Evidence map›Paper›PMID 25966453›Full record

ArticleJournal of health economics2015

Welfare implications of learning through solicitation versus diversification in health care.

Anirban Basu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of health economics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. The impact of health literacy on healthcare spending: theory and evidence from China.International journal of health economics and management · 2026
    Article
  2. How to Examine External Validity Within an Experiment.Journal of economics & management strategy · 2023
    Article
  3. Evidence generation, decision making, and consequent growth in health disparities.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Anirban BasuDepartment of Pharmacy, Health Services and Economics, University of Washington, and The NBER, Cambridge, MA 1959 NE Pacific St, Box 357660, Seattle, WA 98195-7660, United States; NBER, Cambridge, MA, United States. Electronic address: basua@uw.edu.

Funding

Advancing Instrumental Variable Methods in Comparative Effectiveness ResearchRC4CA155809 · NCI · UNIVERSITY OF WASHINGTON · PI BASU, ANIRBAN · 2010 to 2010
$1.5M
Instrumental Variable Methods for Censored Cost Data and an Application in ProstaR01CA155329 · NCI · UNIVERSITY OF WASHINGTON · PI BASU, ANIRBAN · 2011 to 2013
$1.3M
NCI NIH HHS R01 CA155329NCI NIH HHS R01CA155329NCI NIH HHS RC4 CA155809NCI NIH HHS RC4CA155809
6 · The paper itself

Abstract

Using Roy's model of sorting behavior, I study welfare implications of learning about medical care quality through the current health care data production infrastructure that relies on solicitation of research subjects. Due to severe adverse-selection issues, I show that such learning could be biased and welfare decreasing. Direct diversification of treatment receipt may solve these issues but is infeasible. Unifying Manski's work on diversified treatment choice under ambiguity and Heckman's work on estimating heterogeneous treatment effects, I propose a new infrastructure based on temporary diversification of access that resolves the prior issues and can identify nuanced effect heterogeneity.

Indexed as

BiasLearningModels, PsychologicalQuality of Health CareComparative Effectiveness ResearchModels, StatisticalPatient SelectionComparative effectiveness researchDiversificationEconomic evaluationHeterogeneityInstrumental variablesLearning

Identifiers

PMID25966453
PMCPMC5845847

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.