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Record W3198696150 · doi:10.5334/ijic.icic20506

Partnering to spread & scale: How two health systems came together to better the integrated care experience

2021· article· en· W3198696150 on OpenAlexaffabout
Shiran Isaacksz

Bibliographic record

VenueInternational Journal of Integrated Care · 2021
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsGeneral partnershipIntegrated careHealth carePopulationScale (ratio)NursingPresentation (obstetrics)MedicineGerontologyBusinessPolitical scienceGeography

Abstract

fetched live from OpenAlex

IntroductionIn Ontario, Canada two large health systems came together to scale out an evidenced based integrated care model. St. Joseph’s Health System (SJHS) Integrated Comprehensive Care (ICC) program began (2012) in Ontario, Canada within a single surgical stream and has since scaled to all surgeries and complex/chronic patients across a large regional area (patient population of 1.4M). University Health Network (UHN), Canada’s largest hospital-based research organization, partnered with SJHS including St. Joseph’s Home Care and VHA and in four months, rolled-out this model in surgery. Learnings from this partnership are immense. This presentation will share what worked and needed to be adjusted for the diverse needs of Canada’s largest urban centre (Toronto). Practice Change Implemented Working in partnership following ICCs evidenced based approach to integrated care of One Team, One Record, One number to call 24/7, One Fund, and co-designing with patients and providers the program was implemented within 4 months launching in June 2019. This patient-led program focused on what the most pressing needs and concerns were for patients and is already receiving anecdotal reports of improvements for hundreds of patients, their caregivers as well as clinicians.Aim and Theory of ChangeImproving patient/caregiver experience, quality of work life for providers, cost effectiveness and quality outcomes & health are main aims of ICC (Quadruple Aim). Change efforts focused first on demonstrating success within a small patient population and are now supporting spread across UHN, Canada’s largest education and research hospital.Targeted Population and StakeholdersUHN Thoracic surgical stream (1,500 patients a year), all remaining surgical streams, more complex COPD/CHF/Pneumonia, and social medicine pathway. By 2020 the program expects to reach thousands of patients. Stakeholders include patient partners, caregivers existing and new Home & Community care providers, community health centers, existing complimentary programs; specialty clinics and physicians, primary care teams; patients and caregivers; acute care hospitals; governmentTimeline4 months for first surgical stream, 6 months for COPD/CHF/Pneumonia, final year for remaining surgical streams and Social Medicine work is ongoingHighlightsSuccessfully duplicated/transplanted evidenced-based model of integrated care within a different geographic region and hospital culture.Creation of One Team, One Record, One Number to call 24/7, One Fund resulting in:•Improved transitions•Reduced length of stays•Avoidance of Unnecessary Emergency Department visits•Consistency in Care•Improved Communication and CollaborationSustainability/TransferabilitySimilarities with respect to geographic make-up and distribution of patient population and strong relationship across leadership teams enabled a ‘leap of faith’ taken supported by a confidence in the successes demonstrated within SJHS. Transferability was impacted by need to navigate pre-existing partnerships, size and acuity of patient population.Conclusions Through this partnership the team has many insights to share. Key areas of discussion and learning include:•Implementing and applying the foundational elements of the ICC model•The importance and learnings from patient and frontline led co-design•Opportunities and impact of financial levers to support sustainable system change•Access to and use of simple available technology to enable an integrated team approach

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.126
GPT teacher head0.484
Teacher spread0.358 · 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 teacher head, 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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Citations1
Published2021
Admission routes2
Has abstractyes

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