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Impact of an Intensive Care Unit Telemedicine Program on Patient Outcomes in an Integrated Health Care System

2014· article· en· W2090373984 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJAMA Internal Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversity of Toronto
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesU.S. Department of Veterans Affairs
KeywordsMedicineIntensive care unitIntensive careEmergency medicineObservational studyVeterans AffairsTelemedicineHealth careIntervention (counseling)Mortality rateIntensive care medicineNursingInternal medicine

Abstract

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IMPORTANCE: Intensive care unit (ICU) telemedicine (TM) programs have been promoted as improving access to intensive care specialists and ultimately improving patient outcomes, but data on effectiveness are limited and conflicting. OBJECTIVE: To examine the impact of ICU TM on mortality rates and length of stay (LOS) in an integrated health care system. DESIGN, SETTING, AND PARTICIPANTS: Observational pre-post study of patients treated in 8 "intervention" ICUs (7 hospitals within the US Department of Veterans Affairs health care system) during 2011-2012 that implemented TM monitoring during the post-TM period as well as patients treated in concurrent control ICUs that did not implement an ICU TM program. INTERVENTION: Implementation of ICU TM monitoring. MAIN OUTCOMES AND MEASURES: Unadjusted and risk-adjusted ICU, in-hospital, and 30-day mortality rates and ICU and hospital LOS for patients who did or did not receive treatment in ICUs equipped with TM monitoring. RESULTS: Our study included 3355 patients treated in our intervention ICUs (1708 in the pre-TM period and 1647 in the post-TM period) and 3584 treated in the control ICUs during the same period. Patient demographics and comorbid illnesses were similar in the intervention and control ICUs during the pre-TM and post-TM periods; however, predicted ICU mortality rates were modestly lower for admissions to the intervention ICUs compared with control ICUs in both the pre-TM (3.0% vs 3.6%; P = .02) and post-TM (2.8% vs 3.5%; P < .001) periods. Implementation of ICU TM was not associated with a significant decline in ICU, in-hospital, or 30-day mortality rates or LOS in unadjusted or adjusted analyses. For example, unadjusted ICU mortality in the pre-TM vs post-TM periods were 2.9% vs 2.8% (P = .89) for the intervention ICUs and 4.0% vs 3.4% (P = .31) for the control ICUs. Unadjusted 30-day mortality during the pre-TM vs post-TM periods were 7.7% vs 7.8% (P = .91) for the intervention ICUs and 12.0% vs 10.2% (P = .08) for the control ICUs. Evaluation of interaction terms comparing the magnitude of mortality rate change during the pre-TM and post-TM periods in the intervention and control ICUs failed to demonstrate a significant reduction in mortality rates or LOS. CONCLUSIONS AND RELEVANCE: We found no evidence that the implementation of ICU TM significantly reduced mortality rates or LOS.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.414
Teacher spread0.380 · 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