Evidence map›Paper›PMID 38664713›Full record

ArticleIsrael journal of health policy research2024

Trust in public health policy in the time of the COVID-19 epidemic in Israel.

Jochanan Benbassat

Abstract readLetter
In one paragraph

Article in Israel journal of health policy research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Jochanan BenbassatDepartment of Health Policy Research, Myers-JDC-Brookdale Institute, Jerusalem, Israel. jochanan.benbassat@gmail.com.ORCID http://orcid.org/0000-0002-6217-5821

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The government of Israel provides universal health care through four health care organizations ("sick funds") that enjoy general public trust. In hindsight, the response of the government to the COVID-19 epidemic seems reasonable. In the first year of the epidemic, tests and vaccines were developed and other measures were taken, including social distancing, focusing on risk factors for infection and disease severity, and improving treatment. The COVID-19 mortality rate between January 2000 and June 2021 was around 750 per million inhabitants, well below the OECD average of 1300. Still, although the control measures were largely well received, the media and an ad hoc non-governmental Emergency Council for the coronavirus crisis in Israel criticized the government's response to the epidemic thereby contributing to a decline in public trust in government policy. This commentary provides an overview of the importance of trust in medical institutions and the difficulties of evaluating healthcare decisions in an attempt to justify three conclusions. First, when physicians and self-appointed experts publicly disapprove of a government policy, they should consider the trade-off between improving care and undermining public trust. Second, when evaluating a medical decision, experts should not ask, "Would I have acted differently?" but rather, "Was the decision under review completely unreasonable?" Thirdly, criticism is certainly worth listening to. However, I believe that by calling for organized resistance against the government, the publicly announced establishment of the Emergency Council for the Corona crisis blatantly crossed the line between constructive criticism and destructive mistrust.

Indexed as

COVID-19Health PolicyTrustHumansIsraelPublic HealthSARS-CoV-2COVID-19Medical errorProfessional opinionPublic trust

Identifiers

PMID38664713
PMCPMC11044392

What OpenQuestion holds

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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.