The surgical management of advanced ovarian cancer involves complex surgery. Implementation of a quality management program has a major impact on survival. The goal of this work was to develop a list of quality indicators (QIs) for advanced ovarian cancer surgery that can be used to audit and improve the clinical practice. This task has been carried out under the auspices of the European Society of Gynaecologic Oncology (ESGO).Methods
Quality indicators were based on scientific evidence and/or expert consensus. A 4-step evaluation process included a systematic literature search for the identification of potential QIs and the documentation of scientific evidence, physical meetings of an ad hoc multidisciplinarity International Development Group, an internal validation of the targets and scoring system, and an external review process involving physicians and patients.Results
Ten structural, process, or outcome indicators were selected. Quality indicators 1 to 3 are related to achievement of complete cytoreduction, caseload in the center, training, and experience of the surgeon. Quality indicators 4 to 6 are related to the overall management, including active participation to clinical research, decision-making process within a structured multidisciplinary team, and preoperative workup. Quality indicator 7 addresses the high value of adequate perioperative management. Quality indicators 8 to 10 highlight the need of recording pertinent information relevant to improvement of quality. An ESGO-approved template for the operative report has been designed. Quality indicators were described using a structured format specifying what the indicator is measuring, measurability specifications, and targets. Each QI was associated with a score, and an assessment form was built.Conclusions
The ESGO quality criteria can be used for self-assessment, for institutional or governmental quality assurance programs, and for the certification of centers. Quality indicators and corresponding targets give practitioners and health administrators a quantitative basis for improving care and organizational processes in the surgical management of advanced ovarian cancer.