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Record W2040774658 · doi:10.1111/acem.12491

Just Another Crowding Paper

2014· letter· en· W2040774658 on OpenAlexaboutno aff
Sandra M. Schneider

Bibliographic record

VenueAcademic Emergency Medicine · 2014
Typeletter
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCrowdingHeadlineNewspaperMedicineCrowding outPublicationPublic relationsLawPsychologyPolitical scienceEconomicsAdvertisingBusiness

Abstract

fetched live from OpenAlex

Imagine the impact of a paper entitled “Operative mortality increased by 3%.” Or perhaps a newspaper headline, “Woman in labor waits in hospital hallway for 6 hours.” In this month's Academic Emergency Medicine (AEM), we have an article that once again demonstrates serious consequences of boarding inpatients in our emergency departments (EDs) while they wait for hospital beds.1 Unfortunately for patients throughout the United States and some parts of Canada, this article will not have the impact it should. It will most likely become just another crowding paper. As a decision editor for AEM, my job is to select the best science on the best topics for our readers. As many of you who are authors realize, we take only a few of the many papers that are submitted. So my first reaction when receiving this paper was to reject it, not because the science was bad, but because it was yet another crowding paper. It, like all the others, shows that crowding is bad, very bad for our patients. So why publish another crowding paper? A year or so ago a group of us met with some federal policy-makers in Washington, DC, to discuss crowding and its consequences. The policy wonks were perplexed, as they thought the crowding issue had been solved. They had not seen it in the recent literature for more than 6 months, so it must be fixed. Lesson learned: we have to keep our issues in the forefront. Many emergency physicians who work in large crowded EDs have resigned themselves to boarding. There will always be boarding and crowding; they have given up hope that a solution will be found. It is easy to understand this, but such feelings lead to the normalization of deviance.2 In the space shuttle program there was an unsolvable problem with the heat shields. Over time workers accepted the heat shield failure as a natural part of business and no longer looked for a solution. The failure of the heat shield caused the shuttle disaster in the 1980s and cost the lives of many talented scientists. We cannot allow ourselves to consider boarding and crowding as normal. It will cost the lives of our patients. In 2002, an elderly woman spent 72 hours in the hallway of an ED in England. Her story became front page news and the public outcry led to the 4-hour target where 90%+ patients must leave the ED within 4 hours. While this rule led to some gaming of the data, most hospitals met the target to avoid financial penalties.3 The 4-hour target has been slackened somewhat, but there still is a priority to move patients swiftly through the ED and onto inpatient floors. Recently Australia has enacted its own brand of time targets.4 Even Canada has begun to implement time targets, with each province taking a slightly different approach. Of the four major countries that first developed emergency medicine as a specialty, only the United States has not dealt with boarding and crowding in its EDs. Hospitals now publicly report the ED length of stay for admitted patients. In the most recent reporting cycle, nearly 25% of hospitals did not report this measurement, according to HospitalCompare.gov. Of the hospitals that did report, nearly 60% reported median times of greater than 4 hours (recall the target in England is 90%+ patients leave within 4 hours) and 14% reported median times greater than 6 hours! Included in the group of hospitals that perform the worst are many hospitals listed in ratings of our “best hospitals.”5 So what will it take to end the practice of boarding inpatients in the ED? Clearly it will not be an elderly woman in the hall for 3 days. What will it take to move our patients into care areas that are appropriate for their disease? When we will stop having specialty care floors (oncology, cardiology, etc.) where patients are congregated to get the best care, but overflow patients are kept in a crowded generic ED? How much proof do we need to prove this practice is the most important safety issue facing our patients? The answers are not clear. What is clear is that we must continue to publish “another crowding paper.” We cannot become immune to boarders in our EDs, to see them as inevitable. Our research should be targeted to get the attention of the public and of special interest groups such as AARP. Our research should be targeted and distributed to policy-makers in Washington, DC, and our state health departments. We need to work in concert with these policy groups to devise ways to remove boarders from our EDs. The solutions are complex, tied to hospital reimbursement and operations. But unless hospitals see this as a problem, they will not go looking for a solution. In many cases they have already normalized this deviance. My hope is that someday future emergency physicians will look at the large body of work devoted to crowding and consider it as foreign as phrenology or urine therapy. Tales of inpatients waiting for hours or days will be akin to doctors using their bare hands to perform thoracotomies. Or, if we do not continue to pursue this research, they may wonder why we gave up.

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)0.022
metaresearch head score (Gemma)0.163
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: none
Teacher disagreement score0.094
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.163
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.002
Science and technology studies0.0080.004
Scholarly communication0.0230.017
Open science0.0030.007
Research integrity0.0140.015
Insufficient payload (model declined to judge)0.0940.061

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 head0.075
GPT teacher head0.358
Teacher spread0.284 · 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".

Quick stats

Citations3
Published2014
Admission routes1
Has abstractyes

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