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Abstract 195: The Importance Of Assessing Inter-regional Systems Of Healthcare In Patients With ST-Elevation Myocardial Infarction (STEMI): Examples From A Systematic Field Evaluation

2012· article· en· W2531447012 on OpenAlexaffabout
Laurie Lambert, Yongling Xiao, Simon Kouz, Stéphane Rinfret, Dave Ross, Eli Segal, Philippe L. L’Allier, Sébastien Maire, Alain Vanasse, Céline Carroll, C. Beauchamp, Maude Giguère, Peter Bogaty

Bibliographic record

VenueCirculation Cardiovascular Quality and Outcomes · 2012
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsHôpital FleurimontMontreal Heart InstituteCegep regional de LanaudiereMcGill University Health CentreInstitut National d'Excellence en Santé et en Services SociauxSanté MontérégieInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineHealth carePercutaneous coronary interventionMyocardial infarctionThrombolysisMedical emergencyEmergency medicineCardiology

Abstract

fetched live from OpenAlex

BACKGROUND: INESSS is a government-funded independent body that aids in evidence-based policy-making. Its cardiology evaluation unit recently completed a second systematic province-wide field evaluation of STEMI care in Quebec during a 6-month period in 2008-2009 in collaboration with a committee of clinical experts. The main objectives were to improve STEMI care by: 1) providing individual feedback to hospitals; and 2) identifying problems related to systems of STEMI care through analysis of inter-regional data. METHODS: At least 3 clinicians and 2 administrators of each of the 80 participating hospitals received a portrait of STEMI care for the province, their region and their hospital. Individual report cards ranked the healthcare region and the hospital for 14 measures of care. For the inter-regional analyses, we examined characteristics of existing networks of STEMI care such as the corridors of service for transfers for primary percutaneous coronary intervention (PPCI). RESULTS: At the provincial level, 82% of treated patients (n=1608) received PPCI. The majority (61%, n=987) were transferred from a non-tertiary centre with a median door-in door-out delay of 51 minutes (min) (10-90th percentile: 26-135) and a median door-to-device delay of 112 min (75-209). Notably, the 2 healthcare regions with the greatest number of STEMI patients had among the lowest proportions of patients treated (whether with PPCI or fibrinolysis) within recommended delays (39% and 32%, respectively). One of these regions had 9 community hospitals and a single PPCI center that did not have cardiac surgery-on-site (SOS) while the other region had 11 community hospitals and 6 PCI centers (1 no SOS and 5 SOS). In the latter region, >60% of STEMI patients had a direct admission PPCI but 3/6 centers had a median door-to-device time >90 min and there was a large variation in center volume. Only 22% of STEMI patients transferred for PPCI had a door-to device ≤90 min and choice of PPCI center was often not geographically optimal. Two PPCI centers received <5 transfers for PPCI. In the region with a single noSOS PPCI center, 76% of patients were transferred for PPCI but this center treated only 20% of these patients, 80% being sent to one of 4 PPCI centers in neighbouring regions. Only 19% of the transferred patients were treated ≤90 min, the median delay being 111 min (82-181). Sub-optimal utilization of the noSOS PPCI center in this region was also indicated by the low prevalence of direct admission PPCI (21%) compared with 2 other regions that had a single PPCI center (42% and 48%, respectively). CONCLUSIONS: Our province-wide evaluation of STEMI care indicates that it is important to examine systems of care as well as in-hospital processes. In 2 poorly-performing but high-output regions of Quebec, transfer for PPCI was the predominant choice of treatment of the community hospitals despite long delays. Moreover, recourse to certain PPCI centers appeared to be sub-optimal for both direct admission PPCI and transfer for PPCI. Thus, to improve systems of STEMI care, healthcare organizers must identify ways to optimize both choice of reperfusion strategy and corridors of service.

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)0.013
metaresearch head score (Gemma)0.002
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 score0.013
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.216
GPT teacher head0.455
Teacher spread0.238 · 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".

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Citations0
Published2012
Admission routes2
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