The impact of familism on future care planning for Korean parents caring for their children living with disabilities

2019 ◽  
Vol 29 (4) ◽  
pp. 264-277
Author(s):  
Clara Choi ◽  
Mike O’Brien
Keyword(s):  
Care Planning ◽  
Korean Parents ◽  
Future Care ◽  
The Impact

The impact of national context on future care planning for Korean parents in Korea and in New Zealand caring for their children living with disabilities: A cross-national study

2020 ◽  
pp. 002087282094962
Author(s):  
Clara Choi ◽  
Mike O’Brien
Keyword(s):  
New Zealand ◽  
Planning Process ◽  
National Study ◽  
Care Planning ◽  
Care Provision ◽  
Structured Interviews ◽  
Korean Parents ◽  
Future Care ◽  
Cross National Study ◽  
The Impact

An increasing concern of families caring for children living with disabilities is related to planning for their future care. This qualitative study explores how the country contexts shape the plans for future care provision of Korean parents in New Zealand and Korea. Data were collected using semi-structured interviews with parents ( n = 18) and professionals ( n = 18). The study revealed that there are differences and similarities regarding the social reality of future care planning among Koreans in different national contexts. Recommendations are made In support of future care planning process taking its place as a conventional phase of care provision for people living with disabilities.

Discussion and documentation of future care: a before-and-after study examining the impact of an alternative approach to recording treatment decisions on advance care planning in an acute hospital

2017 ◽  
Vol 10 (2) ◽  
pp. e12-e12 ◽  
Author(s):  
Alexandra C Malyon ◽  
Julia R Forman ◽  
Jonathan P Fuld ◽  
Zoë Fritz
Keyword(s):  
End Of Life ◽  
Advance Care Planning ◽  
Treatment Decisions ◽  
Care Planning ◽  
New Approach ◽  
Significance Level ◽  
Oncology Ward ◽  
Future Care ◽  
Advance Care ◽  
The Impact

ObjectiveTo determine whether discussion and documentation of decisions about future care was improved following the introduction of a new approach to recording treatment decisions: the Universal Form of Treatment Options (UFTO).MethodsRetrospective review of the medical records of patients who died within 90 days of admission to oncology or respiratory medicine wards over two 3-month periods, preimplementation and postimplementation of the UFTO. A sample size of 70 per group was required to provide 80% power to observe a change from 15% to 35% in discussion or documentation of advance care planning (ACP), using a two-sided test at the 5% significance level.ResultsOn the oncology ward, introduction of the UFTO was associated with a statistically significant increase in cardiopulmonary resuscitation decisions documented for patients (pre-UFTO 52% to post-UFTO 77%, p=0.01) and an increase in discussions regarding ACP (pre-UFTO 27%, post-UFTO 49%, p=0.03). There were no demonstrable changes in practice on the respiratory ward. Only one patient came into hospital with a formal ACP document.ConclusionsDespite patients’ proximity to the end-of-life, there was limited documentation of ACP and almost no evidence of formalised ACP. The introduction of the UFTO was associated with a change in practice on the oncology ward but this was not observed for respiratory patients. A new approach to recording treatment decisions may contribute to improving discussion and documentation about future care but further work is needed to ensure that all patients’ preferences for treatment and care at the end-of-life are known.

scholarly journals ANTICIPATORY CARE PLANNING: UNDERSTANDING THE IMPACT THAT TALKING ABOUT PLANNING FOR FUTURE CARE HAS ON RELATIVES/FRIENDS OF CARE HOME RESIDENTS

2014 ◽  
Vol 4 (Suppl 1) ◽  
pp. A17.2-A17
Author(s):  
Tamsin McGlinchey ◽  
Philip Saltmarsh ◽  
Rebecca Bancroft ◽  
Stephen Mason ◽  
Gerard Corcoran ◽  
...  
Keyword(s):  
Care Home ◽  
Care Planning ◽  
Future Care ◽  
The Impact

An introduction to advance care planning: practice at the frontline

2018 ◽  
Author(s):  
Anjali Mullick ◽  
Jonathan Martin
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Communication Skills ◽  
Advance Care Planning ◽  
Use Case ◽  
Care Planning ◽  
Practical Advice ◽  
Future Care ◽  
Case Vignettes ◽  
Advance Care

Advance care planning (ACP) is a process of formal decision-making that aims to help patients establish decisions about future care that take effect when they lose capacity. In our experience, guidance for clinicians rarely provides detailed practical advice on how it can be successfully carried out in a clinical setting. This may create a barrier to ACP discussions which might otherwise benefit patients, families and professionals. The focus of this paper is on sharing our experience of ACP as clinicians and offering practical tips on elements of ACP, such as triggers for conversations, communication skills, and highlighting the formal aspects that are potentially involved. We use case vignettes to better illustrate the application of ACP in clinical practice.

Advance care planning: the future

2020 ◽  
pp. bmjspcare-2020-002304
Author(s):  
Judith Rietjens ◽  
Ida Korfage ◽  
Mark Taubert
Keyword(s):  
Advance Care Planning ◽  
Public Awareness ◽  
Care Planning ◽  
Decisional Capacity ◽  
Best Interest ◽  
Awareness Campaigns ◽  
People With Dementia ◽  
Future Care ◽  
Advance Care ◽  
Improve Patient

ObjectivesThere is increased global focus on advance care planning (ACP) with attention from policymakers, more education programmes, laws and public awareness campaigns.MethodsWe provide a summary of the evidence about what ACP is, and how it should be conducted. We also address its barriers and facilitators and discuss current and future models of ACP, including a wider look at how to best integrate those who have diminished decisional capacity.ResultsDifferent models are analysed, including new work in Wales (future care planning which includes best interest decision-making for those without decisional capacity), Asia and in people with dementia.ConclusionsACP practices are evolving. While ACP is a joint responsibility of patients, relatives and healthcare professionals, more clarity on how to apply best ACP practices to include people with diminished capacity will further improve patient-centred care.

7 Exploring healthcare professionals’ attitudes to future care planning with older adults in hospital: qualitative research co-design through multi-professional patient and carer involvement

2018 ◽  
Vol 8 (3) ◽  
pp. 362.2-362
Author(s):  
Anna-Maria Bielinska ◽  
Stephanie Archer ◽  
Catherine Urch ◽  
Ara Darzi
Keyword(s):  
Older Adults ◽  
Decision Making ◽  
End Of Life Care ◽  
Healthcare Professionals ◽  
List Type ◽  
Care Planning ◽  
Life Care ◽  
Topic Guide ◽  
Future Care ◽  
Advance Care

IntroductionDespite evidence that advance care planning in older hospital inpatients improves the quality of end-of-life care (Detering 2010) future care planning (FCP) with older adults remains to be normalised in hospital culture. It is therefore crucial to understand the attitudes of healthcare professionals to FCP in older patients in the hospital setting. Co-design with patients carers and healthcare professionals can generate more detailed meaningful data through better conversations.AimsTo co-design a semi-structured interview (SSI) topic guide to explore healthcare professionals’ attitudes to FCP with older adults in hospital.MethodsA multi-professional research group including a panel of patient and carer representatives co-designed an in-depth topic guide for a SSI exploring healthcare professionals’ attitudes to FCP with older adults in hospital.ResultsThe co-designed topic guide encourages participants to explore personal and system-level factors that may influence attitudes to FCP and practice in hospital amongst healthcare staff. Co-designed topics for inclusion in the SSI schedule include:Potential differences between specialist and generalist approaches to FCPThe influence of perceived hierarchy and emergency–decision making ability in professionals on FCP discussionsThe relevance to transitions of careAttitudes to FCP beyond the biomedical paradigm including perceived well–being and psychosocial aspects of careDigital FCP tools including patient–led FCP.ConclusionCo-designing qualitative research with older people and multi-disciplinary professionals may narrow translational gaps in implementing FCP by setting joint research priorities. Data generated from a co-designed study may expand understanding of hospital-based anticipatory decision-making with older adults.Reference. Detering KM, Hancock AD, Reade MC, Silvester W. The impact of advance care planning on end of life care in elderly patients: randomised controlled trial. BMJ23 March 2010;340:c1345.

scholarly journals Racial Differences in the Impact of Subjective Life Expectancy on Advance Care Planning

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 903-903
Author(s):  
Yifan Lou ◽  
Deborah Carr
Keyword(s):  
Life Expectancy ◽  
Racial Differences ◽  
Advance Care Planning ◽  
Living Will ◽  
Care Planning ◽  
Power Of Attorney ◽  
Risk Of Death ◽  
Advance Care ◽  
Survival Expectations ◽  
The Impact

Abstract The need for advance care planning (ACP) is heightened during the COVID-19 pandemic, especially for older Blacks and Latinx persons who are at a disproportionate risk of death from both infectious and chronic disease. A potentially important yet underexplored explanation for well-documented racial disparities in ACP is subjective life expectancy (SLE), which may impel or impede ACP. Using Health and Retirement Study data (n=7484), we examined the extent to which perceived chances of living another 10 years (100, 51-99, 50, 1-49, or 0 percent) predict three aspects of ACP (living will (LW), durable power of attorney for health care designations (DPAHC), and discussions). We use logistic regression models to predict the odds of each ACP behavior, adjusted for sociodemographic, health, and depressive symptoms. We found modest evidence that SLE predicts ACP behaviors. Persons who are 100% certain they will be alive in ten years are less likely (OR = .68 and .71, respectively) whereas those with pessimistic survival prospects are more likely (OR = 1.23 and 1.15, respectively) to have a LW and a DPAHC, relative to those with modest perceived survival. However, upon closer inspection, these patterns hold only for those whose LW specify aggressive measures versus no LW. We found no race differences for formal aspects of planning (LW, DPAHC) although we did detect differences for informal discussions. Blacks with pessimistic survival expectations are more likely to have discussions, whereas Latinos are less likely relative to whites. We discuss implications for policies and practices to increase ACP rates.

Implementing clinical decision support for oncology advanced care planning: A systems engineering framework to optimize the usability and utility of a machine learning predictive model in clinical practice.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 330-330
Author(s):  
Teja Ganta ◽  
Stephanie Lehrman ◽  
Rachel Pappalardo ◽  
Madalene Crow ◽  
Meagan Will ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Predictive Model ◽  
Systems Engineering ◽  
Care Planning ◽  
Learning Models ◽  
Predictive Tool ◽  
Risk Of Death ◽  
The Impact ◽  
Machine Learning Models

330 Background: Machine learning models are well-positioned to transform cancer care delivery by providing oncologists with more accurate or accessible information to augment clinical decisions. Many machine learning projects, however, focus on model accuracy without considering the impact of using the model in real-world settings and rarely carry forward to clinical implementation. We present a human-centered systems engineering approach to address clinical problems with workflow interventions utilizing machine learning algorithms. Methods: We aimed to develop a mortality predictive tool, using a Random Forest algorithm, to identify oncology patients at high risk of death within 30 days to move advance care planning (ACP) discussions earlier in the illness trajectory. First, a project sponsor defined the clinical need and requirements of an intervention. The data scientists developed the predictive algorithm using data available in the electronic health record (EHR). A multidisciplinary workgroup was assembled including oncology physicians, advanced practice providers, nurses, social workers, chaplain, clinical informaticists, and data scientists. Meeting bi-monthly, the group utilized human-centered design (HCD) methods to understand clinical workflows and identify points of intervention. The workgroup completed a workflow redesign workshop, a 90-minute facilitated group discussion, to integrate the model in a future state workflow. An EHR (Epic) analyst built the user interface to support the intervention per the group’s requirements. The workflow was piloted in thoracic oncology and bone marrow transplant with plans to scale to other cancer clinics. Results: Our predictive model performance on test data was acceptable (sensitivity 75%, specificity 75%, F-1 score 0.71, AUC 0.82). The workgroup identified a “quality of life coordinator” who: reviews an EHR report of patients scheduled in the upcoming 7 days who have a high risk of 30-day mortality; works with the oncology team to determine ACP clinical appropriateness; documents the need for ACP; identifies potential referrals to supportive oncology, social work, or chaplain; and coordinates the oncology appointment. The oncologist receives a reminder on the day of the patient’s scheduled visit. Conclusions: This workgroup is a viable approach that can be replicated at institutions to address clinical needs and realize the full potential of machine learning models in healthcare. The next steps for this project are to address end-user feedback from the pilot, expand the intervention to other cancer disease groups, and track clinical metrics.

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