Geriatric patients are at increased risk of developing postoperative neurocognitive disorders, including delirium. Existing evidence-based perioperative interventions need to be implemented into routine care to improve postoperative outcomes. In this qualitative interview study, we wanted to collect stakeholder experiences to understand the implementation process of a multi-component intervention to prospectively facilitate future implementation.

Descriptive qualitative evaluation research.

Single-centre at a German major urban academic hospital.

22 interviews were conducted with n = 7 geriatric patients after surgery who had received a comprehensive geriatric assessment and an individualised perioperative multi-component intervention, and n = 15 healthcare professionals, including nurses, physicians and medical assistants working in the perioperative care.

Semi-structured interviews were conducted, addressing the implementation procedure of the multicomponent intervention and the experience with it within the routine setting.

The implementation outcomes were adoption, acceptance, appropriateness, feasibility and sustainability.

Transcribed audio recordings were analysed with directed content analysis. Most intervention components could be adopted during the pilot trial. Implementation barriers were identified. Limited resources and logistic constraints threatened feasibility and sustainability. Acceptance of patients and healthcare providers regarding an intervention depended on its perceived appropriateness, which varied per intervention component, workspace and duration of the implementation.

We were able to replicate and extend previous findings on the implementation of improved perioperative care. To facilitate the implementation success and motivation to implement evidence-based measures, resource allocation needs to be adjusted and standard operational procedures, as well as the cross-sectional collaboration, must be simplified.

NCT03325413.

There is limited evidence regarding the outcomes and impacts of Patient and public involvement (PPI) in research, mainly based on narrative studies. Existing frameworks for supporting and evaluating PPI often require adaptation to specific contexts, and comprehensive instruments are needed. From an international perspective, strengthening the scientific foundation that underpins PPI is crucial to generate stronger evidence to understand which approaches work best, in which contexts, and with what effects.

To promote PPI implementation in German health research, this project aims to (1) Establish an evaluation framework, (2) Develop a modular evaluation tool in the form of a questionnaire and (3) Pilot and psychometrically validate the tool.

A three-phase mixed methods approach will be employed, integrating qualitative and quantitative data. First, we will explore with researchers, research partners and other stakeholders in health services research what contributes to meaningful and successful PPI through a web-based survey and focus groups. Findings are discussed in a codesign workshop in which participants agree on an evaluation framework based on a LOGIC model. Second, items from international instruments that evaluate PPI are deductively assigned to the evaluation framework. Further items are developed based on the focus groups from phase 1. Cognitive pretests and qualitative review will be conducted with researchers and patients in order to refine the item pool and develop the evaluation tool. Third, the evaluation tool with modules for researchers and patients will be piloted in a web-based survey. Data analysis will include thematic analysis for qualitative data and descriptive and psychometric analyses for quantitative data. A participatory research team will provide ongoing support throughout all project phases.

Ethical approval has been obtained from the Local Ethics Committee of the Centre for Psychosocial Medicine, University Medical Centre Hamburg-Eppendorf (LPEK-0889). The study will follow the principles of the Helsinki Declaration and good scientific practice. Results will be disseminated at national and international conferences, public symposiums and in peer-reviewed journals, contributing to the internationally developing field of PPI in research and addressing relevant research gaps.

Data quality in epidemiological studies is a basic requirement for good scientific research. The aim of this study was to examine an important indicator of data quality, data completeness, by investigating predictors of missing data.

Baseline data of a cohort study, the population-based Hamburg City Health Study, were used. Missingness was investigated at the levels of a whole research unit, on the two segments of health service utilisation and psychosocial variables, and two sensitive items (income and number of sexual partners). Predictors for missingness were sociodemographic variables, cognitive abilities and the mode of data collection. Associations were estimated using binary and multinomial logistic regression models.

Of 10 000 participants (mean age=62.4 years; 51.1% women), 32.9% had complete data at the unit level, 66.8% had partially missing data and 0.3% missed all items. The highest proportions of missing values were found for income (27.8%) and the number of sexual partners (36.7%). At both the unit, segment and item level, older age, female sex, low education, a foreign mother language and cognitive impairment were significant predictors for missingness.

For analysing population-based data, dealing with missingness is equally important at all levels of analysis. During the design and conduct of the study, the identified groups may be targeted to reach higher levels of data completeness.