AbstractObjective: Many older individuals receive rehabilitation in an out-of-hospital setting (OOHS) after acute hospitalization; however, its effect onmobility and unplanned hospital readmission is unclear. Therefore, a systematic review and meta-analysis were conducted on this topic.Data Sources: Medline OVID, Embase OVID, and CINAHL were searched from their inception until February 22, 2018.Study Selection: OOHS (ie, skilled nursing facilities, outpatient clinics, or community-based at home) randomized trials studying the effect ofmultidisciplinary rehabilitation were selected, including those assessing exercise in older patients (mean age 65y) after discharge from hospitalafter an acute illness.Data Extraction: Two reviewers independently selected the studies, performed independent data extraction, and assessed the risk of bias.Outcomes were pooled using fixed- or random-effect models as appropriate. The main outcomes were mobility at and unplanned hospitalreadmission within 3 months of discharge.Data Synthesis: A total of 15 studies (1255 patients) were included in the systematic review and 12 were included in the meta-analysis (7assessing mobility using the 6-minute walk distance [6MWD] test and 7 assessing unplanned hospital readmission). Based on the 6MWD, patientsreceiving rehabilitation walked an average of 23 m more than controls (95% confidence interval [CI]Z: 1.34 to 48.32; I2: 51%). Rehabilitationdid not lower the 3-month risk of unplanned hospital readmission (risk ratio: 0.93; 95% CI: 0.73-1.19; I2: 34%). The risk of bias was present,mainly due to the nonblinded outcome assessment in 3 studies, and 7 studies scored this unclearly.Conclusion: OOHS-based multidisciplinary rehabilitation leads to improved mobility in older patients 3 months after they are discharged fromhospital following an acute illness and is not associated with a lower risk of unplanned hospital readmission within 3 months of discharge.However, the wide 95% CIs indicate that the evidence is not robust.
The origins of SWOT analysis have been enigmatic, until now. With archival research, interviews with experts and a review of the available literature, this paper reconstructs the original SOFT/SWOT approach, and draws potential implications. During a firm's planning process, all managers are asked to write down 8 to 10 key planning issues faced by their units. Each manager grades, with evidence, these issues as either safeguarding the Satisfactory; opening Opportunities; fixing Faults; or thwarting Threats: hence SOFT (which is later merely relabeled to Strengths, Weaknesses, Opportunities and Threats, or SWOT). Subgroups of managers have several dialogues about these issues with the instruction to include the needs and expectations of all the firm's stakeholders. Their developed resolutions or proposals become input for the executive planning committee to articulate corporate purpose(s) and strategies. SWOT's originator, Robert Franklin Stewart, emphasized the crucial role that creativity plays in the planning process. The SOFT/SWOT approach curbs mere top-down strategy making to the benefit of strategy alignment and implementation; Introducing digital means to parts of SWOT's original participative, long-range planning process, as suggested herein, could boost the effectiveness of organizational strategizing, communication and learning. Archival research into the deployment of SOFT/SWOT in practice is needed.
BACKGROUND: Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them.METHODS: Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined.RESULTS: We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small.CONCLUSIONS: We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.
