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Record W2736005035 · doi:10.1097/lbr.0000000000000415

Superspecialization and Health Care Cost

2017· editorial· en· W2736005035 on OpenAlexaboutno aff
Manuel L. Ribeiro Neto, Atul C. Mehta

Bibliographic record

VenueJournal of Bronchology & Interventional Pulmonology · 2017
Typeeditorial
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHealth careFamily medicinePublic relationsEconomic growthPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Who strive—you don’t know how the others strive To paint a little thing like that you smeared Carelessly passing with your robes afloat,- Yet do much less, so much less, Someone says, (I know his name, no matter)—so much less! Well, less is more, Lucrezia … (poem “Andrea del Sarto”, by Robert Browning, 1855). Health care cost in the United States is the highest in the world. In addition, it has been increasing linearly in the past 2 decades. A recent study estimated that health care expenditure on treatment of chronic respiratory diseases alone is increasing by 3.7% per year, reaching approximately 130 billion dollars in 2013.1 It is imperative that we attempt to identify the causes of this high-cost care, to be able to bend the curve of health care expenditure.2 Whether medical specialization, subspecialization, and superspecialization such as Interventional Pulmonology is one of the causes of this high-cost care is an interesting and unsettled debate. Is specialization a part of the problem or a part of the solution? There are good arguments on both sides. Training in specialization is more expensive and specialists may use expensive technology more commonly than do generalists. In addition, the ratio of specialists to primary care physicians is higher in the United States compared with that in other countries. These factors may contribute to the high cost of health care in the country.2,3 Challenging this belief, however, studies have shown that specialized care has reduced cost in many medical areas.4–6 We believe that specialization could and should be a part of the solution. Health care is experiencing a paradigm shift from volume-based care to value-based care. Value-based care entails the achievement of best outcomes at lowest cost. One essential component of the shift toward value-based care is the organization of patient care around specific medical conditions. In this model of care, physicians are experts in their field, familiar with the best available data to diagnose, treat, and prognosticate patients with those specific conditions. This scenario allows specialized physicians to develop and apply cost-reducing strategies while achieving the best outcomes for a specific patient population.7 Some examples from the field of bronchoscopy illustrate how specialized care can increase the value of the product—that is, ensuring the best outcomes while reducing cost for the patients. In patients with stage I pulmonary sarcoidosis, it is common to perform endobronchial ultrasound (EBUS) with transbronchial needle aspiration (TBNA) to confirm the presence of noncaseating granulomas. This has been well demonstrated by many studies in the past decade; in these studies a significant number of patients with stage I pulmonary sarcoidosis were included and they underwent EBUS-TBNA.8–10 However, a landmark study from Winterbauer et al11 from 1973 showed that patients with bilateral symmetric hilar adenopathy with uveitis, erythema nodosum, or no symptoms can be safely diagnosed with sarcoidosis without histologic proof. Thus, clinical acumen still remains the most reliable technique for making a diagnosis of stage I sarcoidosis. Physicians specialized in sarcoidosis can potentially gain enough experience to reach the same outcome—that is, diagnosis of sarcoidosis at lowest cost. We believe that with training and enough enthusiasm anyone can perform a procedure; yet, the “best interventionalist is the one who knows when not to perform an intervention.” Subspecialization can play a major role in this respect to reduce the health care cost while preserving patient welfare. The use of bronchoscopy to diagnose ventilator-associated pneumonia is probably a less-disputed scenario, but it is still a good example of specialization contributing to value-based care. A randomized controlled trial from the Canadian Critical Care Trials Group elegantly showed that we can achieve the same outcomes (eg, 28-day mortality) doing less (endotracheal aspiration instead of bronchoscopy with bronchoalveolar lavage).12 Critical care specialists familiar with this topic may be more prone to follow this less-invasive approach. Finally, we cite one more example from the lung cancer literature. In patients with suspected non–small-cell lung cancer, a staging strategy combining endosonography (EBUS and endoscopic ultrasound) and surgical stating, when compared with surgical staging alone, improved outcomes (ie, higher diagnostic accuracy) with fewer thoracotomies.13 Bronchoscopists with greater experience in EBUS should be able to perform better staging compared with less-experienced bronchoscopists, and consequently contribute to this value-based care.14 In other words, “Medical Mediastinoscopy” should preferably be performed at the centers of excellence to achieve the most cost-effective outcomes. There is no dearth of such examples in the literature in the diverse fields of superspecialization. The debate around specialization and health care cost will probably continue for a long time. In the meantime, specialized physicians should simply do their part. The responsibility of reducing heath care costs rests on the shoulders of superspecialists. This could be achieved by striking a balance between applying their clinical acumen and relying on technology. Authors strongly believe that, case by case, interventional pulmonologists should try to achieve the best outcomes for their patients with the least amount of interventions at the lowest possible cost—because it has been known for a long time that, sometimes, less is more. Manuel L. Ribeiro Neto, MD Atul C. Mehta, MD■ ■ ■ ■

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)0.002
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.161
GPT teacher head0.529
Teacher spread0.368 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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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Citations0
Published2017
Admission routes1
Has abstractyes

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