In aging populations, multimorbidity (two or more chronic diseases in the same person [1, 2] is very common [3-5]. Patients with multimorbidity have complex health and social needs, are at risk of being admitted to the hospital or residential care home and require a wide range of interventions [6]. To satisfy the needs of these patients and their families, new innovative integrated care models are needed. To be effective, they should have primary care as the cornerstone of care [7]; effective integration between care levels [8, 9]; empowered patient´ and carers/families' [8]; and it should be patient-centered. The use of information and communication technology (ICT) platforms could

BackgroundThis paper crystallises the experience developed by the pan-European PALANTE Consortium in dealing with the generation of relevant evidence from heterogeneous eHealth services for patient empowerment in nine European Regions. The European Commission (EC) recently funded a number of pan-European eHealth projects aimed at empowering European patients/citizens thus transforming the traditional patient/citizen role in the management of their health (e.g., PALANTE, SUSTAIN, CARRE, HeartCycle, Empower). However, the heterogeneity of the healthcare systems, of the implemented services and of the target patients, the use of ad-hoc definitions of the salient concepts and the development of small-size experiences have prevented the dissemination of “global” results and the development of cumulative knowledge. The main challenge has been the generation of large-scale evidence from heterogeneous small-size experiences.DiscussionThree lessons have been collectively learnt during the development of the PALANTE project, which involves 9 sites that have implemented different eHealth services for empowering different typologies of patients. These lessons have been refined progressively through project meetings, reviews with the EC Project Officer and Reviewers. The paper illustrates the ten steps followed to develop the three lessons.The first lesson learnt is about how EC-funded projects should develop cumulative knowledge by avoiding self-crafted measures of outcome and by adopting literature-grounded definitions and scales. The second lesson learnt is about how EC-funded projects should identify ambitious, cross-pilot policy and research questions that allow pooling of data from across heterogeneous experiences even if a multi-centre study design was not agreed before. The third lesson learnt is about how EC-funded projects should open their collections of data and make them freely-accessible to the scientific community shortly after the conclusion of the project in order to guarantee the replicability of results and conclusions.SummaryThe three lessons might provide original elements for fuelling the ongoing debate about the capability of the EC to develop evidence-based policies by pooling evidence from heterogeneous, local experiences.

IntroductionClinically complex patients often require multiple medications. Polypharmacy is associated with inappropriate prescriptions, which may lead to negative outcomes. Few effective tools are available to help physicians optimise patient medication. This study assesses whether an electronic medication management support system (eMMa) reduces hospitalisation and mortality and improves prescription quality/safety in patients with polypharmacy.Methods and analysisPlanned design: pragmatic, parallel cluster-randomised controlled trial; general practices as randomisation unit; patients as analysis unit. As practice recruitment was poor, we included additional data to our primary endpoint analysis for practices and quarters from October 2017 to March 2021. Since randomisation was performed in waves, final study design corresponds to a stepped-wedge design with open cohort and step-length of one quarter. Scope: general practices, Westphalia-Lippe (Germany), caring for BARMER health fund-covered patients. Population: patients (≥18 years) with polypharmacy (≥5 prescriptions). Sample size: initially, 32 patients from each of 539 practices were required for each study arm (17 200 patients/arm), but only 688 practices were randomised after 2 years of recruitment. Design change ensures that 80% power is nonetheless achieved. Intervention: complex intervention eMMa. Follow-up: at least five quarters/cluster (practice). recruitment: practices recruited/randomised at different times; after follow-up, control group practices may access eMMa. Outcomes: primary endpoint is all-cause mortality and hospitalisation; secondary endpoints are number of potentially inappropriate medications, cause-specific hospitalisation preceded by high-risk prescribing and medication underuse. Statistical analysis: primary and secondary outcomes are measured quarterly at patient level. A generalised linear mixed-effect model and repeated patient measurements are used to consider patient clusters within practices. Time and intervention group are considered fixed factors; variation between practices and patients is fitted as random effects. Intention-to-treat principle is used to analyse primary and key secondary endpoints.Ethics and disseminationTrial approved by Ethics Commission of North-Rhine Medical Association. Results will be disseminated through workshops, peer-reviewed publications, local and international conferences.Trial registrationNCT03430336. ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/NCT03430336).

Background To investigate patients’ perspectives on polypharmacy and the use of a digital decision support system to assist general practitioners (GPs) in performing medication reviews. Methods Qualitative interviews with patients or informal caregivers recruited from participants in a cluster-randomized controlled clinical trial (cRCT). The interviews were transcribed verbatim and analyzed using thematic analysis. Results We conducted 13 interviews and identified the following seven themes: the patients successfully integrated medication use in their everyday lives, used medication plans, had both good and bad personal experiences with their drugs, regarded their healthcare providers as the main source of medication-related information, discussed medication changes with their GPs, had trusting relationships with them, and viewed the use of digital decision support tools for medication reviews positively. No unwanted adverse effects were reported. Conclusions Despite drug-related problems, patients appeared to cope well with their medications. They also trusted their GPs, despite acknowledging polypharmacy to be a complex field for them. The use of a digital support system was appreciated and linked to the hope that reasons for selecting specific medication regimens would become more comprehensible. Further research with a more diverse sampling might add more patient perspectives. Trial registration ClinicalTrials.gov, NCT03430336. Registered on February 6, 2018.

Background The Implementation Leadership Scale (ILS) was developed to assess leadership behavior with regard to being proactive, knowledgeable, supportive, or perseverant in implementing evidence-based practices (EBPs). As part of a study on the implementation of a digitally supported polypharmacy management application in primary care, the original ILS was translated and validated for use in the German language. Rationale This study aimed to translate the original ILS into German and evaluate its psychometric properties. Methods The validation sample consisted of 198 primary care physicians in a cluster-randomized controlled trial in which the intervention group implemented a digitally supported clinical decision support system for polypharmacy management. The ILS was assessed using a 12-item scale. The study included a process evaluation with two evaluation waves between 2019 and 2021. The ILS was used within this process evaluation study to assess the leadership support with regard to the implementation of the polypharmacy management. The ILS was translated in a multi-step process, including pre-testing of the instrument and triple, back-and-forth translation of the instrument. We tested the reliability (Cronbach’s alpha) and validity (construct and criterion-related validity) of the scale. Results The four-dimensional structure of the instrument was confirmed (comparative fit index = .97; root mean square error of approximation = .06). Convergent validity was demonstrated by correlations with organizational innovation climate, social capital, and workload, which was consistent with the proposed hypothesis. Criterion-related validity of the ILS was demonstrated by predicting the organizational readiness for change scores using structural equation modeling. The reliability of the scale was good (α = .875). Conclusion The German version of the ILS created in this study is a reliable and valid measure. The original four-dimensional structure of the ILS was confirmed in a primary care setting. Further psychometric testing is needed to establish the validity and reliability of the ILS and to transfer it to other health care settings. It is a useful tool for identifying the areas for implementation leadership development. Further research is needed on how, why, and when distinct types of leadership behaviors have different effects on healthcare organizations in implementation processes.

No abstract

Putting into place ICT-supported, integrated health and social care services means that a multitude of stakeholders are affected by changes to their working process and often to their economic performance. In this chapter, the authors describe their approach to assessing integrated eCare services to enable care integrators in making strategic decisions during development and early operation. The approach is founded on cost-benefit analysis. It stands out from other assessment frameworks in that it 1) allows identifying and addressing stakeholders that lose through the service and thus may become strong veto players, 2) allows monitoring of the actual and prospective service development over time, 3) includes non-financial factors that in many cases have a major impact on the behaviour of a stakeholder, and 4) provides probabilistic methods for achieving rigorous results from data of varying quality. Following an exemplary integration case developed from one of their pilot projects, the steps of the assessment process are described, including an exemplary interpretation of the analytic results and their application in practice. The chapter concludes with an outlook on future work.

No abstract