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Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEmergency Medicine News · 2018
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWonderEmergency departmentTheme (computing)Health careMedical diagnosisPsychologyMedicinePolitical sciencePsychiatryLawSocial psychologyComputer science

Abstract

fetched live from OpenAlex

emergency medicine, uncertainty: emergency medicine, uncertaintyUncertainty is the driving force of the emergency department—it drives frightened patients to the ED to seek help and makes emergency physicians seek answers to puzzling diagnoses. Yet, payers and governments are hesitant to accept the reality of this uncertainty because the search for solutions can increase health care costs. A measurement of uncertainty called the U-Scale, under development by researchers at the Sidney Kimmel Medical College at Thomas Jefferson University in Philadelphia, may give emergency physicians and payers important clues about why patients come to the ED, go home unsure about their health status, and then return to the ED. Kristin Rising, MD, the director of acute care transition and an associate professor of emergency medicine at Jefferson, has focused her work on the patients' perspective about their needs when they returned to the emergency department. “The primary theme that has come up has been this ongoing fear and uncertainty that patients experience related to having symptoms,” she said. “It's scary and uncomfortable for many, and they don't know what they indicate. Do I have a new horrible disease and I'm going to die tomorrow? They don't know how to treat the symptoms or what they mean.” Dr. Rising said patients wonder why they have symptoms, so they come to a place where they can get answers, and this has been an underappreciated problem. “We need some way to tangibly measure this, and down the line measure their uncertainties better,” she said. Samuel G. Campbell, MB, BCh, a professor of emergency medicine at Dalhousie University in Halifax, Nova Scotia, Canada, said uncertainty is not limited to patients. Emergency physicians are often called upon to make decisions about patients based on inadequate knowledge, like one case where the “perfect storm” of uncertainty deferred the diagnosis for 24 hours of a diabetic patient on dialysis who suffered a seizure. (Acad Emerg Med 2007;14[8]:743; http://bit.ly/2JOXqrE.) The day after the seizure, the patient was seen by two emergency physicians, a cardiologist, and a neurologist. She was found to have been on warfarin for previous deep vein thrombosis a day after she was referred to the ED. A neurology consultant suspected spinal epidural hematoma, and an MRI showed a fracture at T12 with spinal compression. She was admitted to neurology with traumatic paraplegia. Dr. Campbell and his colleagues said error-producing conditions can result from uncertainty and the need to find an answer quickly can interfere with EPs' ability to diagnose a patient correctly. Dr. Campbell said this case was a classic example where a number of error-producing conditions interacted to produce a missed or delayed diagnosis. “I think it goes into this whole notion of uncertainty to a large degree. Emergency medicine is defined by decisions that people make with inadequate knowledge,” he said. The Price of Uncertainty Dr. Rising and her colleagues, in validating the U-Scale, identified domains of uncertainty related to new or ongoing symptoms. (J Health Psychol 2018. doi: 10.1177/1359105317752827. [Epub ahead of print]; http://bit.ly/2JVU7iw.) These symptoms involved recent ED patients who took part in group concept mapping. Patients were guided through brainstorming, sorting, and refining a set of ideas dealing with questions such as “When experiencing symptoms, people might choose to go to the emergency department when they feel uncertain about...?” The authors noted that their findings suggest that “uncertainty as measured by the U-Scale is only partially related to the state of anxiety and neuroticism, and thus, we are measuring something unique in the patient health care experience.” They said they hope to refine the scale to make it applicable to a variety of populations. Marianna D. LaNoue, PhD, an author of the study, said they want to test the scale in a more suburban setting to make sure they are capturing the full scope of the uncertainty. “The central hypothesis of the work is that the patients are not there because they know they have an acute problem but because they don't know what the right thing to do is,” she said. It is that uncertainty that some payers are seeking to control. The Centers for Medicare and Medicaid Services, for example, have set certain penalties for hospitals with patients who return for admission with 30 days at a high rate. Anthem, the nation's largest health insurance company, started to deny payment in 2015 for emergency department visits that the company decided were not truly emergencies. Its policy started in Kentucky, and has spread across several states. The company took a step back, however, when physicians, medical societies, and patients protested in February. Physicians admitted that some patients sought care in the emergency department unnecessarily, but that there is an equal risk that patients will avoid the emergency department when they need it because they fear the cost of an unreimbursed visit. A primary reason for both actions is uncertainty.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.668
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0350.001

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 head0.045
GPT teacher head0.357
Teacher spread0.311 · 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