MétaCan
Menu
Back to cohort
Record W2127916012 · doi:10.5858/2003-127-23-csia

Customer Satisfaction in Anatomic Pathology

2003· article· en· W2127916012 on OpenAlexaboutno aff
Richard J. Zarbo, Raouf E. Nakhleh, Molly K. Walsh

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationCustomer satisfactionQuality assuranceMedicinePatient satisfactionContext (archaeology)Family medicineHealth careMedical educationNursingPathologyExternal quality assessmentMarketingBusiness

Abstract

fetched live from OpenAlex

CONTEXT: Measurement of physicians' and patients' satisfaction with laboratory services has recently become a requirement of health care accreditation agencies in the United States. To our knowledge, this is the first customer satisfaction survey of anatomic pathology services to provide a standardized tool and benchmarks for subsequent measures of satisfaction. OBJECTIVE: This Q-Probes study assessed physician satisfaction with anatomic pathology laboratory services and sought to determine characteristics that correlate with a high level of physician satisfaction. DESIGN: In January 2001, each laboratory used standardized survey forms to assess physician customer satisfaction with 10 specific elements of service in anatomic pathology and an overall satisfaction rating based on a scale of rankings from a 5 for excellent to a 1 for poor. Data from up to 50 surveys returned per laboratory were compiled and analyzed by the College of American Pathologists. A general questionnaire collected information about types of services offered and each laboratory's quality assurance initiatives to determine characteristics that correlate with a high level of physician satisfaction. SETTING: Hospital-based laboratories in the United States (95.8%), as well as others from Canada and Australia. PARTICIPANTS: Ninety-four voluntary subscriber laboratories in the College of American Pathologists Q-Probes quality improvement program participated in this survey. Roughly 70% of respondents were from hospitals with occupied bedsizes of 300 or less, 65% were private nonprofit institutions, just over half were located in cities, one third were teaching hospitals, and 19% had pathology residency training programs. MAIN OUTCOME MEASURES: Overall physician satisfaction with anatomic pathology and 10 selected aspects of the laboratory service (professional interaction, diagnostic accuracy, pathologist responsiveness to problems, pathologist accessibility for frozen section, tumor board presentations, courtesy of secretarial and technical staff, communication of relevant information, teaching conferences and courses, notification of significant abnormal results, and timeliness of reporting). RESULTS: The database of 3065 physician surveys was derived from 94 laboratories. An average of 32.6 surveys (median 30) was returned per institution, with a range of 5 to 50 surveys per institution. The mean response rate was 35.6% (median 32.5%). The median (50th percentile) laboratory had an overall median satisfaction score of 4.4. The lowest satisfaction scores that were obtained all related to poor communication, which included timeliness of reporting, communication of relevant information, and notification of significant abnormal results. Statistically significant associations of customer satisfaction with certain institutional characteristics and laboratory performance improvement activities were identified. CONCLUSIONS: The importance of this satisfaction survey lies not in its requirement as an exercise for accrediting agencies but in understanding the needs of the customer (in this case the physician) to direct performance improvement in the delivery of quality anatomic pathology laboratory services.

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)0.003
metaresearch head score (Gemma)0.013
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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.027
GPT teacher head0.350
Teacher spread0.323 · 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".

Quick stats

Citations60
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueArchives of Pathology & Laboratory MedicineSame topicClinical Laboratory Practices and Quality ControlFrench-language works237,207