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Record W2148186608 · doi:10.1258/jrsm.2011.110264

The grass isn't always greener

2012· article· en· W2148186608 on OpenAlexaboutno aff
David Bryson

Bibliographic record

VenueJournal of the Royal Society of Medicine · 2012
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careCommonwealthPer capitaMedicinePolitical scienceLawPopulationEnvironmental health

Abstract

fetched live from OpenAlex

Several years ago, at the height of President Obama's attempts to reform US healthcare, Iowan Senator Chuck Grassley, an opponent of fair and enlightened medical care, commented that had Senator Kennedy (brother of former President John F Kennedy) been treated for his brain tumour in Britain, he would have been denied care because of his age and left to die. Such a profound statement raises two important questions – first, what does Senator Grassley really know about healthcare in Britain, and second, how did a guy with a name like Chuck Grassley ever get elected to the US Senate? In a 2010 review of healthcare in the US and six other industrialized nations – Australia, Canada, Germany, the Netherlands, New Zealand and the UK – the Commonwealth Fund reported that America spent more than $2 trillion on healthcare, $7290 per person, in 2007. That same year, we in Britain spent $2992 per capita. The US ranked last in overall performance. Britain ranked second, first in terms of quality of healthcare.1 Such a disparity is nothing new. In 2000, the World Health Organization (WHO) published an assessment of the world's health systems. America ranked 37 out of 191 countries. Britain was 18th with the French healthcare service topping the table. For those Americans with health insurance the US can indeed be a fantastic place to get medical care. If you require hospitalization, you are likely to be admitted to a single en-suite room in a shiny and airy hospital replete with coffee shops, a bookstore, and in some cases, a small food court offering a choice of dining experiences. If specialist investigations like a CT or MRI are required, they will be performed almost immediately. Providing you have the resources or the appropriate insurance, you are virtually guaranteed a no-holds barred approach to the investigation and management of your ailment. But 15% of Americans – approximately 1 in 7 – don't have health coverage and thus no regular access to a doctor. Those who get sick and don't have insurance have two options: (1) keep their fingers crossed they qualify for government assistance; or (2) try to pay the bill and risk bankruptcy in the process. Last year, a family friend in America's Midwest, from Senator Grassley's own state no less, had an emergency below-knee amputation. The bill for the procedure – payment for the expertise of the surgeon and anaesthetist, for the stay in hospital and the care it provided – came to $30,000. He was lucky and was approved for state assistance, Medicaid as it is known. He had no job and no insurance, which is partly why his condition deteriorated and ended up requiring the procedure. Had he not qualified, he would have been left homeless and carless, stripped of all his worldly possessions to fund his healthcare. Even if you have health insurance it doesn't guarantee access to all the resources the US system has to offer. Insurance companies are, after all, out to make a profit and they can place restrictions and stipulations on your care – they can dictate which physician or surgeon treats you and can impose limits on the nature of the care you receive. If you want to go the extra mile, you will have to fund the difference. Also, every time you visit a doctor you will be required to make some contribution to the payment, colloquially known as a co-payment, which works out at around 10–20% of the cost of the consultation. The reason I mention all this is because I can't help but feel that, all too often, we in Britain fail to realize, or remember, just how lucky we are. It is well over half a century since the inception of the NHS and the creation of a far-reaching welfare state. The NHS is now the fourth largest employer in the world – behind the Chinese army, Wal-Mart, and the Indian Railways – but Aneurin Bevan's founding principles remain at the core of the British system: free medical care for all. Whether young or old, rich or poor, you will be treated just the same. That doesn't happen very much anymore, anywhere. It is something we should be proud of – really proud. In Britain, if you are sick and you need it, you will receive world class, evidence-based healthcare. At no point will anybody ask you to pay some, or all, of your healthcare costs. We may spend considerably less on healthcare per citizen than the US (of the six countries analysed by the US Commonwealth Foundation in 2010, only New Zealand spent less than Britain) but we have more hospital beds per capita, more nurses and midwives per 10,000, fewer deaths due to medical and surgical errors, a lower infant mortality rate and longer life expectancy;2,3 healthcare in this country is more accessible, equitable and efficient. In short, we have a healthcare service that 45 million uninsured Americans, and countless more people in both wealthier and less privileged nations, can only dream about. Of course, the NHS is not infallible. There will always be shortcomings and room for improvement. Now, I don't know enough about the proposed changes for the NHS to say whether it will be a good or a bad thing. What I do know is this – the NHS is here, it is ours, and we should be proud of it. For those people who deride it, who find reason to complain about the care they receive, I suggest they consider seeking healthcare elsewhere – America perhaps. Just be sure to take your chequebook and scrutinize your insurance policy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.061
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0100.008
Scholarly communication0.0110.013
Open science0.0010.005
Research integrity0.0040.012
Insufficient payload (model declined to judge)0.0610.022

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.407
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2012
Admission routes1
Has abstractyes

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