Developing an integrated geriatric care planning approach in home care
Bibliographic record
Abstract
Introduction \nThe demand for home care services in Canada is on the rise, as older adults wish to remain in their own homes as long as possible and deinstitutionalization of care continues to promise significant savings to the system (Better Home Care, 2016, p. 90). The provision of home care services to the older population is complicated by their increased likelihood to have two or more chronic health conditions and tendency to require care from multiple providers to meet their often complex physical, functional, social, cognitive and psychosocial needs (Health Council of Canada, 2012; Statistics Canada, 2015). In Ontario, home care service allocation, care planning and care delivery are further fragmented as a result of the multi-layered and complex funding and coordination model that exists across the province (Health Quality Ontario, 2012; Local Health Integration Networks, 2014a). More integrated care planning at the point-of-care has the potential to improve the delivery and experience of person- and family-centred geriatric home care (Harvey, Dollard, Marshall, & Mittinty, 2018). This study aimed to develop an implementation framework for a new integrated geriatric care planning approach, at the point-of-care in home care. Key objectives included: a) to investigate the geriatric assessment practices of point-of-care providers; b) to collect ideas from older adults and their family/friend caregivers for improving person-and family-centred goal-setting; and c) to co-design solutions for more integrated geriatric care planning with older adults, their family/friend caregivers and point-of-care providers. \nMethods \nThe Medical Research Council (MRC) Framework for Developing Complex Interventions and the Co-creating Knowledge Translation Framework guided this study (Craig et al., 2013; Powell et al., 2013). A sequential transformative mixed methods design from a pragmatic theoretical lens was applied, using an ideology of collective creativity to meaningfully engage older adults, their family/friend caregivers, and point-of-care providers (Creswell, Clark, Gutmann, & Hanson, 2003; Feilzer, 2010; Sanders & Stappers, 2008; Sanders & Stappers, 2012). Phase one data collection involved scoping the literature, clinical expert key informant interviews (N = 7) and a web-based survey of point-of-care providers (N = 350). Phase two data collection involved solutions-focused key informant interviews with older adults and their family/friend caregivers (N = 25). Quantitative data analysis involved psychometric testing and descriptive statistics. Qualitative data analysis involved inductive and deductive coding techniques and framework analysis (Gale, Heath, Cameron, Rashid, & Redwood, 2013; Lofland, Snow, Anderson, & Lofland, 2006). The data were brought together as an implementation framework during the interpretation phase of this research through a co-design workshop with older adults, their family/friend caregivers and point-of-care providers (N = 19). \nResults \nA new survey for assessing geriatric care assessment practices (G-CAP survey) was developed and demonstrated acceptable test-retest reliability (M ICC = 0.58; M kappa = 0.63), discriminative (M t = 3.0; M p = 0.01) and divergent/convergent (M r= |0.39|) construct validity for use with point-of-care nurses, occupational therapists and physiotherapists in home care. Survey data revealed that point-of-care providers use their observation and interview skills (M = 4.50 on a 5 point scale where 1= never and 5= often-always) far more often than standardized assessment tools for client assessment (M = 1.72) and rarely share assessment data with or receive assessment from other providers (M =3.75; M =3.46). Interview data indicated that older adults and their family/friend caregivers want to be engaged in conversations about their goals in relation to their daily lives, personal background and medical history. An implementation framework for integrated geriatric care planning at the point-of-care emerged, involving three key influencing factors: 1) inclusive assessment practices; 2) dialogue-based goal-setting; and 3) flexible communication strategies. \nConclusions \nIntegrated care planning for service allocation and point-of-care delivery in geriatric home care would be better supported by assessment, goal-setting and communication practices that equally address the information needs and person- and family-centred care experiences desired by older adults, their family/friend caregivers and point-of-care providers in order to promote virtual home care teams. Future research should focus on prototyping strategies, technology, tools and evaluation criteria and measures to operationalize the implementation framework.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".