Examining the Care Transition Experiences of Home Care Clients Using Journey Mapping
Bibliographic record
Abstract
As a priority area of the Canadian government, home care is heavily relied on to support an integrated, accessible, and sustainable health system. VHA Home Healthcare is a large home care agency in Ontario, Canada. Home care provides services that span personal support, nursing, physical and occupational therapy and more to assist people in remaining in their homes and community. Although home care is associated with delayed and reduced hospital use, some home care recipients will require hospital admission. Unplanned hospital admissions in Ontario account for CAD 1.2 billion in healthcare spending. However, to date, little attention has been paid to the unique needs of clients receiving home care and experiencing a transition to and from the hospital. The proposed study aimed to answer the following research questions: 1)What is the experience of home care clients transitioning from home to hospital and back home and having their home care services resumed? 2)What are opportunities and recommendations to better support home care clients transitioning to and from the hospital? Our study used a descriptive qualitative design by conducting individual interviews and applying a patient journey mapping approach. Patient journey mapping involved identifying the clients’ experience, their touch points across the system, pain points and facilitators. A total of 7 clients and caregivers participated in 12 interviews across two phases. We analyzed the data using qualitative content analysis, and aggregated findings visually depicted the journey on a map. Our results demonstrated that participants experienced hospital admissions as challenging, whether planned or unplanned. Pain points involved having an adverse outcome while in the hospital, including missed or delayed care, attempting to seek additional information to fill knowledge gaps, and sensing not being listened to. Once discharged, clients reported managing multiple service providers and agencies for exacerbated care needs and receiving inconsistent and limited information when in the community. Participants described the system and individual facilitators that mitigated the pain points. These involved having consistent and supportive coordinators and providers in the community before and after the discharge home, having a discharge plan, and accessing an interprofessional team when hospitalized. At a personal level, many participants relied on past professional and personal experience when advocating and navigating the health care system. Self-advocacy skills were essential to ensure that participants had a quality care transition. Our study has several important implications. Notably, patient journey mapping is an effective tool to diagram the home care client journey. Findings also indicate that clients and caregivers often mitigate poor outcomes using advocacy skills and personal and professional experiences. To this end, we can learn from client journeys and leverage clients’ lived experiences to design interventions targeting pain points during care transitions.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".