Opioid Use Disorder: A Qualitative Exploratory Analysis of Potential Misunderstandings in Patients with Chronic Non-Cancer Pain.

Purpose: Substance use disorders (SUD) are a challenging comorbidity in patients with chronic non-cancer pain (CNCP) as they complicate diagnosis and therapy, especially when opioids are part of the therapeutic regimen. A definite diagnosis of opioid use disorder (OUD) in patients with CNCP on long-term opioid therapy (LTOT) is a prerequisite for effective and targeted therapy but may be complicated as some criteria of OUD might be attributed to the desire of the patient to relieve the pain. For instance, the desire to increase the dose can be based on both a SUD as well as inadequate pain therapy. Many scientific studies use standardized questions. Therefore, potential misunderstandings due to possible diagnostic overlaps often cannot be clarified. Methods: 14 qualitative guided interviews were conducted and analyzed (Kuckartz content analysis), with the intention to verify if patient's initial response to simple questions based on the wording of the DSM-5, as commonly used in research and practice, were consistent with the results of a more in-depth inquiry. Results: The results suggest that without in-depth investigation, there is a particular risk of false-positive assessment of the DSM-5 criteria for OUD when opioids are prescribed, especially when the questions are considered independently of chronic pain. The risk of a false-negative assessment has also been shown in isolated cases. Conclusion: Only after asking for and describing specific situations it was possible to determine whether the patient's positive or negative answers were based on a misunderstanding of the question. To avoid misdiagnosis, staff conducting DSM-5 interviews should be trained in pain-specific follow-up questions that may help to uncover diagnostic confounding.

Digital Medication Management in Polypharmacy­Findings of a Cluster-Randomized, Controlled Trial With a Stepped-Wedge Design in Primary Care Practices (AdAM).

BACKGROUND: Inappropriate drug prescriptions for patients with polypharmacy can have avoidable adverse consequences. We studied the effects of a clinical decision-support system (CDSS) for medication management on hospitalizations and mortality. METHODS: This stepped-wedge, cluster-randomized, controlled trial involved an open cohort of adult patients with polypharmacy in primary care practices (=clusters) in Westphalia-Lippe, Germany. During the period of the intervention, their medication lists were checked annually using the CDSS. The CDSS warns against inappropriate prescriptions on the basis of patient-related health insurance data. The combined primary endpoint consisted of overall mortality and hospitalization for any reason. The secondary endpoints were mortality, hospitalizations, and high-risk prescription. We analyzed the quarterly health insurance data of the intention-to-treat population with a mixed logistic model taking account of clustering and repeated measurements. Sensitivity analyses addressed effects of the COVID-19 pandemic and other effects. RESULTS: 688 primary care practices were randomized, and data were obtained on 42 700 patients over 391 994 quarter years. No significant reduction was found in either the primary endpoint (odds ratio [OR] 1.00; 95% confidence interval [0.95; 1.04]; p = 0.8716) or the secondary endpoints (hospitalizations: OR 1.00 [0.95; 1.05]; mortality: OR 1.04 [0.92; 1.17]; high-risk prescription: OR 0.98 [0.92; 1.04]). CONCLUSION: The planned analyses did not reveal any significant effect of the intervention. Pandemic-adjusted analyses yielded evidence that the mortality of adult patients with polypharmacy might potentially be lowered by the CDSS. Controlled trials with appropriate follow-up are needed to prove that a CDSS has significant effects on mortality in patients with polypharmacy.

Validation of the German Normalisation Process Theory Measure G-NoMAD: translation, adaptation, and pilot testing.

BACKGROUND: Implementing evidence-based healthcare practices (EBPs) is a complex endeavour and often lags behind research-informed decision processes. Understanding and systematically improving implementation using implementation theory can help bridge the gap between research findings and practice. This study aims to translate, pilot, and validate a German version of the English NoMAD questionnaire (G-NoMAD), an instrument derived from the Normalisation Process Theory, to explore the implementation of EBPs. METHODS: Survey data has been collected in four German research projects and subsequently combined into a validation data set. Two versions of the G-NoMAD existed, independently translated from the original English version by two research groups. A measurement invariance analysis was conducted, comparing latent scale structures between groups of respondents to both versions. After determining the baseline model, the questionnaire was tested for different degrees of invariance (configural, metric, scalar, and uniqueness) across samples. A confirmatory factor analysis for three models (a four-factor, a unidimensional, and a hierarchical model) was used to examine the theoretical structure of the G-NoMAD. Finally, psychometric results were discussed in a consensus meeting, and the final instructions, items, and scale format were consented to. RESULTS: A total of 539 health care professionals completed the questionnaire. The results of the measurement invariance analysis showed configural, partial metric, and partial scalar invariance indicating that the questionnaire versions are comparable. Internal consistency ranged from acceptable to good (0.79 ≤ α ≤ 0.85) per subscale. Both the four factor and the hierarchical model achieved a better fit than the unidimensional model, with indices from acceptable (SRMR = 0.08) to good (CFI = 0.97; TLI = 0.96). However, the RMSEA values were only close to acceptable (four-factor model: χ2164 = 1029.84, RMSEA = 0.10; hierarchical model: χ2166 = 1073.43, RMSEA = 0.10). CONCLUSIONS: The G-NoMAD provides a reliable and promising tool to measure the degree of normalisation among individuals involved in implementation activities. Since the fit was similar in the four-factor and the hierarchical model, priority should be given to the practical relevance of the hierarchical model, including a total score and four subscale scores. The findings of this study support the further usage of the G-NoMAD in German implementation settings. TRIAL REGISTRATION: Both the AdAM project (No. NCT03430336, 06/02/2018) and the EU-project ImpleMentAll (No. NCT03652883, 29/08/2018) were registered on ClinicalTrials.gov. The ImplementIT study was registered at the German Clinical Trial Registration (No. DRKS00017078, 18/04/2019). The G-NoMAD validation study was registered at the Open Science Framework (No7u9ab, 17/04/2023).

Factors facilitating the implementation of a clinical decision support system in primary care practices: a fuzzy set qualitative comparative analysis.

BACKGROUND: Understanding how to implement innovations in primary care practices is key to improve primary health care. Aiming to contribute to this understanding, we investigate the implementation of a clinical decision support system (CDSS) as part of the innovation fund project AdAM (01NVF16006). Originating from complexity theory, the practice change and development model (PCD) proposes several interdependent factors that enable organizational-level change and thus accounts for the complex settings of primary care practices. Leveraging the PCD, we seek to answer the following research questions: Which combinations of internal and external factors based on the PCD contribute to successful implementation in primary care practices? Given these results, how can implementation in the primary care setting be improved? METHODS: We analyzed the joint contributions of internal and external factors on implementation success using qualitative comparative analysis (QCA). QCA is a set-theoretic approach that allows to identify configurations of multiple factors that lead to one outcome (here: successful implementation of a CDSS in primary care practices). Using survey data, we conducted our analysis based on a sample of 224 primary care practices. RESULTS: We identified two configurations of internal and external factors that likewise enable successful implementation. The first configuration enables implementation based on a combination of Strong Inside Motivation, High Capability for Development, and Strong Outside Motivation; the second configuration based on a combination of Strong Inside Motivators, Many Options for Development and the absence of High Capability for Development. CONCLUSION: In line with the PCD, our results demonstrate the importance of the combination of internal and external factors for implementation outcomes. Moreover, the two identified configurations show that different ways exist to achieve successful implementation in primary care practices. TRIAL REGISTRATION: AdAM was registered on ClinicalTrials.gov ( NCT03430336 ) on February 6, 2018.

Use of an electronic medication management support system in patients with polypharmacy in general practice: study protocol of a quantitative process evaluation of the AdAM trial.

BACKGROUND: Interventional studies on polypharmacy often fail to significantly improve patient-relevant outcomes, or confine themselves to measuring surrogate parameters. Interventions and settings are complex, with many factors affecting results. The AdAM study's aim is to reduce hospitalization and death by requiring general practitioners (GPs) to use a computerized decision-support system (CDSS). The study will undergo a process evaluation to identify factors for successful implementation and to assess whether the intervention was implemented as intended. OBJECTIVE: To evaluate our complex intervention, based on the Medical Research Council's guideline dimensions. RESEARCH QUESTIONS: We will assess implementation (reach, fidelity, dose, tailoring) by asking: (1) Who took part in the intervention (proportion of GPs using the CDSS, proportion of patients enrolled in them)? Information on GPs' and patients' characteristics will also be collected. (2) How many and which medication alerts were dealt with? (3) Was the intervention implemented as intended? (4) On what days did GPs use the intervention tool? METHODS: The process evaluation is part of a stepped-wedge cluster-randomized controlled trial. Characteristics of practices, GPs and patients using the CDSS will be compared with the non-participating population. CDSS log data will be analyzed to evaluate how the number of medication alerts changed between baseline and 2 months later, and to identify the kind of alerts that were dealt with. Comparison of enrolled patients on weekdays versus weekends will shed light on GPs' use of the CDSS in the absence or presence of patients. Outcomes will be presented using descriptive statistics, and significance tests will be used to identify associations between them. We will conduct subgroup analyses, including time effects to account for software improvements. DISCUSSION: This study protocol is the basis for conducting analyses of the quantitative process evaluation. By providing insight into how GPs conduct medication reviews, the evaluation will provide context to the trial results and support their interpretation. The evaluation relies on the proper documentation by GPs, potentially limiting its explanatory power.

Effectiveness of the application of an electronic medication management support system in patients with polypharmacy in general practice: a study protocol of cluster-randomised controlled trial (AdAM).

INTRODUCTION: Clinically 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 ANALYSIS: Planned 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 DISSEMINATION: Trial approved by Ethics Commission of North-Rhine Medical Association. Results will be disseminated through workshops, peer-reviewed publications, local and international conferences. TRIAL REGISTRATION: NCT03430336. ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/NCT03430336).

Gewalt und Gewaltprävention in der stationären Altenpflege während der COVID-19-Pandemie.

Violence and Violence Prevention in Nursing Homes during the COVID-19 Pandemic - A partial analysis of Interviews with Managers or Team Leaders Abstract. Background: During the first wave of the COVID-19 pandemic, strict infection control measures were in force in long-term residential care in Germany that burdened staff and isolated residents socially. Both are considered risk factors for violence in long-term residential care. Questions: How does violence develop in nursing homes under pandemic conditions from the point of view of managers and how do strategies for preventing violence change? Methods: Semi-structured telephone interviews were conducted with staff in 43 nursing homes: 25 with service managers, 15 with nurse managers, 28 with nursing team leaders and 10 with registered nurses with extended tasks. The interviews were recorded as audio, transcribed and analysed in five steps following the "Thematic Framework Analysis". Results: The infection control measures were partly perceived as deprivation of freedom. Residents, relatives and staff partly reacted most with verbal violence. Nevertheless, the issue of violence was not a major concern for management and preventive measures were not carried out. Conclusions: The results show that strategies to prevent violence might not be sufficiently established in the institutions involved and would have to be adapted to the conditions of the pandemic. Further research is needed to evaluate infection control measures in their potential to increase the incidence of violence.

Effect of an interprofessional care concept on the hospitalization of nursing home residents: study protocol for a cluster-randomized controlled trial.

BACKGROUND: The rising number of nursing home (NH) residents and their increasingly complex treatment needs pose a challenge to the German health care system. In Germany, there is no specialized geriatric medical care for NH residents. Nursing staff and general practitioners (GPs) in particular have to compensate for the additional demand, which is compounded by organizational and structural hurdles. As a result, avoidable emergency calls and hospital admissions occur. In the SaarPHIR project (Saarländische PflegeHeimversorgung Integriert Regelhaft), a complex intervention focusing on a medical care concept was developed in a participatory practice-based approach involving NH representatives and GPs. The complex intervention addresses the collaboration between nurses and GPs and aims to help restructure and optimize the existing daily care routine. It is expected to improve the medical care of geriatric patients in NHs and reduce stressful, costly hospital admissions. The intervention was pilot-tested during the first 12 months of the project. In the present study, its effectiveness, cost-effectiveness, and safety will be evaluated. METHODS: The study is a cluster-randomized controlled trial, comparing an intervention group with a control group. The intervention includes a concept of interprofessional collaboration, in which GPs group into regional cooperating teams. Teams are encouraged to cooperate more closely with NH staff and to provide on-call schedules, pre-weekend visits, joint team meetings, joint documentation, and improved medication safety. At least 32 NHs in Saarland, Germany (with at least 50 residents each) will be included and monitored for 12 months. The primary endpoint is hospitalization. Secondary endpoints are quality of life, quality of care, and medication safety. The control group receives treatment as usual. Process evaluation and health economic evaluation accompany the study. The data set contains claims data from German statutory health insurance companies as well as primary data. Analysis will be conducted using a generalized linear mixed model. CONCLUSION: A reduction in hospital admissions of NH residents and relevant changes in secondary endpoints are expected. In turn, these will have a positive impact on the economic assessment. TRIAL REGISTRATION: German Clinical Trials Register: DRKS00017129. Registered on 23 April 2019. https://www.drks.de/drks_web/setLocale_EN.do.

Dynamic tensile forces drive collective cell migration through three-dimensional extracellular matrices.

Collective cell migration drives tissue remodeling during development, wound repair, and metastatic invasion. The physical mechanisms by which cells move cohesively through dense three-dimensional (3D) extracellular matrix (ECM) remain incompletely understood. Here, we show directly that migration of multicellular cohorts through collagenous matrices occurs via a dynamic pulling mechanism, the nature of which had only been inferred previously in 3D. Tensile forces increase at the invasive front of cohorts, serving a physical, propelling role as well as a regulatory one by conditioning the cells and matrix for further extension. These forces elicit mechanosensitive signaling within the leading edge and align the ECM, creating microtracks conducive to further migration. Moreover, cell movements are highly correlated and in phase with ECM deformations. Migrating cohorts use spatially localized, long-range forces and consequent matrix alignment to navigate through the ECM. These results suggest biophysical forces are critical for 3D collective migration.

Three-dimensional traction force microscopy of engineered epithelial tissues.

Several biological processes, including cell migration, tissue morphogenesis, and cancer metastasis, are fundamentally physical in nature; each implicitly involves deformations driven by mechanical forces. Traction force microscopy (TFM) was initially developed to quantify the forces exerted by individual isolated cells in two-dimensional (2D) culture. Here, we extend this technique to estimate the traction forces generated by engineered three-dimensional (3D) epithelial tissues embedded within a surrounding extracellular matrix (ECM). This technique provides insight into the physical mechanisms that underlie tissue morphogenesis in 3D.