Dataset Information

Factors influencing shared decision-making in long-term care facilities.

ABSTRACT:

Background

Shared decision-making, a communicative process to reach decisions based on informed preferences, evidence, and co-created goals, improves care satisfaction and patients' quality of life. However, shared decision-making has not been widely implemented in long-term care facilities, and few studies have examined how to promote the shared decision-making practice. This study aimed to identify the influencing factors of shared decision-making based on the Person-centered Practice Framework in long-term care facilities.

Methods

A total of 300 staff (nursing staff, social workers, and personal care workers) in 13 Korean long-term care facilities participated in this study. Data from 280 respondents were finally analyzed, excluding respondents with missing values. Data were collected using structured questionnaires that included items on shared decision-making, personal factors (e.g., knowledge about dementia, person-centered care education, person-centered attitude, communication behavior, and job tenure), and care environment factors (e.g., person-centered climate, staffing level, effective staff relationships, supportive supervisors, and power-sharing). Multilevel linear regression analyses were performed using Mplus Version 8.8.

Results

The mean shared decision-making score was 35.78 (range 8-45). Staff with experience of person-centered care education (β = 0.198, p = 0.034), a higher person-centered attitude score (β = 0.201, p = 0.007), and a higher communication behavior score (β = 0.242, p < 0.001) were more likely to report a higher shared decision-making score. In addition, staff who viewed their care environment as more person-centered were more likely to report a higher shared decision-making score (β = 0.416, p < 0.001).

Conclusions

This study highlights that personal (e.g., person-centered care education, person-centered attitude, and communication behavior) and care environment (e.g., person-centered climate) factors could influence shared decision-making for long-term care residents. These findings could be foundational evidence for facilitating shared decision-making practice in long-term care settings.

SUBMITTER: Kim DE

PROVIDER: S-EPMC10508015 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

Factors influencing shared decision-making in long-term care facilities.

Kim Da Eun DE Kim Min Jung MJ

BMC geriatrics 20230919 1

<h4>Background</h4>Shared decision-making, a communicative process to reach decisions based on informed preferences, evidence, and co-created goals, improves care satisfaction and patients' quality of life. However, shared decision-making has not been widely implemented in long-term care facilities, and few studies have examined how to promote the shared decision-making practice. This study aimed to identify the influencing factors of shared decision-making based on the Person-centered Practice ...[more]

PMID: 37726675

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Project description:AIM:The aim of this study was to explore shared decision-making among residents, their families and staff to determine relevant strategies to support shared decision-making in long-term care (LTC). BACKGROUND:Meaningful engagement of long-term care home (LTCH) residents and their families in care decisions is key in the provision of quality of care. Shared decision-making is an interprofessional approach to increasing resident and family engagement in care decisions which can lead to higher quality decisions, more relevant care interventions and greater resident, family, and staff satisfaction. Despite these advantages, shared decision-making has not been widely implemented in practice in LTC. METHODS:The study took place in one LTCH in Toronto, Ontario, Canada. A qualitative descriptive design was used to explore how residents, family members and staff described how they collaborate when making decisions concerning resident care, and their perceptions of facilitators and challenges to a collaborative approach to decision-making. Individual interviews were conducted with nine participants: residents, families and staff. Data were analysed using content and thematic analysis. FINDINGS:Four main themes that described resident, family and staff perspectives of shared decision-making were as follows: (a) oral communication pathways for information sharing; (b) supporting resident decision-making autonomy; (c) relational aspects of care facilitate shared decision-making; and (d) lack of effective communication creates barriers to shared decision-making. CONCLUSION:As the demand for LTC continues to increase, it is crucial that healthcare providers engage in collaborative, relational practices that foster high-quality resident care. While a relational approach to care can facilitate shared decision-making, there are opportunities to further cultivate shared decision-making in LTCHs through more effective communication and collaboration. IMPLICATIONS FOR PRACTICE:Understanding how information is shared and decisions are made can facilitate shared decision-making in LTCHs. The strategies identified from this study could be further co-developed and implemented in LTCHs.

Project description:BackgroundInsight into factors that influence antibiotic prescribing is crucial when developing interventions aimed at a more rational use of antibiotics. We examined factors that influence antibiotic prescribing in long-term care facilities, and present a conceptual model that integrates these factors.MethodsSemi-structured qualitative interviews were conducted with physicians (n?=?13) and nursing staff (n?=?13) in five nursing homes and two residential care homes in the central-west region of the Netherlands. An iterative analysis was applied to interviews with physicians to identify and categorize factors that influence antibiotic prescribing, and to integrate these into a conceptual model. This conceptual model was triangulated with the perspectives of nursing staff.ResultsThe analysis resulted in the identification of six categories of factors that can influence the antibiotic prescribing decision: the clinical situation, advance care plans, utilization of diagnostic resources, physicians' perceived risks, influence of others, and influence of the environment. Each category comprises several factors that may influence the decision to prescribe or not prescribe antibiotics directly (e.g. pressure of patients' family leading to antibiotic prescribing) or indirectly via influence on other factors (e.g. unfamiliarity with patients resulting in a higher physician perceived risk of non-treatment, in turn resulting in a higher tendency to prescribe antibiotics).ConclusionsOur interview study shows that several non-rational factors may affect antibiotic prescribing decision making in long-term care facilities, suggesting opportunities to reduce inappropriate antibiotic use. We developed a conceptual model that integrates the identified categories of influencing factors and shows the relationships between those categories. This model may be used as a practical tool in long-term care facilities to identify local factors potentially leading to inappropriate prescribing, and to subsequently intervene at the level of those factors to promote appropriate antibiotic prescribing.

Project description:IntroductionChile is committed to actively involving patients in their healthcare. However, little is known about how this is translated into clinical encounters. Breast cancer (BC) is the first cause of cancer-related death in Chilean women. National policy guarantees standard care, and treatment decisions should be made along this process that can have long-term consequences for women. So, BC is a particularly well-suited case study to understand the complexity of patient participation in decision-making.ObjectiveTo identify the factors that affect the active involvement of patients in the BC treatment decision-making process, considering the perspectives and practices of health professionals and women facing the disease.Method and analysisWe will conduct a mixed-method study through a convergent parallel design in three stages: (1) A qualitative study: non-participant observation of the tumour board (TB) meetings; semi-structured interviews with key informants from TBs; documentary analyses; semi-structured interviews with women facing BC; and non-participant observations of clinical encounters; (2) a cross-sectional study with 445 women facing BC stages I-III from three hospitals in Santiago, Chile. We will measure the level of expected participation, experienced participation, decisional conflict, quality of life (QoL) and satisfaction with healthcare. Descriptive analysis will be performed, and multivariable binary logistic regression models will be adjusted to identify factors associated with high levels of QoL or satisfaction; (3) an integration study will bring together the data through a joint display technique.Ethics and disseminationThe study has been conceived and will be conducted according to international and local agreements for ethical research. Ethical approval has been granted by two Ethics Committees in Chile.The results will be disseminated to scientific and lay audiences (publications in scientific journals and conferences, seminars and a website for plain language dissemination).

Project description:BackgroundDigital innovations are yet to make real impacts in the care home sector despite the considerable potential of digital health approaches to help with continued staff shortages and to improve quality of care. To understand the current landscape of digital innovation in long-term care facilities such as nursing and care homes, it is important to find out which clinical decision support tools are currently used in long-term care facilities, what their purpose is, how they were developed, and what types of data they use.ObjectiveThe aim of this review was to analyze studies that evaluated clinical decision support tools in long-term care facilities based on the purpose and intended users of the tools, the evidence base used to develop the tools, how the tools are used and their effectiveness, and the types of data the tools use to contribute to the existing scientific evidence to inform a roadmap for digital innovation, specifically for clinical decision support tools, in long-term care facilities.MethodsA review of the literature published between January 1, 2010, and July 21, 2021, was conducted, using key search terms in 3 scientific journal databases: PubMed, Cochrane Library, and the British Nursing Index. Only studies evaluating clinical decision support tools in long-term care facilities were included in the review.ResultsIn total, 17 papers were included in the final review. The clinical decision support tools described in these papers were evaluated for medication management, pressure ulcer prevention, dementia management, falls prevention, hospitalization, malnutrition prevention, urinary tract infection, and COVID-19 infection. In general, the included studies show that decision support tools can show improvements in delivery of care and in health outcomes.ConclusionsAlthough the studies demonstrate the potential of positive impact of clinical decision support tools, there is variability in results, in part because of the diversity of types of decision support tools, users, and contexts as well as limited validation of the tools in use and in part because of the lack of clarity in defining the whole intervention.

Project description:BackgroundMedication problems among patients with long-term conditions (LTCs) are well documented. Measures to support LTC management include: medicine optimisation services by community pharmacists such as the Medicine Use Review (MUR) service in England, implementation of shared decision making (SDM), and the availability of rapid access clinics in primary care. This study aimed to investigate the experience of patients with LTCs about SDM including medication counselling and their awareness of community pharmacy medication review services.MethodsA mixed research method with a purposive sampling strategy to recruit patients was used. The quantitative phase involved two surveys, each requiring a sample size of 319. The first was related to SDM experience and the second to medication counselling at discharge. Patients were recruited from medical wards at St. George's and Croydon University Hospitals.The qualitative phase involved semi-structured interviews with 18 respiratory patients attending a community rapid access clinic. Interviews were audio-recorded and transcribed verbatim. Thematic analysis using inductive/deductive approaches was employed. Survey results were analysed using descriptive statistics.ResultsThe response rate for surveys 1 and 2 survey was 79% (n = 357/450) and 68.5% (240/350) respectively. Survey 1 showed that although 70% of patients had changes made to their medications, only 40% were consulted about them and two-thirds (62.2%) wanted to be involved in SDM. In survey 2, 37.5% of patients thought that medication counselling could be improved. Most patients (88.8%) were interested in receiving the MUR service; however 83% were not aware of it. The majority (57.9%) were interested in receiving their discharge medications from community pharmacies. The interviews generated three themes; lack of patient-centered care and SDM, minimal medication counselling provided and lack of awareness about the MUR service.ConclusionAlthough patients wanted to take part in SDM, yet SDM and medication counselling are not optimally provided. Patients were interested in the MUR service; however there was lack of awareness and referral for this service. The results propose community pharmacy as a new care pathway for medication supply and counselling post discharge. This promotes a change of health policy whereby community-based services are used to enhance the performance of acute hospitals.

Project description:BackgroundShared decision-making (SDM) is highly relevant in oncology but rarely implemented in routine care. In a stepped-wedge cluster randomized implementation trial, the outcome evaluation of a theoretically and empirically based multi-component SDM implementation program did not show a statistically significant effect on patient-reported SDM uptake. Within this SDM implementation trial, a thorough a priori planned process evaluation was conducted. Thus, the aim of this study was to investigate factors influencing SDM implementation in the context of a multi-component SDM implementation program.MethodsWe conducted qualitative process evaluation of a stepped-wedge SDM implementation trial. Qualitative data included interviews with nurses and physicians of participating departments, field notes by the study team, and meeting minutes. Data were analyzed via deductive and inductive qualitative content analysis on basis of the Consolidated Framework for Implementation Research (CFIR).ResultsTranscripts of 107 interviews with 126 nurses and physicians, 304 pages of field note documentation, and 125 pages of meeting minutes were analyzed. Major factors influencing SDM implementation were found for all domains of the CFIR: a) four regarding characteristics of the individuals involved (e.g., perceived personal relevance, individual motivation to change), b) eleven regarding the inner setting (e.g., leadership engagement, networks and communication, available resources, compatibility with clinical practice), c) two regarding the outer setting (e.g., culture of health care delivery), d) eight regarding characteristics of the intervention (e.g., relative advantage, adaptability), and e) three regarding the implementation process (e.g., integration into existing structures). Furthermore, we found strong interrelations between several of the influencing factors within and between domains.ConclusionsThis comprehensive process evaluation complements the outcome evaluation of the SDM implementation trial and adds to its interpretation. The identified influencing factors can be used for planning, conducting, and evaluating SDM implementation in the future.Trial registrationclinicaltrials.gov, NCT03393351, registered 8 January 2018, https://clinicaltrials.gov/ct2/show/NCT03393351.

Dataset Information

Factors influencing shared decision-making in long-term care facilities.

Background

Methods

Results

Conclusions

Publications

Factors influencing shared decision-making in long-term care facilities.

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