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      Evaluation of integrated care services in Catalonia: population-based and service-based real-life deployment protocols

      research-article
      1 , 2 , , 1 , 2 , 1 , 3 , 1 , 2 , 1 , 2 , 1 , 2 , 1 , 2 , 4 , 1 , 2 , 5 , 6 , 7 , 2 , 8 , 9 , 10 , 1 , 2 , 11 , 12 , 13 , 14 , 15 , 16 , 12 , 9 , 17 , 18 , 12 , 6 , 19 , 4 , 6 , 7 , 2 , 11 , 5 , 1 , 2 ,
      BMC Health Services Research
      BioMed Central
      Chronic patients, Integrated care services, Multimorbidity, Service transferability, Home hospitalization, Prehabilitation, Digital tools, Implementation science, Risk assessment, Multi-criteria decision analysis

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          Abstract

          Background

          Comprehensive assessment of integrated care deployment constitutes a major challenge to ensure quality, sustainability and transferability of both healthcare policies and services in the transition toward a coordinated service delivery scenario. To this end, the manuscript articulates four different protocols aiming at assessing large-scale implementation of integrated care, which are being developed within the umbrella of the regional project Nextcare (2016–2019), undertaken to foster innovation in technologically-supported services for chronic multimorbid patients in Catalonia (ES) (7.5 M inhabitants).

          Whereas one of the assessment protocols is designed to evaluate population-based deployment of care coordination at regional level during the period 2011–2017, the other three are service-based protocols addressing: i) Home hospitalization; ii) Prehabilitation for major surgery; and, iii) Community-based interventions for frail elderly chronic patients. All three services have demonstrated efficacy and potential for health value generation. They reflect different implementation maturity levels. While full coverage of the entire urban health district of Barcelona-Esquerra (520 k inhabitants) is the main aim of home hospitalization, demonstration of sustainability at Hospital Clinic of Barcelona constitutes the core goal of the prehabilitation service. Likewise, full coverage of integrated care services addressed to frail chronic patients is aimed at the city of Badalona (216 k inhabitants).

          Methods

          The population-based analysis, as well as the three service-based protocols, follow observational and experimental study designs using a non-randomized intervention group (integrated care) compared with a control group (usual care) with a propensity score matching method. Evaluation of cost-effectiveness of the interventions using a Quadruple aim approach is a central outcome in all protocols. Moreover, multi-criteria decision analysis is explored as an innovative method for health delivery assessment. The following additional dimensions will also be addressed: i) Determinants of sustainability and scalability of the services; ii) Assessment of the technological support; iii) Enhanced health risk assessment; and, iv) Factors modulating service transferability.

          Discussion

          The current study offers a unique opportunity to undertake a comprehensive assessment of integrated care fostering deployment of services at regional level. The study outcomes will contribute refining service workflows, improving health risk assessment and generating recommendations for service selection.

          Trials registration

          NCT03130283 (date released 04/06/2018), NCT03768050 (date released 12/05/2018), NCT03767387 (date released 12/05/2018).

          Electronic supplementary material

          The online version of this article (10.1186/s12913-019-4174-2) contains supplementary material, which is available to authorized users.

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          Most cited references20

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          The one number you need to grow.

          Companies spend lots of time and money on complex tools to assess customer satisfaction. But they're measuring the wrong thing. The best predictor of top-line growth can usually be captured in a single survey question: Would you recommend this company to a friend? This finding is based on two years of research in which a variety of survey questions were tested by linking the responses with actual customer behavior--purchasing patterns and referrals--and ultimately with company growth. Surprisingly, the most effective question wasn't about customer satisfaction or even loyalty per se. In most of the industries studied, the percentage of customers enthusiastic enough about a company to refer it to a friend or colleague directly correlated with growth rates among competitors. Willingness to talk up a company or product to friends, family, and colleagues is one of the best indicators of loyalty because of the customer's sacrifice in making the recommendation. When customers act as references, they do more than indicate they've received good economic value from a company; they put their own reputations on the line. And they will risk their reputations only if they feel intense loyalty. The findings point to a new, simpler approach to customer research, one directly linked to a company's results. By substituting a single question--blunt tool though it may appear to be--for the complex black box of the customer satisfaction survey, companies can actually put consumer survey results to use and focus employees on the task of stimulating growth.
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            Personalised Prehabilitation in High-risk Patients Undergoing Elective Major Abdominal Surgery: A Randomized Blinded Controlled Trial.

            The aim of this study was to assess the impact of personalized prehabilitation on postoperative complications in high-risk patients undergoing elective major abdominal surgery.
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              A model for assessment of telemedicine applications: mast.

              Telemedicine applications could potentially solve many of the challenges faced by the healthcare sectors in Europe. However, a framework for assessment of these technologies is need by decision makers to assist them in choosing the most efficient and cost-effective technologies. Therefore in 2009 the European Commission initiated the development of a framework for assessing telemedicine applications, based on the users' need for information for decision making. This article presents the Model for ASsessment of Telemedicine applications (MAST) developed in this study. MAST was developed through workshops with users and stakeholders of telemedicine. Based on the workshops and using the EUnetHTA Core HTA Model as a starting point a three-element model was developed, including: (i) preceding considerations, (ii) multidisciplinary assessment, and (iii) transferability assessment. In the multidisciplinary assessment, the outcomes of telemedicine applications comprise seven domains, based on the domains in the EUnetHTA model. MAST provides a structure for future assessment of telemedicine applications. MAST will be tested during 2010-13 in twenty studies of telemedicine applications in nine European countries in the EC project Renewing Health.
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                Author and article information

                Contributors
                +34-932-275-540 , baltaxe@clinic.cat
                +34-932-275-540 , jroca@clinic.cat
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                11 June 2019
                11 June 2019
                2019
                : 19
                : 370
                Affiliations
                [1 ]Hospital Clinic de Barcelona, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
                [2 ]Center for Biomedical Network Research in Respiratory Diseases (CIBERES), Madrid, Spain
                [3 ]CAPSBE. Consorci d’Atenció Primaria de Salut. Barcelona Esquerra, Barcelona, Spain
                [4 ]Royal Philips Netherlands BV acting through Philips Homecare, Boeblingen, Germany
                [5 ]ISNI 0000 0000 9127 6969, GRID grid.22061.37, Area d’Atenció Sanitària, , Servei Català de la Salut, ; Barcelona, Catalonia Spain
                [6 ]ISNI 0000000123317762, GRID grid.454735.4, Chronic Care Program. Ministry of Health, , Generalitat de Catalunya, ; Barcelona, Catalonia Spain
                [7 ]Respiratory Department, Institut de Recerca Biomedica (IRBLeida), Lleida, Spain
                [8 ]ISNI 0000 0004 1936 7443, GRID grid.7914.b, Department of Economics, , University of Bergen, ; Bergen, Norway
                [9 ]ISNI 0000 0004 0644 9941, GRID grid.414003.2, Assuta Medical Centers, ; Tel Aviv-Yafo, Israel
                [10 ]ISNI 0000 0000 9558 4598, GRID grid.4494.d, Department of Epidemiology, , University of Groningen, University Medical Center Groningen, ; Groningen, the Netherlands
                [11 ]Eurecat. Technological Center of Catalonia, Barcelona, Catalunya Spain
                [12 ]ISNI 0000 0001 0671 0327, GRID grid.413521.0, Agència de Qualitat i Avaluació Sanitàries de Catalunya (AQuAS), ; Barcelona, Catalonia Spain
                [13 ]Institut Català de la Salut, Serveis Centrals, Barcelona, Catalonia Spain
                [14 ]ISNI 0000 0004 1755 8959, GRID grid.432291.f, Badalona Serveis Assistencials (BSA), ; Badalona, Catalonia Spain
                [15 ]GRID grid.10403.36, Medical Statistics Core Facility, , Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Hospital Clinic, ; Barcelona, Spain
                [16 ]GRID grid.7080.f, Biostatistics Unit, Faculty of Medicine, , Universitat Autònoma de Barcelona, ; Barcelona, Spain
                [17 ]ISNI 0000000092621349, GRID grid.6906.9, School of Health Policy and Management, , Erasmus University Rotterdam, ; Rotterdam, the Netherlands
                [18 ]ISNI 0000000092621349, GRID grid.6906.9, Institute for Medical Technology Assessment, , Erasmus University Rotterdam, ; Rotterdam, the Netherlands
                [19 ]GRID grid.440820.a, Central Catalonia Chronicity Research Group (C3RG), , University of Vic – Central University of Catalonia, ; 08500 Vic, Spain
                Article
                4174
                10.1186/s12913-019-4174-2
                6560864
                31185997
                7e7d54b8-c0aa-477b-ad6a-31d709511bae
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 20 February 2019
                : 20 May 2019
                Funding
                Funded by: Horizon 2020 Framework Programme ()
                Award ID: 689802
                Award Recipient :
                Categories
                Study Protocol
                Custom metadata
                © The Author(s) 2019

                Health & Social care
                chronic patients,integrated care services,multimorbidity,service transferability,home hospitalization,prehabilitation,digital tools,implementation science,risk assessment,multi-criteria decision analysis

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