Economic Implications of Extended-Release Metoprolol Succinate for Heart Failure in the MERIT-HF Trial: A US Perspective of the MERIT-HF Trial

The economics of heart failure care

Heart failure (HF) poses a significant economic burden in the US, with costs projected to reach $70 billion by 2030. Cost-effectiveness analyses play a pivotal role in assessing the economic value of HF therapies. In this review, we overview the cost-effectiveness of HF therapies and discuss ways to improve patient access. Based on current costs, guideline directed medical therapies for HF with reduced ejection fraction provide high economic value except for sodium-glucose cotransporter-2 inhibitors, which provide intermediate economic value. Combining therapy with the four pillars of medical therapy also has intermediate economic value, with incremental cost-effectiveness ratios ranging from $73,000 to $98,500/ quality adjusted life-years. High economic value procedures include cardiac resynchronization devices, implantable cardioverter-defibrillators, and coronary artery bypass surgery. In contrast, advanced HF therapies have previously demonstrated intermediate to low economic value, but newer data appear more favorable. Given the affordability challenges of HF therapies, additional efforts are needed to ensure optimal care for patients. The recent Inflation Reduction Act contains provisions to reform policy pertaining to drug price negotiation and out-of-pocket spending, as well as measures to increase access to existing programs, including the Medicare low-income subsidy. On a patient level, it is also important to encourage patient and physician awareness and discussions surrounding medical costs. Overall, a broad approach to improving available therapies and access to care is needed to reduce the growing clinical and economic morbidity of HF.

2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure" replaces the "2013 ACCF/AHA Guideline for the Management of Heart Failure" and the "2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure." The 2022 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with heart failure.

METHODS

A comprehensive literature search was conducted from May 2020 to December 2020, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (PubMed), EMBASE, the Cochrane Collaboration, the Agency for Healthcare Research and Quality, and other relevant databases. Additional relevant clinical trials and research studies, published through September 2021, were also considered. This guideline was harmonized with other American Heart Association/American College of Cardiology guidelines published through December 2021. Structure: Heart failure remains a leading cause of morbidity and mortality globally. The 2022 heart failure guideline provides recommendations based on contemporary evidence for the treatment of these patients. The recommendations present an evidence-based approach to managing patients with heart failure, with the intent to improve quality of care and align with patients' interests. Many recommendations from the earlier heart failure guidelines have been updated with new evidence, and new recommendations have been created when supported by published data. Value statements are provided for certain treatments with high-quality published economic analyses.

2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: Executive Summary: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure" replaces the "2013 ACCF/AHA Guideline for the Management of Heart Failure" and the "2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure." The 2022 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with heart failure.

METHODS

A comprehensive literature search was conducted from May 2020 to December 2020, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (PubMed), EMBASE, the Cochrane Collaboration, the Agency for Healthcare Research and Quality, and other relevant databases. Additional relevant clinical trials and research studies, published through September 2021, were also considered. This guideline was harmonized with other American Heart Association/American College of Cardiology guidelines published through December 2021. Structure: Heart failure remains a leading cause of morbidity and mortality globally. The 2022 heart failure guideline provides recommendations based on contemporary evidence for the treatment of these patients. The recommendations present an evidence-based approach to managing patients with heart failure, with the intent to improve quality of care and align with patients' interests. Many recommendations from the earlier heart failure guidelines have been updated with new evidence, and new recommendations have been created when supported by published data. Value statements are provided for certain treatments with high-quality published economic analyses.

2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure

AIM

The "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure" replaces the "2013 ACCF/AHA Guideline for the Management of Heart Failure" and the "2017 ACC/AHA/HFSA Focused Update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure." The 2022 guideline is intended to provide patient-centric recommendations for clinicians to prevent, diagnose, and manage patients with heart failure.

METHODS

A comprehensive literature search was conducted from May 2020 to December 2020, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from MEDLINE (PubMed), EMBASE, the Cochrane Collaboration, the Agency for Healthcare Research and Quality, and other relevant databases. Additional relevant clinical trials and research studies, published through September 2021, were also considered. This guideline was harmonized with other American Heart Association/American College of Cardiology guidelines published through December 2021.

STRUCTURE

Heart failure remains a leading cause of morbidity and mortality globally. The 2022 heart failure guideline provides recommendations based on contemporary evidence for the treatment of these patients. The recommendations present an evidence-based approach to managing patients with heart failure, with the intent to improve quality of care and align with patients' interests. Many recommendations from the earlier heart failure guidelines have been updated with new evidence, and new recommendations have been created when supported by published data. Value statements are provided for certain treatments with high-quality published economic analyses.

Long-term monitoring in primary care for chronic kidney disease and chronic heart failure: a multi-method research programme

Background

Long-term monitoring is important in chronic condition management. Despite considerable costs of monitoring, there is no or poor evidence on how, what and when to monitor. The aim of this study was to improve understanding, methods, evidence base and practice of clinical monitoring in primary care, focusing on two areas: chronic kidney disease and chronic heart failure.

Objectives

The research questions were as follows: does the choice of test affect better care while being affordable to the NHS? Can the number of tests used to manage individuals with early-stage kidney disease, and hence the costs, be reduced? Is it possible to monitor heart failure using a simple blood test? Can this be done using a rapid test in a general practitioner consultation? Would changes in the management of these conditions be acceptable to patients and carers?

Design

Various study designs were employed, including cohort, feasibility study, Clinical Practice Research Datalink analysis, seven systematic reviews, two qualitative studies, one cost-effectiveness analysis and one cost recommendation.

Setting

This study was set in UK primary care.

Data sources

Data were collected from study participants and sourced from UK general practice and hospital electronic health records, and worldwide literature.

Participants

The participants were NHS patients (Clinical Practice Research Datalink: 4.5 million patients), chronic kidney disease and chronic heart failure patients managed in primary care (including 750 participants in the cohort study) and primary care health professionals.

Interventions

The interventions were monitoring with blood and urine tests (for chronic kidney disease) and monitoring with blood tests and weight measurement (for chronic heart failure).

Main outcome measures

The main outcomes were the frequency, accuracy, utility, acceptability, costs and cost-effectiveness of monitoring.

Results

Chronic kidney disease: serum creatinine testing has increased steadily since 1997, with most results being normal (83% in 2013). Increases in tests of creatinine and proteinuria correspond to their introduction as indicators in the Quality and Outcomes Framework. The Chronic Kidney Disease Epidemiology Collaboration equation had 2.7% greater accuracy (95% confidence interval 1.6% to 3.8%) than the Modification of Diet in Renal Disease equation for estimating glomerular filtration rate. Estimated annual transition rates to the next chronic kidney disease stage are ≈ 2% for people with normal urine albumin, 3–5% for people with microalbuminuria (3–30 mg/mmol) and 3–12% for people with macroalbuminuria (> 30 mg/mmol). Variability in estimated glomerular filtration rate-creatinine leads to misclassification of chronic kidney disease stage in 12–15% of tests in primary care. Glycaemic-control and lipid-modifying drugs are associated with a 6% (95% confidence interval 2% to 10%) and 4% (95% confidence interval 0% to 8%) improvement in renal function, respectively. Neither estimated glomerular filtration rate-creatinine nor estimated glomerular filtration rate-Cystatin C have utility in predicting rate of kidney function change. Patients viewed phrases such as ‘kidney damage’ or ‘kidney failure’ as frightening, and the term ‘chronic’ was misinterpreted as serious. Diagnosis of asymptomatic conditions (chronic kidney disease) was difficult to understand, and primary care professionals often did not use ‘chronic kidney disease’ when managing patients at early stages. General practitioners relied on Clinical Commissioning Group or Quality and Outcomes Framework alerts rather than National Institute for Health and Care Excellence guidance for information. Cost-effectiveness modelling did not demonstrate a tangible benefit of monitoring kidney function to guide preventative treatments, except for individuals with an estimated glomerular filtration rate of 60–90 ml/minute/1.73 m2, aged < 70 years and without cardiovascular disease, where monitoring every 3–4 years to guide cardiovascular prevention may be cost-effective. Chronic heart failure: natriuretic peptide-guided treatment could reduce all-cause mortality by 13% and heart failure admission by 20%. Implementing natriuretic peptide-guided treatment is likely to require predefined protocols, stringent natriuretic peptide targets, relative targets and being located in a specialist heart failure setting. Remote monitoring can reduce all-cause mortality and heart failure hospitalisation, and could improve quality of life. Diagnostic accuracy of point-of-care N-terminal prohormone of B-type natriuretic peptide (sensitivity, 0.99; specificity, 0.60) was better than point-of-care B-type natriuretic peptide (sensitivity, 0.95; specificity, 0.57). Within-person variation estimates for B-type natriuretic peptide and weight were as follows: coefficient of variation, 46% and coefficient of variation, 1.2%, respectively. Point-of-care N-terminal prohormone of B-type natriuretic peptide within-person variability over 12 months was 881 pg/ml (95% confidence interval 380 to 1382 pg/ml), whereas between-person variability was 1972 pg/ml (95% confidence interval 1525 to 2791 pg/ml). For individuals, monitoring provided reassurance; future changes, such as increased testing, would be acceptable. Point-of-care testing in general practice surgeries was perceived positively, reducing waiting time and anxiety. Community heart failure nurses had greater knowledge of National Institute for Health and Care Excellence guidance than general practitioners and practice nurses. Health-care professionals believed that the cost of natriuretic peptide tests in routine monitoring would outweigh potential benefits. The review of cost-effectiveness studies suggests that natriuretic peptide-guided treatment is cost-effective in specialist settings, but with no evidence for its value in primary care settings.

Limitations

No randomised controlled trial evidence was generated. The pathways to the benefit of monitoring chronic kidney disease were unclear.

Conclusions

It is difficult to ascribe quantifiable benefits to monitoring chronic kidney disease, because monitoring is unlikely to change treatment, especially in chronic kidney disease stages G3 and G4. New approaches to monitoring chronic heart failure, such as point-of-care natriuretic peptide tests in general practice, show promise if high within-test variability can be overcome.

Future work

The following future work is recommended: improve general practitioner–patient communication of early-stage renal function decline, and identify strategies to reduce the variability of natriuretic peptide.

Study registration

This study is registered as PROSPERO CRD42015017501, CRD42019134922 and CRD42016046902.

Funding

This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 9, No. 10. See the NIHR Journals Library website for further project information.

Impact of hospitalisation on health-related quality of life in patients with chronic heart failure

BACKGROUND

Empirical identification of the direct impact of hospitalisation in the change in utility could provide an interpretation for some of the unexplained variance in quality of life responses in clinical practice and clinical trials and provide assistance to researchers in assessing the impact of a hospitalisation in the context of economic evaluations. This study had the goal of determining the impact of nonfatal hospitalisations on the quality of life of a cohort of patients previously diagnosed with heart failure by using their quality of life measurements before and after hospitalisation.

METHODS

The impact of hospitalisation on health-related quality of life was estimated by calculating the difference in utility measured using the EQ-5D-3L in patients that were hospitalised and had records of utility before and after hospitalisation. The variation in differences between the utilities pre and post hospitalisation was explained through two multiple linear regression models using (1) the individual patient characteristics and (2) the hospitalisation characteristics as explanatory variables.

RESULTS

The mean difference between health-related quality of life measurement pre and post hospitalisation was found to be 0.020 [95% CI: - 0.020, 0.059] when measured with the EQ-5D index, while there was a mean decrease of - 0.012 [95% CI: - 0.043, 0.020] in the utility measured with the visual analogue scale. Differences in utility variation according to the primary cause for hospitalisation were found. Regression models showed a statistically significant impact of body mass index and serum creatinine in the index utility differences and of serum creatinine for utilities measured with the visual analogue scale.

CONCLUSIONS

Knowing the impact of hospitalisation on health-related quality of life is particularly relevant for informing cost-effectiveness studies designed to assess health technologies aimed at reducing hospital admissions. Through using patient-level data it was possible to estimate the variation in utilities before and after the average hospitalisation and for hospitalisations due to the most common causes for hospital admission. These estimates for (dis) utility could be used in the calculations of effectiveness on economic evaluations, especially when discrete event simulations are the employed modelling technique.

How to Address Uncertainty in Health Economic Discrete-Event Simulation Models: An Illustration for Chronic Obstructive Pulmonary Disease

Background. Evaluation of personalized treatment options requires health economic models that include multiple patient characteristics. Patient-level discrete-event simulation (DES) models are deemed appropriate because of their ability to simulate a variety of characteristics and treatment pathways. However, DES models are scarce in the literature, and details about their methods are often missing. Methods. We describe 4 challenges associated with modeling heterogeneity and structural, stochastic, and parameter uncertainty that can be encountered during the development of DES models. We explain why these are important and how to correctly implement them. To illustrate the impact of the modeling choices discussed, we use (results of) a model for chronic obstructive pulmonary disease (COPD) as a case study. Results. The results from the case study showed that, under a correct implementation of the uncertainty in the model, a hypothetical intervention can be deemed as cost-effective. The consequences of incorrect modeling uncertainty included an increase in the incremental cost-effectiveness ratio ranging from 50% to almost a factor of 14, an extended life expectancy of approximately 1.4 years, and an enormously increased uncertainty around the model outcomes. Thus, modeling uncertainty incorrectly can have substantial implications for decision making. Conclusions. This article provides guidance on the implementation of uncertainty in DES models and improves the transparency of reporting uncertainty methods. The COPD case study illustrates the issues described in the article and helps understanding them better. The model R code shows how the uncertainty was implemented. For readers not familiar with R, the model's pseudo-code can be used to understand how the model works. By doing this, we can help other developers, who are likely to face similar challenges to those described here.

Pharmacological interventions for heart failure in people with chronic kidney disease

BACKGROUND

Approximately half of people with heart failure have chronic kidney disease (CKD). Pharmacological interventions for heart failure in people with CKD have the potential to reduce death (any cause) or hospitalisations for decompensated heart failure. However, these interventions are of uncertain benefit and may increase the risk of harm, such as hypotension and electrolyte abnormalities, in those with CKD.

OBJECTIVES

This review aims to look at the benefits and harms of pharmacological interventions for HF (i.e., antihypertensive agents, inotropes, and agents that may improve the heart performance indirectly) in people with HF and CKD.

SEARCH METHODS

We searched the Cochrane Kidney and Transplant Register of Studies through 12 September 2019 in consultation with an Information Specialist and using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Register (ICTRP) Search Portal and ClinicalTrials.gov.

SELECTION CRITERIA

We included randomised controlled trials of any pharmacological intervention for acute or chronic heart failure, among people of any age with chronic kidney disease of at least three months duration.

DATA COLLECTION AND ANALYSIS

Two authors independently screened the records to identify eligible studies and extracted data on the following dichotomous outcomes: death, hospitalisations, worsening heart failure, worsening kidney function, hyperkalaemia, and hypotension. We used random effects meta-analysis to estimate treatment effects, which we expressed as a risk ratio (RR) with 95% confidence intervals (CI). We assessed the risk of bias using the Cochrane tool. We applied the GRADE methodology to rate the certainty of evidence.

MAIN RESULTS

One hundred and twelve studies met our selection criteria: 15 were studies of adults with CKD; 16 studies were conducted in the general population but provided subgroup data for people with CKD; and 81 studies included individuals with CKD, however, data for this subgroup were not provided. The risk of bias in all 112 studies was frequently high or unclear. Of the 31 studies (23,762 participants) with data on CKD patients, follow-up ranged from three months to five years, and study size ranged from 16 to 2916 participants. In total, 26 studies (19,612 participants) reported disaggregated and extractable data on at least one outcome of interest for our review and were included in our meta-analyses. In acute heart failure, the effects of adenosine A1-receptor antagonists, dopamine, nesiritide, or serelaxin on death, hospitalisations, worsening heart failure or kidney function, hyperkalaemia, hypotension or quality of life were uncertain due to sparse data or were not reported. In chronic heart failure, the effects of angiotensin-converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARB) (4 studies, 5003 participants: RR 0.85, 95% CI 0.70 to 1.02; I² = 78%; low certainty evidence), aldosterone antagonists (2 studies, 34 participants: RR 0.61 95% CI 0.06 to 6.59; very low certainty evidence), and vasopressin receptor antagonists (RR 1.26, 95% CI 0.55 to 2.89; 2 studies, 1840 participants; low certainty evidence) on death (any cause) were uncertain. Treatment with beta-blockers may reduce the risk of death (any cause) (4 studies, 3136 participants: RR 0.69, 95% CI 0.60 to 0.79; I² = 0%; moderate certainty evidence). Treatment with ACEi or ARB (2 studies, 1368 participants: RR 0.90, 95% CI 0.43 to 1.90; I² = 97%; very low certainty evidence) had uncertain effects on hospitalisation for heart failure, as treatment estimates were consistent with either benefit or harm. Treatment with beta-blockers may decrease hospitalisation for heart failure (3 studies, 2287 participants: RR 0.67, 95% CI 0.43 to 1.05; I² = 87%; low certainty evidence). Aldosterone antagonists may increase the risk of hyperkalaemia compared to placebo or no treatment (3 studies, 826 participants: RR 2.91, 95% CI 2.03 to 4.17; I² = 0%; low certainty evidence). Renin inhibitors had uncertain risks of hyperkalaemia (2 studies, 142 participants: RR 0.86, 95% CI 0.49 to 1.49; I² = 0%; very low certainty). We were unable to estimate whether treatment with sinus node inhibitors affects the risk of hyperkalaemia, as there were few studies and meta-analysis was not possible. Hyperkalaemia was not reported for the CKD subgroup in studies investigating other therapies. The effects of ACEi or ARB, or aldosterone antagonists on worsening heart failure or kidney function, hypotension, or quality of life were uncertain due to sparse data or were not reported. Effects of anti-arrhythmic agents, digoxin, phosphodiesterase inhibitors, renin inhibitors, sinus node inhibitors, vasodilators, and vasopressin receptor antagonists were very uncertain due to the paucity of studies.

AUTHORS' CONCLUSIONS

The effects of pharmacological interventions for heart failure in people with CKD are uncertain and there is insufficient evidence to inform clinical practice. Study data for treatment outcomes in patients with heart failure and CKD are sparse despite the potential impact of kidney impairment on the benefits and harms of treatment. Future research aimed at analysing existing data in general population HF studies to explore the effect in subgroups of patients with CKD, considering stage of disease, may yield valuable insights for the management of people with HF and CKD.

Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review

BACKGROUND

Heart failure (HF) is a well-recognized public health concern and imposes high economic and societal costs. Decision analytic models exist for evaluating the economic ramifications associated with HF. Despite this, studies that appraise these modelling approaches for augmenting best-practice decisions remain scarce.

OBJECTIVE

Our objective was to conduct a systematic literature review (SLR) of published economic models for the management of HF and describe their general and methodological features.

METHODS

This SLR employed a combination of relevant search terms associated with HF, which were used in a number of databases, including MEDLINE, Embase, the National Health Service Economic Evaluation Database, Cost-Effectiveness Analysis Registry, ScHARR Health Utilities Database and Cochrane Library Database. A number of model features (i.e. model structure, specification, outcomes assessed, scenario and sensitivity analysis, key model drivers) were extracted and subsequently summarized.

RESULTS

Of 64 publications retained, a selection of modelling approaches were identified, including Markov (n = 28), trial-based analytic (n = 22), discrete-event simulation (n = 6), survival analytic (n = 7) and decision-tree modelling (n = 1) approaches. The bulk of publications employed either a cost-utility (n = 27) or cost-effectiveness (n = 36) analysis and evaluated more than one study outcome, which typically included overall costs (n = 59), incremental cost-effectiveness ratios (n = 55), life-years gained (n = 48) and willingness-to-pay thresholds (n = 37). Most publications focused on patients with chronic HF (n = 40) and used New York Heart Association (NYHA) disease classifications to categorize patients and determine disease severity. Few (n = 19) publications documented the use of hospitalization states for modelling patient outcomes and associated costs. A quality assessment of the included publications revealed most articles demonstrated reasonable methodological value.

CONCLUSIONS

We identified numerous decision analytic modelling approaches for evaluating the cost effectiveness of pharmacologic treatments in HF. A Markov cohort model approach was most commonly used, and most models relied on NYHA classes as a proxy of HF severity, disease progression and prognosis.

Quality of health economic evaluations for the ACC/AHA stable ischemic heart disease practice guideline: A systematic review

BACKGROUND

The American College of Cardiology/American Heart Association (ACC/AHA) recently published a rigorous framework to guide integration of economic data into clinical guidelines. We assessed the quality of economic evaluations in a major ACC/AHA clinical guidance report.

METHODS

We systematically identified cost-effectiveness analyses (CEAs) of RCTs cited in the ACC/AHA 2012 Guideline for the Diagnosis and Management of Patients with Stable Ischemic Heart Disease. We extracted: (1) study identifiers; (2) parent RCT information; (3) economic analysis characteristics; and (4) study quality using the Quality of Health Economic Studies instrument (QHES).

RESULTS

Quality scores were categorized as high (≥75 points) or low (<75 points). Of 1,266 citations in the guideline, 219 were RCTs associated with 77 CEAs. Mean quality score was 81 (out of 100) and improved over time, though 29.9% of studies were low-quality. Cost-per-QALY was the most commonly reported primary outcome (39.0%). Low-quality studies were less likely to report study perspective, use appropriate time horizons, or address statistical and clinical uncertainty. Funding was overwhelmingly private (83%). A detailed methodological assessment of high-quality studies revealed domains of additional methodological issues not identified by the QHES.

CONCLUSIONS

Economic evaluations of RCTs in the 2012 ACC/AHA ischemic heart disease guideline largely had high QHES scores but methodological issues existed among "high-quality" studies. Because the ACC/AHA has generally been more systematic in its integration of scientific evidence compared to other professional societies, it is likely that most societies will need to proceed more cautiously in their integration of economic evidence.

When to use discrete event simulation (DES) for the economic evaluation of health technologies? A review and critique of the costs and benefits of DES

Modelling in economic evaluation is an unavoidable fact of life. Cohort-based state transition models are most common, though discrete event simulation (DES) is increasingly being used to implement more complex model structures. The benefits of DES relate to the greater flexibility around the implementation and population of complex models, which may provide more accurate or valid estimates of the incremental costs and benefits of alternative health technologies. The costs of DES relate to the time and expertise required to implement and review complex models, when perhaps a simpler model would suffice. The costs are not borne solely by the analyst, but also by reviewers. In particular, modelled economic evaluations are often submitted to support reimbursement decisions for new technologies, for which detailed model reviews are generally undertaken on behalf of the funding body. This paper reports the results from a review of published DES-based economic evaluations. Factors underlying the use of DES were defined, and the characteristics of applied models were considered, to inform options for assessing the potential benefits of DES in relation to each factor. Four broad factors underlying the use of DES were identified: baseline heterogeneity, continuous disease markers, time varying event rates, and the influence of prior events on subsequent event rates. If relevant, individual-level data are available, representation of the four factors is likely to improve model validity, and it is possible to assess the importance of their representation in individual cases. A thorough model performance evaluation is required to overcome the costs of DES from the users' perspective, but few of the reviewed DES models reported such a process. More generally, further direct, empirical comparisons of complex models with simpler models would better inform the benefits of DES to implement more complex models, and the circumstances in which such benefits are most likely.

Simulation model for cost estimation of integrated care concepts of heart failure patients

BACKGROUND

As a direct result of the population growing older the total number of chronic illnesses increases. The future expenditure for care of chronically ill patients is an ever-present challenge for the health care system. New solutions based on integrated care or the inclusion of telemedical systems in the treatment procedure can be essential for reducing the future financial burden. Therefore a detailed economic model was developed, which enables the comparison of health and cost outcomes for conventional medical care and different integrated care concepts in heart failure treatment.

METHODS

F0r modelling, the discrete event technique was used. The model takes outpatient care as well as inpatient care into account to estimate the total occurring costs. It enables the treatment of patients by a physician, a specialist or a clinical ambulance for the simulation of the outpatient care. For inpatient care the model considers the total-costs of the hospitalization and rate of re-admission and furthermore the costs which occur because of special medical treatments or necessary stay at intensive care units. To rate the severity of symptoms patients can be classified using NYHA groups. To outline some of the potential model results, two scenarios have been simulated to compare both methods of care regarding overall costs.

RESULTS

The developed simulation model allows comparing health and cost outcomes of different integrated care concepts for the treatment of heart failure patients. Additionally to the simulation of standard outpatient and inpatient care procedures in Austria the approach of a telemedical monitoring system for heart failure patients was implemented in this economic model. With the simulated scenarios it could be shown that under the given simulation parameters the telemedical system can lead to cost savings of up to 8% within the first three years.

CONCLUSIONS

The developed model represents a comprehensive tool, which opens a wide field of possible simulation scenarios for the treatment of heart failure patients with special focus on overall cost estimations and reimbursement strategies. The simulated scenarios show that telemedical care has the potential of improved health outcomes and economic benefits.

Cost-effectiveness of heart failure therapies

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. Management of HF involves accurate diagnosis and implementation of evidence-based treatment strategies. Costs related to the care of patients with HF have increased substantially over the past 2 decades, partly owing to new medications and diagnostic tests, increased rates of hospitalization, implantation of costly novel devices and, as the disease progresses, consideration for heart transplantation, mechanical circulatory support, and end-of-life care. Not surprisingly, HF places a huge burden on health-care systems, and widespread implementation of all potentially beneficial therapies for HF could prove unrealistic for many, if not all, nations. Cost-effectiveness analyses can help to quantify the relationship between clinical outcomes and the economic implications of available therapies. This Review is a critical overview of cost-effectiveness studies on key areas of HF management, involving pharmacological and nonpharmacological clinical therapies, including device-based and surgical therapeutic strategies.

Decision-analytic models to simulate health outcomes and costs in heart failure: a systematic review

Chronic heart failure (CHF) is a critical public health issue with increasing effect on the healthcare budgets of developed countries. Various decision-analytic modelling approaches exist to estimate the cost effectiveness of health technologies for CHF. We sought to systematically identify these models and describe their structures. We performed a systematic literature review in MEDLINE/PreMEDLINE, EMBASE, EconLit and the Cost-Effectiveness Analysis Registry using a combination of search terms for CHF and decision-analytic models. The inclusion criterion required 'use of a mathematical model evaluating both costs and health consequences for CHF management strategies'. Studies that were only economic evaluations alongside a clinical trial or that were purely descriptive studies were excluded. We identified 34 modelling studies investigating different interventions including screening (n = 1), diagnostics (n = 1), pharmaceuticals (n = 15), devices (n = 13), disease management programmes (n = 3) and cardiac transplantation (n = 1) in CHF. The identified models primarily focused on middle-aged to elderly patients with stable but progressed heart failure with systolic left ventricular dysfunction. Modelling approaches varied substantially and included 27 Markov models, three discrete-event simulation models and four mathematical equation sets models; 19 studies reported QALYs. Three models were externally validated. In addition to a detailed description of study characteristics, the model structure and output, the manuscript also contains a synthesis and critical appraisal for each of the modelling approaches. Well designed decision models are available for the evaluation of different CHF health technologies. Most models depend on New York Heart Association (NYHA) classes or number of hospitalizations as proxy for disease severity and progression. As the diagnostics and biomarkers evolve, there is the hope for better intermediate endpoints for modelling disease progression as those that are currently in use all have limitations.

What are the costs of heart failure?

Heart failure , a syndrome associated with increasing prevalence, high mortality, and frequent hospital admissions, imposes a significant economic burden on western healthcare systems that is expected to further increase in the future due to the ageing population. Hospitalizations are responsible for the largest part of treatment costs and, thus, the main target for strategies aiming at cost reduction. Current literature suggests that evidence-based therapy with drugs, devices, and modern disease management programmes improves clinical outcomes of the large population of heart failure patients in a largely cost-effective manner. However, comprehensive knowledge about the cost of treatment is important to guide clinicians in the responsible allocation of today's limited health-care resources. This review provides information about the total cost of heart failure and the contribution of different treatment components to the overall costs.

A cost-saving strategy for inpatient management of advanced decompensated heart failure patients: the Cardiomyopathy Unit

BACKGROUND

This article analyzes the relative costs and revenues of the Tufts Medical Center Cardiomyopathy Unit (CMU), a recent innovation for grouping and managing advanced decompensated heart failure patients.

METHODS AND RESULTS

We selected a retrospective sample of all patients with the primary diagnosis of heart failure, primary procedure of pulmonary artery catheterization, and with no other hospitalization procedures, admitted to Tufts Medical Center between 2000 and 2006. Regression models were used to estimate the cost for the intervention group and controls. Propensity analysis was used to test for selection bias in the comparison groups. We identified 114 hospitalizations meeting these criteria. Patients in the CMU group were well-balanced compared with controls with respect to demographic and clinical variables. Estimated direct medical costs for CMU and control groups were $11,817 (95% CI $7678-$16,106) and $17,236 (95% CI $11,199-$23,493), respectively. A similar pattern of cost differentials was displayed among propensity-matched sample groups. Net revenue was $12,609 (95% CI $9578-$16,845) and $15,627 (95% CI $11,871-$20,877) in the CMU and control groups, respectively.

CONCLUSIONS

The inpatient CMU may offer a lower cost and higher contribution margin alternative for the management of advanced heart failure patients requiring hemodynamic monitoring without other major inpatient procedures.

Economic burden of heart failure in the elderly

Heart failure (HF) ranks among the most costly chronic diseases in developed countries. At present these countries devote 1-2% of all healthcare expenditures towards HF. In the US, these costs are estimated at $US30.2 billion for 2007. The burden of HF is greatest among the elderly, with 80% of HF hospitalizations and 90% of HF-related deaths in this cohort. As a result, approximately three-quarters of the resources for HF care are consumed by elderly patients. As demographic shifts increase the number of elderly individuals in both developed and developing nations, the resources devoted to HF care will likely further increase. Hospitalization accounts for roughly two-thirds of HF costs, but procedures, outpatient visits and medications also consume significant financial resources. HF also adversely impacts patient quality of life, and these relevant effects may not be captured in pure cost analyses. The cost effectiveness of several pharmacological interventions has been explored. In general, neurohormonal antagonists used for outpatient treatment of chronic HF are relatively cost effective, in part by reducing hospitalizations. Because HF poses such an enormous financial burden, efficient resource allocation for its management is a major societal and governmental challenge. In order to make informed decisions and allocate resources for HF care rationally, detailed data regarding costs and resource use will be essential. Further studies are needed to examine the impact of pharmacological and non-pharmacological interventions on costs and resource use in elderly individuals with HF.

Clinical Reminders Attached to Echocardiography Reports of Patients With Reduced Left Ventricular Ejection Fraction Increase Use of β-Blockers

Background— Although β-blockers are known to prolong survival for patients with reduced left ventricular ejection fraction, they are often underused. We hypothesized that a reminder attached to the echocardiography report would increase the use of β-blockers for patients with reduced left ventricular ejection fraction.

Methods and Results— We randomized 1546 consecutive patients with a left ventricular ejection fraction <45% found on echocardiography at 1 of 3 laboratories to a reminder for use of β-blockers or no reminder. Patients were excluded from analysis if they died within 30 days of randomization (n=89), did not receive medications through the Veterans Affairs system after 30 days (n=180), or underwent echocardiography at >1 laboratory (n=6). The primary outcome was a prescription for an oral β-blocker between 1 and 9 months after randomization. The mean age of the 1271 included patients was 69 years; 60% had a history of heart failure, and 51% were receiving treatment with β-blockers at the time of echocardiography. More patients randomized to the reminder had a subsequent β-blocker prescription (74%, 458 of 621) compared with those randomized to no reminder (66%, 428 of 650; P =0.002). The effect of the reminder was not significantly different for subgroups based on patient location (inpatient versus outpatient) or prior use of β-blockers.

Conclusions— A reminder attached to the echocardiography report increased the use of β-blockers in patients with depressed left ventricular systolic function.