Undertaking multi-centre randomised controlled trials in primary care: learnings and recommendations from the PULsE-AI trial researchers.

BACKGROUND: Conducting effective and translational research can be challenging and few trials undertake formal reflection exercises and disseminate learnings from them. Following completion of our multicentre randomised controlled trial, which was impacted by the COVID-19 pandemic, we sought to reflect on our experiences and share our thoughts on challenges, lessons learned, and recommendations for researchers undertaking or considering research in primary care. METHODS: Researchers involved in the Prediction of Undiagnosed atriaL fibrillation using a machinE learning AlgorIthm (PULsE-AI) trial, conducted in England from June 2019 to February 2021 were invited to participate in a qualitative reflection exercise. Members of the Trial Steering Committee (TSC) were invited to attend a semi-structured focus group session, Principal Investigators and their research teams at practices involved in the trial were invited to participate in a semi-structured interview. Following transcription, reflexive thematic analysis was undertaken based on pre-specified themes of recruitment, challenges, lessons learned, and recommendations that formed the structure of the focus group/interview sessions, whilst also allowing the exploration of new themes that emerged from the data. RESULTS: Eight of 14 members of the TSC, and one of six practices involved in the trial participated in the reflection exercise. Recruitment was highlighted as a major challenge encountered by trial researchers, even prior to disruption due to the COVID-19 pandemic. Researchers also commented on themes such as the need to consider incentivisation, and challenges associated with using technology in trials, especially in older age groups. CONCLUSIONS: Undertaking a formal reflection exercise following the completion of the PULsE-AI trial enabled us to review experiences encountered whilst undertaking a prospective randomised trial in primary care. In sharing our learnings, we hope to support other clinicians undertaking research in primary care to ensure that future trials are of optimal value for furthering knowledge, streamlining pathways, and benefitting patients.

Estimating the Treatment and Prophylactic Economic Value of New Antimicrobials in Managing Antibiotic Resistance and Serious Infections for Common Pathogens in the USA: A Population Modelling Study.

BACKGROUND: Antimicrobial resistance is a growing public health concern. There is a global need to estimate the population-level value of developing new antimicrobials and to ensure the effective use of existing antimicrobials as strategies to counteract antimicrobial resistance. To this aim, population-level value criteria need to be considered alongside conventional value measures. OBJECTIVE: The objective of this study was to develop a novel modelling approach to estimate the value of new antimicrobials, considering the transmission, diversity and enablement elements of STEDI value. METHODS: We developed a population-based mathematical model for the assessment of antimicrobial value considering both prophylactic use of antimicrobials and the treatment of selected serious hospital-acquired infections in hospitals in the USA at a population level. Large-scale clinical and population healthcare data were used to inform a modelling-based analysis assessing the impact of introducing a new antimicrobial compared with continuing with no new antimicrobial, accounting for the transmission, diversity and enablement value of antimicrobial agents. RESULTS: Over a 10-year period, the addition of a new antimicrobial as part of an antimicrobial stewardship strategy in the USA was estimated to result in a proportional reduction of 9.03% in projected antimicrobial resistance levels. This yielded an estimated reduction of $64.3 million in hospitalization costs and a gain of over 153,000 quality-adjusted life-years at an economic value of over $15.4 billion over 10 years. Considering input uncertainty, the estimate of monetary benefit ranged from $11.1 to $21.4 billion. CONCLUSIONS: The use of a new antimicrobial for treatment and prophylactic indications yields considerable clinical and economic benefits including transmission diversity and enablement value. These findings may provide decision makers with important evidence to support investment in new antimicrobials and antimicrobial stewardship policy that address the patient, population and system burden associated with antimicrobial resistance.

Capturing Value Attributes in the Economic Evaluation of Ceftazidime with Avibactam for Treating Severe Aerobic Gram-Negative Bacterial Infections in the United Kingdom.

INTRODUCTION: Antimicrobial resistance remains a serious and growing threat to public health, both globally and in the UK, leading to diminishing effectiveness of antimicrobials. Despite a clear need for new antimicrobials, the clinical pipeline is insufficient, driven by high research and development costs and limited expected returns on investment. To counteract this, National Institute for Health and Care Excellence (NICE) and National Health Service (NHS) England have launched a reimbursement mechanism, de-linked from volume of sales, that aims to reduce economic risk by recognising the broader population-level value of antimicrobials. The objective of this study was to quantify the value of ceftazidime-avibactam for treating gram-negative infections in the UK considering some of these broader value elements unique to antimicrobials. METHODS: A previously developed dynamic disease transmission and cost-effectiveness model was applied to assess the value of introducing ceftazidime-avibactam to UK treatment practice in the management of gram-negative hospital-acquired infections in line with the licenced indications for ceftazidime-avibactam. Model inputs were parameterised using sources aligned to the UK perspective. RESULTS: The introduction of ceftazidime-avibactam into a two-line treatment sequence saved over 2300 lives, leading to a gain of 27,600 life years and 22,000 quality-adjusted life years (QALY) at an additional cost of £17 million, over a ten-year transmission period. Ceftazidime-avibactam was associated with a net monetary benefit of £642 million at willingness to pay threshold of £30,000 per QALY; even at a lower threshold of £20,000 per QALY, the net monetary benefit is £422 million. DISCUSSION: Increasing the diversity of antimicrobial treatments through the introduction of an additional antimicrobial, in this instance ceftazidime-avibactam, was associated with substantial clinical and economic benefits, when considering broader population-level value. Despite revealing considerable benefits, the value of ceftazidime-avibactam is only partially reflected in this analysis. Further efforts are required to fully operationalise the spectrum, transmission, enablement, diversity and insurance (STEDI) value framework and accurately reflect the population-level value of antimicrobials.

Clinical and Economic Value of Reducing Antimicrobial Resistance in the Management of Hospital-Acquired Infections with Limited Treatment Options in Greece.

INTRODUCTION: Antimicrobial resistance (AMR) is a major public health threat worldwide. Greece has the highest burden of infections due to antibiotic-resistant bacteria among European Union/European Economic Area (EU/EEA) countries. One of the most serious AMR threats in Greece is hospital-acquired infections (HAIs) with limited treatment options (LTO) caused by resistant gram-negative pathogens. Thus, this study sought to estimate the current AMR burden in Greece and the value of reducing AMR to gram-negative pathogens for the Greek healthcare system. METHODS: The current model was adapted from a previously published and validated model of AMR to investigate the overall and AMR-specific burden of treating the most common HAIs with LTO in Greece and scenarios to demonstrate the benefits associated with reducing AMR levels from a third-party payer perspective. Clinical and economic outcomes were estimated over a 10-year time horizon; life years (LYs) and quality-adjusted life years (QALYs) were calculated over a lifetime (based on the annual number of infections over 10 years) at a willingness-to-pay of €30,000 per QALY gained and a 3.5% discount rate. RESULTS: In Greece, the current AMR levels in HAIs with LTO caused by four gram-negative pathogens account for > 316,000 hospital bed days, €73 million in hospitalisation costs, and > 580,000 LYs and 450,000 QALYs lost over 10 years. The monetary burden is estimated at €13.9 billion. A reduction in current AMR levels by 10-50% results in clinical and economic benefit; 29,264-151,699 bed days may be saved, leading to decreased hospitalisation costs (€6.8 million-€35.3 million) and a gain in LYs (85,328-366,162) and QALYs (67,421-289,331), associated with a monetary benefit of between €2.0 billion and €8.7 billion. CONCLUSION: This study shows the substantial clinical and economic burden AMR represents to the Greek healthcare system and the value that can be achieved by effectively reducing AMR levels.

An Economic Evaluation Estimating the Clinical and Economic Burden of Increased Vancomycin-Resistant Enterococcus faecium Infection Incidence in Japan.

INTRODUCTION: While incidence rates of vancomycin-resistant Enterococcus faecium have remained comparatively low in Japan, there have been increasing reports of more vancomycin-resistant Enterococcus (VRE) outbreaks, requiring costly measures to contain. Increased incidence of VRE in Japan may lead to more frequent and harder to contain outbreaks with current control measures, causing a significant burden to the healthcare system in Japan. This study aimed to demonstrate the clinical and economic burden of vancomycin-resistant E. faecium infections to the Japanese healthcare system and the impact of increasing rates of vancomycin resistance. METHODS: A de novo deterministic analytic model was developed to assess the health economic outcomes of treating hospital-acquired VRE infections; patients are treated according to a two-line treatment strategy, dependent on their resistance status. The model considers hospitalisation costs and the additional cost of infection control. Scenarios investigated the current burden of VRE infections and the additional burden of increased incidence of VRE. Outcomes were assessed over a 1-year and 10-year time horizon from a healthcare payer's perspective in a Japanese setting. Quality-adjusted life years (QALYs) were valued with a willingness-to-pay threshold of ¥5,000,000 ($38,023), and costs and benefits were discounted at a rate of 2%. RESULTS: Current VRE incidence levels in enterococcal infections in Japan equates to ¥130,209,933,636 ($996,204,669) in associated costs and a loss of 185,361 life years (LYs) and 165,934 QALYs over 10 years. A three-fold increase (1.83%) is associated with an additional ¥4,745,059,504 ($36,084,651) in total costs on top of the current cost burden as well as an additional loss of 683 LYs over a lifetime, corresponding to 616 QALYs lost. CONCLUSION: Despite low incidence rates, VRE infections already represent a substantial economic burden to the Japanese healthcare system. The substantial increase in costs associated with a higher incidence of VRE infections could result in a significant economic challenge for Japan.

Quantifying the Economic and Clinical Value of Reducing Antimicrobial Resistance in Gram-negative Pathogens Causing Hospital-Acquired Infections in Australia.

INTRODUCTION: Antimicrobial resistance (AMR) is a global public health challenge requiring a global response to which Australia has issued a National Antimicrobial Resistance Strategy. The necessity for continued-development of new effective antimicrobials is required to tackle this immediate health threat is clear, but current market conditions may undervalue antimicrobials. We aimed to estimate the health-economic benefits of reducing AMR levels for drug-resistant gram-negative pathogens in Australia, to inform health policy decision-making. METHODS: A published and validated-dynamic health economic model was adapted to the Australian setting. Over a 10-year time horizon, the model estimates the clinical and economic outcomes associated with reducing current AMR levels, by up to 95%, of three gram-negative pathogens in three hospital-acquired infections, from the perspective of healthcare payers. A willingness-to-pay threshold of AUD$15,000-$45,000 per quality-adjusted life-year (QALY) gained and a 5% discount rate (for costs and benefits) were applied. RESULTS: Over ten years, reducing AMR for gram-negative pathogens in Australia is associated with up to 10,251 life-years and 8924 QALYs gained, 9041 bed-days saved and 6644 defined-daily doses of antibiotics avoided. The resulting savings are estimated to be $10.5 million in hospitalisation costs, and the monetary benefit at up to $412.1 million. DISCUSSION: Our results demonstrate the clinical and economic value of reducing AMR impact in Australia. Of note, since our analysis only considered a limited number of pathogens in the hospital setting only and for a limited number of infection types, the benefits of counteracting AMR are likely to extend well beyond the ones demonstrated here. CONCLUSION: These estimates demonstrate the consequences of failure to combat AMR in the Australian context. The benefits in mortality and health system costs justify consideration of innovative reimbursement schemes to encourage the development and commercialisation of new effective antimicrobials.

Patient-reported outcome measures and patient engagement in heart failure clinical trials: multi-stakeholder perspectives.

There are many consequences of heart failure (HF), including symptoms, impaired health-related quality of life (HRQoL), and physical and social limitations (functional status). These have a substantial impact on patients' lives, yet are not routinely captured in clinical trials. Patient-reported outcomes (PROs) can quantify patients' experiences of their disease and its treatment. Steps can be taken to improve the use of PROs in HF trials, in regulatory and payer decisions, and in patient care. Importantly, PRO measures (PROMs) must be developed with involvement of patients, family members, and caregivers from diverse demographic groups and communities. PRO data collection should become more routine not only in clinical trials but also in clinical practice. This may be facilitated by the use of digital tools and interdisciplinary patient advocacy efforts. There is a need for standardization, not only of the PROM instruments, but also in procedures for analysis, interpretation and reporting PRO data. More work needs to be done to determine the degree of change that is important to patients and that is associated with increased risks of clinical events. This 'minimal clinically important difference' requires further research to determine thresholds for different PROMs, to assess consistency across trial populations, and to define standards for improvement that warrant regulatory and reimbursement approvals. PROs are a vital part of patient care and drug development, and more work should be done to ensure that these measures are both reflective of the patient experience and that they are more widely employed.

Efficacy and safety of intensive versus conventional glucose targets in people with type 2 diabetes: a systematic review and meta-analysis.

OBJECTIVE: The aim of study is to re-evaluate the risk-benefits of intensive glycemic control in the context of multi-factorial intervention in adults with T2D. METHODS: We searched Ovid MEDLINE, Embase, Cochrane, and CINHAL for randomized control trials comparing standard glucose targets to intensive glucose targets with pre-specified HbA1clevels. Subgroup analysis was also performed to account for the inclusion of glucose only versus multi-factorial intervention trials. Results are reported as risk ratio (RR) and 95% confidence interval (CI). RESULTS: Fifty-seven publications including 19 trials were included. Compared to conventional glycemic control, intensive glycemic control decreased the risk of non-fatal myocardial infarction (0.8, 0.7-0.91), macroalbuminuria (0.72, 0.5--0.87), microalbuminuria (0.67, 0.52-0.85), major amputation (0.6, 0.38-0.96), retinopathy (0.75 ,0.63-0.9), and nephropathy (0.78, 0.63-0.97). The risk of hypoglycemia increased with intensive glycemic control than conventional treatment (2.04, 1.34-3.1). No reduction in all-cause or cardiovascular mortality was observed. However, in the context of multifactorial intervention, intensive glucose control was associated with a significant reduction in all-cause mortality (0.74, 0.57-0.95). CONCLUSION: Targeting HbA1c levels should be individualized based on the clinical status, balancing risks and benefits and potential risk for developing these complications among people with T2D.

Estimating the Clinical and Economic Impact of Introducing a New Antibacterial into Greek Clinical Practice for the Management of Hospital-Acquired Infections with Limited Treatment Options.

INTRODUCTION: Hospital-acquired infections (HAIs) and growing antimicrobial resistance (AMR) represent a significant healthcare burden globally. Especially in Greece, HAIs with limited treatment options (LTO) pose a serious threat due to increased morbidity and mortality. This study aimed to estimate the clinical and economic value of introducing a new antibacterial for HAIs with LTO in Greece. METHODS: A previously published and validated dynamic model of AMR was adapted to the Greek setting. The model estimated the clinical and economic outcomes of introducing a new antibacterial for the treatment of HAIs with LTO in Greece. The current treatment pathway was compared with introducing a new antibacterial to the treatment sequence. Outcomes were assessed from a third-party payer perspective, over a 10-year transmission period, with quality-adjusted life years (QALYs) and life years (LYs) gained considered over a lifetime horizon. RESULTS: Over the next 10 years, HAIs with LTO in Greece account for approximately 1.4 million hospital bed days, hospitalisation costs of more than €320 million and a loss of approximately 403,000 LYs (319,000 QALYs). Introduction of the new antibacterial as first-line treatment provided the largest clinical and economic benefit, with savings of up to 93,000 bed days, approximately €21 million in hospitalisation costs and an additional 286,000 LYs (226,000 QALYs) in comparison to the current treatment strategy. The introduction of a new antibacterial was linked to a monetary benefit of €6.8 billion at a willingness to pay threshold of €30,000 over 10 years. CONCLUSION: This study highlights the considerable clinical and economic benefit of introducing a new antibacterial for HAIs with LTO in Greece. This analysis shows the additional benefit when a new antibacterial is introduced to treatment sequences. These findings can be used to inform decision makers to implement policies to ensure timely access to new antibacterial treatments in Greece.

Antimicrobial resistance is a major issue for the Greek healthcare system. The overuse of antibacterial agents contributes to the growing resistance levels, making currently available treatment options less effective. As a result, there is an imperative need to address antimicrobial resistance in Greece. This study developed a mathematical model to investigate the clinical and economic benefits of introducing a new antibacterial to current treatment practice. The model uses regression equations to describe the relationships between inputs and outputs from a published and validated model, which describes the transmission and treatment of infections. The model is used to estimate the impact of a new treatment in Greece, considering differing treatment sequence scenarios. The largest health and financial benefits were seen when a new antibacterial was introduced at first line prior to currently used treatments. Over 10 years, savings of up to 93,000 hospital bed days and €21 million in hospitalisation costs could be achieved, as well as a gain of 286,000 patient life years and 226,000 patient quality-adjusted life years (QALYs), a measure of a patient's quality and length of life, over their remaining lifetime. The introduction of a new antibacterial into the current treatment pathway resulted in an overall monetary benefit of €6.8 billion over 10 years, when additional QALYs are valued at €30,000. This study demonstrates considerable health economic benefits of introducing a new antibacterial in Greece and can help inform decision makers when developing a national action plan to combat resistance and improve access to treatments.

Estimating the Economic and Clinical Value of Introducing Ceftazidime/Avibactam into Antimicrobial Practice in Japan: A Dynamic Modelling Study.

BACKGROUND: Antimicrobial resistance (AMR) is one of the most serious public health challenges worldwide, including in Japan. Globally, research and development of new antimicrobials has stalled due to unfavorable market conditions, which undervalue antimicrobials. Furthermore, Japan faces the additional challenge of delayed commercialization for a number of recently approved treatments. OBJECTIVE: This study aims to examine the impact on AMR of introducing a new anti-infective treatment, ceftazidime/avibactam, into current treatment strategies. It reports the resulting clinical and economic outcomes from the perspective of healthcare payers in Japan. METHODS: A previously published and validated dynamic disease transmission model was adapted to the Japanese setting. The model estimated health economic outcomes for treating three Gram-negative hospital-acquired infections, under different treatment strategies, from a healthcare payers' perspective. Outcomes were assessed over a 10-year time horizon with a willingness-to-pay threshold of ¥5,000,000 (US$45,556) per quality-adjusted life-year (QALY) gained and an annual discount rate of 2% applied to costs and benefits. RESULTS: Introducing ceftazidime/avibactam in the framework of a diversification strategy with piperacillin/tazobactam is associated with reducing 798,640 bed days, equating to ¥21.0 billion (US$190.9 million) savings in hospitalization costs, and a gain of 363,034 life-years, or 308,641 QALYs. This translates into a monetary benefit of ¥1.56 trillion (US$14.3 billion) to Japanese healthcare payers. DISCUSSION: Introducing a new antimicrobial agent into clinical practice is associated with considerable clinical and economic benefits. This analysis demonstrates that the approach taken to incorporate a new antimicrobial agent into clinical practice impacts on the scale of these clinical and economic benefits; greater benefits are associated with earlier use of antimicrobials as part of an antimicrobial stewardship program. CONCLUSION: This analysis shows that changing the way in which a new antimicrobial is used within a treatment strategy has the potential for additional significant clinical and economic value.

Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: cost-effectiveness of a screening strategy evaluated in a randomized controlled trial in England.

OBJECTIVE: The PULsE-AI trial sought to determine the effectiveness of a screening strategy that included a machine learning risk prediction algorithm in conjunction with diagnostic testing for identification of undiagnosed atrial fibrillation (AF) in primary care. This study aimed to evaluate the cost-effectiveness of implementing the screening strategy in a real-world setting. METHODS: Data from the PULsE-AI trial - a prospective, randomized, controlled trial conducted across six general practices in England from June 2019 to February 2021 - were used to inform a cost-effectiveness analysis that included a hybrid screening decision tree and Markov AF disease progression model. Model outcomes were reported at both individual- and population-level (estimated UK population ≥30 years of age at high-risk of undiagnosed AF) and included number of patients screened, number of AF cases identified, mean total and incremental costs (screening, events, treatment), quality-adjusted-life-years (QALYs), and incremental cost-effectiveness ratio (ICER). RESULTS: The screening strategy was estimated to result in 45,493 new diagnoses of AF across the high-risk population in the UK (3.3 million), and an estimated additional 14,004 lifetime diagnoses compared with routine care only. Per-patient costs for high-risk individuals who underwent the screening strategy were estimated at £1,985 (vs £1,888 for individuals receiving routine care only). At a population-level, the screening strategy was associated with a cost increase of approximately £322 million and an increase of 81,000 QALYs. The screening strategy demonstrated cost-effectiveness versus routine care only at an accepted ICER threshold of £20,000 per QALY-gained, with an ICER of £3,994/QALY. CONCLUSIONS: Compared with routine care only, it is cost-effective to target individuals at high risk of undiagnosed AF, through an AF risk prediction algorithm, who should then undergo diagnostic testing. This AF risk prediction algorithm can reduce the number of patients needed to be screened to identify undiagnosed AF, thus alleviating primary care burden.

Intensive glycemic control and macrovascular, microvascular, hypoglycemia complications and mortality in older (age ≥60years) or frail adults with type 2 diabetes: a systematic review and meta-analysis from randomized controlled trial and observation studies.

INTRODUCTION: Guidelines for type 2 diabetes (T2D) recommend individualized HbA1c targets to take into account patient age or frailty. We synthesized evidence from randomized controlled trials and observational studies for intensive glycemic control (HbA1c target ≤58 mmol/mol) versus standard care, in elderly (age ≥60 years) or frail adults with T2D. METHODS: Searches were performed utilizing recognized terms for T2D, frailty, older age, and HbA1c control and outcomes of interest. Meta-analysis was performed where possible. Primary outcomes included all-cause mortality, severe hypoglycemia, and hospital admission rates. Vascular complications, cognitive decline, and falls/fractures were secondary outcomes. RESULTS: 7,528 studies were identified of which 15 different clinical studies were selected. No difference was noted in all-cause mortality with intensive control (pooled hazard ratio 0.96, 95% confidence interval 0.90-1.03), but risk of severe hypoglycemia increased (2.45, 2.22-2.72). Intensive control was associated reductions in microvascular (0.73, 0.68-0.79) and macrovascular complications (0.84, 0.79-0.89). Outcome data for risk of hospitalization, cognition, and falls/fractures were limited. CONCLUSION: Intensive glycemic control was associated with reduced rates of complications but increased severe hypoglycemia. Significant heterogeneity exists and the impact of different drug regimens is unclear. Caution is needed when setting glycemic targets in elderly or frail individuals.

Identification of undiagnosed atrial fibrillation using a machine learning risk-prediction algorithm and diagnostic testing (PULsE-AI) in primary care: a multi-centre randomized controlled trial in England.

Aims: The aim of the PULsE-AI trial was to assess the effectiveness of a machine learning risk-prediction algorithm in conjunction with diagnostic testing for identifying undiagnosed atrial fibrillation (AF) in primary care in England. Methods and results: Eligible participants (aged ≥30 years without AF diagnosis; n = 23 745) from six general practices in England were randomized into intervention and control arms. Intervention arm participants, identified by the algorithm as high risk of undiagnosed AF (n = 944), were invited for diagnostic testing (n = 256 consented); those who did not accept the invitation, and all control arm participants, were managed routinely. The primary endpoint was the proportion of AF, atrial flutter, and fast atrial tachycardia diagnoses during the trial (June 2019-February 2021) in high-risk participants. Atrial fibrillation and related arrhythmias were diagnosed in 5.63% and 4.93% of high-risk participants in intervention and control arms, respectively {odds ratio (OR) [95% confidence interval (CI)]: 1.15 (0.77-1.73), P = 0.486}. Among intervention arm participants who underwent diagnostic testing (28.1%), 9.41% received AF and related arrhythmia diagnoses [vs. 4.93% (control); OR (95% CI): 2.24 (1.31-3.73), P = 0.003]. Conclusion: The AF risk-prediction algorithm accurately identified high-risk participants in both arms. While the proportions of AF and related arrhythmia diagnoses were not significantly different between high-risk arms, intervention arm participants who underwent diagnostic testing were twice as likely to receive arrhythmia diagnoses compared with routine care. The algorithm could be a valuable tool to select primary care groups at high risk of undiagnosed AF who may benefit from diagnostic testing.

Estimating the Economic and Clinical Value of Reducing Antimicrobial Resistance to Three Gram-negative Pathogens in Japan.

Background: Antimicrobial resistance (AMR) represents a significant global public health crisis. Despite ample availability of Gram-positive antibiotics, there is a distinct lack of agents against Gram-negative pathogens, including carbapenem-resistant Enterobacterales, which remains a real threat in Japan. The AMR Action Plans aim to mitigate the growing public health concern posed by AMR. Objective: This study aims to estimate the clinical and economic outcomes of drug-resistant Gram-negative pathogens forecasts for Japan to guide resource allocation defined within the upcoming National AMR Action Plan. Methods: A previously published and validated dynamic health economic model was adapted to the Japanese setting. The model used a 10-year time horizon with a willingness-to-pay threshold of ¥5 000 000 (US $46 827) and discounting was applied at a rate of 2% to costs and benefits. Clinical and economic outcomes were assessed as a function of varying AMR levels of three Gram-negative pathogens in Japan by up to 100% of the current level. Results: Reducing drug-resistant Gram-negative pathogens in Japan has the potential to save 4 249 096 life years, corresponding to 3 602 311 quality-adjusted life years. The associated maximum clinical and economic gains were estimated at up to 4 422 284 bed days saved, up to 3 645 480 defined daily doses of antibiotics avoided, up to ¥117.6 billion (US $1.1 billion) saved in hospitalization costs, and a net monetary benefit of up to ¥18.1 trillion (US $169.8 billion). Discussion: Learnings from this study can be used by the Japanese government to help inform decision-making on the strategies that may be included in the upcoming National AMR Action Plan and facilitate allocation of the required budget. Conclusions: This analysis demonstrated the considerable economic and clinical value of reducing AMR levels of three Gram-negative pathogens in Japan and could be utilized to support the valuation of antimicrobial treatment and resistance in Japan and more broadly.

Clinical cost evaluation and health benefits of post-bariatric intervention for patients with type 2 diabetes living in the UK.

To assess associated healthcare costs and risk of developing obesity-related comorbidities among patients with type 2 diabetes with severe obesity and receiving insulin treatment, following bariatric surgery (BS). A retrospective cohort study was conducted from a UK electronic primary care database. Propensity score matching (1:1) was performed for BS with non-BS cohort. Follow-up was over 5 years (694 person-years), comparing drug utilization with clinical cost differences, such as visits to General practitioners (GPs), hospitalization, and laboratory use. Cox proportional regression was used to compute differences in the risk of obesity-related comorbidities and chi-square analysis to explore differences in insulin independency and diabetes remission proportions during follow-up. Eighty patients who received BS were matched to 80 non-BS (N = 160). The baseline mean age was 48.3 years (SD: 12.9) (61% female), and body mass index was 39.3 kg/m2 (SD: 9.3). During follow-up, antidiabetic drug cost was significantly lower in the BS group than in the non-BS (median cost/person [£]: 527.77 [interquartile range (IQR): 1196.11] vs. 1564.13 [IQR: 1576.01]; p < 0.001). Overall, aggregate cost analysis showed a significant total healthcare cost reduction in the BS group (median cost/person [£]: 1597.96 [IQR: 2631.84] vs. 2440.12 [IQR: 2242.95]; p = 0.050). BS significantly protected against obesity-related comorbidities compared with the non-BS (adjusted hazard ratio: 0.56; 95% confidence interval: 0.32-0.96; p = 0.036) and increased insulin independency throughout all follow-up points: at year 5: 48.1% versus 28.9%; p = 0.044, respectively. While BS shows evidence of cost efficiency, cost saving was not identified. The efficiency is evident by the protective effect against crude obesity-related comorbidities associated with increased insulin independency.

Non-Price-Related Determinants of Value and Access for Novel Non-small Cell Lung Cancer Treatments: A Cross-Country Review of HTA Decision Making.

INTRODUCTION: Access and funding for newly approved treatments for non-small cell lung cancer (NSCLC) are often dependent on Health Technology Assessment (HTA) involving cost-effectiveness analysis. Whilst methods used by HTA agencies share many similarities, final decisions may differ. This may be the result, not just of price considerations, but also of variation in value judgements by different agencies. The aim of this study was to review international HTA evaluations to identify determinants of value and access for NSCLC treatments. METHODS: A targeted review and analysis was undertaken of published HTAs for NSCLC across HTA agencies in six countries (Australia, Canada, England, France, Ireland and Scotland). Analysis of extracted data consisted of three stages: descriptive analysis, bivariate analysis and multivariable analysis. RESULTS: The analysis included 163 HTAs that assessed oncological treatments for NSCLC from 2003 to 2019. The majority of HTA decisions (67.5%) were positive. However, some evidence of heterogeneity in HTA decisions and the factors informing them were identified. The most influential factors included in the multivariate model related to the HTA agency conducting the appraisal, the year of market authorisation, treatment type and the line of treatment. CONCLUSION: Heterogenous decision-making frameworks can present a challenge to developing HTA submissions. This research contributes to understanding decision-making factors and why countries make different decisions.

Spatial dependence and determinants of conservation easement adoptions in the United States.

A conservation easement is a market-based instrument for environmental protection. It has achieved rapid growth in the United States over the past few decades. As of 2015, 1.75% of the country's total land was placed under the restriction of conservation easements. In this study, spatial dependence in adopting conservation easements in the United States and the underlying determinants are examined through a spatial econometric model. The spatial panel data covers 50 individual states and six five-year intervals from 1990 to 2015. The findings reveal that spatial correlation in adopting conservation easements across individual states has become stronger over the study period, and the indirect spillover effect for most covariates is as high as one-third of the total effect. In addition, conservation easements have been utilized to protect threatened or strained natural resources. Populations with higher income or better education generally have helped the development of conservation easements. Government programs and policies favoring conservation easements also have positive impacts on easement adoption. These results can aid policymakers, landowners, and easement holders to efficiently allocate resources in acquiring conservation easements and managing currently eased land.

Detecting undiagnosed atrial fibrillation in UK primary care: Validation of a machine learning prediction algorithm in a retrospective cohort study.

AIMS: To evaluate the ability of a machine learning algorithm to identify patients at high risk of atrial fibrillation in primary care. METHODS: A retrospective cohort study was undertaken using the DISCOVER registry to validate an algorithm developed using a Clinical Practice Research Datalink (CPRD) dataset. The validation dataset included primary care patients in London, England aged ≥30 years from 1 January 2006 to 31 December 2013, without a diagnosis of atrial fibrillation in the prior 5 years. Algorithm performance metrics were sensitivity, specificity, positive predictive value, negative predictive value (NPV) and number needed to screen (NNS). Subgroup analysis of patients aged ≥65 years was also performed. RESULTS: Of 2,542,732 patients in DISCOVER, the algorithm identified 604,135 patients suitable for risk assessment. Of these, 3.0% (17,880 patients) had a diagnosis of atrial fibrillation recorded before study end. The area under the curve of the receiver operating characteristic was 0.87, compared with 0.83 in algorithm development. The NNS was nine patients, matching the CPRD cohort. In patients aged ≥30 years, the algorithm correctly identified 99.1% of patients who did not have atrial fibrillation (NPV) and 75.0% of true atrial fibrillation cases (sensitivity). Among patients aged ≥65 years (n = 117,965), the NPV was 96.7% with 91.8% sensitivity. CONCLUSIONS: This atrial fibrillation risk prediction algorithm, based on machine learning methods, identified patients at highest risk of atrial fibrillation. It performed comparably in a large, real-world population-based cohort and the developmental registry cohort. If implemented in primary care, the algorithm could be an effective tool for narrowing the population who would benefit from atrial fibrillation screening in the United Kingdom.

Identification of undiagnosed atrial fibrillation patients using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI): Study protocol for a randomised controlled trial.

Atrial fibrillation (AF) is associated with an increased risk of stroke, enhanced stroke severity, and other comorbidities. However, AF is often asymptomatic, and frequently remains undiagnosed until complications occur. Current screening approaches for AF lack either cost-effectiveness or diagnostic sensitivity; thus, there is interest in tools that could be used for population screening. An AF risk prediction algorithm, developed using machine learning from a UK dataset of 2,994,837 patients, was found to be more effective than existing models at identifying patients at risk of AF. Therefore, the aim of the trial is to assess the effectiveness of this risk prediction algorithm combined with diagnostic testing for the identification of AF in a real-world primary care setting. Eligible participants (aged ≥30 years and without an existing AF diagnosis) registered at participating UK general practices will be randomised into intervention and control arms. Intervention arm participants identified at highest risk of developing AF (algorithm risk score ≥ 7.4%) will be invited for a 12­lead electrocardiogram (ECG) followed by two-weeks of home-based ECG monitoring with a KardiaMobile device. Control arm participants will be used for comparison and will be managed routinely. The primary outcome is the number of AF diagnoses in the intervention arm compared with the control arm during the research window. If the trial is successful, there is potential for the risk prediction algorithm to be implemented throughout primary care for narrowing the population considered at highest risk for AF who could benefit from more intensive screening for AF. Trial Registration: NCT04045639.