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Enregistrement W2013504325 · doi:10.3310/hta9030

Improving the referral process for familial breast cancer genetic counselling: findings of three randomised controlled trials of two interventions

2005· review· en· W2013504325 sur OpenAlex

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Notice bibliographique

RevueHealth Technology Assessment · 2005
Typereview
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueBRCA gene mutations in cancer
Établissements canadiensUniversity of Ottawa
Organismes subventionnairesHealth Technology Assessment ProgrammeNational Science CouncilEconomic and Social Research CouncilNational Institute for Health and Care Research
Mots-clésMedicinePsychological interventionReferralBreast cancerGenetic counselingRandomized controlled trialCancerFamily medicineInternal medicineNursing

Résumé

récupéré en direct d'OpenAlex

OBJECTIVES: To evaluate the effectiveness and cost-effectiveness of two complementary interventions, using familial breast cancer as a model condition. The primary care intervention consisted of providing computerised referral guidelines and related education to GPs. The nurse counsellor intervention evaluated genetic nurses as substitutes for specialist geneticists in the initial assessment and management of referred patients. DESIGN: The computerised referral guidelines study was a pragmatic, cluster randomised controlled trial (RCT) with general practices randomised to intervention or control groups. The nurse counsellor intervention was tested in two concurrent RCTs conducted in separate UK health service locations, using predetermined definitions of equivalence. SETTING: The computerised referral guidelines trial took place in general practices in Scotland from November 2000 to June 2001. The nurse counsellor intervention took place in a regional genetics clinic in Scotland, and in two health authorities in Wales served by a single genetics service during 2001. PARTICIPANTS: The computerised referral guidelines study involved GPs and referred patients. Both nurse counsellor intervention trials included women referred for the first time, aged 18 years or over and whose main concern was family history of breast cancer. INTERVENTIONS: The software system was developed with GPs, presenting cancer genetic referral guidelines in a checklist approach. Intervention GPs were invited to postgraduate update education sessions, and both intervention and control practices received paper-based guidelines. The intervention period was November 2000 to June 2001. For the nurse counsellor trial, trial 1 ran outpatient sessions with the same appointment length as the standard service offered by geneticists, but the nurse counsellor saw new patients at the first appointment and referred back to the GP or on to a clinical geneticist according to locally developed protocol, under the supervision of a consultant geneticist. The control intervention was the current service, which comprised an initial and a follow-up appointment with a clinical geneticist. In trial 2, a nurse counsellor ran outpatient sessions with the same appointment length as the new consultant-based cancer genetics service and new patients were seen at the first appointment and referred as in trial 1. The control intervention was a new service, and comprised collection of family history by telephone followed by a consultation with a clinical assistant or a specialist registrar, supervised by a consultant. The intervention was implemented between 1998 and 2001. MAIN OUTCOME MEASURES: In the software system trial, the primary outcome was GPs' confidence in their management of patients with concerns about family history of breast cancer. For the nurse counsellor trial, the primary outcome was patient anxiety, measured using standard scales. RESULTS: In the software system trial, 57 practices (230 GPs) were randomised to the intervention group and 29 (116 GPs) to the control group. No statistically significant differences were detected in GPs' confidence or any other outcomes. Fewer than half of the intervention GPs were aware of the software, and only 22 reported using it in practice. The estimated total cost was GBP3.12 per CD-ROM distributed (2001 prices). For the two arms of the nurse counsellor trial, 289 patients (193 intervention, 96 control) and 297 patients (197 intervention and 100 control) consented, were randomised, returned a baseline questionnaire and attended the clinic for trials 1 and 2 respectively. The analysis in both cases suggested equivalence in all anxiety scores, and no statistically significant differences were detected in other outcomes in either trial. A cost-minimisation analysis suggested that the cost per counselling episode was GBP10.23 lower in intervention arm than in the control arm and GBP10.89 higher in the intervention arm than in the control arm (2001 prices) for trials 1 and 2, respectively. Taking the trials together, the costs were sensitive to the grades of doctors and the time spent in consultant supervision of the nurse counsellor, but they were only slightly affected by the grade of nurse counsellor, the selected discount rate and the lifespan of equipment. CONCLUSIONS: Computer-based systems in the primary care intervention cannot be recommended for widespread use without further evaluation and testing in real practice settings. Genetic nurse counsellors may be a cost-effective alternative to assessment by doctors. This trial does not provide definitive evidence that the general policy of employing genetics nurse counsellors is sound, as it was based on only three individuals. Future evaluations of computer-based decision support systems for primary care must first address their efficacy under ideal conditions, identify barriers to the use of such systems in practice, and provide evidence of the impact of the policy of such systems in routine practice. The nurse counsellor trial should be replicated in other settings to provide reassurance of the generalisability of the intervention and other models of nurse-based assessment, such as in outreach clinics, should be developed and evaluated. The design of future evaluations of professional substitution should also address issues such as the effect of different levels of training and experience of nurse counsellors, and learning effects.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,979
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0040,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,117
Tête enseignante GPT0,485
Écart entre enseignants0,367 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle