are considered effective in containing health care expenditures; however, information on their impact on quality of cardiovascular care is limited. We aimed to evaluate the effects of GBP on utilization, outcomes, and costs for 3 major cardiovascular conditions. Methods We analyzed claims data of hospital admissions in Maryland from fiscal year 2013 to 2018. Using segmented regression, we evaluated temporal trends in hospitalizations, length of stay, percutaneous coronary intervention and coronary artery bypass grafting volumes, case mix-adjusted 30-day readmission rates, risk-standardized mortality rates, and hospitalization charges in patients with principal diagnosis of heart failure, acute ischemic stroke, and acute myocardial infarction (AMI) in relation to GBP implementation. Trends in global cardiovascular procedure charges/volumes were also studied. Results Hospitalization rates for congestive heart failure and AMI remained unaffected by GBP, while the gradient of ischemic stroke admissions decreased ( P trend P trend =0.03). Inpatient coronary artery bypass grafting surgeries decreased ( P trend P trend =0.0069). There were no significant changes in mortality for any of the 3 conditions. Hospitalization charges increased for ischemic stroke ( P trend P trend =0.1), and decreased for AMI ( P trend =0.0005). We observed a significant increase in electrocardiography rate charges ( P trend P trend =0.0003). Conclusions Introducing GBP in Maryland had no perceivable adverse effects on inpatient outcomes and quality indicators for 3 major cardiovascular conditions. Savings were observed in the AMI cohort, possibly due to reduced unnecessary readmissions, efficiency improvements, or shifts to outpatient care. Reduced cardiovascular procedure volumes were counterbalanced by a proportional rise in charges. State-level adoption of GBP with pay-for-performance incentives may be effective for cost containment without adversely impacting quality of cardiovascular care.

Background: Non-invasive Cardiovascular imaging (NICI), including cardiovascular magnetic resonance (CMR) imaging provides important information to guide the management of patients with cardiovascular conditions. Current rates of NICI use and potential policy determinants in the United States of America (US) and England remain unexplored.Methods: We compared NICI activity in the US (Medicare fee-for-service, 2011–2015) and England (National Health Service, 2012–2016). We reviewed recommendations related to CMR from Clinical Practice Guidelines, Appropriate Use Criteria (AUC), and Choosing Wisely. We then categorized recommendations according to whether CMR was the only recommended NICI technique (substitutable indications). Reimbursement policies in both settings were systematically collated and reviewed using publicly available information.Results: The 2015 rate of NICI activity in the US was 3.1 times higher than in England (31,055 vs. 9,916 per 100,000 beneficiaries). The proportion of CMR of all NICI was small in both jurisdictions, but nuclear cardiac imaging was more frequent in the US in absolute and relative terms. American and European CPGs were similar, both in terms of number of recommendations and proportions of indications where CMR was not the only recommended NICI technique (substitutable indications). Reimbursement schemes for NICI activity differed for physicians and hospitals between the two settings.Conclusions: Fee-for-service physician compensation in the US for NICI may contribute to higher NICI activity compared to England where physicians are salaried. Reimbursement arrangements for the performance of the test may contribute to the higher proportion of nuclear cardiac imaging out of the total NICI activity. Differences in CPG recommendations appear not to explain the variation in NICI activity between the US and England.

Background: Global budgets (GB), an innovative method of hospital payment, have been considered effective in containing expenditures. In January 2014, the state of Maryland introduced Global Budget Revenues (GBR), transitioning from per case to capitated, population-based payments (PBP). Under this model, hospitals are provided yearly funds, thus being financially incentivized to improve efficiency of services. Prices are set by the Health Services Cost Review Commission (HSCRC), which collects data and monitors hospitals’ quality of care. Potential adverse incentives of GB would include underprovision of necessary services or avoiding sicker, high cost patients (cream skimming). This study aimed to evaluate the effects of GBR on the care of hospitalized patients with important CV conditions. Methods: We analyzed HSCRC inpatient claim databases containing anonymized information on statewide hospital admissions between fiscal years 2013 and 2018. Using ICD codes, we identified patients with a principal diagnosis of heart failure (CHF), acute myocardial infarction (AMI), and acute ischemic stroke (AIS) from a pool of 1,959,237 inpatient admissions. Outcome measures were: hospitalizations, length of stay (LOS), inpatient PCI and CABG procedure rates, casemix adjusted 30-day readmission rates (CARR), risk standardized in-hospital mortality, and hospitalization charges. Trends in outcome measures before and after GBR implementation were compared using segmented regression analysis, with p values indicating trend change. Results: With introduction of GBR, CHF and AMI hospitalization trends did not change significantly, whereas AIS admissions stabilized downward (p Conclusions: Adoption of GBR in Maryland had no harmful effects on in-hospital outcomes and quality measures. There was a modest improvement in potentially avoidable hospitalizations and mildly reduced utilization offset by significant rise in charges. Some observations could result from care shifts to the outpatient setting. Quality of CV care was not affected by GBR suggesting that efficiency improvements might have occurred in other areas of the healthcare system. Additionally, combining GB with pay for performance programs and assiduous quality monitoring might have mitigated adverse incentives. As GBR transitions to Maryland Total Cost of Care, long-term effects of PBP on CV outcomes will require further investigation.

The English National Health Service (NHS) has failed to meet the four-hour waiting time target to admit, transfer or discharge 95 per cent of patients attending Accident and Emergency Departments (A&E) since 2013. A growing number of patients requiring inpatient care are waiting on trolleys longer than four hours before admission to a hospital bed. This study examines the role of bed occupancy in the deterioration of A&E performance in the NHS. Longitudinal panel data methods are used to analyse hospital data (n = 72,129,886) for 143 Trusts from 1st June 2016 to 31st October 2019. The average bed occupancy rate across the study period was 93.2%. A 1% increase in bed occupancy was associated with a 9.5 percentage point decrease in the Trusts’ probabilitay of meeting the waiting target, and an approximately 6 patient increase in four hours to 12 -hs trolley waits per 1,000 admissions. These relationships became more pronounced with rising bed occupancy levels above a 90% threshold. Bed occupancy is associated with significant negative spill-over effects on A&E performance. We estimate a minimum investment in 3,861 additional inpatient beds across the NHS to improve A&E performance in England. Relevant lessons can be derived for health care systems that have observed similar trends in increasing bed occupancy and deteriorations in A&E performance, including Ireland, Canada and Israel.

The bundling of clinical expertise in centralised treatment centres is considered an effective intervention to improve quality and efficiency of acute stroke care. In 2010, 8 London Trusts were converted into Hyper Acute Stroke Units. The intention was to discontinue acute stroke services in 22 London hospitals. However, in reality, provision of services declined only gradually, and 2 years later, 15% of all patients were still treated in Trusts without a Hyper Acute Stroke Unit. This study evaluates the impact of centralising London's stroke care on 7 process and outcome indicators using a difference-in-difference analysis with two treatment groups, Hyper Acute and discontinued London Trusts, and data on all stroke patients recorded in the hospital episode statistics database from April 2006 to April 2014. The policy resulted in improved thrombolysis treatment and lower rates of pneumonia in acute units. However, 6 indicators worsened in the Trusts that were meant to discontinue services, including deaths within 7 and 30 days, readmissions, brain scan rates, and thrombolysis treatment. The reasons for these results are difficult to uncover and could be related to differences in patient complexity, data recording, or quality of care. The findings highlight that actual implementation of centralisation policies needs careful monitoring and evaluation.

Hospital bed occupancy rates in the English National Health Service have risen to levels considered clinically unsafe. This study assesses the association of increased bed occupancy with changes in the percentage of overnight patients discharged from hospital on a given day, and their subsequent 30-day readmission rate. Longitudinal panel data methods are used to analyse secondary care records (n = 4,193,590) for 136 non-specialist Trusts between April 2014 and February 2016. The average bed occupancy rate across the study period was 90.4%. A 1% increase in bed occupancy was associated with a 0.49% rise in the discharge rate, and a 0.011% increase in the 30-day readmission rate for discharged patients. These associations became more pronounced once bed occupancy exceeded 95%. When bed occupancy rates were high, hospitals discharged a greater proportion of their patients. Those were mostly younger and less clinically complex, suggesting that hospitals are successfully prioritising early discharge amongst least vulnerable patients. However, while increased bed occupancy was not associated with a substantial increase in overall 30-day readmission rates, the relationship was more pronounced in older and sicker patients, indicating possible links with short-fallings in discharge processes.

Since its inception in 2002, the Global Fund to Fight AIDS, Tuberculosis and Malaria (the Global Fund) has disbursed more than US$39 billion across 120 countries. Funding provided by donors, mainly the USA, France, the UK, Germany, and Japan, has undoubtedly affected the lives of millions of people. As the Global Fund approaches its Sixth Replenishment Conference—to be held in France in October, 2019—the recently published results report1 appears to make a compelling case for further investment.

Governments across low-income and middle-income countries have pledged to achieve universal health coverage by 2030, which comes at a time where healthcare systems are subjected to multiple and persistent pressures, such as poor access to care services and insufficient medical supplies. While the political willingness to provide universal health coverage is a step into the right direction, the benefits of it will depend on the quality of healthcare services provided. In thisanalysis paper, we ask whether there are any lessons that could be learnt from the English National Health Service, a healthcare system that has been providing comprehensive and high-quality universal health coverage for over 70 years. The key areas identified relate to the development of a coherent strategy to improve quality, to boost public health as a measure to reduce disease burden, to adopt evidence-based priority setting methods that ensure efficient spending of financial resources, to introduce an independent way of inspecting and regulating providers, and to allow for task-shifting, specifically in regions where staff retention is low.

All healthcare systems show variation in the quality of care provided, whether that means access to primary care services,1 ambulance response times,2 Accident & Emergency waiting times3 or treatment processes and outcomes.4–6 Monitoring this variation in quality can serve multiple purposes: informing patients about where best to seek care;7 allowing clinicians to compare their performance with that of their peers and thus identify targets for local-level quality improvement efforts, and supporting the development of national policy. Though, what all these have in common is a trust in the reliability of the data to adequately reflect healthcare quality—sometimes a questionable assumption. In BMJ Quality and Safety , Hofstede et al 8 have addressed a common situation where providers (such as hospitals, general practices or community teams) are ranked according to their performance on a quality indicator. Rankings are used often to make direct performance comparisons between providers and used to identify positive or negative outliers. Yet, one of the downsides of this approach is that the ranks of providers can be susceptible to chance fluctuations in the indicators. The precision of rankings, that is their reliability, therefore has to be carefully assessed when developing these kinds of approaches to reporting the quality of care. This is particularly the case when payment is linked to performance,9 or when ongoing quality improvement efforts might be undermined by measurement errors. Performance measures are driven by patient case-mix, differences in care provided and chance variation, with their accuracy to reflect on real quality variation determined by two components.10 The first is the reliability of the indicator for each healthcare provider. This component (the ‘within-provider uncertainty’) is highly dependent on the number of patients receiving the type of care in question at each provider and is likely to be …

ObjectiveTo assess trends in 30-day emergency readmission rates across England over one decade.DesignRetrospective study design.Setting150 non-specialist hospital trusts in England.Participants23 069 134 patients above 18 years of age who were readmitted following an initial admission (n=62 584 297) between April 2006 and February 2016.Primary and secondary outcomesWe examined emergency admissions that occurred within 30 days of discharge from hospital (‘emergency readmissions’) as a measure of healthcare quality. Presented are overall readmission rates, and disaggregated by the nature of the indexed admission, including whether it was elective or emergency, and by clinical health condition recorded. All rates were risk-adjusted for patient age, gender, ethnicity, socioeconomic status, comorbidities and length of stay.ResultsThe average risk-adjusted, 30-day readmission rate increased from 6.56% in 2006/2007 to 6.76% (PConclusionsOverall, emergency readmission rates in England remained relatively stable across the observation period, with trends of slight increases contained post 2012/2013. However, there were large variations in trends across clinical areas, with some experiencing marked increases in readmission rates. This highlights the need to better understand variations in outcomes across clinical subgroups to allow for targeted interventions that will ensure highest standards of care provided for all patients.