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Record W2219037751 · doi:10.1155/2008/147302

The Cycle of Fifths

2008· article· en· W2219037751 on OpenAlexaffvenue
Paul C. Adams

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2008
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsUniversity Hospital
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

To a student of music, the cycle of fifths refers to a concept in music theory in which every subsequent musical note in a scale moving clockwise is a fifth away from the previous note. To a gastroenterologist, it may confer another more ominous concept that is a fundamental reason why wait times for colonoscopy will continue to grow. There are few examples in contemporary medicine in which healthy people have been recommended to undergo surveillance procedures at intervals for the rest of their lives. Examples could include mammography and pap smears. Guidelines for screening colonoscopy are evolving, but a large percentage of the adult population could potentially be eligible on the basis of age, previous history of polyps, occult blood in stool or family history of colon cancer. In the case of a positive family history of colon cancer or in a patient in which polyps have been discovered, a cycle of colonoscopy may be initiated every five years on a lifelong basis. Thus, a new referral to remove a polyp in a 50-year-old woman may actually be a referral for eight colonoscopies until her death from other causes at 85 years of age. As these patients enter the waiting game for colonoscopy appointments, a clogging problem develops that is progressive and seemingly unending. A new gastroenterologist begins a busy practice and, in the background, their colonoscopy practice is already building five years from their starting day (Figure 1). The wait times build depending on the number of available slots and the number of referrals. This is modelled for several scenarios (Table 1). The number of second colonoscopies after five years is reduced in the model because of noncompliance, death and relocation. However, as the new initial colonoscopies overlap with repeat colonoscopies, the number of slots available is greatly reduced. As a result, the wait times increase significantly after year 5 (Figure 2). This problem compounds for a second time at year 10, when the number of available slots decreases again. Figure 1) The effects on wait times as initial colonoscopy referrals (•) overlap repeat surveillance colonoscopy (○) Figure 2) Effect of referral rate on waiting times. As initial colonoscopy bookings overlap repeat colonoscopy bookings, there is a marked increase in waiting times because there are fewer slots available for new bookings. This problem compounds at years 10, 15 ... TABLE 1 Modelling scenarios to estimate wait times for a gastroenterologist with 10 colonoscopy slots per week This problem becomes like a snowball rolling down a hill. The wait times continue to increase as long as the number of slots available is less than the number of referrals. There are no easy solutions to this problem. Hospital budgets are seemingly unable to expand existing endoscopy facilities to accommodate the increased demand for these services. Ambulatory endoscopy centres are developing, but gastroenterologists resent the lack of overhead fees that are enjoyed by other specialists (radiology, cardiology). There are many variables in the future that may affect this issue. These may include endoscopy by non-physicians, technical fees to encourage ambulatory endoscopy, or replacement of surveillance by imaging techniques. Scheduling software could be used more effectively to allow physicians to titrate input to capacity. The real losers in this cascade are the symptomatic patients who face significant wait times, because apparently normal cases have beaten them into the queue. The gastroenterologist risks becoming a ‘normoscopist’ because all of their slots have been filled by repeat colonoscopy. Another approach may be to dedicate hospital endoscopy slots to symptomatic patients, and follow-up cases to ambulatory endoscopy centres. As the ambulatory centre begins to clog, new centres need to be constructed. While this may be music to the ears of many gastroenterologists, there are significant financial hurdles before this could become a reality.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.344
Teacher spread0.301 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2008
Admission routes2
Has abstractyes

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