Background: Patient Reported Experience Measures are promoted to be used as an integrated measurement approach in which outcomes are used to improve individual care (micro level), organisational quality (meso level) and external justification (macro level). However, a deeper understanding of implementation issues of these measures is necessary. The narrative Patient Reported Experience Measure “Dit vind ik ervan!” (English “How I feel about it!”) is used in the Dutch disability care sector, but insight into its’ current use is lacking. We aimed to provide insight into experiences with the implementation and current ways of working with “Dit vind ik ervan!” as an integrated measurement strategy. A descriptive qualitative study was done at a disability care organisation. Data were collected by nine documentations, seven observations, 11 interviews and three focus groups. We applied deductive content analysis using the Consolidated Framework for Implementation Research as a framework. Results: Our analysis revealed facilitators and barriers for the implementation of “Dit vind ik ervan!”. We found most barriers at the micro level. Professionals and clients appreciated the measure’s narrative approach, but struggled to perform it with communication vulnerable clients. Some clients, professionals and team leaders were unfamiliar with the measure’s aim and benefit. On the meso level, implementation was done top-down, and the management’s vision using the measure as an integrated measurement approach was insufficiently shared throughout the organisation. Conclusions: Our study shows that Patient Reported Experience Measures have the potential to be used as an integrated measurement strategy. Yet, we found barriers at the micro level, which might have influenced using the measurement outcomes at the meso and macro level. Tailored implementation strategies, mostly focusing on designing and preparing the implementation on themicro level, need to be developed in co-creation with all stakeholders.
Citizen science can be a powerful approach to foster the successful implementation of technological innovations in health, care or well-being. Involving experience experts as co-researchers or co-designers of technological innovations facilitates mutual learning, community building, and empowerment. By utilizing the expert knowledge of the intended users, innovations have a better chance to get adopted and solve complex health-related problems. As citizen science is still a relatively new practice for health and well-being, little is known about effective methods and guidelines for successful collaboration. This scoping review aims to provide insight in (1) the levels of citizen involvement in current research on technological innovations for health, care or well-being, (2) the used participatory methodologies, and (3) lesson’s learned by the researchers. A scoping review was conducted and reported in accordance with the PRISMA-ScR guidelines. The search was performed in SCOPUS in January 2021 and included peer-reviewed journal and conference papers published between 2016 and 2020. The final selection (N = 83) was limited to empirical studies that had a clear focus on technological innovations for health, care or well-being and involved citizens at the level of collaboration or higher. Our results show a growing interest in citizens science as an inclusive research approach. Citizens are predominantly involved in the design phase of innovations and less in the preparation, data-analyses or reporting phase. Eight records had citizens in the lead in one of the research phases. Researcher use different terms to describe their methodological approach including participatory design, co-design, community based participatory research, co-creation, public and patient involvement, partcipatory action research, user-centred design and citizen science. Our selection of cases shows that succesful citizen science projects develop a structural and longitudinal partnership with their collaborators, use a situated and adaptive research approach, and have researchers that are willing to abandon traditional power dynamics and engage in a mutual learning experience.
MULTIFILE
Background: A patient decision aid (PtDA) can support shared decision making (SDM) in preference-sensitive care, with more than one clinically applicable treatment option. The development of a PtDA is a complex process, involving several steps, such as designing, developing and testing the draft with all the stakeholders, known as alpha testing. This is followed by testing in ‘real life’ situations, known as beta testing, and then finalising the definite version. Our aim was developing and alpha testing a PtDA for primary treatment of early stage breast cancer, ensuring that the tool is considered relevant, valid and feasible by patients and professionals. Methods: Our qualitative descriptive study applied various methods including face-to-face think-aloud interviews, a focus group and semi-structured telephone interviews. The study population consisted of breast cancer patients facing the choice between breast-conserving therapy with or without preceding neo-adjuvant chemotherapy and mastectomy, and professionals involved in breast cancer care in dedicated multidisciplinary breast cancer teams. Results: A PtDA was developed in four iterative test rounds, taking nearly 2 years, involving 26 patients and 26 professionals. While the research group initially opted for simplicity for the sake of implementation, the clinicians objected that the complexity of the decision could not be ignored. Other topics of concern were the conflicting views of professionals and patients regarding side effects, the amount of information and how to present it. Conclusion: The development was an extensive process, because the professionals rejected the simplifications proposed by the research group. This resulted in the development of a completely new draft PtDA, which took double the expected time and resources. The final version of the PtDA appeared to be well-appreciated by professionals and patients, although its acceptability will only be proven in actual practice (beta testing)
