Value of information analysis in telehealth for chronic heart failure management

Consolidated Health Economic Evaluation Reporting Standards - Value of Information (CHEERS-VOI): Explanation and Elaboration

OBJECTIVES

Although the ISPOR Value of Information (VOI) Task Force's reports outline VOI concepts and provide good-practice recommendations, there is no guidance for reporting VOI analyses. VOI analyses are usually performed alongside economic evaluations for which the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 Statement provides reporting guidelines. Thus, we developed the CHEERS-VOI checklist to provide reporting guidance and checklist to support the transparent, reproducible, and high-quality reporting of VOI analyses.

METHODS

A comprehensive literature review generated a list of 26 candidate reporting items. These candidate items underwent a Delphi procedure with Delphi participants through 3 survey rounds. Participants rated each item on a 9-point Likert scale to indicate its relevance when reporting the minimal, essential information about VOI methods and provided comments. The Delphi results were reviewed at 2-day consensus meetings and the checklist was finalized using anonymous voting.

RESULTS

We had 30, 25, and 24 Delphi respondents in rounds 1, 2, and 3, respectively. After incorporating revisions recommended by the Delphi participants, all 26 candidate items proceeded to the 2-day consensus meetings. The final CHEERS-VOI checklist includes all CHEERS items, but 7 items require elaboration when reporting VOI. Further, 6 new items were added to report information relevant only to VOI (eg, VOI methods applied).

CONCLUSIONS

The CHEERS-VOI checklist should be used when a VOI analysis is performed alongside economic evaluations. The CHEERS-VOI checklist will help decision makers, analysts and peer reviewers in the assessment and interpretation of VOI analyses and thereby increase transparency and rigor in decision making.

Pros and cons of telemedicine: implications in cardiology and cardiovascular medicine

The COVID-19 pandemic has highlighted the vitalness of telehealth in our medical world, where considering a restructuring of healthcare services has become paramount. Indeed, in the context of this still ongoing pandemic, medical institutions must strive to improve telehealth technologies and implement solid future research directions in this growing field - to be able to persevere in meeting the needs of the patients. As long as no conclusive evidence exists regarding the fields where telemedicine is most worthwhile, healthcare systems will always keep the dread of wasting resources on developing ineffective programs. We gathered that telemedicine has been attributed a considerable attention in managing cardiac/cardiovascular conditions; nevertheless, further studies with solid designs are still needed to confirm its validity/utility within these specialties.

Domains and Methods Used to Assess Home Telemonitoring Scalability: Systematic Review

BACKGROUND

The COVID-19 pandemic catalyzed the adoption of home telemonitoring to cope with social distancing challenges. Recent research on home telemonitoring demonstrated benefits concerning the capacity, patient empowerment, and treatment commitment of health care systems. Moreover, for some diseases, it revealed significant improvement in clinical outcomes. Nevertheless, when policy makers and practitioners decide whether to scale-up a technology-based health intervention from a research study to mainstream care delivery, it is essential to assess other relevant domains, such as its feasibility to be expanded under real-world conditions. Therefore, scalability assessment is critical, and it encompasses multiple domains to ensure population-wide access to the benefits of the growing technological potential for home telemonitoring services in health care.

OBJECTIVE

This systematic review aims to identify the domains and methods used in peer-reviewed research studies that assess the scalability of home telemonitoring-based interventions under real-world conditions.

METHODS

The authors followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines and used multiple databases (PubMed, Scopus, Web of Science, and EconLit). An integrative synthesis of the eligible studies was conducted to better explore each intervention and summarize relevant information concerning the target audience, intervention duration and setting, and type of technology. Each study design was classified based on the strength of its evidence. Lastly, the authors conducted narrative and thematic analyses to identify the domains, and qualitative and quantitative methods used to support scalability assessment.

RESULTS

This review evaluated 13 articles focusing on the potential of scaling up a home telemonitoring intervention. Most of the studies considered the following domains relevant for scalability assessment: problem (13), intervention (12), effectiveness (13), and costs and benefits (10). Although cost-effectiveness was the most common evaluation method, the authors identified seven additional cost analysis methods to evaluate the costs. Other domains were less considered, such as the sociopolitical context (2), workforce (4), and technological infrastructure (3). Researchers used different methodological approaches to assess the effectiveness, costs and benefits, fidelity, and acceptability.

CONCLUSIONS

This systematic review suggests that when assessing scalability, researchers select the domains specifically related to the intervention while ignoring others related to the contextual, technological, and environmental factors, which are also relevant. Additionally, studies report using different methods to evaluate the same domain, which makes comparison difficult. Future work should address research on the minimum required domains to assess the scalability of remote telemonitoring services and suggest methods that allow comparison among studies to provide better support to decision makers during large-scale implementation.

Evidence-Based Medicine in Otolaryngology, Part XI: Modeling and Analysis to Support Decisions

OBJECTIVE

To provide a resource to educate clinical decision makers about the analyses and models that can be employed to support data-driven choices.

DATA SOURCES

Published studies and literature regarding decision analysis, decision trees, and models used to support clinical decisions.

REVIEW METHODS

Decision models provide insights into the evidence and its implications for those who make choices about clinical care and resource allocation. Decision models are designed to further our understanding and allow exploration of the common problems that we face, with parameters derived from the best available evidence. Analysis of these models demonstrates critical insights and uncertainties surrounding key problems via a readily interpretable yet quantitative format. This 11th installment of the Evidence-Based Medicine in Otolaryngology series thus provides a step-by-step introduction to decision models, their typical framework, and favored approaches to inform data-driven practice for patient-level decisions, as well as comparative assessments of proposed health interventions for larger populations.

CONCLUSIONS

Information to support decisions may arise from tools such as decision trees, Markov models, microsimulation models, and dynamic transmission models. These data can help guide choices about competing or alternative approaches to health care.

IMPLICATIONS FOR PRACTICE

Methods have been developed to support decisions based on data. Understanding the related techniques may help promote an evidence-based approach to clinical management and policy.