Evidence map›Paper›PMID 25218798›Full record

ArticleBMC family practice2014

Rating general practitioner consultation performance in cancer care: does the specialty of assessors matter? A simulated patient study.

Moyez Jiwa, Georgia Halkett, Xingqiong Meng, Melissa Berg

Abstract read
In one paragraph

Article in BMC family practice, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Moyez JiwaCurtin University, GPO Box U1987, Perth, Australia. m.jiwa@curtin.edu.au.
Georgia Halkett
Xingqiong Meng
Melissa Berg

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients treated for prostate cancer may present to general practitioners (GPs) for treatment follow up, but may be reticent to have their consultations recorded. Therefore the use of simulated patients allows practitioner consultations to be rated. The aim of this study was to determine whether the speciality of the assessor has an impact on how GP consultation performance is rated.

methodsSix pairs of scenarios were developed for professional actors in two series of consultations by GPs. The scenarios included: chronic radiation proctitis, Prostate Specific Antigen (PSA) 'bounce', recurrence of cancer, urethral stricture, erectile dysfunction and depression or anxiety. Participating GPs were furnished with the patient's past medical history, current medication, prostate cancer details and treatment, details of physical examinations. Consultations were video recorded and assessed for quality by two sets of assessors- a team of two GPs and two Radiation Oncologists deploying the Leicester Assessment Package (LAP). LAP scores by the GPs and Radiation Oncologists were compared.

resultsEight GPs participated. In Series 1 the range of LAP scores by GP assessors was 61%-80%, and 67%-86% for Radiation Oncologist assessors. The range for GP LAP scores in Series 2 was 51%- 82%, and 56%-89% for Radiation Oncologist assessors. Within GP assessor correlations for LAP scores were 0.31 and 0.87 in Series 1 and 2 respectively. Within Radiation Oncologist assessor correlations were 0.50 and 0.72 in Series 1 and 2 respectively. Radiation Oncologist and GP assessor scores were significantly different for 4 doctors and for some scenarios. Anticipatory care was the only domain where GPs scored participants higher than Radiation Oncologist assessors.

conclusionThe assessment of GP consultation performance is not consistent across assessors from different disciplines even when they deploy the same assessment tool.

Indexed as

Clinical CompetencePatient SimulationQuality Assurance, Health CareAnxietyDepressionDisease ManagementErectile DysfunctionFemaleGeneral PracticeHumansKallikreinsMaleNeoplasm Recurrence, LocalPhysician-Patient RelationsProctitisProstate-Specific AntigenKallikreinsKLK3 protein, humanProstate-Specific Antigen

Identifiers

PMID25218798
PMCPMC4176849

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.