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PD58-06 IMPLEMENTING AND EVALUATING THE EFFICACY OF AN ACUTE CARE UROLOGY MODEL OF CARE IN A LARGE COMMUNITY HOSPITAL

2019· article· en· W2940617966 on OpenAlexaboutno aff
Abirami Kirubarajan, Roger Buckley, Shawn Khan, Rebecca Richard, Veselina Stefanova, Nicole Golda

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineReferralRenal colicAcute careEmergency departmentPatient careComplaintChartGeneral surgeryFamily medicineNursingAlternative medicineHealth care

Abstract

fetched live from OpenAlex

INTRODUCTION AND OBJECTIVES:To compare the rate of hospital based outcomes including 30-day readmission rates, perioperative mortality, and length of stay (LOS) in patients with urologic malignancies who underwent surgery as part of treatment in academic and community hospitals METHODS: We retrospectively reviewed the Vizient CDB (Irving, Texas) from September 2014 to December 2017.Vizient includes approximately 97% of academic hospitals (AH) and more than 40 community hospitals (CH).This is a comparative database and measures performance within and between institutions.Data include patient demographics, readmission rates, costs, LOS, case mix index (CMI) and mortality.Patients aged !18 were included and ICD-9 codes were used to identify patients with urologic malignancies who underwent surgical treatment.Chi square and student t-tests were used to compare categorical and continuous variables, respectively RESULTS: We identified a total of 37,628 cases.There were 33,290 (88%) procedures performed in AH and 4,330 (12%) in CH.These included prostatectomy (18,540), radical nephrectomy (rNx) 8,059, partial nephrectomy (pNx) (5,287), radical cystectomy (4,421), radical nephroureterectomy (rNu) (1,006), and partial cystectomy (321).There were no significant differences in 30-day readmission rates or mortality for any procedure between academic and community hospitals (Table 1), p> 0.05 for all.LOS was significantly lower for radical cystectomy and prostatectomy in AH (P<0.01 for both) and lower for rNx in CH (p[0.03).Academic hospitals had a significantly lower amount of partial cystectomies performed when compared to community centers (6.2% vs 16.2% P<0.001), and a similar number of partial nephrectomies performed (39.8% vs 38.0%, P[0.2).The mean direct cost for index admission was significantly higher in AH for rNx, pNx, rNu, and prostatectomy.Case complexity measured using the CMI was similar between the community and academic hospitals CONCLUSIONS: The Vizient CDB provides a novel resource for observational data at US hospitals.Despite academic and community hospitals having similar case complexity, direct costs were lower in community hospitals without an associated increase in readmission rates or deaths.The only clinically significant difference in length of stay was shorter stays for cystectomy in academic centers

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)0.024
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.438
Threshold uncertainty score0.872

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0040.002
Open science0.0030.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.002

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 head0.066
GPT teacher head0.475
Teacher spread0.409 · 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 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
Published2019
Admission routes1
Has abstractyes

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