A Randomized, Controlled Trial to Improve Advance Care Planning Among Patients Undergoing Cardiac Surgery
ABSTRACT Although many healthcare providers and researchers consider it necessary to assist patients with end-stage chronic illnesses to plan for the end of life, they tend to avoid discussing end-of-life issues with patients before major surgery. Consequently, surgical patients and their families generally have insufficient knowledge to make plans in case of life-threatening complications.
The objective of this study was to evaluate short-term effects of Patient-Centered Advance Care Planning (PC-ACP).
Thirty-two dyads of patients undergoing cardiac surgery and their surrogates were randomly assigned to receive either the PC-ACP intervention (PC-ACP) or usual care.
Measures studied were patient-surrogate congruence regarding goals for future medical care, patient and surrogate knowledge of advance care planning and anxiety, and patient decisional conflict. Congruence and anxiety were measured before and after the intervention. Decisional conflict and knowledge of advance care planning were measured after the intervention.
Compared with the control group, PC-ACP significantly improved patient-surrogate congruence (Delta=1.27, P<0.01) and reduced patients' decisional conflict (Delta=-0.77, P<0.05). Anxiety change (pre/post) did not differ between treatment and control groups. No difference in knowledge of advance care planning was found between the 2 groups.
The PC-ACP can be an effective approach to advance care planning. Its specificity and relevance to patients' actual medical conditions (as exemplified by its plans for potential complications related to cardiac surgery) can lead to greater patient-surrogate congruence without increasing decisional conflict and anxiety.
- SourceAvailable from: Rebecca A Aslakson
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- "Supplementing interactions with clinicians, decision aids for ACP have, among other findings, demonstrated effectiveness in increasing patients’ knowledge about treatment options, reducing decisional conflict, clarifying patients’ treatment preferences, and increasing completion of advance directives [16-23]. None, however, have been developed or evaluated for use in a high-risk surgical setting [24,25]. "
ABSTRACT: Background High-risk surgery patients may lose decision-making capacity as a result of surgical complications. Advance care planning prior to surgery may be beneficial, but remains controversial and is hindered by a lack of appropriate decision aids. This study sought to examine stakeholders’ views on the appropriateness of using decision aids, in general, to support advance care planning among high-risk surgery populations and the design of such a decision aid. Methods Key informants were recruited through purposive and snowball sampling. Semi-structured interviews were conducted by phone until data collected reached theoretical saturation. Key informants were asked to discuss their thoughts about advance care planning and interventions to support advance care planning, particularly for this population. Researchers took de-identified notes that were analyzed for emerging concordant, discordant, and recurrent themes using interpretative phenomenological analysis. Results Key informants described the importance of initiating advance care planning preoperatively, despite potential challenges present in surgical settings. In general, decision aids were viewed as an appropriate approach to support advance care planning for this population. A recipe emerged from the data that outlines tools, ingredients, and tips for success that are needed to design an advance care planning decision aid for high-risk surgical settings. Conclusions Stakeholders supported incorporating advance care planning in high-risk surgical settings and endorsed the appropriateness of using decision aids to do so. Findings will inform the next stages of developing the first advance care planning decision aid for high-risk surgery patients.BMC Palliative Care 06/2014; 13:32. DOI:10.1186/1472-684X-13-32 · 1.79 Impact Factor
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- "We set the ratios (used in the overall adherence to intervention content elements) and ratings (used in the pacing, overall dyad responsiveness and quality index) based on the analysis of previous pilot studies (Song et al. 2005, in press). We reviewed the intervention sessions delivered during the pilot studies to set a percentage of completed elements to be considered as satisfactory in delivery of the overall content elements. "
ABSTRACT: This paper is a description of a method to develop and conduct a customized psycho-educational intervention fidelity assessment as part of pilot work for an efficacy study. A tool designed to assess treatment fidelity to a psycho-education intervention for patients with end-stage renal disease and their surrogate decision makers, Sharing the Patient's Illness Representations to Increase Trust, is presented as an illustration. Despite the specificity and idiosyncrasy of individual interventions and the call to systematically evaluate treatment fidelity, how to accomplish this goal has not been clarified. Tools to adequately measure treatment fidelity are lacking. We developed the Sharing the Patient's Illness Representations to Increase Trust Treatment Fidelity Assessment tool by identifying elements that were idiosyncratic to the intervention and those that could be adapted from existing tools. The tool has four components: overall adherence to the intervention content elements; pacing of the intervention delivery; overall dyad responsiveness; and, overall quality index of intervention delivery. The study was undertaken between 2006 and 2008. Inter-rater reliability ranged from 0.80 to 0.87 for the four components. The tool showed utility in training and monitoring, such as detecting unplanned content elements delivered and the use of proscribed communication behaviours. Psycho-educational interventions are one of the most common types of nursing interventions worldwide. Use of fidelity assessment tools customized to the individual interventions may enhance systematic evaluation of training and monitoring treatment fidelity.Journal of Advanced Nursing 03/2010; 66(3):673-82. DOI:10.1111/j.1365-2648.2009.05216.x · 1.69 Impact Factor
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- "Ditto and colleagues (2001) found that surrogates who participated in a discussion intervention with healthy patients were no better at identifying patient preferences than was a control group of surrogates who did not hold discussions with patients. However, a discussion intervention targeted at patients about to undergo heart surgery showed success (Song et al. 2005). We aim to clarify the results of prior studies by asking: Question 3: Do spouses who have discussed end-of-life treatment preferences with their surrogates, spouses who have discussed end-of-life treatment preferences with others, and spouses who have not discussed their end-of-life treatment preferences with anyone have surrogates who differ in accuracy and who rely on their own preferences to the same degree? "
ABSTRACT: When terminally ill patients become mentally incapacitated, the patient's surrogate often makes treatment decisions in collaboration with health care providers. We examine how surrogates' errors in reporting their spouse's preferences are affected by their gender, status as durable power of attorney for health care (DPAHC), whether the surrogate and spouse held discussions about end-of-life preferences, and the spouse's health status. We apply structural equation models to data from 2,750 married couples in their mid 60s who participated in the 2004 wave of the Wisconsin Longitudinal Study. Surrogates reported their spouse's preferences incorrectly 13 and 26 percent of the time in end-of-life scenarios involving cognitive impairment and physical pain, respectively. Surrogates projected their own preferences onto the spouse. Similar patterns emerged regardless of surrogate gender, surrogate status as DPAHC, marital discussions about end-of-life, or spousal health status. We discuss implications for the process of surrogate decision-making and for future research.Research on Aging 06/2009; 31(4):463-491. DOI:10.1177/0164027509333683 · 1.23 Impact Factor