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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Background—Self-management interventions are widely implemented in care for patients with heart failure (HF). Trials however show inconsistent results and whether specific patient groups respond differently is unknown. This individual patient data meta-analysis assessed the effectiveness of self-management interventions in HF patients and whether subgroups of patients respond differently. Methods and Results—Systematic literature search identified randomized trials of selfmanagement interventions. Data of twenty studies, representing 5624 patients, were included and analyzed using mixed effects models and Cox proportional-hazard models including interaction terms. Self-management interventions reduced risk of time to the combined endpoint HF-related all-0.71- in Conclusions—This study shows that self-management interventions had a beneficial effect on time to HF-related hospitalization or all-cause death, HF-related hospitalization alone, and elicited a small increase in HF-related quality of life. The findings do not endorse limiting selfmanagement interventions to subgroups of HF patients, but increased mortality in depressed patients warrants caution in applying self-management strategies in these patients.
Background: The number of people with multiple chronic conditions receiving primary care services is growing. To deal with their increasingly complex health care demands, professionals from different disciplines need to collaborate. Interprofessional team (IPT) meetings are becoming more popular. Several studies describe important factors related to conducting IPT meetings, mostly from a professional perspective. However, in the light of patient-centeredness, it is valuable to also explore the patients’ perspective. Objective: The aim was to explore the patients’ perspectives regarding IPT meetings in primary care. Methods: A qualitative study with a focus group design was conducted in the Netherlands. Two focus group meetings took place, for which the same patients were invited. The participants, chronically ill patients with experience on interprofessional collaboration, were recruited through the regional patient association. Participants discussed viewpoints, expectations, and concerns regarding IPT meetings in two rounds, using a focus group protocol and selected video-taped vignettes of team meetings. The first meeting focused on conceptualization and identification of themes related to IPT meetings that are important to patients. The second meeting aimed to gain more in-depth knowledge and understanding of the priorities. Discussions were audio-taped and transcribed verbatim, and analyzed by means of content analysis. Results: The focus group meetings included seven patients. Findings were divided into six key categories, capturing the factors that patients found important regarding IPT meetings: (1) putting the patient at the center, (2) opportunities for patients to participate, (3) appropriate team composition, (4) structured approach, (5) respectful communication, and (6) informing the patient about meeting outcomes. Conclusions: Patients identified different elements regarding IPT meetings that are important from their perspective. They emphasized the right of patients or their representatives to take part in IPT meetings. Results of this study can be used to develop tools and programs to improve interprofessional collaboration.
