Privacy rights and improving knowledge are not hierarchical needs: data protection and good epidemiologic standard (DP_GOES) checklist for retrospective observational studies using secondary data.

Starting with the Nuremberg Code in 1947, several guidelines were developed to formulate rules to guide research on humans and safeguard the rights and well-being of subjects participating in clinical research. In recent years, retrospective observational studies based on disease and drug registries, surveillance systems, hospital-based data lakes and platforms, and unstructured data have gained progressively greater attention in the medical literature. Although several guidelines and checklists are currently available to develop and evaluate a protocol for observational studies, issues concerning ethical considerations, data protection and data access have been often ignored. We propose the Data Protection and Good Epidemiologic Standard (DP_GOES) checklist for the development and evaluation of the protocol of observational, retrospective studies based on secondary data. The checklist is divided into four parts, 9 sections and 68 items, and should help to verify whether the study protocol respects the constraints of the regulatory requirements and provisions of data protection authorities, while ensuring that the study may generate robust evidence potentially useful to promote health, supplying more effective healthcare, and guaranteeing system sustainability. The DP_GOES checklist represents a novel and integrative contribution, as it systematically combines epidemiological research standards with data protection principles. Its practical value lies in offering a structured and operational tool that supports both researchers and evaluators in conducting and assessing retrospective observational studies based on secondary data in a rigorous, transparent, and ethically accepted manner.