Increasing cost-effectiveness of AEDs using algorithms to optimise location.

OBJECTIVES: Volunteer responder systems (VRSs) aim to decrease time to defibrillation by dispatching trained volunteers to automated external defibrillators (AEDs) and out-of-hospital cardiac arrest (OHCA) victims. AEDs are often underutilized due to poor placement. This study provides a cost-effectiveness analysis of adding AEDs at strategic locations to maximize quality-adjusted life years (QALYs). METHODS: We simulated combined volunteer, police, firefighter, and emergency medical service response scenarios to OHCAs, and applied our methods to a case study of Amsterdam, the Netherlands. We compared the competing strategies of placing additional AEDs, using steps of 40 extra AEDs (0, 40, …, 1480), in addition to the existing 369 AEDs. Incremental cost-effectiveness ratios (ICERs) were calculated for each increase in additional AEDs, from a societal perspective. The effect of AED connection and time to connection on survival to hospital admission and neurological outcome at discharge was estimated using logistic regression, using OHCA data from Amsterdam from 2006 to 2018. Other model inputs were obtained from literature. RESULTS: Purchasing up to 1120 additional AEDs (ICER €75,669/QALY) was cost-effective at a willingness-to-pay threshold of €80,000/QALY, when positioned strategically. Compared to current practice, adding 1120 AEDs resulted in a gain of 0.111 QALYs (95% CI 0.110-0.112) at an increased cost of €3792 per OHCA (95% CI €3778-€3807). Health benefits per AED diminished as more AEDs were added. CONCLUSIONS: Our study identified cost-effective strategies to position AEDs at strategic locations in a VRS. The case study findings advocate for a substantial increase in the number of AEDs in Amsterdam.

A direct comparison in diagnostic performance of CDUS, FDG-PET/CT and MRI in patients suspected of giant cell arteritis.

OBJECTIVES: This study directly compares diagnostic performance of Colour Duplex Ultrasound (CDUS), Fluor-18-deoxyglucose Positron Emission Tomography Computed Tomography (FDG-PET/CT) and Magnetic Resonance Imaging (MRI) in patients suspected of giant cell arteritis (GCA). METHODS: Patients with suspected GCA were included in a nested-case control pilot study. CDUS, whole body FDG-PET/CT and cranial MRI were performed within 5 working days after initial clinical evaluation. Clinical diagnosis after six months follow-up by experienced rheumatologists in the field of GCA, blinded for imaging, was used as reference standard. Diagnostic performance of the imaging modalities was determined. Stratification for GCA subtype was performed and imaging results were evaluated in different risk stratification groups. RESULTS: In total, 23 patients with GCA and 19 patients suspected of but not diagnosed with GCA were included. Sensitivity was 69.6% (95%CI 50.4%-88.8%) for CDUS, 52.2% (95%CI 31.4%-73.0%) for FDG-PET/CT and 56.5% (95%CI 35.8%-77.2%) for MRI. Specificity was 100% for CDUS, FDG-PET/CT and MRI. FDG-PET/CT was negative for GCA in all isolated cranial GCA patients (n = 8), while MRI was negative in all isolated extracranial GCA patients (n = 4). In 4 GCA patients with false-negative (n = 2; intermediate and high risk) or inconclusive (n = 2; low and intermediate risk) CDUS results, further imaging confirmed diagnosis. CONCLUSIONS: Sensitivity of CDUS was highest, while specificity was excellent in all imaging modalities. Nevertheless, confidence intervals of all imaging modalities were overlapping. Following EULAR recommendations, CDUS can be used as a first test to diagnose GCA. With insufficient evidence for GCA, further testing considering GCA subtype is warranted.

A Blueprint for Multi-use Disease Modeling in Health Economics: Results from Two Expert-Panel Consultations.

BACKGROUND: The current use of health economic decision models in HTA is mostly confined to single use cases, which may be inefficient and result in little consistency over different treatment comparisons, and consequently inconsistent health policy decisions, for the same disorder. Multi-use disease models (MUDMs) (other terms: generic models, whole disease models, disease models) may offer a solution. However, much is uncertain about their definition and application. The current research aimed to develop a blueprint for the application of MUDMs. METHODS: We elicited expert opinion using a two-round modified Delphi process. The panel consisted of experts and stakeholders in health economic modelling from various professional backgrounds. The first questionnaire concerned definition, terminology, potential applications, issues and recommendations for MUDMs and was based on an exploratory scoping review. In the second round, the panel members were asked to reconsider their input, based on feedback regarding first-round results, and to score issues and recommendations for priority. Finally, adding input from external advisors and policy makers in a structured way, an overview of issues and challenges was developed during two team consensus meetings. RESULTS: In total, 54 respondents contributed to the panel results. The term 'multi-use disease models' was proposed and agreed upon, and a definition was provided. The panel prioritized 10 potential applications (with comparing alternative policies and supporting resource allocation decisions as the top 2), while 20 issues (with model transparency and stakeholders' roles as the top 2) were identified as challenges. Opinions on potential features concerning operationalization of multi-use models were given, with 11 of these subsequently receiving high priority scores (regular updates and revalidation after updates were the top 2). CONCLUSIONS: MUDMs would improve on current decision support regarding cost-effectiveness information. Given feasibility challenges, this would be most relevant for diseases with multiple treatments, large burden of disease and requiring more complex models. The current overview offers policy makers a starting point to organize the development, use, and maintenance of MUDMs and to support choices concerning which diseases and policy decisions they will be helpful for.

Validating Health Economic Models With the Probabilistic Analysis Check dashBOARD.

OBJECTIVES: Health economic (HE) models are often considered as "black boxes" because they are not publicly available and lack transparency, which prevents independent scrutiny of HE models. Additionally, validation efforts and validation status of HE models are not systematically reported. Methods to validate HE models in absence of their full underlying code are therefore urgently needed to improve health policy making. This study aimed to develop and test a generic dashboard to systematically explore the workings of HE models and validate their model parameters and outcomes. METHODS: The Probabilistic Analysis Check dashBOARD (PACBOARD) was developed using insights from literature, health economists, and a data scientist. Functionalities of PACBOARD are (1) exploring and validating model parameters and outcomes using standardized validation tests and interactive plots, (2) visualizing and investigating the relationship between model parameters and outcomes using metamodeling, and (3) predicting HE outcomes using the fitted metamodel. To test PACBOARD, 2 mock HE models were developed, and errors were introduced in these models, eg, negative costs inputs, utility values exceeding 1. PACBOARD metamodeling predictions of incremental net monetary benefit were validated against the original model's outcomes. RESULTS: PACBOARD automatically identified all errors introduced in the erroneous HE models. Metamodel predictions were accurate compared with the original model outcomes. CONCLUSIONS: PACBOARD is a unique dashboard aiming at improving the feasibility and transparency of validation efforts of HE models. PACBOARD allows users to explore the working of HE models using metamodeling based on HE models' parameters and outcomes.

Opportunities for personalised follow-up in breast cancer: the gap between daily practice and recurrence risk.

PURPOSE: Follow-up guidelines barely diverge from a one-size-fits-all approach, even though the risk of recurrence differs per patient. However, the personalization of breast cancer care improves outcomes for patients. This study explores the variation in follow-up pathways in the Netherlands using real-world data to determine guideline adherence and the gap between daily practice and risk-based surveillance, to demonstrate the benefits of personalized risk-based surveillance compared with usual care. METHODS: Patients with stage I-III invasive breast cancer who received surgical treatment in a general hospital between 2005 and 2020 were selected from the Netherlands Cancer Registry and included all imaging activities during follow-up from hospital-based electronic health records. Process analysis techniques were used to map patients and activities to investigate the real-world utilisation of resources and identify the opportunities for improvement. The INFLUENCE 2.0 nomogram was used for risk prediction of recurrence. RESULTS: In the period between 2005 and 2020, 3478 patients were included with a mean follow-up of 4.9 years. In the first 12 months following treatment, patients visited the hospital between 1 and 5 times (mean 1.3, IQR 1-1) and received between 1 and 9 imaging activities (mean 1.7, IQR 1-2). Mammogram was the prevailing imaging modality, accounting for 70% of imaging activities. Patients with a low predicted risk of recurrence visited the hospital more often. CONCLUSIONS: Deviations from the guideline were not in line with the risk of recurrence and revealed a large gap, indicating that it is hard for clinicians to accurately estimate this risk and therefore objective risk predictions could bridge this gap.

Cost-effectiveness of home-based screening of the general population for albuminuria to prevent progression of cardiovascular and kidney disease.

Background: Chronic kidney disease (CKD) is often detected late, leading to substantial health loss and high treatment costs. Screening the general population for albuminuria identifies individuals at high risk of kidney events and cardiovascular disease (CVD) who may benefit from early start of preventive interventions. Previous studies on the cost-effectiveness of albuminuria population screening were inconclusive, but were based on survey or cohort data rather than an implementation study, modelled screening as performed by general practitioners rather than home-based screening, and often included only benefits with respect to kidney events. We evaluated the cost-effectiveness of home-based general population screening for increased albuminuria based on real-world data obtained from a prospective implementation study taking into account prevention of CKD as well as CVD events. Methods: We developed an individual-level simulation model to compare home-based screening using a urine collection device with usual care (no home-based screening) in individuals of the general population aged 45-80, based on the THOMAS study (Towards HOMe-based Albuminuria Screening). Cost-effectiveness was assessed from the Dutch healthcare perspective with a lifetime horizon. The costs of the screening process and benefits of preventing CKD progression (dialysis and kidney transplantation) and CVD events (non-fatal myocardial infarction, non-fatal stroke, fatal CVD event) were reflected. Albuminuria detection led to treatment of identified risk factors. The model subsequently simulated CKD progression, the occurrence of CVD events, and death. The risks of experiencing CVD events were calculated using the SCORE2 CKD risk prediction model and individual-level data from the THOMAS study. Relative treatment effectiveness, quality of life scores, resource use, and cost inputs were obtained from literature. Model outcomes were the number of CKD and CVD-related events, total costs, quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER) per QALY gained by screening versus usual care. All results were obtained through probabilistic analysis. Findings: The absolute difference between screening versus usual care in lifetime probability of dialysis, kidney transplantation, non-fatal myocardial infarction, non-fatal stroke, and fatal CVD events were 0.2%, 0.05%, 0.6%, 0.6%, and 0.2%, respectively. This led to relative decreases compared to usual care in lifetime incidence of these events of 10.7%, 11.1%, 5.1%, 4.1%, and 1.6%, respectively. The incremental costs and QALYs of screening were €1607 and 0.17 QALY, respectively, which led to a corresponding ICER of €9225/QALY. The probability of screening being cost-effective for the Dutch willingness-to-pay threshold for preventive population screening of €20,000/QALY was 95.0%. Implementing the screening in the subgroup of 45-64 years old reduced the ICER (€7946/QALY), whereas implementing screening in the subgroup of 65-80 years old increased the ICER (€10,310/QALY). A scenario analysis assuming treatment optimization in all individuals with newly diagnosed risk factors or known risk factors not within target range reduced the ICER to €7083/QALY, resulting from the incremental costs and QALY gain of €2145 and 0.30, respectively. Interpretation: Home-based screening for increased albuminuria to prevent CVD and CKD events is likely cost-effective. More health benefits can be obtained by screening younger individuals and better optimization of care in individuals identified with newly diagnosed or known risk factors outside target range. Funding: Dutch Kidney Foundation, Top Sector Life Sciences & Health of the Dutch Ministry of Economic Affairs.

Introducing Open Science in Teaching Health Economic Modelling.

Open Science is gaining ground in all research fields, including health economics and outcomes research (HEOR). However, teaching Open Science is still in its infancy. This paper describes the design, implementation and evaluation of a teaching activity focusing on introducing Open Science during a Master's course during which participants have to develop a discrete event simulation. The teaching activity was organised as a series of lectures introducing different aspects of the Open Science philosophy and practices, such as good software coding practices, version control systems and reproducible research. The participants' increase in Open Science knowledge was elicited through a survey before and after the teaching innovation. After the teaching innovation, participants' knowledge of Open Science increased and they reported an improvement in Open Science-related skills, such as using a script-based statistical software, identifying and re-using open data, and collaborative script development. During the evaluation at the end of the course, the course participants mentioned that the Open Science-related content was interesting but would fit better within a course in which broader research-related content is taught. Based on this feedback, we will most likely narrow the scope of the Open-Science-related content in this course to Open Source Modelling which may better fit the scope of the course. This paper contains links to the teaching activities we developed and other resources which may be used to design teaching activities on Open Science. Herewith, we hope to inspire other teachers in including Open Science into their teaching.

Diagnostic yield of a proactive strategy for early detection of cardiovascular disease versus usual care in adults with type 2 diabetes or chronic obstructive pulmonary disease in primary care in the Netherlands (RED-CVD): a multicentre, pragmatic, cluster-randomised, controlled trial.

BACKGROUND: Progressive cardiovascular diseases (eg, heart failure, atrial fibrillation, and coronary artery disease) are often diagnosed late in high-risk individuals with common comorbidities that might mimic or mask symptoms, such as chronic obstructive pulmonary disease (COPD) and type 2 diabetes. We aimed to assess whether a proactive diagnostic strategy consisting of a symptom and risk factor questionnaire and low-cost and accessible tests could increase diagnosis of progressive cardiovascular diseases in patients with COPD or type 2 diabetes in primary care. METHODS: In this multicentre, pragmatic, cluster-randomised, controlled trial (RED-CVD), 25 primary care practices in the Netherlands were randomly assigned to usual care or a proactive diagnostic strategy conducted during routine consultations and consisting of a validated symptom questionnaire, followed by physical examination, N-terminal-pro-B-type natriuretic peptide measurement, and electrocardiography. We included adults (≥18 years) with type 2 diabetes, COPD, or both, who participated in a disease management programme. Patients with an established triple diagnosis of heart failure, atrial fibrillation, and coronary artery disease were excluded. In the case of abnormal findings, further work-up or treatment was done at the discretion of the general practitioner. The primary endpoint was the number of newly diagnosed cases of heart failure, atrial fibrillation, and coronary artery disease, adjudicated by an expert clinical outcome committee using international guidelines, at 1-year follow-up, in the intention-to-treat population. FINDINGS: Between Jan 31, 2019, and Oct 7, 2021, we randomly assigned 25 primary care centres: 11 to usual care and 14 to the intervention. We included patients between June 21, 2019, and Jan 31, 2022. Following exclusion of ineligible patients and those who did not give informed consent, 1216 participants were included: 624 (51%) in the intervention group and 592 (49%) in the usual care group. The mean age of participants was 68·4 years (SD 9·4), 482 (40%) participants were female, and 734 (60%) were male. During 1 year of follow-up, 50 (8%) of 624 participants in the intervention group and 18 (3%) of 592 in the control group were newly diagnosed with heart failure, atrial fibrillation, or coronary artery disease (adjusted odds ratio 2·97 [95% CI 1·66-5·33]). This trial is registered with the Netherlands Trial Registry, NTR7360, and was completed on Jan 31, 2023. INTERPRETATION: An easy-to-use, proactive, diagnostic strategy more than doubled the number of new diagnoses of heart failure, atrial fibrillation, and coronary artery disease in patients with type 2 diabetes or COPD in primary care compared with usual care. Although the effect on patient outcomes remains to be studied, our diagnostic strategy might contribute to improved early detection and timely initiation of treatment in individuals with cardiovascular disease. FUNDING: Dutch Heart Foundation.