Background: The concept of Functional Independence (FI), defined as ‘functioning physically safe and independent from other persons, within one’s context”, plays an important role in maintaining the functional ability to enable well-being in older age. FI is a dynamic and complex concept covering four clinical outcomes: physical capacity, empowerment, coping flexibility, and health literacy. As the level of FI differs widely between older adults, healthcare professionals must gain insight into how to best support older people in maintaining their level of FI in a personalized manner. Insight into subgroups of FI could be a first step in providing personalized support This study aims to identify clinically relevant, distinct subgroups of FI in Dutch community-dwelling older people and subsequently describe them according to individual characteristics. Results: One hundred fifty-three community-dwelling older persons were included for participation. Cluster analysis identified four distinctive clusters: (1) Performers – Well-informed; this subgroup is physically strong, well-informed and educated, independent, non-falling, with limited reflective coping style. (2) Performers – Achievers: physically strong people with a limited coping style and health literacy level. (3) The reliant- Good Coper representing physically somewhat limited people with sufficient coping styles who receive professional help. (4) The reliant – Receivers: physically limited people with insufficient coping styles who receive professional help. These subgroups showed significant differences in demographic characteristics and clinical FI outcomes. Conclusions: Community-dwelling older persons can be allocated to four distinct and clinically relevant subgroups based on their level of FI. This subgrouping provides insight into the complex holistic concept of FI by pointing out for each subgroup which FI domain is affected. This way, it helps to better target interventions to prevent the decline of FI in the community-dwelling older population.
Abstract Business Process Management (BPM) is an important discipline for organizations to manage their business processes. Research shows that higher BPM-maturity leads to better process performance. However, contextual factors such as culture seem to influence this relationship. The purpose of this paper is to investigate the role of national culture on the relationship between BPM-maturity and process performance. A multiple linear regression analysis is performed based on data from six different countries within Europe. Although the results show a significant relationship between BPM-maturity and process performance, no significant moderation effect of national culture has been found. The cultural dimension long term orientation shows a weak negative correlation with both BPM-maturity and process performance. Through a post-hoc moderation analysis on each dimension of BPM-maturity, we further find that long term orientation negatively moderates the relationship between process improvement and process performance. Three other moderation effects are also discovered. The results of this study contribute to insights into the role of culture in the field of BPM.
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Objective: To describe the discrimination and calibration of clinical prediction models, identify characteristics that contribute to better predictions and investigate predictors that are associated with unplanned hospital readmissions.Design: Systematic review and meta-analysis.Data source: Medline, EMBASE, ICTPR (for study protocols) and Web of Science (for conference proceedings) were searched up to 25 August 2020.Eligibility criteria for selecting studies: Studies were eligible if they reported on (1) hospitalised adult patients with acute heart disease; (2) a clinical presentation of prediction models with c-statistic; (3) unplanned hospital readmission within 6 months. Primary and secondary outcome measures: Model discrimination for unplanned hospital readmission within 6 months measured using concordance (c) statistics and model calibration. Meta-regression and subgroup analyses were performed to investigate predefined sources of heterogeneity. Outcome measures from models reported in multiple independent cohorts and similarly defined risk predictors were pooled.Results: Sixty studies describing 81 models were included: 43 models were newly developed, and 38 were externally validated. Included populations were mainly patients with heart failure (HF) (n=29). The average age ranged between 56.5 and 84 years. The incidence of readmission ranged from 3% to 43%. Risk of bias (RoB) was high in almost all studies. The c-statistic was <0.7 in 72 models, between 0.7 and 0.8 in 16 models and >0.8 in 5 models. The study population, data source and number of predictors were significant moderators for the discrimination. Calibration was reported for 27 models. Only the GRACE (Global Registration of Acute Coronary Events) score had adequate discrimination in independent cohorts (0.78, 95% CI 0.63 to 0.86). Eighteen predictors were pooled. Conclusion: Some promising models require updating and validation before use in clinical practice. The lack of independent validation studies, high RoB and low consistency in measured predictors limit their applicability.PROSPERO registration number: CRD42020159839.
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