MétaCan
Menu
Back to cohort
Record W3176147849 · doi:10.1177/20543581211027969

An Environmental Scan and Evaluation of Quality Indicators Across Canadian Kidney Transplant Centers

2021· article· en· W3176147849 on OpenAlexafffundabout
Tamara Glavinovic, Amanda J. Vinson, Samuel A. Silver, Seychelle Yohanna

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2021
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsSt. Joseph’s Healthcare HamiltonKingston Health Sciences CentreMcMaster UniversityQueen's UniversityNova Scotia Health AuthorityUniversity of TorontoDalhousie UniversityHealth Sciences CentreSunnybrook Health Science Centre
FundersKidney Foundation of CanadaCanadian Institutes of Health ResearchCanadian Society of Nephrology
KeywordsMedicineKidney transplantationReferralNephrologyHealth careDialysisDelphi methodTransplantationFamily medicineIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Kidney transplantation is the optimal treatment for an individual requiring kidney replacement therapy, resulting in improved survival and quality of life while costing the health care system less than maintenance dialysis. Achieving and maintaining a kidney transplant requires extensive coordination of several different health care services. To improve the quality of kidney transplant care, quality metrics or indicators that encompass all aspects of the individual's journey to transplant should be measured in a standardized fashion. OBJECTIVE: To identify, categorize, and evaluate strengths and weaknesses of kidney transplant quality indicators currently being used across Canada. DESIGN: An environmental scan of quality indicators being used by kidney organizations and programs. SETTING: A 16-member volunteer pan-Canadian panel with expertise in nephrology, transplant, and quality improvement. SAMPLE: Transplant programs, as well as provincial transplant and kidney agencies across Canada. METHODS: Indicators were first categorized based on the period of transplant care and then using the Institute of Medicine and Donabedian frameworks. A 4-member subcommittee rated each indicator using a modified version of the Delphi consensus technique based on the American College of Physician/Agency for Healthcare Research and Quality criteria. Consensus ratings were subsequently shared with the entire 16-member panel for additional comments. RESULTS: We identified 46 measures related to transplant care across 7 Canadian provinces (9 referral and evaluation, 9 waitlist activity and outcomes, 6 hospitalization for transplant surgery, 12 posttransplant care, 6 organ utilization, 4 living donor). We rated 24 indicators (52%) as necessary to distinguish high-quality from low-quality care, most of which measured effective (n = 10) or efficient (n = 6) care. Only 7 (15%) of 46 indicators evaluated person-centered or equitable care. Fourteen common indicators were measured by 5 of 7 provinces, 10 of which were deemed "necessary," measuring safe (n = 2), effective (n = 5), efficient (n = 2), and equitable (n = 1) care. LIMITATIONS: The panel lacked patient and allied health representation. CONCLUSIONS: There are a large number of kidney transplant quality indicators currently being used in Canada, some of which are common across provinces and focus primarily on measuring effective care. Person-centered and equitable care indicators were lacking, and only half of these indicators were deemed "necessary" for quality improvement. Our results should complement ongoing work to achieve national consensus on the standardization of quality indicators in kidney transplantation.

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)0.039
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.961
Threshold uncertainty score0.637

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.073
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0140.028
Science and technology studies0.0060.002
Scholarly communication0.0040.001
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.323
Teacher spread0.301 · 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.

Study designObservational
DomainEvaluation
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".

Quick stats

Citations4
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Kidney Health and DiseaseSame topicDialysis and Renal Disease ManagementFrench-language works237,207