(9) Cost-effectiveness of screening strategies to detect heart failure in patients with type 2 diabetes

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Papers

PMCID: 4802923 (link)

Year: 2016

Reviewer Paper ID: 9

Project Paper ID: 47

Q1 - Title

Question description: Does the title clearly identify the study as an economic evaluation and specify the interventions being compared?

Explanation: The title of the manuscript clearly indicates that the study is an economic evaluation by using the term 'cost-effectiveness' and specifies the interventions being compared, which are 'screening strategies to detect heart failure in patients with type 2 diabetes.'

Quotes:

  • Title: 'Cost-effectiveness of screening strategies to detect heart failure in patients with type 2 diabetes'

Q2 - Abstract

Question description: Does the abstract provide a structured summary that includes the context, key methods, results, and alternative analyses?

Explanation: The abstract is structured and includes context, key methods, results, and alternative analyses. It outlines the importance of early HF detection in T2DM patients, the description of a Markov model used for cost-effectiveness analysis, the main cost-effectiveness results for different willingness-to-pay thresholds, and scenario analyses considering HFpEF treatments.

Quotes:

  • Early HF detection in older T2DM patients may be worthwhile because treatment may be initiated in an early stage...
  • We assessed the cost-effectiveness of five screening strategies in patients with T2DM aged 60 years or over.
  • Cost-effectiveness of all screening strategies improved with the increase in effectiveness of treatment for HFpEF.

Q3 - Background and objectives

Question description: Does the introduction provide the context for the study, the study question, and its practical relevance for decision-making in policy or practice?

Explanation: The introduction section provides a detailed context for the study by highlighting the prevalence and risks of heart failure in older T2DM patients, clarifies the study question regarding the cost-effectiveness of various screening strategies, and discusses its practical relevance for policy implementation by suggesting the potential for large-scale implementation in primary care settings.

Quotes:

  • Type 2 diabetes mellitus (T2DM) is known to increase the risk for cardiovascular disease, including coronary artery disease and 'diabetic cardiomyopathy'.
  • ...27.7 % had unrecognized heart failure (HF)...
  • Early HF detection in older T2DM patients may be worthwhile because treatment may be initiated in an early stage.
  • ...there is no such HF screening program among older community-dwelling T2DM patients diabetes in the Netherlands. We therefore assessed the long-term health effect and costs of five screening strategies...

Q4 - Health economic analysis plan

Question description: Was a health economic analysis plan developed, and if so, where is it available?

Explanation: There is no mention in the manuscript of a specific health economic analysis plan being developed or where it might be available. The text extensively discusses the methods, model, and analyses performed, but it doesn't refer to a separate health economic analysis plan.

Quotes:

  • "In the base-case analysis we assumed no beneficial prognostic effects of treatment for patients with HFpEF. We performed scenario analyses in which we evaluated the cost-effectiveness considering varying prognostic beneficial treatment effects in this type of HF."
  • "To assess long-term consequences in terms of costs and health effects of the five screening strategies compared to no screening (usual care), a Markov decision analytic cohort model of HF progression was developed (Fig. 1)."

Q5 - Study population

Question description: Are the characteristics of the study population (e.g., age range, demographics, socioeconomic, or clinical characteristics) described?

Explanation: The study population characteristics are described in terms of the age, gender, history of specific diseases, and symptoms used in the screening strategies within the methods section. The study specifically focused on patients with type 2 diabetes aged 60 years or over, providing insights on clinical and demographic traits.

Quotes:

  • We assessed the cost-effectiveness of five screening strategies in patients with T2DM aged 60 years or over.
  • All T2DM patients enlisted in primary care practices in the South-West of the Netherlands were eligible to participate.
  • All 581 participants underwent a 1-day standardized diagnostic assessment including history taking, physical examination, electrocardiography (ECG), blood tests, and echocardiography.

Q6 - Setting and location

Question description: Is relevant contextual information (such as setting and location) provided that may influence the findings of the study?

Explanation: The manuscript provides relevant contextual information, including details on the setting and location which may influence study findings. It specifies that the study was conducted within Dutch primary care practices and incorporates Dutch healthcare guidelines and cost parameters which shape the study outcomes.

Quotes:

  • We built a Markov model with a lifetime horizon... Cost-effectiveness was calculated from a Dutch healthcare perspective as additional costs (Euros) per additional quality-adjusted life-year (QALY) gained.
  • The study complied with the declaration of Helsinki and was approved by the institutional review and ethics boards of the University Medical Center Utrecht and the Admiraal de Ruyter Hospital in Goes, the Netherlands.
  • All T2DM patients enlisted in primary care practices in the South-West of the Netherlands were eligible to participate.

Q7 - Comparators

Question description: Are the interventions or strategies being compared described, along with the rationale for their selection?

Explanation: The manuscript provides a detailed description of the five screening strategies being compared for detecting heart failure in older type 2 diabetes patients. It also discusses the rationale for selecting these strategies, which include leveraging the electronic medical record and symptoms assessment, with some incorporating physical examination, NTproBNP measurement, ECG, and direct echocardiography.

Quotes:

  • "We assessed the cost-effectiveness of five screening strategies in patients with T2DM aged 60 years or over."
  • "EMR/symptoms; a strategy based on information available from the Electronic Medical Record (EMR) of general practitioners, i.e., age, gender, history of ischaemic heart disease, asthma or COPD, hypertension, peripheral arterial disease, transient ischaemic attack or stroke, combined with the assessment of presence of the following symptoms; dyspnea, fatigue, ankle oedema, nocturia, or palpitations.
  • "For willingness to pay values in the range of $6050/QALY-$31,000/QALY for men and $6300/QALY-$42,000/QALY for women, screening-based checking the electronic medical record for patient characteristics and medical history plus the assessment of symptoms had the highest probability of being cost-effective."

Q8 - Perspective

Question description: What perspective(s) were adopted by the study, and why were they chosen?

Explanation: The study adopted a Dutch healthcare perspective in its cost-effectiveness analysis. This perspective was chosen as it incorporates costs directly related to screening, diagnosis, and heart failure-related healthcare costs, which are crucial for evaluating the financial implications within the Dutch primary care context for patients with heart failure and type 2 diabetes.

Quotes:

  • "Cost-effectiveness was calculated from a Dutch healthcare perspective as additional costs (Euros) per additional quality-adjusted life-year (QALY) gained."
  • "Our analysis was conducted from a healthcare perspective, incorporating costs directly related to screening and diagnosis, and HF-related costs for detected and undetected HF patients within different NYHA-classes."

Q9 - Time horizon

Question description: What is the time horizon for the study, and why is it appropriate?

Explanation: The manuscript specifies that the study utilizes a lifetime horizon for its cost-effectiveness analysis, which is often appropriate in health economics to fully capture all long-term costs and benefits of interventions over the entire remaining lifespan of the patient cohort.

Quotes:

  • We built a Markov model with a lifetime horizon based on the prognostic results from our screening study of 581 patients with T2DM, extended with evidence from literature.
  • The model was designed to simulate hypothetical cohorts of men and women with T2DM initially screened for HF at age 60.
  • The simulation stopped when all 581 patients in the hypothetical cohort had died.

Q10 - Discount rate

Question description: What discount rate(s) were used, and what was the rationale for choosing them?

Explanation: The article does not specify the rationale for using the discount rates, but it does mention the rates used for discounting costs and health effects.

Quotes:

  • Life-years, QALYs, and costs per person were calculated over a lifetime horizon, with costs and health effects discounted at 4 and 1.5 % per year, respectively, according to Dutch guidelines.

Q11 - Selection of outcomes

Question description: What outcomes were used as measures of benefit and harm?

Explanation: The manuscript identifies specific outcomes to measure benefits and harms in terms of life-years, QALYs, and costs. These outcomes are important in the context of assessing the effectiveness of the screening strategies for heart failure in patients with type 2 diabetes.

Quotes:

  • Cost-effectiveness was calculated from a Dutch healthcare perspective as additional costs (Euros) per additional quality-adjusted life-year (QALY) gained.
  • Health effects were determined by calculating expected life-years and quality-adjusted life-years (QALYs).
  • Life-years, QALYs, and costs per person were calculated over a lifetime horizon, with costs and health effects discounted at 4 and 1.5 % per year, respectively, according to Dutch guidelines.

Q12 - Measurement of outcomes

Question description: How were the outcomes used to capture benefits and harms measured?

Explanation: The outcomes used to capture benefits and harms in the study were primarily measured in terms of life-years, quality-adjusted life-years (QALYs), and costs. The study employed a Markov model over a lifetime horizon to assess the long-term health effects and costs of various screening strategies, assigning utility scores to different health states based on EuroQol-5D (EQ5D) measurements. These methodologies effectively captured both the benefits of early heart failure detection and treatment, as well as the costs associated with different screening strategies.

Quotes:

  • Cost-effectiveness was calculated from a Dutch healthcare perspective as additional costs (Euros) per additional quality-adjusted life-year (QALY) gained.
  • Health outcomes were determined by calculating expected life-years and quality-adjusted life-years (QALYs). Utilities for each of the eight HF states and the state of diabetes without HF were based on the EQ5D-scores obtained in the UHFO-DM2 study.
  • A Markov decision analytic cohort model of HF progression was developed... long-term expected health effects and costs of each (screening) strategy can be calculated by multiplying the total time spent in each state by the utilities and costs corresponding to these states.

Q13 - Valuation of outcomes

Question description: What population and methods were used to measure and value the outcomes?

Explanation: The article explains that a population of T2DM patients aged 60 years or over was used and employed a Markov model to measure outcomes. The model used transition probabilities based on different health states, calculated QALYs, and assigned utilities and costs to these states.

Quotes:

  • We assessed the cost-effectiveness of five screening strategies in patients with T2DM aged 60 years or over.
  • We built a Markov model with a lifetime horizon based on the prognostic results from our screening study of 581 patients with T2DM, extended with evidence from literature.
  • Each health state is assigned a (time-dependent) utility and cost. The long-term expected health effects and costs of each (screening) strategy can be calculated by multiplying the total time spent in each state by the utilities and costs corresponding to these states, respectively.

Q14 - Measurement and valuation of resources and costs

Question description: How were the costs valued in the study?

Explanation: The article describes that costs were valued based on tariffs set by the Dutch Healthcare Authority. It states that the analysis considered both direct screening costs and long-term heart failure-related costs. Specific details about costs covering investigations, consultations, and long-term management were based on Dutch guidelines and specific tariffs.

Quotes:

  • All costs were based on tariffs set by the Dutch Healthcare Authority (1 January 2011) according to Dutch guidelines.
  • Our analysis was conducted from a healthcare perspective, incorporating costs directly related to screening and diagnosis, and HF-related costs for detected and undetected HF patients within different NYHA-classes.

Q15 - Currency, price, date, and conversion

Question description: What are the dates of the estimated resource quantities and unit costs, and what currency and year were used for conversion?

Explanation: The manuscript states that all costs were based on tariffs set by the Dutch Healthcare Authority as of 1 January 2011, but it does not specify any estimation dates for resource quantities. Additionally, it mentions that cost calculations and findings are in Euros, but no specific conversion year is provided for the currency itself.

Quotes:

  • All costs were based on tariffs set by the Dutch Healthcare Authority (1 January 2011) according to Dutch guidelines.
  • Cost-effectiveness was calculated from a Dutch healthcare perspective as additional costs (Euros) per additional quality-adjusted life-year (QALY) gained.

Q16 - Rationale and description of model

Question description: If a model was used, was it described in detail, including the rationale for its use? Is the model publicly available, and where can it be accessed?

Explanation: The manuscript describes the Markov model used in the study in detail, including the rationale for its use, but it does not mention the public availability of the model or where it can be accessed.

Quotes:

  • We built a Markov model with a lifetime horizon based on the prognostic results from our screening study of 581 patients with T2DM, extended with evidence from literature.
  • To assess long-term consequences in terms of costs and health effects of the five screening strategies compared to no screening (usual care), a Markov decision analytic cohort model of HF progression was developed.
  • Markov models assume that a patient is always in one of the predefined health states... and use transition probabilities to allow patients to transition between health states over time.

Q17 - Analytics and assumptions

Question description: What methods were used for analyzing or statistically transforming data, extrapolation, and validating any models used?

Explanation: The article uses a Markov model to simulate the long-term consequences in terms of costs and health effects of the screening strategies, considers transition probabilities, and assigns utilities and costs to different health states. Probabilistic sensitivity analyses were performed using Monte Carlo simulation to evaluate robustness.

Quotes:

  • To assess long-term consequences in terms of costs and health effects of the five screening strategies compared to no screening (usual care), a Markov decision analytic cohort model of HF progression was developed.
  • Probabilistic sensitivity analyses were performed using Monte Carlo simulation based on 10,000 samples.
  • Each health state is assigned a (time-dependent) utility and cost.

Q18 - Characterizing heterogeneity

Question description: What methods were used to estimate how the results vary for different sub-groups?

Explanation: The manuscript does not specify any methods used to estimate how results vary for different sub-groups. It primarily focuses on comparing screening strategies for heart failure in older T2DM patients but does not discuss specific sub-group analysis methods.

Quotes:

  • We built a Markov model with a lifetime horizon based on the prognostic results from our screening study of 581 patients with T2DM, extended with evidence from literature. Cost-effectiveness was calculated from a Dutch healthcare perspective as additional costs (Euros) per additional quality-adjusted life-year (QALY) gained.
  • To assess robustness of the results given the uncertainty in the evidence (Table 2), probabilistic sensitivity analyses were performed using Monte Carlo simulation based on 10,000 samples.

Q19 - Characterizing distributional effects

Question description: How were the impacts distributed across different individuals, and were adjustments made to reflect priority populations?

Explanation: The manuscript primarily focuses on the cost-effectiveness of different heart failure screening strategies for patients with type 2 diabetes aged 60 and over. It does not specifically discuss the distribution of impacts across different individuals or make explicit adjustments to reflect priority populations.

Quotes:

  • Screening-based checking the electronic medical record for patient characteristics and medical history plus the assessment of symptoms had the highest probability of being cost-effective.
  • The model was designed to simulate hypothetical cohorts of men and women with T2DM initially screened for HF at age 60.
  • Although we did account for higher health-care costs for individuals with undetected HF, we did not consider the costs of a possible acute life-threatening exacerbation of HF necessitating hospital admission.

Q20 - Characterizing uncertainty

Question description: What methods were used to characterize sources of uncertainty in the analysis?

Explanation: The manuscript mentions that probabilistic sensitivity analysis was used to assess the robustness of outcomes, addressing sources of uncertainty. This analysis helps to quantify the impact of variable inputs on the model outcomes and provides insight into the stability of results under uncertain conditions.

Quotes:

  • We performed probabilistic sensitivity analysis to assess robustness of these outcomes.
  • To assess robustness of the results given the uncertainty in the evidence (Table 2), probabilistic sensitivity analyses were performed using Monte Carlo simulation based on 10,000 samples.

Q21 - Approach to engagement with patients and others affected by the study

Question description: Were patients, service recipients, the general public, communities, or stakeholders engaged in the design of the study? If so, how?

Explanation: The manuscript does not mention any engagement of patients, service recipients, the general public, communities, or other stakeholders in the design of the study. The text focuses on describing the study methodology, which involves a screening study of patients with type 2 diabetes, but does not mention stakeholder involvement in the study design.

Quotes:

  • The UHFO-DM2 study... All T2DM patients enlisted in primary care practices in the South-West of the Netherlands were eligible to participate.
  • The study complied with the declaration of Helsinki and was approved by the institutional review and ethics boards of the University Medical Center Utrecht and the Admiraal de Ruyter Hospital in Goes, the Netherlands.

Q22 - Study parameters

Question description: Were all analytic inputs or study parameters (e.g., values, ranges, references) reported, including uncertainty or distributional assumptions?

Explanation: The manuscript provides a comprehensive report of analytic inputs and study parameters, including sensitivity, specificity, and costs for screening strategies, as well as uncertainties expressed as distributions (e.g., Beta and Gamma) for these parameters. This information is detailed in the methods and supplementary tables within the document.

Quotes:

  • - 'For each screening strategy NYHA-specific sensitivities were calculated and for each of these sensitivities a beta-distribution was specified with the true positives and total positives as parameters. Similarly, beta distributions were assigned to the specificities of each of the screening strategies. Gamma distributions with parameters using a variance equal to the mean were used for the costs.'
  • - 'Input parameters for the Markov model men and women with type 2 diabetes of 60 years or older'
  • - 'To assess robustness of the results given the uncertainty in the evidence (Table 2), probabilistic sensitivity analyses were performed using Monte Carlo simulation based on 10,000 samples.'

Q23 - Summary of main results

Question description: Were the mean values for the main categories of costs and outcomes reported, and were they summarized in the most appropriate overall measure?

Explanation: The manuscript reports mean values for the main categories of costs and outcomes. Specific costs and quality-adjusted life-years (QALYs) for different screening strategies are summarized, and incremental cost-effectiveness ratios (ICERs) are presented to provide a comprehensive measure of overall cost-effectiveness.

Quotes:

  • 'Life-years, QALYs, and costs per person were calculated over a lifetime horizon, with costs and health effects discounted at 4 and 1.5 % per year, respectively, according to Dutch guidelines.'
  • 'The incremental cost-effectiveness ratios (ICERs) were calculated by first ranking all strategies in order of improving health outcomes and calculating the additional costs of obtaining these health outcomes.'
  • 'The incremental comparison of expected life years, QALYs, costs, and ICERs for five screening strategies for heart failure in patients with type 2 diabetes of 60 years or older.'

Q24 - Effect of uncertainty

Question description: How did uncertainty about analytic judgments, inputs, or projections affect the findings? Was the effect of the choice of discount rate and time horizon reported, if applicable?

Explanation: The manuscript reports on the effect of various models and assumptions used in the Markov model evaluation, such as different scenarios of medication effectiveness for HFpEF. However, the specific impact of the choice of discount rate and time horizon is not directly discussed, although the general influence of modeling choices is assessed through sensitivity analyses and scenario analyses, suggesting these factors were considered.

Quotes:

  • To assess robustness of the results given the uncertainty in the evidence, probabilistic sensitivity analyses were performed using Monte Carlo simulation based on 10,000 samples.
  • Health effects were determined by calculating expected life-years and quality-adjusted life-years (QALYs). Utilities for each of the eight HF states and the state of diabetes without HF were based on the EQ5D-scores obtained in the UHFO-DM2 study.
  • Life-years, QALYs, and costs per person were calculated over a lifetime horizon, with costs and health effects discounted at 4 and 1.5 % per year, respectively, according to Dutch guidelines.

Q25 - Effect of engagement with patients and others affected by the study

Question description: Did patient, service recipient, general public, community, or stakeholder involvement make a difference to the approach or findings of the study?

Explanation: The manuscript focuses on the cost-effectiveness analysis of screening strategies for heart failure in patients with type 2 diabetes, and it does not mention any involvement of patients, service recipients, the general public, community members, or other stakeholders in the study design, execution, or analysis. Thus, it cannot be determined that such involvement made a difference to the approach or findings of the study.

Quotes:

  • The study complied with the declaration of Helsinki and was approved by the institutional review and ethics boards of the University Medical Center Utrecht and the Admiraal de Ruyter Hospital in Goes, the Netherlands.
  • All 581 participants underwent a 1-day standardized diagnostic assessment including history taking, physical examination, electrocardiography (ECG), blood tests, and echocardiography.
  • Our model was based on real-life medication prescriptions in screen-detected HF cases from a cohort study in 581 T2DM patients aged 60 years or over.
  • Currently, there is no such HF screening program among older community-dwelling T2DM patients diabetes in the Netherlands.

Q26 - Study findings, limitations, generalizability, and current knowledge

Question description: Were the key findings, limitations, ethical or equity considerations, and their potential impact on patients, policy, or practice reported?

Explanation: The manuscript contains explicit discussions on key findings, limitations, equity considerations, and potential impacts on patients and policy. Key findings are discussed, particularly the cost-effectiveness of certain screening strategies for heart failure among T2DM patients. The limitations are acknowledged, such as the lack of consideration for acute exacerbations. Ethical considerations related to patient consent and adherence to ethical guidelines are also mentioned.

Quotes:

  • Conclusions: Screening for heart failure...is cost-effective at the commonly used willingness-to-pay threshold of $20,000/QALY.
  • Screening community-dwelling T2DM patients of 60 years or over annually for HF in the Dutch primary care setting results in a small increase in life expectancy and QALYs at relatively low costs.
  • Study complied with the declaration of Helsinki and was approved by the institutional review and ethics boards.
  • Strengths and limitations of the study:...However, when evaluating screening strategies often a single cut-off is used and the 20 % cut-off we applied has been used in earlier studies. Although we did account for higher health-care costs...

SECTION: TITLE
Cost-effectiveness of screening strategies to detect heart failure in patients with type 2 diabetes


SECTION: ABSTRACT
Background

Heart failure (HF), especially with preserved ejection fraction (HFpEF) is common in older patients with type 2 diabetes (T2DM), but often not recognized. Early HF detection in older T2DM patients may be worthwhile because treatment may be initiated in an early stage, with clear beneficial treatment in those with reduced ejection fraction (HFrEF), but without clear prognostic beneficial treatment in those with HFpEF. Because both types of HF may be uncovered in older T2DM, screening may improve health outcomes at acceptable costs. We assessed the cost-effectiveness of five screening strategies in patients with T2DM aged 60 years or over.We assessed the cost-effectiveness of five screening strategies in patients with T2DM aged 60 years or over.

Methods

We built a Markov model with a lifetime horizon based on the prognostic results from our screening study of 581 patients with T2DM, extended with evidence from literature.We built a Markov model with a lifetime horizon based on the prognostic results from our screening study of 581 patients with T2DM, extended with evidence from literature. with T2DM, extended with evidence from literature. Cost-effectiveness was calculated from a Dutch healthcare perspective as additional costs (Euros) per additional quality-adjusted life-year (QALY) gained.Cost-effectiveness was calculated from a Dutch healthcare perspective as additional costs (Euros) per additional quality-adjusted life-year (QALY) gained.Cost-effectiveness was calculated from a Dutch healthcare perspective as additional costs (Euros) per additional quality-adjusted life-year (QALY) gained. We performed probabilistic sensitivity analysis to assess robustness of these outcomes. Scenario analyses were performed to assess the influence of the availability of effective treatment of heart failure with preserved ejection fraction.

Results

For willingness to pay values in the range of $6050/QALY-$31,000/QALY for men and $6300/QALY-$42,000/QALY for women, screening-based checking the electronic medical record for patient characteristics and medical history plus the assessment of symptoms had the highest probability of being cost-effective.
For higher willingness-to-pay values, direct echocardiography was the preferred screening strategy. Cost-effectiveness of all screening strategies improved with the increase in effectiveness of treatment for HFpEF.

Conclusions

Screening for HF in older community-dwelling patients with T2DM is cost-effective at the commonly used willingness-to-pay threshold of $20.000/QALY by checking the electronic medical record for patient characteristics and medical history plus the assessment of symptoms. The simplicity of such a strategy makes it feasible for implementation in existing primary care diabetes management programs.

SECTION: INTRO
Background

Type 2 diabetes mellitus (T2DM) is known to increase the risk for cardiovascular disease, including coronary artery disease and 'diabetic cardiomyopathy'. Heart disease is hence a major cause of death among T2DM patients. In a screening study, we recently showed that among T2DM patients aged 60 years or over, 27.7 % had unrecognized heart failure (HF); 22.9 % HF with preserved ejection fraction (HFpEF) and 4.8 % HF with reduced ejection fraction (HFrEF). For HFrEF prognostically beneficial treatment is available, while this is lacking for HFpEF. New drugs for HFpEF, however, are currently under investigation.

Early HF detection in older T2DM patients may be worthwhile because treatment may be initiated in an early stage.
Moreover, adequate diagnosis of HF may prevent misclassification of symptoms, such as shortness of breath as a respiratory disease. However, in the light of limited healthcare resources, balancing healthcare interventions and costs has become increasingly important. Screening older T2DM patients for HF will induce costs for testing, as well as downstream costs for additional check-ups and treatment. On the other hand, early HF detection may increase health effects through early treatment initiation. As treatment may prevent HF progression, this might save costs on the long-term. If a screening strategy shows it can achieve health effects at acceptable costs, large-scale implementation within existing primary care diabetes management programs may be advocated. Currently, there is no such HF screening program among older community-dwelling T2DM patients diabetes in the Netherlands. We therefore assessed the long-term health effect and costs of five screening strategies to detect HF in T2DM patients aged 60 years or over in the Dutch primary care setting.

SECTION: METHODS
Methods

The UHFO-DM2 study

We conducted the 'UHFO-DM2' screening study from February 2009 to March 2010, within which participants were followed for 1 year. All T2DM patients enlisted in primary care practices in the South-West of the Netherlands were eligible to participate.All T2DM patients enlisted in primary care practices in the South-West of the Netherlands were eligible to participate. In total 581 patients who did not already have a cardiologist-confirmed diagnosis of HF and gave written informed consent were included in the study. The study complied with the declaration of Helsinki and was approved by the institutional review and ethics boards of the University Medical Center Utrecht and the Admiraal de Ruyter Hospital in Goes, the Netherlands.The study complied with the declaration of Helsinki and was approved by the institutional review and ethics boards of the University Medical Center Utrecht and the Admiraal de Ruyter Hospital in Goes, the Netherlands. The study is registered in the register of the Central Committee on Research Involving Human Subjects (NL22717.041.08).

All 581 participants underwent a 1-day standardized diagnostic assessment including history taking, physical examination, electrocardiography (ECG), blood tests, and echocardiography. Presence of HF (HFpEF or HFrEF) was determined by an expert-panel consisting of two cardiologists and an experienced general practitioner (GP) who followed the criteria for HF of the recent European Society of Cardiology guidelines. Preference-based utilities were measured with the EuroQol-5D (EQ5D) instrument during the baseline visit. After 3 and 12 months the participants filled out the same questionnaires, plus an additional questionnaire on medication use.

Overview of the screening strategies

EMR/symptoms; a strategy based on information available from the Electronic Medical Record (EMR) of general practitioners, i.e., age, gender, history of ischaemic heart disease, asthma or COPD, hypertension, peripheral arterial disease, transient ischaemic attack or stroke, combined with the assessment of presence of the following symptoms; dyspnea, fatigue, ankle oedema, nocturia, or palpitations.


EMR/symptoms/PhysicalExam; strategy 1 plus features from the physical examination (PE): pulmonary crepitations, jugular venous distension, ankle oedema, or a laterally displaced apex beat.

EMR/symptoms/PhysicalExam/NTproBNP; strategy 2 plus measurement of natriuretic peptide (NTproBNP) applying the exclusionary cut-point of 15 pmol/L ( 125 pg/ml).

EMR/symptoms/PhysicalExam/NTproBNP/ECG; strategy 3 plus ECG.

Echocardiography; everybody is directly referred for echocardiography.

We assessed the cost-effectiveness of five screening strategies:

Strategy 1 to 4 are based on recently developed diagnostic screening models to estimate the risk of HF in T2DM patients. A risk of 20 % was used for ruling out HF, and to estimate the sensitivity and specificity of the different strategies. In our screening models, patients were referred for echocardiography if the HF risk was =20 %. All the initial, once-in-a-life screening strategies were followed by annual assessment of EMR/symptoms.

Model structure

SECTION: FIG
Schematic representation of the model structure. NYHA New York Heart Association, HF heart failure. Within each NYHA state patients can either have detected or undetected heart failure. Following the screening strategy patients can be diagnosed with heart failure and transition from the undetected to the detected state may take place. Patients can transition from NYHA IV to NYHA I because of the (small) probability of transitioning to a better NYHA state in 1 month. From the diabetes without HF and any of the NYHA states individuals can die from causes other than HF and transition to 'Death other'

SECTION: METHODS
To assess long-term consequences in terms of costs and health effects of the five screening strategies compared to no screening (usual care), a Markov decision analytic cohort model of HF progression was developed

To assess long-term consequences in terms of costs and health effects of the five screening strategies compared to no screening (usual care), a Markov decision analytic cohort model of HF progression was developed
(Fig. 1). Markov models assume that a patient is always in one of the predefined health states. In this, here representing HF progression, and use transition probabilities to allow patients to transition between health states over time. Each health state is assigned a (time-dependent) utility and cost. The long-term expected health effects and costs of each (screening) strategy can be calculated by multiplying the total time spent in each state by the utilities and costs corresponding to these states, respectively.Each health state is assigned a (time-dependent) utility and cost. The long-term expected health effects and costs of each (screening) strategy can be calculated by multiplying the total time spent in each state by the utilities and costs corresponding to these states, respectively. We refer to the literature for further information..

The model was designed to simulate hypothetical cohorts of men and women with T2DM initially screened for HF at age 60. The model employed 3-months' time cycles, corresponding to the regular interval of diabetes consultations and a lifetime horizon, i.e., the simulation stopped when all 581 patients in the hypothetical cohort had died. In the model, all individuals started in the diabetes without HF health state, or one of the four HF states based on the four New York Heart Association (NYHA) classes, subdivided in the categories 'detected' or 'undetected'. In all screening, strategies individuals suspected of HF underwent echocardiography as the cornerstone investigation, which was assumed to be the reference standard with a sensitivity and specificity of 1.0.

Individuals without HF at the time of the initial screening could develop HF in subsequent years, which would transfer them to the health state NYHA II undetected. They could then be detected by the subsequent annual screening similar to the individuals with HF who were missed with the initial screening. Finally, all individuals could die from causes unrelated to HF, while HF patients could also die because of HF.

Input parameters

SECTION: TABLE
Sensitivity, specificity, and costs of heart failure screening strategies in patients with type 2 diabetes of 60 years or older

Parameters 0No screening 1EMR symptoms 2EMR symptomsPhysical exam 3EMR symptomsPhysical examNTproBNP 4EMR symptomsPhysical examNTproBNP ECG 5Echocardio-graphy Distribution Source Sensitivitya NYHA 1 0.000 0.250 0.250 0.250 0.500 1.000 Beta Cohort NYHA 2 0.000 0.853 0.853 0.879 0.862 1.000 Beta Cohort NYHA 3 0.000 0.923 0.949 0.897 0.897 1.000 Beta Cohort NYHA 4 0.000 1.000 1.000 1.000 1.000 1.000 Beta Cohort Specificity 1.000 0.610 0.617 0.652 0.676 1.000 Beta Cohort Screening GP $0.00b $6.39 $15.17 $36.67 $61.77 $0.00c Gamma Dutch tariff Echocardiography $169.38 $169.38 $169.38 $169.38 $169.38 $169.38 Gamma Dutch tariff ECG stress test $94.75 $94.75 $94.75 $94.75 $94.75 $94.75 Gamma Dutch tariff

For each screening strategy NYHA-specific sensitivities were calculated and for each of these sensitivities a beta-distribution was specified with the true positives and total positives as parameters. Similarly, beta distributions were assigned to the specificities of each of the screening strategies. Gamma distributions with parameters using a variance equal to the mean were used for the costs


EMR Electronic Medical Record, GP general physician

aIn general, more extensive screening strategies yielded higher sensitivity and specificity at higher costs, except for NYHA 2 when adding ECG and for NYHA 3 when adding NTproBNP and/or ECG

bStrategy costs in case of no screening are kept fixed at $0 in the sensitivity analyses

cThere are no GP costs here as everyone is, after their regular diabetes checkup, directly sent for echocardiography

Input parameters for the Markov model men and women with type 2 diabetes of 60 years or older


Parameters Men Women Distribution Data source Detected Undetected Detected Undetected Incidence (100,000 person-years) 658 666 Fixed Population estimates 23;24 HF Prevalence NYHA I 0.007 0.000 Dirichlet Cohort study NYHA II 0.148 0.142 Dirichlet Cohort study NYHA III 0.047 0.031 Dirichlet Cohort study NYHA IV 0.000 0.000 Dirichlet Cohort study Mortality (year) 0.010 0.007 Fixed Population estimates HF Mortality (year) NYHA I 0.042 0.043 0.035 0.036 Fixed Cohort estimate NYHA II 0.066 0.067 0.056 0.057 Fixed Cohort estimate NYHA III 0.103 0.105 0.087 0.089 Fixed Cohort estimate NYHA IV 0.159 0.163 0.137 0.139 Fixed Cohort estimate Annual HF costsa NYHA I $1777 $1786 $1172 $1100 Gamma Cost study NYHA II $2099 $2114 $1370 $1302 Gamma Cost study NYHA III $3235 $3275 $2070 $2018 Gamma Cost study NYHA IV $8752 $8912 $5470 $5490 Gamma Cost study Medication prescription ACE-inhibitors 0.53 0.53 0.27 0.18 Cohort study Beta-blockers 0.57 0.50 0.50 0.50 Cohort study Utilitiesb Diabetes without diagnosed HF 0.868 Beta Cohort study NYHA I 0.855 0.817 Beta Cohort study NYHA II 0.790 0.739 Beta Cohort study NYHA III 0.734 0.685 Beta Cohort study NYHA IV 0.665 0.683 Beta Cohort study

aAnnual HF costs were mostly higher for undetected than for detected HF patients. Annual HF costs for detected female HF patients in NYHA class I-III were somewhat higher than for undetected female HF patients in corresponding NYHA classes because of higher use of primary care and medication

bUtilities were assumed to be the same in men and women. Utilities were higher for detected than for undetected HF patients except for NYHA class IV, where utilities were 0.665 and 0.683, respectively

SECTION: METHODS
The baseline distribution of individuals over the different health states was based on the UHFO-DM2 screening study with a screen-detected prevalence of HF of 27.7 % (22.9 % for HFpEF and 4.8 % for HFrEF) and the sensitivity and specificity of the screening strategy (Table 1). The risk of death from causes other than HF was based on age- and gender-specific Dutch life tables (Table 2), whereas the risk of death from HF was estimated according to the Seattle Heart Failure (SHF) model. The survival estimates of the SHF model were calculated using the mean predictor values from the UHFO-DM2 cohort, stratified by gender and age categories (60-70, 70-80 and 80+ years). The SHF model parameters daily defined dose for diuretic use, percentage lymphocytes, and uric acid were not obtained in the UHFO-DM2 cohort and therefore derived from the ELITE2 cohort, which was used for the validation of the SHF cohort. The SHF model was developed in cases with HFrEF, whereas in the UHFO-DM2 cohort the majority of newly detected cases of HF had HFpEF (82.6 %). In the main analysis, we therefore conservatively assumed there is no medication effect for patients with HFpEF.

Medication prescription of patients with undetected HF was based on the observed proportion of individuals in the UHFO-DM2 cohort using specific medication prior to their HF diagnosis. For detected HF the observed proportion of medication use 1 year after diagnosis in the UHFO-DM2 cohort was used (Table 2). With modeling, compliance to prescribed medication was assumed as no evidence for this patient group was available. The probabilities of healthy individuals to develop HF were based on age- and gender- stratified HF incidence in the Netherlands, taking into account the presence of diabetes. Transition probabilities between different NYHA-states were derived from 1-month transition probabilities of 65-years old HF patients who are on medical therapy. With increasing age, the probability to regress to a worse state (higher NYHA-class) was increased similar to the increasing mortality risk according to the SHF model in the corresponding NYHA classes, taking into account whether the patient had detected or undetected HF. The probability to regress to a better state was calculated accordingly.

Health outcomes

Health effects were determined by calculating expected life-years and quality-adjusted life-years (QALYs). Utilities for each of the eight HF states and the state of diabetes without HF were based on the EQ5D-scores obtained in the UHFO-DM2 study
Health effects were determined by calculating expected life-years and quality-adjusted life-years (QALYs). Utilities for each of the eight HF states and the state of diabetes without HF were based on the EQ5D-scores obtained in the UHFO-DM2 study (Table 2). The utilities for undetected HF were based on scores obtained before diagnosis, whereas utilities for diabetes without HF and detected HF states were based on EQ5D-scores obtained 1 year after diagnosis.

Costs

Our analysis was conducted from a healthcare perspective, incorporating costs directly related to screening and diagnosis, and HF-related costs for detected and undetected HF patients within different NYHA-classes.
Costs for screening and diagnosis included costs for investigations and consultation and, in case of a calculated risk of HF 20 %, a cardiologist consultation including echocardiography. If HF was diagnosed, costs of a cardiac ECG stress test were added. In the Netherlands, it is common practice for cardiologists to perform this test as a first step in the assessment if angina pectoris or myocardial ischaemia is involved. All costs were based on tariffs set by the Dutch Healthcare Authority (1 January 2011) according to Dutch guidelines (Table 1).

Long-term HF-related costs were split up into costs for all HF patients (hospitalization and nursing care) and costs for patients with detected HF (extra GP consultation and medication use), stratified by gender and age. All T2DM patients have regular GP consultations and receive anti-diabetes medication and the vast majority receives blood pressure lowering drugs and statins. We therefore solely used the increase in costs related to the detection of HF. Costs for all HF patients were additionally weighted over NYHA classes using hazard ratios for hospitalization per NYHA class, which were adjusted for detected and undetected HF using the ratio of their mortality risks based on the SHF model.

Analyses

Life-years, QALYs, and costs per person were calculated over a lifetime horizon, with costs and health effects discounted at 4 and 1.5 % per year, respectively, according to Dutch guidelines.
Life-years, QALYs, and costs per person were calculated over a lifetime horizon, with costs and health effects discounted at 4 and 1.5 % per year, respectively, according to Dutch guidelines.es. To assess robustness of the results given the uncertainty in the evidence (Table 2), probabilistic sensitivity analyses were performed using Monte Carlo simulation based on 10,00To assess robustness of the results given the uncertainty in the evidence (Table 2), probabilistic sensitivity analyses were performed using Monte Carlo simulation based on 10,000 samples.probabilistic sensitivity analyses were performed using Monte Carlo simulation based on 10,000 samples. The incremental cost-effectiveness ratios (ICERs) were calculated by first ranking all strategies in order of improving health outcomes and calculating the additional costs of obtaining these health outcomes. Strategies offering no additional health benefits, or additional health benefits at too high costs compared to other strategies were considered 'dominated', i.e., less favourable and not cost-effective, which was visualized in a cost-effectiveness frontier. Model development and analyses were done with Microsoft Excel 2010.

Scenario analyses for HFpEF medication

We distinguished between screening for HFrEF and HFpEF, because the prevalence is much higher for HFpEF, while convincing evidence-based therapy is only available for HFrEF. Treatment of HFpEF is focused on reduction of symptoms of fluid overload, adequate blood pressure control and management of comorbid conditions. Diuretics are the only option for symptom relief, but their prognostic effects have never been adequately evaluated. Other drugs, including beta-blockers, angiotensin-converting-enzyme inhibitors, angiotensin II receptor blockers and mineralo-corticoid inhibitors have been tested in randomized-controlled trials in patients with HFpEF, mainly in addition to diuretics, with at the best a statistically non-significant relative risk reduction in all-cause mortality of around 10 %.

Currently, medication for HFpEF has only shown at best a tendency to a mortality-reducing effect. Therefore, scenario analyses were performed to assess the potential cost-effectiveness if evidence on effective medication for HFpEF becomes available in the future. We varied the effectiveness of medication for patients with HFpEF from 0 to 100 %, with increments of 10 %, of the effectiveness for HFrEF. Hence, 100 % implies equal effectiveness in HFpEF as in HFrEF. Incremental QALYs and costs of the screening strategies were evaluated for each of these HFpEF medication effectiveness scenarios. Scenario analyses were performed to assess the potential cost-effectiveness if mortality reducing effective medication for HFpEF becomes available in the future. We varied the effectiveness of medication for patients with HFpEF from 0 to 100 % effectiveness compared to the effect in HFrEF, with increments of 10 %, i.e., 100 % implies equal effectiveness in HFpEF as in HFrEF. The ICER of the screening strategies was evaluated for each of these scenarios of medication effectiveness in HFpEF.

SECTION: RESULTS
Results

SECTION: TABLE
The incremental comparison of expected life years, QALYs, costs, and ICERs for five screening strategies for heart failure in patients with type 2 diabetes of 60 years or older


Strategy 0No screening 1EMR symptoms 2EMR symptomsPhysical Exam 3EMR symptomsPhysical examNTproBNP 4EMR symptomsPhysical examNTproBNP ECG 5Echocardiography Life expectancy (years) Men 14.726 14.742 14.742 14.742 14.742 14.742 Women 16.830 16.851 16.851 16.851 16.851 16.852 QALY expectancy (years) Men 12.345 12.477 12.477 12.477 12.477 12.479 Women 14.047 14.215 14.215 14.216 14.215 14.217 Expected costs pp (euros) Men $6795 $7605 $7611 $7625 $7642 $7667 Women $5024 $6086 $6093 $6107 $6125 $6152 Strategy comparison NA 1 vs 0 2 vs 1 3 vs 1 4 vs 1 5 vs 1 Additional QALYs to comparator Men NA 0.132 0.000 0.000 0.000 0.002 Women NA 0.168 0.000 0.000 0.000 0.002 Additional costs to comparator Men NA $810 NA NA NA $62 Women NA $1063 NA NA NA $66 ICER Men NA $6115a Dominated Dominated Dominated $29,100 Women NA $6318a Dominated Dominated Dominated $39,326

In the upper part of the table the absolute expected life-years, QALYs, and costs are given for each strategy. In the lower part, for each strategy these life-years, QALYs and costs are compared to the current optimal strategy

EMR Electronic Medical Record, ICER incremental cost-effectiveness ratio

aThis is the strategy expected to be optimal for a WTP of $20,000 per QALY

SECTION: FIG
Incremental cost-effectiveness planes for patients with type 2 diabetes of 60 years or older. a Men. b Women

SECTION: RESULTS
The average expected life-years and QALYs for 60-year old men and women with T2DM increased with HF screening, starting at the age of 60. For men, the expected life-years were 14.726 (12.345 QALYs) for usual care (no screening) and 14.742 (12.477 QALYs) if EMR/symptoms or strategy 2-4 were used. If echocardiography was performed straightaway in all patients (strategy 5), expected life-years were 14.742 and QALYs 12.479. For women, expected life-years increased from 16.830 (14.047 QALYs) with usual care to 16.851 (14.215 QALYs) if the EMR/symptoms strategy was implemented, and to 16.852 (14.217 QALYs) with the Echocardiography strategy. For usual care, expected lifetime costs for men and women were $6795 and $5024, respectively. These costs increased if screening strategies were performed, with the highest costs for the Echocardiography strategy; $7667 for men and $6152 for women (Table 3). The incremental cost-effectiveness planes for the five screening strategies as compared to usual care (no screening) are presented in Fig. 2.

SECTION: FIG
Cost-effectiveness acceptability curves for patients with type 2 diabetes of 60 years or older. a Men. b Women

Cost-effectiveness frontier patients with type 2 diabetes of 60 years or older. For each strategy life-years, QALYs and costs are compared to the current optimal strategy (lower part Table 3). The results are visualized in this cost-effectiveness frontier, which uses strategy 1 (EMR + symptoms) as the reference point, i.e., the origin

SECTION: RESULTS
The cost-effectiveness acceptability curves (Fig. 3) showed that the EMR/symptoms strategy is the preferred strategy for a willingness to pay (WTP) ranging from $6050/QALY to $31,000/QALY for men and $6300/QALY to $42,000/QALY for women. For lower WTP-values, the usual care (no screening) strategy was optimal, while for higher WTP-values the Echocardiography strategy is the preferred strategy. Comparing the different screening strategies and evaluating ICERs showed that QALYs could only be gained on top of the EMR/symptoms strategy by the Echocardiography strategy, and not by the other three strategies (Table 3 lower part, Fig. 4).

Scenario analyses for HFpEF medication

SECTION: TABLE
The incremental comparison of ICERs for different medication scenarios

Relative effectiveness 1. EMR + symptoms vs0. No screening 5. Echocardiography vs1. EMR + symptoms Men (%) 0 $6115 $29,100 10 $5573 $27,552 20 $5067 $26,157 30 $4591 $24,895 40 $4140 $23,749 50 $3709 $22,705 60 $3293 $21,753 70 $2890 $20,880 80 $2494 $20,079 90 $2102 $19,341 100 $1711 $18,660 Women (%) 0 $6318 $39,326 10 $5888 $38,122 20 $5496 $37,015 30 $5137 $35,998 40 $4807 $35,067 50 $4502 $34,216 60 $4219 $33,442 70 $3995 $32,741 80 $3706 $32,110 90 $3471 $31,547 100 $3248 $31,049

EMR Electronic Medical Record, PE physical examination ICER incremental cost-effectiveness ratio. Relative effectiveness represents HFPEF medication effectiveness as a percentage of the effectiveness in HFREF. For each strategy the incremental life-years, QALYs and costs are compared to the current optimal strategy and the ICER was calculated. Strategies 2, 3, and 4 were dominated by strategy 5

SECTION: RESULTS
The ICERs of all strategies become more favourable with increasing medication effectiveness. For a WTP of $20,000/QALY EMR/symptoms is the preferred strategy. Increasing the relative HFpEF medication effectiveness Echocardiography is the preferred strategy in men if this relative medication effectiveness is 90 % or more. With a WTP of $80.000 Echocardiography is the preferred strategy for any relative effectiveness (Table 4).

SECTION: DISCUSS
Discussion

Screening community-dwelling T2DM patients of 60 years or over annually for HF in the Dutch primary care setting results in a small increase in life expectancy and QALYs at relatively low costs. Checking the EMR for risk factors plus assessment of specific symptoms is the preferred initial, once-in-a-life strategy, with an ICER of $6115 for men and $6318 for women as compared to no screening. For a WTP of $20,000/QALY, a commonly used threshold for patient care in Europe, this strategy would thus be cost-effective. If patients with HFrEF would be treated optimally according to the guidelines, instead of e.g., the current uptake of the most beneficial medication in heart failure, betablockers, which was 58 %, the cost-effectiveness of screening T2DM patients will even be more favourable.

In the base-case analysis we assumed no beneficial prognostic effects of treatment for patients with HFpEF. We performed scenario analyses in which we evaluated the cost-effectiveness considering varying prognostic beneficial treatment effects in this type of HF.
These scenario analysis showed that if beneficial medication becomes available for HFpEF, screening strategies in older T2DM patients would have a more favourable ICER, reaching to $3709/QALY for men and $4502/QALY for women, assuming a treatment effect for HFpEF that is 50 % of the current treatment effect of HFrEF (Table 4).

Strengths and limitations of the study

We assessed multiple screening strategies, all feasible to implement in everyday primary care practice. Our model was based on real-life medication prescriptions in screen-detected HF cases from a cohort study in 581 T2DM patients aged 60 years or over. We only applied a single cut-off point for considering HF to be present. However, when evaluating screening strategies often a single cut-off is used and the 20 % cut-off we applied has been used in earlier studies.

Although we did account for higher health-care costs for individuals with undetected HF, we did not consider the costs of a possible acute life-threatening exacerbation of HF necessitating hospital admission.
Incorporating such a risk in our model would result in much higher costs for the non-screening strategy, and thus in an even more favorable cost-effectiveness of screening. Furthermore, end-of-life costs and health deterioration in patients dying from HF may be underestimated because in the model patients could die while being in any NYHA state, not considering rapid disease progression. For example, in our model 30 % of the patients would die from HF while being in NYHA class II, and any progression to higher NYHA states with its associated health losses immediately prior to death is not taken into account. However, the majority of HF deaths (64 %) in our model occurred in patients with NYHA class 3 and 4, indicating that this underestimation is limited.

Another limitation of our study is that the SHF model was derived from cohorts with only HFrEF patients, while the majority of patients with HF in the UHFO-DM2 cohort had HFpEF. Moreover, some of the predictor values of the SHF model were not available in the UHFO-DM2 cohort. Therefore, the effectiveness of medication incorporated in the SHF model may not translate perfectly to our cohort. This issue has been addressed by assuming that HFpEF patients do not benefit of any treatment. The additional scenario analyses to assess the impact of the availability of prognostically beneficial medication for HFpEF on ICER were added to further address this issue.

Implications for research and policy

Our results support screening for HF among T2DM patients of 60 years or over based on the information available from the EMR plus assessment of specific symptoms suggestive of HF, followed by echocardiography in those with a calculated risk of HF of more than 20 %. Even though only for the (small) proportion of patients with HFrEF mortality-reducing medication is available, this screening strategy is cost-effective when using a WTP of $20,000/QALY. Comparing this HF screening to other screening programs, the cost-effectiveness would be better than for cervix screening for instance, which currently costs $20,000-$50,000/QALY. Furthermore, whenever (evidence for) mortality-reducing medication becomes available for HFpEF, of which many experts are convinced, the incremental costs/QALY of the screening strategies will decrease considerably, as can be seen in the scenario analyses for effectiveness of HFpEF medication (Table 4). The results of this cost-effectiveness analysis were based on the Dutch setting and may not directly be transferred to other countries. Further research is needed to translate our model to settings in other countries.

Our observations are in line with a registration study, which concluded that despite advances in patient management there is further potential to improve both the detection and management of patients with diabetes and coronary artery disease. Furthermore, relatively tight glucose control has some cardiovascular benefits. HbA1c below 7.0 % as the goal to maximize the cardiovascular benefits remains suspended. In addition, a multidisciplinary risk assessment and management program for patients with diabetes mellitus intervention was associated with lower incidences of individual and total cardiovascular complications, as well as all-cause mortality over 3 years follow-up. This study shows risk assessment was an effective approach to reduce future cardiovascular complications in diabetes patients. Also the 'St Vincent's screening to prevent heart failure' study showed that among patients with cardiovascular risk factors, natriuretic peptide-based screening and collaborative care reduced left ventricular dysfunction, HF and major adverse cardiac events, and has a high probability of being cost-effective.

SECTION: CONCL
Conclusions

Screening for heart failure by simply checking the electronic medical record for patient characteristics and medical history plus the assessment of symptoms in community-dwelling patients with type 2 diabetes of 60 years and older is cost-effective at the commonly used willingness-to-pay threshold of $20.000/QALY. The simplicity of such a strategy makes it feasible for implementation in existing primary care diabetes management programs. Cost-effectiveness may improve considerably with the availability of effective treatment for heart failure with preserved ejection fraction.

Anoukh van Giessen and Leandra J.M. Boonman-de Winter contributed equally to this work