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Optimizing Antimicrobial Use in Nursing Homes: No Longer Optional

2007· letter· en· W1531328707 on OpenAlexaboutno aff
Lona Mody

Bibliographic record

VenueJournal of the American Geriatrics Society · 2007
Typeletter
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsnot available
FundersNational Institute on Aging
KeywordsMedicineNursing homesNursingAntimicrobialGerontologyMicrobiology

Abstract

fetched live from OpenAlex

Empirical and often inappropriate antimicrobial usage is extensive in all settings, but particularly in nursing homes (NHs).1 Frequently, a clinical course of antibiotics is initiated without an adequate clinical evaluation. For example, up to one-third of prescriptions for suspected urinary tract infection in NH residents are for asymptomatic patients who are bacteriuric.2 Inappropriate antibiotic usage also results from errors in drug choice, the duration or dosage of antibiotics, and the lack of appropriate laboratory testing. Unnecessary and inappropriate use of antimicrobials, like other systemic drugs, has dire consequences such as drug interactions, adverse drug events, development of antimicrobial resistance, and excess costs.1,3–5 Although appropriate antimicrobial usage is desired, its application in NHs is challenging, predominantly as a consequence of delay in diagnosis due to the absence of on-site physicians, lack of clinical findings in older adults, presentation of infection with generalized systemic symptoms (such as confusion and falls) rather than infection-specific presentation, and lack of on-site diagnostics.1 Several strategies have been studied or proposed to reduce inappropriate antimicrobial practices in NHs. These include antimicrobial use review by the infection control committee to monitor antibiotics prescribed in the NH; development and promotion of programs to optimize judicious antibiotic use; and as-needed audits to assess antibiotic appropriateness, prevalence of antibiotic resistance, and antibiotic-related adverse events.1,6 A recent study in multiple NHs in the United States and Canada evaluated the effectiveness of a more-proactive approach to minimizing inappropriate antimicrobial practices.7 This study advocated the use of clinical algorithms targeted to physicians and nurses and implementing a multicomponent program of education, written material, real-time reminders, and outreach visits to reduce urinary tract infections in NHs. The authors showed a 31% reduction in antimicrobial use for urinary tract infections, although they did not show a reduction in overall antimicrobial use. In another randomized study in 20 NHs in the United States, a multicomponent educational intervention focusing on NH-acquired pneumonia led to a significant improvement in guideline adherence, but the study did not show a change in the use of oral antibiotics.8 This issue of the Journal of the American Geriatrics Society (JAGS) contains two articles that evaluate the effect of educational interventions to optimize overall antimicrobial prescribing for common infections in NHs.9,10 The first study, by Monette et al., was conducted in eight public NHs in Ontario, Canada.9 Their goal was to propose a realistic educational intervention to optimize antibiotic prescribing practices for a variety of infections, including urinary tract infections, skin and soft tissue infections, and pneumonia. Because a facility-wide intervention was used, cluster randomization design was employed to reduce the risk of contamination between study and control units. With the assistance of each facility pharmacist, they developed an antibiotic guide listing common infections; recommended empirical antibiotics; and the dosage, frequency, and duration of treatment. This guide was then mailed twice (2 months apart) to the physicians in the experimental arm. Data on antibiotic prescribing practices were also collected. They demonstrated that inappropriate antibiotic prescriptions decreased 20.5% in the experimental group, compared with 5.1% in the control group. As with any randomized, controlled trial, true effect, confounding, bias, or random error could explain these results. Their study design, sample size calculations, and multivariate analyses reduced the chances of random error and other confounding factors, although the study's high refusal rate (19/30 NHs refused to participate), which could suggest that the study approach may not be generalizable to all NHs, could have introduced some bias. In addition, the need for an in-house pharmacist, because this intervention was essentially a pharmacist-directed intervention, could limit the applicability of this intervention. Nonetheless, the study demonstrated the effectiveness of mailing an antibiotic guide to physicians in reducing inappropriate antibiotic prescribing. The second study, by Schwartz et al.,10 evaluated the effectiveness of educational interventions targeted to physicians providing care at a single large hospital-based NH in Chicago, Illinois. Their intervention consisted of four teaching sessions, which included national guidelines, hospital resistance data, physician feedback, and distribution of booklets detailing institutional guidelines on optimal management of various infections found in NH residents. Their follow-up data showed improvement in the diagnosis of infection as reflected by the documentation of specific infections based on guideline-specific criteria. Furthermore, the authors noted improvement in antibiotic prescribing practices, aligning them more with their institutional guidelines for a sustained follow-up period of 2 years. Although their hospital-based NH facility had the advantage of on-site diagnostic capabilities and on-site infectious disease consultants, the study supports prior evidence that diagnosis and antibiotic prescribing can be improved in a sustained fashion by using educational interventions targeting healthcare providers. These studies prompt the obvious next research questions: Do these educational interventions aimed at adhering to established guidelines and optimizing antibiotic prescriptions eventually lead to reductions in morbidity, hospitalizations, and death and declines in antibiotic resistance? Do these interventions reduce drug interactions and adverse drug events? What are the short- and long-term cost implications? In summary, it is now well known that a significant proportion of antibiotic use in NHs is inappropriate and potentially harmful. Tough systemic challenges in diagnosing and effectively treating infections and the lack of clinical trials have limited prior efforts to optimize antibiotic use in this setting. Recent studies, including the two papers in this month's JAGS, offer simple interventions that could lead to a change in prescribing practices among NH physicians, although periodic education and reminders for all healthcare staff will be required for a sustained effect. Although the facilities that implement these interventions may differ from the study facilities, the proposed interventions are achievable under the leadership of an effective champion—an infection control practitioner or a medical director. With the growing body of evidence demonstrating the effectiveness of simple educational interventions, a proactive approach to curbing and eventually eliminating inappropriate antibiotic usage in NHs is no longer optional. Financial Disclosure: Dr. Mody is employed at the University of Michigan and Ann Arbor Department of Veterans Affairs Medical Center and she has received grant funding through the National Institute on Aging and had received the T. Franklin Award from the American Geriatrics Society and the Association of Subspecialty Professors. Author Contributions: Dr. Mody is the sole contributor to this editorial. Sponsor's Role: None.

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 categoriesMeta-epidemiology (narrow), Research integrity
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 score0.361
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.018
GPT teacher head0.292
Teacher spread0.274 · 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
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".

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Citations14
Published2007
Admission routes1
Has abstractyes

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