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Record W2765726477 · doi:10.5334/ijic.3452

Using Information Communication Technology in Models of Integrated Community-Based Primary Health Care: Exploring ICT in the iCOACH Study

2017· article· en· W2765726477 on OpenAlexaffabout
Carolyn Steele Gray, Jan Barnsley, Dominique Gagnon, Louise Belzile, Timothy Kenealy, James C. Shaw, Nicolette Sheridan, Walter P. Wodchis

Bibliographic record

VenueInternational Journal of Integrated Care · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueWomen's College HospitalUniversity of TorontoUniversité de SherbrookeLunenfeld-Tanenbaum Research Institute
Fundersnot available
KeywordsIntegrated careInformation and Communications TechnologyKnowledge managementInteroperabilityEnablingeHealthHealth careBusinessInformation systemMedicineComputer scienceEngineeringPolitical scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Introduction: Information and communication technology (ICT) is a promising enabler to support delivery of integrated care by inter-disciplinary teams by supporting information sharing across professional and organizational boundaries; arguably a crucial aspect of successful models of integrated care. The literature suggests that there are core components of ICT functionality such as interoperability between systems, supported chronic disease management functions and patient and caregiver access to ICT, are required to support the delivery of integrated models of care. While suggestions on what ICT for integrated care should look like abound in the literature, few studies have explored how ICT is used in practice in the implementation of integrated community-based primary health care.Theory and Methods: We draw on data from interviews with front-line staff and management collected from 2 cases in Canada (one in Ontario and one in Quebec) and 3 case studies in New Zealand collected as part of the iCOACH project. Interview data was thematically coded around three core themes: 1) types of ICT systems adopted; 2) the role ICT plays in the model of care with regard to central activities of integrated care, and 3) perceived value of systems from the perspective of health care providers and organizational managers and leaders.Results: All case sites had some form of ICT system in place (most often electronic medical records), however variation occurs within and across jurisdictions in terms of which integrated care activities were supported by ICT, the level of adoption, and the sophistication of systems. Most models faced significant challenges with regard to between-system interoperability to allow for effective information sharing. There was additional diversity in terms of healthcare provider use and acceptance of available technology. Where systems were lacking, sites would use workarounds, for example co-locating providers who could access multiple systems at a single site.Discussion: Preliminary analyses of case study data suggest that ICT was used to support a range of integrated care activities. Interoperability remains an important, and often elusive, requirement. Front-line providers and organizations showed the ability to creatively work around limitations of ICT, but did not see these as sustainable solutions.Conclusion: ICT systems across the cases varied in terms of maturity and functionality. There was a consensus across sites regarding the importance of ICT to support integrated care, however many cases did without robust systems. Providers and leaders identified the need to adopt ICT systems that supported information sharing across teams to sustain and grow programs.Lessons Learned: Adoption of ICT systems into models of integrated care can occur at different stages of implementation, with many models reaching a point at which integrated ICT systems are required to support effective sustainable growth.Limitations: Case study findings offer unique and in-depth perspective on the adoption of ICT in 9 different models of integrated care. Findings may not be generalizable to all of models of integrated care.Suggestions for future research: Further exploration is required to determine at exactly which point in the implementation process (early vs. sustained adoption) ICT is required.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.000
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 head0.106
GPT teacher head0.343
Teacher spread0.238 · 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 designQualitative
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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Citations3
Published2017
Admission routes2
Has abstractyes

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