Evidence map›Paper›PMID 36100982›Full record

ArticleHealth economics2023

Testing for selection bias and moral hazard in private health insurance: Evidence from a mixed public-private health system.

Clifford Afoakwah, Joshua Byrnes, Paul Scuffham, Son Nghiem

Abstract read
In one paragraph

Article in Health economics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Recovery trajectories after a serious injury or illness: a longitudinal evaluation of health-related quality of life in an Australian cohort.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
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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

4 authors.

Clifford AfoakwahCentre for Applied Health Economics, Griffith University, Queensland, Nathan, Australia.ORCID 0000-0002-8551-3651
Joshua ByrnesCentre for Applied Health Economics, Griffith University, Queensland, Nathan, Australia.ORCID 0000-0001-6562-711X
Paul ScuffhamCentre for Applied Health Economics, Griffith University, Queensland, Nathan, Australia.ORCID 0000-0001-5931-642X
Son NghiemCollege of Health & Medicine, Australian National University, Canberra, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Separating selection bias from moral hazard in private health insurance (PHI) markets has been a challenging task. We estimate selection bias and moral hazard in Australia's mixed public-private health system, where PHI premiums are community-rated rather than risk-rated. Using longitudinal cohort data, with fine-grained measures for medical services predominantly funded by PHI providers, we find consistent and robust estimates of advantageous selection among hospitalized cardiovascular disease (CVD) patients. Specifically, we show that in addition to their risk-averse attributes, CVD patients who purchase PHI use fewer services that are not covered by PHI providers (e.g., general practitioners and emergency departments) and have fewer comorbidities. Finally, unlike previous studies, we show that ex-post moral hazard exists in the use of specific "in-hospital" medical services such as specialist and physician services, miscellaneous diagnostic procedures, and therapeutic treatments. From the perspective of PHI providers, the annual cost of moral hazard translates to a lower bound estimate of $707 per patient, equivalent to a 3.03% reduction in their annual profits.

Indexed as

Cardiovascular DiseasesInsurance, HealthHospitals, PrivateHumansMoralsSelection Biascardiovascular diseasemoral hazardprivate health insuranceselection bias

Identifiers

PMID36100982
PMCPMC10087718

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.