Describing the scope of practice of patient navigators for older adult patients with complex care needs
Bibliographic record
Abstract
Introduction: Transitions in care (e.g., discharge to home) are stressful for patients, especially for older adults living with complex conditions. To bridge the care gap and improve the continuity of care across care transitions, a new model of care was introduced at a large metropolitan hospital in partnership with a community agency that uses patient navigators which are embedded in the hospital’s care teams, including emergency, acute, and rehabilitative care. Patient Navigators are regulated healthcare professionals with experience in care coordination to assist with care planning during a patient's hospital stay, and to support patients/families in their care journey to their home for up to 90 days. There is qualitative evidence demonstrating that patient navigators have increased patient/caregiver satisfaction at the hospital but further evidence is required to characterize the scope of practice of navigators to better understand how they are integrating with the larger clinical team. Aim∕Objectives∕Theories∕Methods: The purpose of this study was to characterize the scope of practice of patient navigators. The objectives were to identify the characteristics of patients who have been supported by a navigator and to determine the reasons for referral and intervention, service length, and post-discharge location. To accomplish this aim, a cohort observational study design approach was used, which included using clinical notes collected by the patient navigator as well as hospital decision-support chart data between November 2019 to November 2021. Frequencies and descriptive statistics were used to analyze the data. Highlights∕Results∕Key Findings: Of the 176 cases referred to the patient navigator, 28 were deemed not appropriate for the service, 53 received consults (3 days or less of support), and 90 were assigned to the navigator caseload. Of the 90 on the navigator caseload, the average age was 78.9 (SD=9.9) and 44 had a caregiver present to support them. The top reasons were: 1) service connection to community service; 2) housing related; 3) discharge planning, and 4) provider connection. The average service days was 74 days (Median=49 days). The post-discharge location were: home (66%), rehab/reactivation (15%), palliative/deceased (13%), long-term care (3%), acute care (1%), or unknown (2%). Conclusion: To our knowledge, this is the first Canadian study to describe a patient navigator program for older adults with complex care needs in a hospital setting. The finding suggest that patient navigators are playing an active role in helping older adult patients by linking them to appropriate services while also supporting patients and caregivers. The data illustrates that it is a high resource service, with clients receiving supports over a 74 day period, but led to a large proportion of clients being returned back home. Since this is a novel care model, the findings will help provide the evidence needed to make a case for implementing patient navigators. Implications: The Patient Navigator played an important role in advocacy liaising with health and social care providers in the community, and a critical role in discharge planning in the hospital providing follow-up support to patients/families while they transitioned back home for up to 90 days.
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".