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      A population-based approach to integrated healthcare delivery: a scoping review of clinical care and public health collaboration

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          Abstract

          Background

          A population-based approach to healthcare goes beyond the traditional biomedical model and addresses the importance of cross-sectoral collaboration in promoting health of communities. By establishing partnerships across primary care (PC) and public health (PH) sectors in particular, healthcare organizations can address local health needs of populations and improve health outcomes. The purpose of this study was to map a series of interventions from the empirical literature that facilitate PC-PH collaboration and develop a resource for healthcare organizations to self-evaluate their clinical practices and identify opportunities for collaboration with PH.

          Methods

          A scoping review was designed and studies from relevant peer-reviewed literature and reports between 1990 and 2017 were included if they met the following criteria: empirical study methodology (quantitative, qualitative, or mixed methods), based in US, Canada, Western Europe, Australia or New Zealand, describing an intervention involving PC-PH collaboration, and reporting on structures, processes, outcomes or markers of a PC-PH collaboration intervention.

          Results

          Out of 2962 reviewed articles, 45 studies with interventions leading to collaboration were classified into the following four synergy groups developed by Lasker’s Committee on Medicine and Public Health: Coordinating healthcare services ( n = 13); Applying a population perspective to clinical practice ( n = 21); Identifying and addressing community health problems ( n = 19), and Strengthening health promotion and health protection ( n = 21). Furthermore, select empirical examples of interventions and their key features were highlighted to illustrate various approaches to implementing collaboration interventions in the field.

          Conclusions

          The findings of our review can be utilized by a range of organizations in healthcare settings across the included countries. Furthermore, we developed a self-evaluation tool that can serve as a resource for clinical practices to identify opportunities for cross-sectoral collaboration and develop a range of interventions to address unmet health needs in communities; however, the generalizability of the findings depends on the evaluations conducted in individual studies in our review.

          From a health equity perspective, our findings also highlight interventions from the empirical literature that address inequities in care by targeting underserved, high-risk populations groups. Further research is needed to develop outcome measures for successful collaboration and determine which interventions are sustainable in the long term.

          Electronic supplementary material

          The online version of this article (10.1186/s12889-019-7002-z) contains supplementary material, which is available to authorized users.

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          Most cited references55

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          The triple aim: care, health, and cost.

          Improving the U.S. health care system requires simultaneous pursuit of three aims: improving the experience of care, improving the health of populations, and reducing per capita costs of health care. Preconditions for this include the enrollment of an identified population, a commitment to universality for its members, and the existence of an organization (an "integrator") that accepts responsibility for all three aims for that population. The integrator's role includes at least five components: partnership with individuals and families, redesign of primary care, population health management, financial management, and macro system integration.
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            Ten Key Principles for Successful Health Systems Integration

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              Measuring population health: a review of indicators.

              This article reviews the historical development of population health indicators. We have long known that environmental, socioeconomic, early life conditions, individual actions, and medical care all interact to affect health. Present quantitative reporting on the impact of these factors on population health grew out of Bills of Mortality published in the 1500s. Since then, regular censuses, civil registration of vital statistics, and international classification systems have improved data quality and comparability. Regular national health interview surveys and application of administrative data contributed information on morbidity, health services use, and some social determinants of health. More recently, traditional health databases and datasets on "nonhealth" sector determinants have been linked. Statistical methods for map-making, risk adjustment, multilevel analysis, calculating population-attributable risks, and summary measures of population health have further helped to integrate information. Reports on the health of populations remain largely confined to focused areas. This paper suggests a conceptual framework for using indicators to report on all the domains of population health. Future ethical development of indicators will incorporate principles of justice, transparency, and effectiveness.
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                Author and article information

                Contributors
                m.shahzad@mail.utoronto.ca
                ross.upshur@gmail.com
                Peter.Donnelly@oahpp.ca
                bharmala@gmail.com
                xiaolin.wei@utoronto.ca
                patrick.feng@utoronto.ca
                adalsteinn.brown@utoronto.ca
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                7 June 2019
                7 June 2019
                2019
                : 19
                : 708
                Affiliations
                [1 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Dalla Lana School of Public Health, , University of Toronto, ; Toronto, Ontario Canada
                [2 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Faculty of Medicine, , University of Toronto, ; Toronto, Canada
                [3 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Division of Clinical Public Health, , Dalla Lana School of Public Health, ; Toronto, Canada
                [4 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Department of Family and Community Medicine, , University of Toronto, ; Toronto, Canada
                [5 ]GRID grid.492573.e, Bridgepoint Collaboratory, Lunenfeld-Tanenbaum Research Institute, , Sinai Health System, ; Toronto, Canada
                [6 ]ISNI 0000 0001 1505 2354, GRID grid.415400.4, Public Health Ontario, ; Toronto, Canada
                [7 ]ISNI 0000 0004 0480 265X, GRID grid.421577.2, Fraser Health Authority, ; Surrey, British Columbia Canada
                [8 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Institute of Health Policy, Management and Evaluation, , Dalla Lana School of Public Health, ; Toronto, Canada
                Author information
                http://orcid.org/0000-0002-3787-9755
                Article
                7002
                10.1186/s12889-019-7002-z
                6556001
                31174501
                8d6502a9-3275-4a40-a1cc-fa9c052f9d43
                © The Author(s). 2019

                Open Access This 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
                : 3 January 2019
                : 17 May 2019
                Funding
                Funded by: Faculty of Medicine, University of Toronto
                Award ID: N/A
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Public health
                population health,primary care,public health,community health,health equity
                Public health
                population health, primary care, public health, community health, health equity

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