Development and Implementation of a Nurse-Led Model of Care Coordination to Provide Health-Sector Continuity of Care for People With Multimorbidity: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Innovative strategies are required to reduce care fragmentation for people with multimorbidity. Coordinated models of health care delivery need to be adopted to deliver consumer-centered continuity of care. Nurse-led services have emerged over the past 20 years as evidence-based structured models of care delivery, providing a range of positive and coordinated health care outcomes. Although nurse-led services are effective in a range of clinical settings, strategies to improve continuity of care across the secondary and primary health care sectors for people with multimorbidity have not been examined. OBJECTIVE: To implement a nurse-led model of care coordination from a multidisciplinary outpatient setting and provide continuity of care between the secondary and primary health care sectors for people with multimorbidity. METHODS: This action research mixed methods study will have two phases. Phase 1 includes a systematic review, stakeholder forums, and validation workshop to collaboratively develop a model of care for a nurse-led care coordination service. Phase 2, through a series of iterative action research cycles, will implement a nurse-led model of care coordination in a multidisciplinary outpatient setting. Three to five iterative action research cycles will allow the model to be refined and further developed with multiple data collection points throughout. RESULTS: Pilot implementation of the model of care coordination commenced in October 2018. Formal study recruitment commenced in May 2019 and the intervention and follow-up phases are ongoing. The results of the data analysis are expected to be available by March 2020. CONCLUSIONS: Nursing, clinician, and patient outcomes and experiences with the nurse-led model of care coordination will provide a template to improve continuity of care between the secondary and primary health care systems. The model template may provide a future pathway for implementation of nurse-led services both nationally and internationally. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15006.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.136 | 0.091 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.042 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".