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Record W2735665664 · doi:10.5334/ijic.3192

Evolving Integrated Care: Moving Towards a Population Health Approach

2017· article· en· W2735665664 on OpenAlexaff
G. Ross Baker, Deborah A. Cohen, Elina Farmanova‐Haynes

Bibliographic record

VenueInternational Journal of Integrated Care · 2017
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of OttawaCanadian Institute for Health InformationUniversity of Toronto
Fundersnot available
KeywordsIntegrated careHealth carePopulationPopulation healthProcess managementNursingComputer scienceBusinessMedicineEnvironmental healthEconomic growthEconomics

Abstract

fetched live from OpenAlex

Introduction: Current investments in integrated care have predominantly focused on downstream strategies designed to reduce the fragmentation of healthcare services. Yet, there is a growing recognition that integrated care strategies must also move upstream and focus on health and wellness at the population level. Progress in this area has been slow, but a number of early adopters of the population health approach in integrated care provide insights into key approaches. This research identifies early initiatives, identifies common design components, and analyzes the lessons-learned.Theory/Methods: We undertook a scoping review of the international literature to define and describe the broad range of initiatives underway using Arskey & O’Malley’s five stage scoping review methodology. Literature included academic and grey literature amongst developed OECD countries between the years 2000 and 2015. These papers were abstracted by two reviewers, thematic elements were identified by the team and the evidence synthesized.Results: Thirty-three papers were identified, describing 14 different initiatives taking place in eight different countries around the world. Most of the initiatives were initiated and lead by healthcare system providers (largely within primary care) who interfaced with local social services in order to meet the health needs of a target population. In some cases integrated care strategies were initiated and lead by public health or some other sector that then linked with healthcare. Target populations most often included seniors but also included other subpopulations including families living in high deprivation neighbourhoods, and mothers and children. Beyond healthcare, these initiatives often focused on such determinants of health as physical and social environments, personal health practices, education and literacy, and income.Discussion: There is a growing need to attend to population health within the context of healthcare delivery, rather than as a set of initiatives divorced from front-line practitioners. Several population health oriented integrated care strategies are underway around the world. These initiatives often face implementation challenges in creating robust partnerships across organizations and the alignment of vision, mandates, roles & responsibilities among partners. In addition, governance challenges and funding incentives must be addressed to support program success. Leadership, use of technology and community engagement are major enablers for success.Conclusions: Health systems in the industrialized world face increasing concerns about aging populations and the growing burden of chronic disease. Population health-oriented integrated care strategies have become an important part of sustainable health system reform. By studying early population health oriented integrated care initiatives, lessons learned from implementation can inform the broader thinking in reorienting models of care.Lessons learned: In the context of daily pressures to deliver care, it can be challenging to integrate population health based approaches, but these may be critical for managing chronic conditions.Limitations: This scoping review is limited to those initiatives reported in the literature. The literature is heterogeneous in terms of focus and methods so detailed comparisons between programs is limited.Suggestions for future research: Additional comparative case study research would help to elaborate on the strategies and mechanism for integrating population health approaches into integrated care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.112
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.112
Threshold uncertainty score0.595

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1120.076
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0110.008
Science and technology studies0.0040.022
Scholarly communication0.0220.028
Open science0.0080.030
Research integrity0.0080.014
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.441
Teacher spread0.405 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
Admission routes1
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