Evidence map›Paper›PMID 21603050›Full record

ArticleOpen medicine : a peer-reviewed, independent, open-access journal2009

Prescription drug insurance and unmet need for health care: a cross-sectional analysis.

Gillian E Hanley

Abstract read
In one paragraph

Article in Open medicine : a peer-reviewed, independent, open-access journal, 2009. 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
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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

1 author.

Gillian E Hanley

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite Canada's universal health insurance coverage, many Canadians still report an unmet need for health care. I investigated whether not having prescription drug insurance increases the likelihood of reporting an unmet need for health care. I hypothesized that people without prescription drug insurance would be more likely than those with insurance to report an unmet health care need.

methodsI included 31 630 people in Ontario 64 years of age or younger who had participated in the Canadian Community Health Survey Cycle 3.1. Multivariate logistic regression models were used to obtain an adjusted odds ratio (OR) for the association between having prescription drug insurance and reporting an unmet need for health care in the past 12 months, adjusting for age, sex, socio-economic status, health status and having a regular medical doctor. The reasons for reporting an unmet need for care were stratified into reasons related or not related to prescription drug insurance. Three separate multivariate logistic regressions were performed to obtain an adjusted OR for the association between prescription drug insurance and unmet need based on the reasons for reporting unmet need.

resultsNot having prescription drug insurance that covers all or part of prescription medication costs increased the likelihood of reporting an unmet need for health care services (adjusted OR 1.27, 95% confidence interval [CI] 1.16-1.39). Not having such insurance significantly increased the likelihood of reporting an unmet need for health care for reasons that were related to prescription drug insurance (adjusted OR 2.21, 95% CI 1.80-2.71). This relation was not significant when the analysis was restricted to people who reported unmet need for health care for reasons that did not relate to prescription drug insurance (adjusted OR 1.12, 95% CI 1.00-1.23).

conclusionsThese results suggest an association between a lack of prescription drug coverage and reporting an unmet need for health care. This association warrants further investigation.

Identifiers

PMID21603050
PMCPMC3090122

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.