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      Management of multimorbidity using a patient-centred care model: a pragmatic cluster-randomised trial of the 3D approach

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          Summary

          Background

          The management of people with multiple chronic conditions challenges health-care systems designed around single conditions. There is international consensus that care for multimorbidity should be patient-centred, focus on quality of life, and promote self-management towards agreed goals. However, there is little evidence about the effectiveness of this approach. Our hypothesis was that the patient-centred, so-called 3D approach (based on dimensions of health, depression, and drugs) for patients with multimorbidity would improve their health-related quality of life, which is the ultimate aim of the 3D intervention.

          Methods

          We did this pragmatic cluster-randomised trial in general practices in England and Scotland. Practices were randomly allocated to continue usual care (17 practices) or to provide 6-monthly comprehensive 3D reviews, incorporating patient-centred strategies that reflected international consensus on best care (16 practices). Randomisation was computer-generated, stratified by area, and minimised by practice deprivation and list size. Adults with three or more chronic conditions were recruited. The primary outcome was quality of life (assessed with EQ-5D-5L) after 15 months' follow-up. Participants were not masked to group assignment, but analysis of outcomes was blinded. We analysed the primary outcome in the intention-to-treat population, with missing data being multiply imputed. This trial is registered as an International Standard Randomised Controlled Trial, number ISRCTN06180958.

          Findings

          Between May 20, 2015, and Dec 31, 2015, we recruited 1546 patients from 33 practices and randomly assigned them to receive the intervention (n=797) or usual care (n=749). In our intention-to-treat analysis, there was no difference between trial groups in the primary outcome of quality of life (adjusted difference in mean EQ-5D-5L 0·00, 95% CI −0·02 to 0·02; p=0·93). 78 patients died, and the deaths were not considered as related to the intervention.

          Interpretation

          To our knowledge, this trial is the largest investigation of the international consensus about optimal management of multimorbidity. The 3D intervention did not improve patients' quality of life.

          Funding

          National Institute for Health Research.

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          Most cited references15

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          Development and validation of the Patient Assessment of Chronic Illness Care (PACIC).

          There is a need for a brief, validated patient self-report instrument to assess the extent to which patients with chronic illness receive care that aligns with the Chronic Care Model-measuring care that is patient-centered, proactive, planned and includes collaborative goal setting; problem-solving and follow-up support. A total of 283 adults reporting one or more chronic illness from a large integrated health care delivery system were studied. Participants completed the 20-item Patient Assessment of Chronic Illness Care (PACIC) as well as measures of demographic factors, a patient activation scale, and subscales from a primary care assessment instrument so that we could evaluate measurement performance, construct, and concurrent validity of the PACIC. The PACIC consists of 5 scales and an overall summary score, each having good internal consistency for brief scales. As predicted, the PACIC was only slightly correlated with age and gender, and unrelated to education. Contrary to prediction, it was only slightly correlated (r = 0.13) with number of chronic conditions. The PACIC demonstrated moderate test-retest reliability (r = 0.58 during the course of 3 months) and was correlated moderately, as predicted (r = 0.32-0.60, median = 0.50, P < 0.001) to measures of primary care and patient activation. The PACIC appears to be a practical instrument that is reliable and has face, construct, and concurrent validity. The resulting questionnaire is in the public domain, and recommendations for its use in research and quality improvement are outlined.
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            Interventions for improving outcomes in patients with multimorbidity in primary care and community settings.

            Many people with chronic disease have more than one chronic condition, which is referred to as multimorbidity. The term comorbidity is also used but this is now taken to mean that there is a defined index condition with other linked conditions, for example diabetes and cardiovascular disease. It is also used when there are combinations of defined conditions that commonly co-exist, for example diabetes and depression. While this is not a new phenomenon, there is greater recognition of its impact and the importance of improving outcomes for individuals affected. Research in the area to date has focused mainly on descriptive epidemiology and impact assessment. There has been limited exploration of the effectiveness of interventions to improve outcomes for people with multimorbidity.
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              • Record: found
              • Abstract: not found
              • Article: not found

              Guiding principles for the care of older adults with multimorbidity: an approach for clinicians: American Geriatrics Society Expert Panel on the Care of Older Adults with Multimorbidity.

              (2012)
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                Author and article information

                Contributors
                Journal
                Lancet
                Lancet
                Lancet (London, England)
                Elsevier
                0140-6736
                1474-547X
                07 July 2018
                07 July 2018
                : 392
                : 10141
                : 41-50
                Affiliations
                [a ]Centre for Academic Primary Care, NIHR School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
                [b ]Bristol Randomised Trials Collaboration, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
                [c ]NIHR School for Primary Care Research, Centre for Primary Care, Division of Population of Health, Health Services Research and Primary Care, Manchester Academic Health Science Centre, University of Manchester, UK
                [d ]Population Health Sciences Division, School of Medicine, University of Dundee, Dundee, UK
                [e ]Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
                Author notes
                [* ]Correspondence to: Prof Chris Salisbury, Centre for Academic Primary Care, NIHR School for Primary Care Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2PS, UK c.salisbury@ 123456bristol.ac.uk
                Article
                S0140-6736(18)31308-4
                10.1016/S0140-6736(18)31308-4
                6041724
                29961638
                1157754c-739e-4fb9-911c-44044d4a768c
                © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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                Medicine
                Medicine

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