MétaCan
Menu
Back to cohort
Record W2462357409 · doi:10.1213/ane.0000000000000823

Drug Shortages in Perioperative Medicine

2015· letter· en· W2462357409 on OpenAlexaboutno aff
Gildàsio S. De Oliveira, Robert J. McCarthy

Bibliographic record

VenueAnesthesia & Analgesia · 2015
Typeletter
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEconomic shortagePerioperativeHarmAnesthesiologyDrugIntensive care medicinePharmacologyPsychiatrySurgeryLawGovernment (linguistics)

Abstract

fetched live from OpenAlex

The United States Food and Drug Administration defines a drug shortage as “a situation in which the total supply of all clinically interchangeable versions of an FDA-regulated drug is inadequate to meet the current or projected demand at the patient level.”a There is evidence that drug shortages are associated with patient harm, including death.1 In 2011, we examined the implications of drug shortages to the practice of anesthesiology and patient safety.2 Although our article was well received during the peer-review process, one of the reviewers was not convinced of the relevance of the topic. The reviewer thought that “the drug shortage problem is likely to be resolved by the time the manuscript is published.” This comment was particularly difficult to address because it likely required us to perform a complex model of economic forecasting for each drug.3 In addition, the decision to discontinue manufacturing a particular medication represents a strategic business decision by the pharmaceutical company using a process analogous to Porter’s Five Forces.4 Business strategic analyses frequently go beyond principles of supply and demand often used by health care economists.5 Our reviewer was wrong. From March 2014 through February 2015, several perioperative injectable medications were included on the national drug shortage list (Table 1).6 Drug shortages have yet to be resolved for the majority of perioperative injectable drugs. Despite significant advocacy by the American Society of Anesthesiologists and an executive order signed by President Obama in October 2011 to mitigate drug shortages,7 the current number of injectable drugs on a national shortage list is larger than in 2010.2 Drug shortages are an ongoing reality in the practice of anesthesiology for the foreseeable future.Table 1: IV Drug Shortages Affecting Anesthesia Practice from March 1, 2014, to February 27, 2015It is obvious that as a member of the perioperative team we need to inform and educate other anesthesiologists, resident physicians, nurse anesthetists, and our perioperative colleagues, including the surgeons, nurses, and health care administrators about the implications of a drug shortage on anesthesia practice and patient safety. The importance and implications of informing the most important stakeholder, the patient, about practice alterations because of drug shortages is less obvious, perhaps because it is so acutely uncomfortable. In this issue of the Anesthesia & Analgesia, Hsia et al.8 studied patients’ desire to be informed about drug shortages before undergoing elective cholecystectomies. Motivated by a national shortage of neostigmine, the authors performed a survey to identify patients’ desire to be informed about drug shortages. The majority of patients (60.9%) wanted to be informed about the drug shortage, even if the use of the substitute represented only slight differences in potential side effects compared with the unavailable drug. The authors explained to patients that this slight difference in side effects would be analogous to treating a headache with acetaminophen instead of aspirin. On the basis of their findings, we can conclude that most patients want to be informed about and engaged in decisions with potential minor consequences to their health care. Increased patient engagement has been shown to result in better care, outcomes, and (maybe) decreased costs in other clinical scenarios.9 Better care with lower costs is sometimes thought to involve conflicting goals for health care systems. However, initial studies have pointed toward patient engagement as a viable pathway to achieve both outcomes.10 Nonetheless, not all patients are able to engage in their own care given the complexities of our health care system. In addition, patients with poor health literacy (approximately 36% of adults in the United States) are unable to process even basic health information and lack a true understanding of their medical condition.11 There are additional barriers to patient engagement. On the patient side, reluctance to consider costs, cultural differences, and cognitive issues may preclude effective engagement.12 On the health care provider side, time restrictions, lack of training, and lack of incentives are significant obstacles.12 Effective strategies to inform patients is the first step. However, effective patient engagement is more difficult than merely informing patients. One of the most beneficial aspects of patient engagement is the development of a shared decision-making model. This model can be used in patients who have “preference-sensitive” treatment options such as the elective cholecystectomy presented in the current study.13 In the event of a drug shortage, patients would balance their risk of having a substitute drug versus postponing their elective procedure. Interestingly, Hsia et al. found that a large proportion of patients (33.6%) would postpone surgery even if the difference in a substituted drug’s side effects was small. This finding may have liability implications if patients undergoing elective procedures are not fully informed of the risks incurred by substituting drugs considered even slightly less safe than the unavailable drug. One major limitation in the study by Hsia et al. is the low response rate obtained in their survey. The authors attempted to address this problem by externally validating their results in a second group of patients from Canada. Readers can interpret the associations presented in the study as valid but the overall descriptive statistics as less reliable because of the potential effect of response bias. Nevertheless, we believe that the associations presented are more important because the overall descriptive statistics are likely to vary according to different health care systems, patients’ degree of health literacy, and overall perception of surgical risk by patients. Like the drought in the American Southwest, shortages of perioperative injectable drugs are our new reality for the foreseeable future. The study by Hsia et al. tells us that patients want to know about shortages of drugs used during anesthesia so that they can make informed health care decisions. We must engage our patients in these discussions, ideally before the day of surgery, to respect their rights to make informed decisions. In addition, by fully informing patients, they can become our partners in seeking health care policies that reduce the incidence of drug shortages in the future. DISCLOSURES Name: Gildasio S. De Oliveira, Jr., MD, MSCI. Contribution: This author contributed to manuscript preparation. Attestation: Gildasio S. De Oliveira, Jr., approved the final manuscript and attests to the integrity of the analysis reported in this manuscript. Name: Robert J. McCarthy, PharmD. Contribution: This author contributed to manuscript preparation. Attestation: Robert J. McCarthy approved the final manuscript and attests to the integrity of the analysis reported in this manuscript. This manuscript was handled by: Steven L. Shafer, 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 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)0.016
metaresearch head score (Gemma)0.126
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 score0.018
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.126
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0030.008
Scholarly communication0.0070.012
Open science0.0030.003
Research integrity0.0180.022
Insufficient payload (model declined to judge)0.0060.003

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 head0.064
GPT teacher head0.290
Teacher spread0.227 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueAnesthesia & AnalgesiaSame topicPharmaceutical Economics and PolicyFrench-language works237,207