Health economics Archives - Marksman Healthcare

Online Elicitation of Personal Utility Functions (OPUF) as a Tool for Personalized Health Decision-Making
Personalized medicine revolves around understanding the necessities of individuals pertaining to their health, treatment preferences, and quality of life. One of the methods to obtain this information is through utility functions, which are quantifiable signs of an individual’s preferences under uncertainty. Utility functions facilitate translation of qualitative judgments (for e.g., choosing between two treatments with different side effects) into a measurable guidance, often applicable in health economics, decision analysis, and planning of patient-centred care. Conventionally, extracting these personal utility functions needed face-to-face interviews or time-consuming surveys, restricting their generalizability and flexibility.(1, 2)

The evolving digital advancements are paving the way for preference elicitation, particularly through online platforms. Online Elicitation of Personal Utility Functions (OPUF) are the web-based tools or applications that help depict and measure individual preferences in real time. These tools usually encompass interactive assignments, visual aids, and adaptive questioning to make the process insightful for users, even without a prior experience with decision theory. OPUF platforms enable users to encounter hypothetical health scenarios, trade-offs, and outcomes in the comfort of their homes, making preference elicitation more user-friendly, scalable, and reactive to specific contexts.(2)

OPUF has several advantages. It minimizes the need for clinician time, reduces data collection costs, and facilitates the inclusion of various, geographically scattered populations. More prominently, it highlights the voice of the individuals in health technology assessment (HTA), economic assessments, and clinical decision-making. By depicting detailed and context-specific preferences, OPUF moves away from one-size-fits-all hypotheses and encourages more impartial and relevant health policy decisions. In resource-limited environments or for rare conditions, where general sweeping statements do not represent lived realities, OPUF provides a crucial link between individual values and population-level healthcare approaches.(2)

Early feasibility studies have shown promising results for OPUF in real-world applications. For instance, findings of a study valuing the EQ-HWB-S, a standard metric of health and wellbeing with nine dimensions, using OPUF in the UK reported that most participants completed the online tool in about 15 minutes, ranking the experience as easy, generating logically consistent and well-ordered utility measurements. Notably, the value sets generated using OPUF varied from those derived through conventional methods, showing that OPUF may summarize preferences in new and possibly more authentic ways.(3) Another large-scale study, incorporating OPUF into the broadly used EQ-5D-5L instrument with 874 UK participants, developed value sets both at the population level and for explicit subgroups and even individual respondents. Findings of this study showed high predictive accuracy of personal preferences and significant heterogeneity that was unexplainable with group-level characteristics, which further highlights OPUF’s potential to encourage accurately personalized health valuation.(4)

However, OPUF has several limitations. Concerns like digital literacy, understanding of abstract trade-offs, and the rational burden of making complex decisions online must be handled with careful design and pilot testing. It is also essential to prioritize confirming the validity, duplicability, and ethical use of these data. Moreover, data privacy issues, informed consent, and avoiding mishandling of preference data for biased or exclusive decision-making must be vigorously handled. Future developments in this domain include incorporating OPUF tools into electronic health records (EHRs), customizing them to different languages and cultures, and integrating artificial intelligence (AI) to enhance adaptivity and minimize respondent fatigue.(2, 3)

With the healthcare landscape shifting toward personalization and shared decision-making, OPUF is gaining prominence as a practical, novel tool to strengthen patient voices. By optimizing the reach of digital platforms and the strength of utility theory, OPUF can be instrumental in changing the understanding, depiction, and application of elements that are truly important to patients. Its role in prioritizing clinical and policy choices with individual values takes it beyond just the methodological innovation, making it an ethical requirement in modern healthcare.

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References
1. Ubels J. The assessment of value in health economics: utility and capability. In: Kohlhammer VW, author; Schildmann J, Buch C, Zerth J, editors. Defining the Value of Medical Interventions: Normative and Empirical Challenges [Internet]. Stuttgart (DE): W. Kohlhammer GmbH; 2021. Available from: https://www.ncbi.nlm.nih.gov/books/NBK585087/
2. Schneider PP, van Hout B, Heisen M, Brazier J, Devlin N. The Online Elicitation of Personal Utility Functions (OPUF) tool: a new method for valuing health states. Wellcome Open Res. 2022 Jan 14;7:14.
3. Schneider P, Ludwig K, Marten O, et al. Using the OPUF approach to create a value set for the EQ-HWB-S: An exploratory feasibility study [version 1; peer review: 1 approved, 1 approved with reservations]. Wellcome Open Res. 2024; 9:359.
4. Schneider P, Brazier J, Devlin N, van Hout B. PCR28 The OPUF Tool: A New Type of Online Survey for Creating Value Sets for the EQ-5D-5L on the Societal-, Group-, and Individual Person Level. Value Health 2022; 25(7):S546.
MarksMan Healthcare

July 29, 2025

Health economics

Online preference elicitation, Patient-centred decision-making, Personal utility functions
Assessing the Value of Preventive Health Interventions
The growing challenges of increasing healthcare costs and changing population needs are making the significance of preventive health interventions more evident. However, even with their ability to transform health outcomes and lower long-term expenses, prevention strategies are often underestimated in traditional assessment frameworks.[1]

Conventional assessments have largely relied on metrics including the incremental cost-effectiveness ratio (ICER) and quality-adjusted life years (QALYs) to validate an intervention’s benefits relative to its cost. While these assessments offer a structured guidance on comparing health interventions, they often fail to evaluate the bigger, long-term, and societal impact of prevention.[2-4]

Evolving research and policy debates highlight the need to reform prevention not just as a cost to be controlled, but also as a valuable investment to achieve significant returns.[2, 3] Preventive health interventions can improve workforce productivity, decrease healthcare utilization, and enhance quality of life; all of which depict the benefits extending well beyond direct clinical outcomes. By justifying the social and economic burden mitigated through prevention, new assessment frameworks aim to indicate the full extent of value these interventions offer.[2-4]

Preventive measures often overlap with demanding social elements of health, such as education, income, and housing. They also often involve stakeholders across different sectors. Intrinsically, capturing the true value of preventive interventions necessitates incorporating different data sources and accounting for non-health outcomes, such as social unity, decreased inequality, and economic flexibility. This difficulty highlights the incompetence of restrictive, health-centred models in fully demonstrating the societal returns of preventive interventions.[2, 3]

To address these challenges, health economic experts highlight the importance of implementing comprehensive analytical methods, such as cost-benefit analysis (CBA), return on investment (ROI), and societal impact evaluations. These methods facilitate the measurement of both health and non-health financial benefits, giving policymakers a precise understanding of the impact of the preventive action in terms of overall wellbeing. Notably, these methods also help associate health investments with larger goals, including economic growth and social equity, redrafting healthcare costs as contributors to long-term prosperity.[2]

In conclusion, a structured value assessment framework for preventive interventions must balance analytical precision with real-world applicability. It should integrate long-term and cross-sectoral impact, and involve different types and sources of evidence to comprehensively represent the priorities of the populations it seeks to serve. By going beyond a narrow focus of cost-effectiveness and adopting an all-encompassing concept of value, health systems can better summarize the real influence of preventive interventions. This broader focus can facilitate smarter, more reasonable investments that encourage overall well-being and promote sustainable growth.

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References
1. Sturmberg JP, Bircher J. Better and fulfilling healthcare at lower costs: The need to manage health systems as complex adaptive systems. F1000Res. 2019; 5(8):789.
2. Mazzucato, M, Roy V. Rethinking value in health innovation: from mystifications towards prescriptions. Journal of Economic Policy Reform. 2018; 22(2):101-119.
3. OECD (2024), Rethinking Health System Performance Assessment: A Renewed Framework. [Accessed 03 Jun 2025]. Available at: https://www.oecd.org/en/publications/rethinking-health-system-performance-assessment_107182c8-en/full-report.html
4. Ostwald DA. Rethinking value assessment of preventive health interventions – A Health ROI Assessor framework. May 2024. [Accessed 03 Jun 2025]. Available at: https://www.ispor.org/docs/default-source/intl2024/20240428-dennis-ostwald-rethinking-value-assessment-of-preventive-health-interventions-ispor-atlanta.pdf?sfvrsn=77256ba_0
MarksMan Healthcare

June 3, 2025

Cost-benefit analysis, Health economics

Preventive health interventions, Value Assessment
Generalized Cost-Effectiveness Analysis for Enhanced Healthcare Decision-Making
In the intricate landscape of healthcare decision-making, the importance of evaluating cost-effectiveness cannot be overstated. This assessment helps determine the best use of resources, ensuring that health interventions provide maximum value for money. Traditional Cost-Effectiveness Analysis (CEA) has long been a cornerstone in health economics, providing insights into which interventions offer the most health benefits per unit of cost. However, this approach is often limited by its reliance on existing data and specific settings, making it challenging to apply universally across different health systems and economic contexts. Additionally, methodological differences between studies, the inability to assess the current mix of interventions, and the assumption that current resource allocation is efficient pose significant challenges.[1,2]

Generalized Cost-Effectiveness Analysis (GCEA), developed under the WHO’s CHOosing Interventions that are Cost-Effective (CHOICE) project, addresses these limitations by providing a more comprehensive, adaptable framework. GCEA evaluates interventions against a generalized comparator, often the null scenario, where no intervention is implemented. This “null” scenario removes the impacts of all currently implemented interventions to provide a baseline for comparison. This approach allows for a broader assessment of the relative cost-effectiveness of various health interventions, even in settings where detailed data might be lacking. Unlike traditional CEA, which tends to focus on comparing new interventions directly to existing alternatives, GCEA uses a standardized framework that facilitates a more universal application across diverse healthcare systems.[3]

One of the profound advantages of GCEA is its capability to guide healthcare decisions in a way that aligns with broader health system goals. For example, when evaluating interventions for chronic diseases, GCEA can incorporate a range of factors including long-term health outcomes, indirect costs, and system-level impacts. This comprehensive perspective ensures that health investments are aligned with strategic priorities such as equity, sustainability, and overall system efficiency. By taking into account indirect costs and long-term effects, GCEA provides a more nuanced understanding of an intervention’s value, making it a critical tool for strategic health planning. Costs should be estimated from the health care sector perspective and society’s perspective.[4]

Moreover, GCEA offers cross-country comparability. By standardizing the analytical framework and using a generalized comparator, GCEA enables policymakers to make more informed decisions based on globally comparable data. This is particularly valuable for low- and middle-income countries, where local data might be sparse, and decisions must be made with consideration of global evidence. GCEA facilitates a more consistent approach to evaluating health interventions, thereby supporting international efforts to harmonize health economic evaluations and promote best practices in resource allocation.[5]

The application of GCEA in real-world scenarios underscores its value. In the context of infectious diseases like malaria, GCEA has been employed to evaluate the cost-effectiveness of various prevention and treatment strategies, including vaccines, antimalarial drugs, and vector control measures. This has provided critical insights for policymakers in regions with high disease burdens, enabling more informed and effective resource allocation decisions. For instance, in several African countries, GCEA findings have directly influenced the adoption of insecticide-treated bed nets and indoor residual spraying as key malaria control strategies. The evidence provided by GCEA demonstrated that these interventions offered a high return on investment in terms of lives saved and disease burden reduced, leading to increased funding and widespread implementation of these programs. Furthermore, GCEA has informed the development of national malaria treatment guidelines, favoring artemisinin-based combination therapies (ACTs) due to their superior cost-effectiveness compared to older, less effective treatments. Similarly, GCEA’s methodology has proven effective in addressing the complexities of global health challenges, offering a robust framework for evaluating interventions in diverse epidemiological settings.[5,6]

Additionally, GCEA is increasingly relevant in assessing innovative and emerging healthcare interventions, such as novel therapies or digital health solutions. For instance, in pharmacoeconomics, GCEA can be used to evaluate new drug pricing models, considering not just the direct costs and clinical benefits, but also broader economic impacts and value elements that traditional CEA might overlook. This makes GCEA an essential tool in the evolving landscape of healthcare technology, where rapid advancements require flexible yet rigorous evaluation methods. [4]

As healthcare systems worldwide strive to achieve Universal Health Coverage (UHC), GCEA’s role becomes increasingly significant. By providing a transparent, evidence-based framework for evaluating the cost-effectiveness of health interventions, GCEA supports the goal of maximizing health benefits within available resources, ultimately contributing to more equitable and efficient health systems. The alignment of GCEA with UHC objectives underscores its potential to drive systemic improvements in healthcare delivery and resource utilization.[3]

However, the implementation of GCEA is not without its challenges. The methodology often requires complex data inputs, and there can be uncertainty in calculating both costs and outcomes, especially when projecting long-term impacts. Additionally, the generalizability of results can be limited by differences in local contexts, healthcare systems, and epidemiological profiles. Careful consideration of these factors is essential to ensure that GCEA provides meaningful and reliable guidance for healthcare decision-making.[3,4]

In conclusion, GCEA represents a significant advancement in health economic evaluation. Its ability to provide a flexible, comprehensive, and globally applicable framework makes it an invaluable tool for guiding healthcare investments. As health systems worldwide strive to achieve more with limited resources, GCEA offers a robust methodology to maximize health outcomes and enhance decision-making, ensuring that every investment in health delivers the highest possible value. By embracing GCEA, policymakers and health professionals can better navigate the complexities of healthcare economics, making well-informed decisions that benefit populations on a global scale.

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References:
1. Thomas R, Chalkidou K. Cost–effectiveness analysis. InHealth system efficiency: How to make measurement matter for policy and management. 2016. European Observatory on Health Systems and Policies.
2. Generalised cost-effectiveness analysis (GCEA). OECD Public Health Explorer. Available from: http://oecdpublichealthexplorer.org/ncd-doc/GCEA/head.html.
3. Generalized Cost-Effectiveness Analysis. World Health Organisation. Available from: https://www.who.int/teams/health-financing-and-economics/economic-analysis/health-technology-assessment-and-benefit-package-design/generalized-cost-effectiveness-analysis.
4. Padula WV, Kolchinsky P. Can Generalized Cost-effectiveness Analysis Leverage Meaningful Use of Novel Value Elements in Pharmacoeconomics to Inform Medicare Drug Price Negotiation?. Value in Health. 2024 Apr 26.
5. Hutubessy RC, Baltussen RM, Torres-Edejer TT, Evans DB. Generalised cost-effectiveness analysis: an aid to decision making in health. Applied Health Economics and Health Policy. 2002 Jan 1;1(2):89-95.
6. Morel CM, Lauer JA, Evans DB. Cost effectiveness analysis of strategies to combat malaria in developing countries. Bmj. 2005 Dec 1;331(7528):1299.
MarksMan Healthcare

February 10, 2025

Generalized Cost-Effectiveness Analysis, Global Health, Health economics, Healthcare Decision-Making
The EconLit Database: Unlocking the Wealth of Health Economic Knowledge
The EconLit database has established itself as the definitive cornerstone for published economic literature. This resource curated by the American Economic Association (AEA), has evolved significantly from its original role as a basic bibliography of economic works. With the rise of digital technology in the 1990s, EconLit became an electronic database, extending its reach and utility with the growing need for readily available economic information. With extensive findings dating back to the late 1980s, this database offers vast archive of Economic literature, providing a comprehensive historical perspective. Updated on a weekly basis, this expertly managed repository encompasses literature from prominent organizations across more than 74 countries and over 130 years.[1]

This database is known to include entries from over 1,000 reputed journals, with an optional full-text package of more than 500 journals, encompassing diverse and comprehensive collection of economic literature. Selected by the AEA based on their relevance and significance to the economic domain, these journals provide high quality data to index in the database.[1]

EconLit’s stringent indexing protocols further ensure proper and precise categorization of each record in the database with its relevant subject descriptors, substantiating the core reliability of the database. This facilitates users in efficiently finding the information they require.[1]

The EconLIt database employs a standard classification system, called the Journal of Economic Literature (JEL) system to classify and organize literature in the field of economics. This system facilitates the categorization of various types of scholarly works, including articles, dissertations, books, book reviews, and working papers. Each JEL code consists of a single alphabet followed by a two-digit numerical character. For example, A00 represents “General Economics and Teaching,” A12 indicates “Relation of Economics to Other Disciplines,” and this pattern continues through to Z, where Z12 denotes “Cultural Economics: Religion,” Z13 refers to “Economic Sociology; Economic Anthropology; Social and Economic Stratification,” and Z19 signifies “Cultural Economics: Other.” This system enhances appropriate categorization and retrieval of economic literature within the EconLit database, ensuring that users can effectively navigate the database and locate relevant resources.[2]

EconLit also uses “official” subject headings, meticulously crafted by the AEA. Paired with JEL Classification codes, these subject headings help the users to identify the relevant records accurately. With its straight, smart, and user-friendly interface, EconLit allows users to perform basic and advanced keyword searches and browse any subject of choice, to filter appropriate literature results by author list, title, or publication date. These features, complemented by Boolean searches, enable users to combine multiple search terms to narrow down their results effectively. In addition to these search functionalities, EconLit provides abstracts for most entries, offering users a snapshot of the content before diving into the full text. This feature is particularly useful for researchers conducting preliminary reviews of literature, saving time and ensuring that they can quickly identify relevant studies.[1-3]

In academia, EconLit is an indispensable tool for conducting economic literature reviews. It helps researchers in identifying gaps in existing research and formulating new research questions. Furthermore, policymakers and practitioners rely on EconLit to access empirical research and theoretical evaluations that guide policy decisions and strategic decision-making. HTA bodies such as the UK NICE often recommend that the industry submissions for cost-effectiveness evidence through comprehensive health technology assessments include EconLit as a source for literature.[4]

The interdisciplinary nature of EconLit also promotes collaboration across various fields of science. Economics frequently overlaps with other areas such as healthcare, sociology, political science, and environmental research, facilitating cross-disciplinary investigations and allowing researchers to draw connections between economics and other social sciences.[1,3]

In summary, the EconLit database is a vital resource for researchers and policymakers in the field of health economics. It provides a comprehensive database of literature that aids in critical analyses and supports evidence based decision-making. With its vast array of peer-reviewed articles, books, and dissertations, it not only enables a deep dive into the principles of health economics but also encourages inter-disciplinary insights into healthcare policy and practice. By providing access to a rich repository of empirical research and theoretical models, EconLit continues to play a critical role in driving advancements in understanding the economic elements influencing health outcomes and the healthcare delivery worldwide.

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References:
1. American Economic Association. About EconLit. Available from https://www.aeaweb.org/econlit/.
2. American Economic Association. JEL Classification Codes. Available from https://www.aeaweb.org/econlit/jelCodes.php.
3. EconLit Database Guide 2006, by Sharon Stillwagon, CSA Training & Information Specialist. Available from https://www.bus.umich.edu/kresgelibrary/downloads/instruction/econlit_guide.pdf.
4. NICE. Incorporating economic evaluation. In: Developing NICE guidelines: the manual. NICE process and methods [PMG20]. Last updated 29 May 2024 Available from: https://www.nice.org.uk/process/pmg20/chapter/incorporating-economic-evaluation
MarksMan Healthcare

July 26, 2024

EconLit Database, Economic outcomes, Health economics, Systematic Literature Reviews