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      Effect of a Hospital-Initiated Program Combining Transitional Care and Long-term Self-management Support on Outcomes of Patients Hospitalized With Chronic Obstructive Pulmonary Disease : A Randomized Clinical Trial

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          Abstract

          Patients hospitalized for chronic obstructive pulmonary disease (COPD) exacerbations have high rehospitalization rates and reduced quality of life.

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          Most cited references19

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          Susceptibility to exacerbation in chronic obstructive pulmonary disease.

          Although we know that exacerbations are key events in chronic obstructive pulmonary disease (COPD), our understanding of their frequency, determinants, and effects is incomplete. In a large observational cohort, we tested the hypothesis that there is a frequent-exacerbation phenotype of COPD that is independent of disease severity. We analyzed the frequency and associations of exacerbation in 2138 patients enrolled in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study. Exacerbations were defined as events that led a care provider to prescribe antibiotics or corticosteroids (or both) or that led to hospitalization (severe exacerbations). Exacerbation frequency was observed over a period of 3 years. Exacerbations became more frequent (and more severe) as the severity of COPD increased; exacerbation rates in the first year of follow-up were 0.85 per person for patients with stage 2 COPD (with stage defined in accordance with Global Initiative for Chronic Obstructive Lung Disease [GOLD] stages), 1.34 for patients with stage 3, and 2.00 for patients with stage 4. Overall, 22% of patients with stage 2 disease, 33% with stage 3, and 47% with stage 4 had frequent exacerbations (two or more in the first year of follow-up). The single best predictor of exacerbations, across all GOLD stages, was a history of exacerbations. The frequent-exacerbation phenotype appeared to be relatively stable over a period of 3 years and could be predicted on the basis of the patient's recall of previous treated events. In addition to its association with more severe disease and prior exacerbations, the phenotype was independently associated with a history of gastroesophageal reflux or heartburn, poorer quality of life, and elevated white-cell count. Although exacerbations become more frequent and more severe as COPD progresses, the rate at which they occur appears to reflect an independent susceptibility phenotype. This has implications for the targeting of exacerbation-prevention strategies across the spectrum of disease severity. (Funded by GlaxoSmithKline; ClinicalTrials.gov number, NCT00292552.)
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            The care span: The importance of transitional care in achieving health reform.

            Under the Affordable Care Act of 2010, a variety of transitional care programs and services have been established to improve quality and reduce costs. These programs help hospitalized patients with complex chronic conditions-often the most vulnerable-transfer in a safe and timely manner from one level of care to another or from one type of care setting to another. We conducted a systematic review of the research literature and summarized twenty-one randomized clinical trials of transitional care interventions targeting chronically ill adults. We identified nine interventions that demonstrated positive effects on measures related to hospital readmissions-a key focus of health reform. Most of the interventions led to reductions in readmissions through at least thirty days after discharge. Many of the successful interventions shared similar features, such as assigning a nurse as the clinical manager or leader of care and including in-person home visits to discharged patients. Based on these findings, we recommend several strategies to guide the implementation of transitional care under the Affordable Care Act, such as encouraging the adoption of the most effective interventions through such programs as the Community-Based Care Transitions Program and Medicare shared savings and payment bundling experiments.
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              Interpreting thresholds for a clinically significant change in health status in asthma and COPD.

              Health status (or Health-Related Quality of Life) measurement is an established method for assessing the overall efficacy of treatments for asthma and chronic obstructive pulmonary disease (COPD). Such measurements can indicate the potential clinical significance of a treatment's effect. This paper is concerned with methods of estimating the threshold of clinical significance for three widely used health status questionnaires for asthma and COPD: the Asthma Quality of Life Questionnaire, Chronic Respiratory Questionnaire and St George's Respiratory Questionnaire. It discusses the methodology used to obtain such estimates and shows that the estimates appear to be fairly reliable; ie. for a given questionnaire, similar estimates may be obtained in different studies. These empirically derived thresholds are all mean estimates with confidence intervals around them. The presence of these confidence intervals affects the way in which the thresholds may be used to draw inferences concerning the clinical relevance of clinical trial results. A new system of judging the magnitude of clinically significant results is proposed. Finally, an attempt is made to translate these thresholds into scenarios that illustrate what a clinically significant change with treatment may mean to an individual patient.
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                Author and article information

                Journal
                JAMA
                JAMA
                American Medical Association (AMA)
                0098-7484
                October 08 2019
                October 08 2019
                : 322
                : 14
                : 1371
                Affiliations
                [1 ]Armstrong Institute for Patient Safety and Quality, Johns Hopkins School of Medicine, Baltimore, Maryland
                [2 ]Division of General Internal Medicine, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
                [3 ]Department of Health, Behavior, and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
                [4 ]Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland
                [5 ]Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
                [6 ]Department of Anesthesiology and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
                [7 ]Division of Health Sciences Informatics, Johns Hopkins School of Medicine, Baltimore, Maryland
                [8 ]Malone Center for Engineering in Healthcare, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland
                [9 ]Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
                [10 ]Johns Hopkins Bayview Medical Center, Baltimore, Maryland
                [11 ]Johns Hopkins Biostatistics Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
                [12 ]Health Policy Research Group, University of Oregon, Eugene
                Article
                10.1001/jama.2019.11982
                6784754
                31593271
                1d0bb6e9-51a7-48f4-bdc6-14320d044a8b
                © 2019
                History

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