Systematic review of learning curves in robot‐assisted surgery

Background Increased uptake of robotic surgery has led to interest in learning curves for robot‐assisted procedures. Learning curves, however, are often poorly defined. This systematic review was conducted to identify the available evidence investigating surgeon learning curves in robot‐assisted sur...

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Veröffentlicht in:BJS Open 2020-02, Vol.4 (1), p.27-44
Hauptverfasser: Soomro, N. A., Hashimoto, D. A., Porteous, A. J., Ridley, C. J. A., Marsh, W. J., Ditto, R., Roy, S.
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Sprache:eng
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Zusammenfassung:Background Increased uptake of robotic surgery has led to interest in learning curves for robot‐assisted procedures. Learning curves, however, are often poorly defined. This systematic review was conducted to identify the available evidence investigating surgeon learning curves in robot‐assisted surgery. Methods MEDLINE, Embase and the Cochrane Library were searched in February 2018, in accordance with PRISMA guidelines, alongside hand searches of key congresses and existing reviews. Eligible articles were those assessing learning curves associated with robot‐assisted surgery in patients. Results Searches identified 2316 records, of which 68 met the eligibility criteria, reporting on 68 unique studies. Of these, 49 assessed learning curves based on patient data across ten surgical specialties. All 49 were observational, largely single‐arm (35 of 49, 71 per cent) and included few surgeons. Learning curves exhibited substantial heterogeneity, varying between procedures, studies and metrics. Standards of reporting were generally poor, with only 17 of 49 (35 per cent) quantifying previous experience. Methods used to assess the learning curve were heterogeneous, often lacking statistical validation and using ambiguous terminology. Conclusion Learning curve estimates were subject to considerable uncertainty. Robust evidence was lacking, owing to limitations in study design, frequent reporting gaps and substantial heterogeneity in the methods used to assess learning curves. The opportunity remains for the establishment of optimal quantitative methods for the assessment of learning curves, to inform surgical training programmes and improve patient outcomes. Antecedentes La aceptación creciente de la cirugía robótica ha generado interés en las curvas de aprendizaje para los procedimientos asistidos por robot. Sin embargo, las curvas de aprendizaje a menudo están mal definidas. Esta revisión sistemática se realizó para identificar la evidencia disponible en relación a las curvas de aprendizaje del cirujano en la cirugía asistida por robot. Métodos En Febrero de 2018, se realizaron búsquedas en MEDLINE, Embase y Cochrane Library, de acuerdo con las recomendaciones PRISMA, junto con búsquedas manuales de congresos clave y de revisiones ya existentes. Los artículos elegibles fueron aquellos que evaluaron las curvas de aprendizaje asociadas con la cirugía asistida por robot efectuada en pacientes. Resultados Las búsquedas bibliográficas identificaron 2.316 registros de
ISSN:2474-9842
2474-9842
DOI:10.1002/bjs5.50235