How Do Patients With Type 2 Diabetes Mellitus Value the Importance of Outcomes? An Overview of Reviews.

OBJECTIVES: We aimed to assess how patients value the importance of type 2 diabetes mellitus (T2DM) related outcomes. METHODS: Overview of systematic reviews (SRs) reporting patients' utilities or disutilities for T2DM outcomes. We searched 3 databases from inception until June 2021. Study selection and data extraction were conducted in pairs. We evaluated the quality of SRs with the Joanna Briggs Institute Checklist, and the overlap with the corrected covered area. We estimated descriptive statistics, and, when possible, conducted metanalysis. RESULTS: We identified 11 SRs, including 119 studies and 70 outcomes. Most reviews were high-quality SRs. The outcomes with the lowest utilities were hypoglycemia with very severe symptoms (acute complications), stroke (macrovascular complications), diabetic peripheral neuropathy with severe pain (microvascular complications), extreme obesity (comorbidities), and insulin only or combined (management of diabetes). Good/excellent glucose control and noninsulin injectable showed higher values than T2DM without complications. The outcomes with the highest disutilities were amputation, depression, major hypoglycemia, stroke, and management using only insulin. CONCLUSIONS: We provide standardized, reliable utility values (or associated disutilities) for T2DM, acute, microvascular and macrovascular complications, related comorbidities and treatments that may support judgments when making clinical recommendations, designing decision support tools, and developing interventions and economic analysis.

Exploring the Effectiveness of Self-Management Interventions in Type 2 Diabetes: A Systematic Review and Network Meta-Analysis.

BACKGROUND: Chronic diseases are a leading cause of global morbidity and mortality. In response to this challenge, self-management interventions (SMIs) have emerged as an essential tool in improving patient outcomes. However, the diverse and complex nature of SMIs pose significant challenges in measuring their effectiveness. This work aims to investigate the comparative effectiveness of SMIs on Type 2 diabetes mellitus (T2DM) outcomes. METHODS: A rigorous analytical framework was employed to assess the relative effectiveness of different SMIs, encompassing both pairwise and network meta-analysis (NMA), as well as component network meta-analysis (CNMA). Various outcomes were considered, including glycated hemoglobin (HbA1c) control, body mass index (BMI) reduction and low-density lipoprotein (LDL) cholesterol. Visualization tools were also utilized to enhance the interpretation of results. RESULTS: SMIs were found promising in improving clinical outcomes and patient-reported measures. However, considerable heterogeneity and inconsistency across studies challenged the validity of NMA results. CNMA along with various visualization tools offered insights into the contributions of individual SMI components, highlighting the complexity of these interventions. DISCUSSION/CONCLUSIONS: SMIs represent a valuable approach to managing chronic conditions, but their effectiveness is context-dependent. Further research is needed to elucidate the contextual factors influencing SMI outcomes. This work contributes to a comprehensive understanding of SMIs' role in T2DM management, aiming to aid decision-makers, clinicians, and patients in selecting tailored interventions.

Economic evaluation of remote monitoring of patients with an implantable cardiac defibrillator (REMOTE-CIED study).

INTRODUCTION: Remote patient monitoring (RPM) of heart failure patients has the potential to reduce healthcare resource use and costs, but current evidence has been inconclusive. This study aims assess the impact of RPM of heart failure patients with an implantable cardioverter defibrillator on medical resource use, direct medical costs, quality-adjusted life years (QALYs), and travel time of patients, and to estimate its commercial headroom in the Netherlands and Germany. METHODS: Data from the REMOTE-CIED randomized controlled trial were used to calculate differences in length of hospital stay, outpatient clinic visits, telephone consults, emergency room visits, and travel time between patients on in-clinic follow-up and RPM in the Netherlands, Germany, and France. Incremental cardiac-related healthcare costs and QALYs were calculated and used to calculate the commercial headroom of RPM in the Netherlands and Germany. The impact of imputation, parameter, and case-mix uncertainty on these outcomes was explored using probabilistic analysis. RESULTS: Length of hospitalization, number of unscheduled admissions, and number of outpatient visits were lower in the remote monitoring group in all three countries. Number of hospital admissions was higher, and number of calls was lower in the Netherlands and Germany but not in France. Costs were lower in both the Netherlands (-€1041, 95% confidence interval (CI): -€3308, €1005) and Germany (-€2865, 95% CI: -€7619, €1105), while incremental effectiveness differed: -0.003 (95% CI: -0.114, 0.107) QALY in the Netherlands and +0.086 (95% CI: -0.083, 0.256) in Germany. Commercial headroom was estimated at €881 (95% CI: -€5430, €7208) in the Netherlands and €5005 (95% CI: -€1339, €11,960) in Germany. DISCUSSION: RPM was found to result in reduced medical resource use and travel time. Whether it is cost saving or cost effective strongly depends on the costs of remote monitoring. TRIAL REGISTRATION NUMBER AND TRIAL REGISTER: ClinicalTrials.gov: NCT01691586.

The early economic evaluation of novel biomarkers to accelerate their translation into clinical applications.

BACKGROUND: Translating prognostic and diagnostic biomarker candidates into clinical applications takes time, is very costly, and many candidates fail. It is therefore crucial to be able to select those biomarker candidates that have the highest chance of successfully being adopted in the clinic. This requires an early estimate of the potential clinical impact and commercial value. In this paper, we aim to demonstratively evaluate a set of novel biomarkers in terms of clinical impact and commercial value, using occurrence of cardiovascular disease (CVD) in type-2 diabetes (DM2) patients as a case study. METHODS: We defined a clinical application for the novel biomarkers, and subsequently used data from a large cohort study in The Netherlands in a modeling exercise to assess the potential clinical impact and headroom for the biomarkers. RESULTS: The most likely application of the biomarkers would be to identify DM2 patients with a low CVD risk and subsequently withhold statin treatment. As a result, one additional CVD event in every 75 patients may be expected. The expected downstream savings resulted in a headroom for a point-of-care device ranging from €119.09 at a willingness to accept of €0 for one additional CVD event, to €0 at a willingness to accept of €15,614 or more. CONCLUSION: It is feasible to evaluate novel biomarkers on outcomes directly relevant to technological development and clinical adoption. Importantly, this may be attained at the same point in time and using the same data as used for the evaluation of association with disease and predictive power.

Using multicriteria decision analysis to support research priority setting in biomedical translational research projects.

Translational research is conducted to achieve a predefined set of economic or societal goals. As a result, investment decisions on where available resources have the highest potential in achieving these goals have to be made. In this paper, we first describe how multicriteria decision analysis can assist in defining the decision context and in ensuring that all relevant aspects of the decision problem are incorporated in the decision making process. We then present the results of a case study to support priority setting in a translational research consortium aimed at reducing the burden of disease of type 2 diabetes. During problem structuring, we identified four research alternatives (primary, secondary, tertiary microvascular, and tertiary macrovascular prevention) and a set of six decision criteria. Scoring of these alternatives against the criteria was done using a combination of expert judgement and previously published data. Lastly, decision analysis was performed using stochastic multicriteria acceptability analysis, which allows for the combined use of numerical and ordinal data. We found that the development of novel techniques applied in secondary prevention would be a poor investment of research funds. The ranking of the remaining alternatives was however strongly dependent on the decision maker's preferences for certain criteria.

Development of a web-based tool for the assessment of health and economic outcomes of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA).

BACKGROUND: The European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) is a European Commission led policy initiative to address the challenges of demographic change in Europe. For monitoring the health and economic impact of the social and technological innovations carried out by more than 500 stakeholder's groups ('commitments') participating in the EIP on AHA, a generic and flexible web-based monitoring and assessment tool is currently being developed. AIM: This paper describes the approach for developing and implementing this web-based tool, its main characteristics and capability to provide specific outcomes that are of value to the developers of an intervention, as well as a series of case studies planned before wider rollout. METHODS: The tool builds up from a variety of surrogate endpoints commonly used across the diverse set of EIP on AHA commitments in order to estimate health and economic outcomes in terms of incremental changes in quality adjusted life years (QALYs) as well as health and social care utilisation. A highly adaptable Markov model with initially three mutually exclusive health states ('baseline health', 'deteriorated health' and 'death') provides the basis for the tool which draws from an extensive database of epidemiological, economic and effectiveness data; and also allows further customisation through remote data entry enabling more accurate and context specific estimation of intervention impact. Both probabilistic sensitivity analysis and deterministic scenario analysis allow assessing the impact of parameter uncertainty on intervention outcomes. A set of case studies, ranging from the pre-market assessment of early healthcare technologies to the retrospective analysis of established care pathways, will be carried out before public rollout, which is envisaged end 2015. CONCLUSION: Monitoring the activities carried out within the EIP on AHA requires an approach that is both flexible and consistent in the way health and economic impact is estimated across interventions and commitments. The added value for users of the MAFEIP-tool is its ability to provide an early assessment of the likelihood that interventions in their current design will achieve the anticipated impact, and also to identify what drives interventions' effectiveness or efficiency to guide further design, development or evaluation.

Design of stepwise screening for prediabetes and type 2 diabetes based on costs and cases detected.

OBJECTIVES: To provide insight into the trade-off between cost per case detected (CPCD) and the detection rate in questionnaire-based stepwise screening for impaired fasting glucose and undiagnosed type 2 diabetes. STUDY DESIGN AND SETTING: We considered a stepwise screening in which individuals whose risk score exceeds a predetermined cutoff value are invited for further blood glucose testing. Using individual patient data to determine questionnaire sensitivity and specificity and external sources to determine screening costs and patient response rates, we rolled back a decision tree to estimate the CPCD and the detection rate for all possible cutoffs on the questionnaire. RESULTS: We found a U-shaped relation between CPCD and detection rate, with high costs per case detected at very low and very high detection rates. Changes in patient response rates had a large impact on both the detection rate and the CPCD, whereas screening costs and questionnaire accuracy mainly impacted the CPCD. CONCLUSION: Our applied method makes it possible to identify a range of efficient cutoffs where higher detection rates can be achieved at an additional cost per detected patient. This enables decision makers to choose an optimal cutoff based on their willingness to pay for additional detected patients.

A method for the early health technology assessment of novel biomarker measurement in primary prevention programs.

Many promising biomarkers for stratifying individuals at risk of developing a chronic disease or subsequent complications have been identified. Research into the potential cost-effectiveness of applying these biomarkers in actual clinical settings has however been lacking. Investors and analysts may improve their venture decision making should they have indicative estimates of the potential costs and effects associated with a new biomarker technology already at the early stages of its development. To assist in obtaining such estimates, this paper presents a general method for the early health technology assessment of a novel biomarker technology. The setting considered is that of primary prevention programs where initial screening to select high-risk individuals eligible for a subsequent intervention occurs, for example, prevention of type 2 diabetes. The method is based on quantifying the health outcomes and downstream healthcare consumption of all individuals who get reclassified as a result of moving from a screening variant based on traditional risk factors to a screening variant based on traditional risk factors plus a novel biomarker. As these individuals form well-defined subpopulations, a combination of disease progression modeling and sensitivity analysis can be used to perform an initial assessment of the maximum increase in screening cost for which the use of the new biomarker technology is still likely to be cost effective.