ArticleJournal of health economics2011
Economics of individualization in comparative effectiveness research and a basis for a patient-centered health care.
Article in Journal of health economics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- A Framework for Using Cost-effectiveness Analysis to Support Pricing and Reimbursement Decisions for New Pharmaceuticals in a Context of Evolving Treatments, Prices, and Evidence.PharmacoEconomics · 2025Article
- Machine Learning Methods to Estimate Individualized Treatment Effects for Use in Health Technology Assessment.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Review
- Tools for the Economic Evaluation of Precision Medicine: A Scoping Review of Frameworks for Valuing Heterogeneity-Informed Decisions.PharmacoEconomics · 2022Article
- A Machine-Learning Approach for Estimating Subgroup- and Individual-Level Treatment Effects: An Illustration Using the 65 Trial.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
- Economic analyses of behavioral health intervention implementation: Perspective on stakeholder engagement.Frontiers in psychiatry · 2022Article
- Evidence generation, decision making, and consequent growth in health disparities.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Assessing provider and racial/ethnic variation in response to the FDA antidepressant box warning.Health services research · 2019Article
- Through the Looking Glass: Estimating Effects of Medical Homes for People with Severe Mental Illness.Health services research · 2017Article
- Article
- Economic Evaluation in Stratified Medicine: Methodological Issues and Challenges.Frontiers in pharmacology · 2016Article
- Welfare implications of learning through solicitation versus diversification in health care.Journal of health economics · 2015Article
- Addressing preference heterogeneity in public health policy by combining Cluster Analysis and Multi-Criteria Decision Analysis: Proof of Method.Health economics review · 2015Article
- Concepts of 'personalization' in personalized medicine: implications for economic evaluation.PharmacoEconomics · 2015Article
- The value of heterogeneity for cost-effectiveness subgroup analysis: conceptual framework and application.Medical decision making : an international journal of the Society for Medical Decision Making · 2014Article
- Heterogeneity in action: the role of passive personalization in comparative effectiveness research.Health economics · 2014Article
- Patient-centered or 'central' patient: Raising the veil of ignorance over randomization.Statistics in medicine · 2012Article
- Autism spectrum disorders: a review of measures for clinical, health services and cost-effectiveness applications.Expert review of pharmacoeconomics & outcomes research · 2012Review
- The impact of comparative effectiveness research on health and health care spending.Journal of health economics · 2011Article
- ESTIMATING PERSON-CENTERED TREATMENT (PeT) EFFECTS USING INSTRUMENTAL VARIABLES: AN APPLICATION TO EVALUATING PROSTATE CANCER TREATMENTS.Journal of applied econometrics (Chichester, England)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
The United States aspires to use information from comparative effectiveness research (CER) to reduce waste and contain costs without instituting a formal rationing mechanism or compromising patient or physician autonomy with regard to treatment choices. With such ambitious goals, traditional combinations of research designs and analytical methods used in CER may lead to disappointing results. In this paper, I study how alternate regimes of comparative effectiveness information help shape the marginal benefits (demand) curve in the population and how such perceived demand curves impact decision-making at the individual patient level and welfare at the societal level. I highlight the need to individualize comparative effectiveness research in order to generate the true (normative) demand curve for treatments. I discuss methodological principles that guide research designs for such studies. Using an example of the comparative effect of substance abuse treatments on crime, I use novel econometric methods to salvage individualized information from an existing dataset.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.