BABEL Advance Care Planning in Long-term Care

Overview

1.0 SUMMARY Most Canadian nursing home (NH) residents are elderly and frail, have multiple chronic health conditions and impairments, and have dementia. In 2014, 244,000 Canadians lived in NHs, including 6% of those ≥65 y.o., at a cost of >$10 billion/yr. NH residents experience high rates of acute illness; approximately 33% have emergency department (ED) visits and 23% are hospitalized yearly. Many of these visits are avoidable, and expose residents to iatrogenic complications. In Manitoba >1.5% of NH residents are admitted to intensive care units yearly, where they receive highly aggressive care. Approximately 30-50% of NH residents die each year, experiencing a progressive burden of severe symptoms leading up to death. Thus, there are serious concerns about Advance Care Planning (ACP) and end-of-life (EOL) care in NHs. Canadians in general have mediocre knowledge of, and engagement in ACP. Also, studies show that values such as quality of life and aversion to being dependent trump survival in determining care preferences. Among hospitalized octogenarians, 61% desired comfort care only, or just a brief trial of aggressive care. A U.S. study found that decisions for LTC residents to be sent to ED were frequently driven by families who felt unprepared for their loved ones' death, and insecure about the quality of NH care, where there had been little or no discussion about ACP. Systematic approaches to ACP in NHs have demonstrated benefits, including: increases in ACP uptake, higher compliance with EOL wishes, higher satisfaction with care and emotional well-being, reduced family stress and anxiety, and lower rates of hospitalization. Generally, multimodal ACP interventions have shown the most benefits. Thus, ACP can improve outcomes for NH residents, their families, and society. The goal of this proposal is to apply best practices in ACP, and demonstrate that it can be implemented it in a scalable, sustainable way across provinces. This will result from delivering the ACP intervention within the existing envelope of NH staffing, and by acquiring most of the data from the Resident Assessment Instrument (RAI), which is completed quarterly for NH residents in 9 provinces. As RAI contains information identifying NH residents at the highest risk for dying within 6-12 months, it will be used to target the ACP intervention to such individuals.

Full Title of Study: “Improving Advance Care Planning for Frail, Elderly Residents in Canadian Nursing Homes: A Subproject of the BABEL Study (Better tArgetting, Better Outcomes for Frail ELderly Patients)”

Study Type

  • Study Type: Interventional
  • Study Design
    • Allocation: Randomized
    • Intervention Model: Parallel Assignment
    • Primary Purpose: Supportive Care
    • Masking: Single (Outcomes Assessor)
  • Study Primary Completion Date: August 9, 2020

Detailed Description

2.0 SPECIFIC AIMS 2.1. Aim 1. Improve intervention acceptability, buy-in, and usability by engaging a diverse group of stakeholders to collaboratively design key details of the study. – Aim 1A: The stakeholder group work to identify and agree upon key principles and practical aspects of ACP in the NH setting. – Aim 1B: Using the key principles and practical aspects, and existing evidence about beneficial approaches to ACP in NHs, the investigator group will devise an evidence-based, integrated ACP intervention that can be applied by existing NH personnel. – Aim 1C: Guided by the results of the stakeholder meeting, the investigator group will identify characteristics of NH residents — available from RAI data routinely and repeatedly available in Canadian NHs — to identify a cohort of residents who are at the highest risk of dying in the following 6-12 months. – Aim 1D: Informed by the results of the stakeholder meeting, and existing data, the investigator group, will agree upon the outcomes to be assessed in this study. 2.2. Aim 2. Design and implement training of NH personnel in application of the systematic approach to ACP devised in Aim#1B. 2.3. Aim 3. For each participating NH, devise an approach for real-time access to, and use of, the RAI data for residents. 2.4. Aim 4. Applying the systematic approach to ACP devised in Aim#1B, to high-risk NH residents identified in Aim#1C, will result in improvement in relevant outcomes identified in Aim#1D. 3.0 METHODOLOGICAL APPROACH 3.1. Aim 1A. During a 1 day meeting in Toronto, the investigators will convene stakeholders including: investigators, NH residents and families, advocacy groups for the elderly, legal experts, NH management, NH staff, an expert on inter-professional care, NH physician, geriatrician, palliative care physician, ethicist, ICU physician, and dietitian. Directed discussions and breakout sessions will be utilized to identify key principles and practical components of ACP in the NH setting. All sessions will be recorded. 3.2. Aim 1B. After the stakeholder meeting, the investigator group will conduct weekly telephone conferences to design an integrated, systematic, evidence-based ACP intervention – which will be referred to as "The BABEL Approach to ACP". It will be informed by both: (a) the stakeholder meeting, and (b) existing, published evidence about approaches to ACP in the long-term care setting that have been demonstrated to improve relevant outcomes. These latter include, but are not limited to: (i) "Let Me Decide", (ii) the methods of Morrison et al., and (iii) "Respecting Choices". Criteria will include: likelihood to improve relevant outcomes, practicability, feasibility, scalability, sustainability and general acceptability. 3.3 Aim 1C. This aim will utilize national RAI data on NH residents, maintained at the University of Waterloo by Dr. John Hirdes. Preliminary work in this direction indicates that 44% of all NH residents in the country have one or more of the following, high-risk characteristics, all available from the RAI data: CHESS score ≥3, cancer, congestive heart failure, leave >25% of their food uneaten. 3.4. Aim 1D. There will be discussion during the stakeholder meeting, specifically addressing which potential outcomes are relevant and should be tracked. Informed by those discussions, and outcomes studied in prior studies of ACP in long-term care, the investigator group will compile a final list of outcomes for the study. 3.5. Aim 2. After design of The BABEL Approach to ACP, the investigator group will continue weekly conference calls to develop a detailed plan to train NH staff in implementing it. The investigators and study coordinators in each province will provide the training, which is expected to include (but may not be limited to) applied learning, intentional case studies, role-playing exercises, targeted discussions and adjunctive print, video, and web-based materials. Criteria for the training methods include: practicability, feasibility, acceptability, scalability, and sustainability. Training will occur in the NHs, and will not include actual residents. 3.6. Aim 3. Local investigators and study coordinators will visit each participating NH, and working with NH personnel will: (i) locate how the NH staff conduct the quarterly RAI surveys, (ii) locate where the data is maintained in the NH, and (iii) devise a method, with the direct assistance of NH personnel, for using the RAI data to identify residents who meet targeting criteria (Aim#1C). 3.7. Aim 4. 3.7.A. GENERAL METHODS: This will be a cluster-randomized study in 24 NHs in Ontario, Manitoba, and Alberta, divided equally between intervention and control (total counts are: Ontario=13, Alberta=6, Manitoba=5). Informed consent will be obtained from cognitively intact residents, and from their substitute decision-maker (SDM). 3.7.B. ACP IN CONTROL NURSING HOMES Eligible residents in the 12 control NHs will receive the prevalent approach to ACP. No elements of The BABEL Approach to ACP will be introduced in the control homes. 3.7.C. ACP INTERVENTION NURSING HOMES The intervention comprises: (i) training on, and introduction of The BABEL Approach to ACP for targeted NH residents, and (ii) after these ACP discussions occur, notifying the resident's primary care physician of the residents' ACP preferences, as elicited by the ACP. Intervention homes will be asked to use the systematic, evidence-based approach to ACP for targeted residents. They will be free to use it in non-targeted residents, but it will not be specifically requested that they do so. 3.7.D. INFORMED CONSENT In both intervention and control homes informed consent will be sought from eligible residents (or surrogate consent from SDMs, for residents deemed to lack capacity to provide informed consent), and separately from SDMs. As the ACP approach of our intervention is not investigational, the investigators believe it does not require informed consent, per se. However, informed consent from residents is required to obtain their personal information, track the course of their ACP wishes/decisions, obtain their clinical outcomes, and include their data in group form in analyses, reports and manuscripts from the research study. Residents' clinical outcome information will be obtained from a combination of: their nursing home records, their physician, emergency departments, urgent care, and hospitals. A separate page on the consent form serves specifically as consent to obtain such medical information. Informed consent from SDMs is required to contact them separately in order to send them a survey assessing their satisfaction with care at end-of-life provided to the NH resident. 3.7.E. ANALYSIS OF RESIDENT OUTCOMES Most of these analyses will use hierarchical (2-level) random effects models to account for clustering within NHs, and possible differences between intervention and control groups that might occur, despite randomization. The provinces will be included as fixed effects; interaction terms between province and Intervention/Control will be included to account for possible influences of existing approaches to ACP undertaken by provinces (e.g. PoET in Ontario). Logistic regression will be used for binary outcomes, Poisson regression for rates, OLS regression for continuous variables. The time-to-event analysis will use Cox proportional hazards regression with fixed effects to represent the nursing homes. Resident-level covariates, obtained from NH records and RAI will be: age at NH admission (stratified), gender, marital status at study entry, elapsed time from NH admission to study entry (stratified), location immediately prior to NH entry (as home, assisted living, other LTC facility, hospital or other acute care facility, Chronic Continuing Care facility [in ON only]), medical conditions/diagnoses, CHESS score at study entry, whether at study entry resident was leaving ≥25% of NH food uneaten, and use of specific medications at study entry. Nursing home-level covariates will be: # of beds (stratified), ownership (public vs. private), and elements of pre-existing ACP approaches as derived from the Nursing Home Environmental Scan (specific variables still to be determined, but will do so before doing any analysis). 3.7.F. ANALYSIS OF SDM OUTCOMES Analysis will use hierarchical (2-level) mixed models to account for clustering within NHs, and possible differences between intervention and control groups that might occur, despite randomization. The provinces will be included as fixed effects; interaction terms between province and Intervention/Control will be included to account for possible influences of existing provincial approaches to ACP (e.g. PoET in Ontario). Covariates, obtained from the SDM participants, NH records, and RAI will include all of the covariates from Section 3.7.E, and in addition: SDM age at resident death (stratified), SDM gender, and SDM relationship to deceased resident. 3.7.G. ANALYSIS OF NH STAFF OUTCOMES Analysis of NH staff self-efficacy in ACP will compare the pre-study to post-study difference in self-efficacy ratings between intervention and control NHs. Analysis, in intervention NHs only, of NH staff perceptions of The BABEL Approach to ACP, and to the training in it's use will be mainly descriptive. Analysis of the semi-structured interview of NH personnel will involve thematic analysis, compared between Control and Intervention homes. 3.7.H. ANALYSIS OF PROCESS OUTCOME OF THE RATE OF DOCUMENTED ACP DISCUSSIONS Analysis will use the hierarchical (2-level) random effects Poisson modeling strategy of section 3.7.E. 3.7.I. SAMPLE SIZE CALCULATION – For this calculation, use was made of PASS 2008 sample size software (NCSS, LLC, Kaysville, Utah). Specifically, the calculation for Two Independent Means with a cluster-randomized design. – This calculation was for the co-primary outcome of the ACP Audit survey given 6 weeks after study entry, specifically the fraction of items #1-7 answered 'Yes'. Thus, the scale goes from from 0-7. – It used the following assumptions: • Mean±SD score: – In Control homes = 5.0±1.5 (72% 'yes') (33, 34) – In Intervention homes = 5.6±1.5 (85% 'yes') – 5% Type I error rate – Average of 150 residents in each NH, of whom 0.5% are in respite care (2) – 44% of NH residents are at high risk of death or other acute outcomes, defined as any of: CHESS ≥ 3, cancer, congestive heart failure, or leave >25% of their food uneaten. (personal communication, Dr. John Hirdes, University of Waterloo) – 75% rate of consent among eligible NH residents – Equal proportion of NHs in intervention and control groups – Intraclass correlation coefficient (ICC) for the primary outcome = 20% Using these assumptions, 12 NHs in each group (24 total) gives power of 83% (total N=1164).

Interventions

  • Other: The BABEL Approach to Advance Care Planning in Nursing Homes
    • In intervention nursing homes, eligible residents will: (i) receive The BABEL Approach to Advance Care Planning (ACP), (ii) after these ACP discussions occur, the resident’s primary care physician will be notified of the residents’ ACP wishes, (iii) a brightly colored document will be placed in a standard location of the NH chart that identifies the resident’s ACP wishes, (iv) paramedics will be educated to know about these sheets and where to find them, and that they should be taken with any resident transferred to another care setting.
  • Other: Control group Advance Care Planning
    • Eligible residents in each control nursing homes will receive the prevalent approach to Advance Care Planning in that nursing home. No elements of The BABEL Approach to Advance Care Planning will be introduced in the control homes.

Arms, Groups and Cohorts

  • Other: Intervention ACP Group
    • The BABEL Approach to Advance Care Planning in Nursing Homes
  • Other: Control ACP Group
    • Control group Advance Care Planning

Clinical Trial Outcome Measures

Primary Measures

  • Advance Care Planning (ACP) Audit
    • Time Frame: 6 weeks after study entry
    • 7 item survey as described in: Heyland et al. Journal of Palliative Care Medicine 2(5), 2012. This will be obtained from the resident for those that have capacity, while for residents lacking capacity it will be completed by the Substitute Decision Maker. Each of the 7 items is scored as Yes (1) or No (0) — thus the scale has a range of 0-7 representing the number of items answered ‘Yes’, with a higher score representing better processes of Advance Care Planning.
  • Comfort in Dying of Nursing Home Residents (CAD-EOLD)
    • Time Frame: After death in nursing home, up to 18 months.
    • This is the 14 item version of this scale scale, as described in these 2 papers: Volicer et al., Alzheimer’s Disease and Associated Disorders 15(4):194-200, 2001. Kiely et al., Alzheimer Dis Assoc Disord. 2006 Jul-Sep;20(3):176-81 As described in the Volicer paper, each item is scores 1-3, with total score then on a scale of 14-42, with lower values indicating greater comfort during the final week of life.

Secondary Measures

  • Rate of transfer from nursing home to emergency department or hospital.
    • Time Frame: Up to 18 months.
    • Rate, per person-years of follow-up, of either of these events among nursing home resident subjects.
  • Rate of admission to hospital
    • Time Frame: Up to 18 months.
    • Rate of this event, per person-years of follow-up, among nursing home resident subjects.
  • Time from study entry to death
    • Time Frame: Up to 18 months.
    • Self-explanatory, with censoring at study end, or when the resident is discharged alive from the study nursing home.
  • Rate of use in nursing home of feeding tubes
    • Time Frame: Up to 18 months.
    • Rate of this event, per person-years of follow-up, among nursing home resident subjects.
  • Rate of use in nursing home of systemic antibiotics
    • Time Frame: Up to 18 months.
    • Rate of this event, per person-years of follow-up, among nursing home resident subjects.
  • Rate in nursing home of transition to palliative (comfort) care
    • Time Frame: Up to 18 months.
    • Rate of this event, per person-years of follow-up, among nursing home resident subjects.
  • Discordance in care at the end of life
    • Time Frame: Up to 18 months.
    • Assessed as the fraction of decedents in Intervention homes for whom, during the final month of life in the nursing home, application of any of five medical interventions was contrary to the stated wishes from the Full BABEL ACP Discussion. The five are: CPR/resuscitation, transfer to emergency, transfer to hospital, use of antibiotics, and insertion of a feeding tube.
  • ACP Self-efficacy of Nursing Home Resident Subjects
    • Time Frame: 6 weeks after study entry — given along with the ACP Audit tool (outcome#1)
    • 5 item self-efficacy scale as described by: Sudore et al., J Pain Symptom Manage 53(4):669-681 e8, 2017 The scale from this survey is the sum of the score (1-5) for each of the five items. This outcome will be assessed only for nursing home residents who possess capacity to complete it.
  • Nursing Home staff self-efficacy in Advance Care Planning (ACP)
    • Time Frame: Completed by staff in all participating nursing homes both before nursing home resident recruitment begins, and again at study completion (18 months after study initiation).
    • This 17-item scale is described in Baughman et al., Am J Hosp Palliat Care. Jun 2017;34(5):435-441. Each item is scored on a 1-5 scale of how confident the respondent is in a given aspect of ACP. The scale is formed by summing scores for all 17 items, thus the range is 17-85, with higher scores indicating greater self-efficacy.
  • Thematic analysis of experiences and feelings of nursing home staff about Advance Care Planning.
    • Time Frame: Performed 18 months after study initiation.
    • Evaluated via thematic analysis of semi-structured interviews of staff in all participating nursing homes. Approximately 3-5 staff in each NH will be invited to participate.
  • Satisfaction with Care at End of Life (SWC-EOLD)
    • Time Frame: Survey sent to family member 4 weeks after death of nursing home resident.
    • This is a 10 item scale, as described in Volicer et al., Alzheimer’s Disease and Associated Disorders 15(4):194-200, 2001. It is to be completed by family members of deceased nursing home resident subjects. Each item is scored on a 1-4 scale, so that the overall score ranges 10-40, with higher values indicating greater satisfaction.
  • Whether plan of care was followed.
    • Time Frame: Survey sent to family member 4 weeks after death of nursing home resident.
    • Single item, on a 1-5 scale of level of agreement, sent after nursing home resident death to the substitute decision maker, asking for level of agreement with the statement “The plan of care that was decided upon for your loved one in the nursing home was what was followed”. To be send along with the survey in outcome#13.

Participating in This Clinical Trial

Inclusion Criteria

  • Residents of participating nursing homes – ≥65 y.o. – At high risk of death in the next 6-12 months, as indicated by data collected on the RAI (Resident Assessment Instrument) that completed quarterly in most Canadian nursing homes. Specifically the high-risk elements are any of: CHESS score ≥3; cancer; congestive heart failure; leave >25% of their food uneaten – Resident and resident's substitute decision-maker provide informed consent to participate. Exclusion Criteria:

  • Resident and substitute decision-maker do not speak either English or French. – Residents who are deemed not be competent to make their own medical decisions AND their substitute decision-maker is a legally assigned public guardian, or they have no substitute decision-maker. – Residents who are transferred to a BABEL study home from another BABEL study home, with the date of transfer being after study initiation. Residents who transferred into a study home from a non-study home are eligible.

Gender Eligibility: All

Minimum Age: 65 Years

Maximum Age: N/A

Are Healthy Volunteers Accepted: No

Investigator Details

  • Lead Sponsor
    • University of Manitoba
  • Collaborator
    • University of Waterloo
  • Provider of Information About this Clinical Study
    • Principal Investigator: Dr. Allan Garland, Professor of Medicine and Community Health Sciences – University of Manitoba
  • Overall Official(s)
    • Allan Garland, MD, Principal Investigator, University of Manitoba

Citations Reporting on Results

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Hirdes JP, Mitchell L, Maxwell CJ, White N. Beyond the 'iron lungs of gerontology': using evidence to shape the future of nursing homes in Canada. Can J Aging. 2011 Sep;30(3):371-90. doi: 10.1017/S0714980811000304. Epub 2011 Aug 19.

Estabrooks CA, Hoben M, Poss JW, Chamberlain SA, Thompson GN, Silvius JL, Norton PG. Dying in a nursing home: treatable symptom burden and its link to modifiable features of work context. J Am Med Dir Assoc. 2015 Jun 1;16(6):515-20. doi: 10.1016/j.jamda.2015.02.007. Epub 2015 Mar 21.

Garland A, Olafson K, Ramsey CD, Yogendran M, Fransoo R. Epidemiology of critically ill patients in intensive care units: a population-based observational study. Crit Care. 2013 Sep 30;17(5):R212. doi: 10.1186/cc13026.

Teixeira AA, Hanvey L, Tayler C, Barwich D, Baxter S, Heyland DK; Canadian Researchers at End of Life Network (CARENET). What do Canadians think of advanced care planning? Findings from an online opinion poll. BMJ Support Palliat Care. 2015 Mar;5(1):40-7. doi: 10.1136/bmjspcare-2013-000473. Epub 2013 Oct 4.

Heyland DK, Frank C, Groll D, Pichora D, Dodek P, Rocker G, Gafni A. Understanding cardiopulmonary resuscitation decision making: perspectives of seriously ill hospitalized patients and family members. Chest. 2006 Aug;130(2):419-28. doi: 10.1378/chest.130.2.419.

Heyland DK, Dodek P, Rocker G, Groll D, Gafni A, Pichora D, Shortt S, Tranmer J, Lazar N, Kutsogiannis J, Lam M; Canadian Researchers End-of-Life Network(CARENET). What matters most in end-of-life care: perceptions of seriously ill patients and their family members. CMAJ. 2006 Feb 28;174(5):627-33. doi: 10.1503/cmaj.050626.

Fried TR, Bradley EH, Towle VR, Allore H. Understanding the treatment preferences of seriously ill patients. N Engl J Med. 2002 Apr 4;346(14):1061-6. doi: 10.1056/NEJMsa012528.

Heyland DK, Barwich D, Pichora D, Dodek P, Lamontagne F, You JJ, Tayler C, Porterfield P, Sinuff T, Simon J; ACCEPT (Advance Care Planning Evaluation in Elderly Patients) Study Team; Canadian Researchers at the End of Life Network (CARENET). Failure to engage hospitalized elderly patients and their families in advance care planning. JAMA Intern Med. 2013 May 13;173(9):778-87. doi: 10.1001/jamainternmed.2013.180.

Stephens C, Halifax E, Bui N, Lee SJ, Harrington C, Shim J, Ritchie C. Provider Perspectives on the Influence of Family on Nursing Home Resident Transfers to the Emergency Department: Crises at the End of Life. Curr Gerontol Geriatr Res. 2015;2015:893062. doi: 10.1155/2015/893062. Epub 2015 Aug 24.

In der Schmitten J, Lex K, Mellert C, Rotharmel S, Wegscheider K, Marckmann G. Implementing an advance care planning program in German nursing homes: results of an inter-regionally controlled intervention trial. Dtsch Arztebl Int. 2014 Jan 24;111(4):50-7. doi: 10.3238/arztebl.2014.0050.

Baron K, Hodgson A, Walshe C. Evaluation of an advance care planning education programme for nursing homes: A Longitudinal study. Nurse Educ Today. 2015 May;35(5):689-95. doi: 10.1016/j.nedt.2015.01.005. Epub 2015 Jan 23.

Hammes BJ, Rooney BL. Death and end-of-life planning in one midwestern community. Arch Intern Med. 1998 Feb 23;158(4):383-90. doi: 10.1001/archinte.158.4.383.

Schwartz CE, Wheeler HB, Hammes B, Basque N, Edmunds J, Reed G, Ma Y, Li L, Tabloski P, Yanko J; UMass End-of-Life Working Group. Early intervention in planning end-of-life care with ambulatory geriatric patients: results of a pilot trial. Arch Intern Med. 2002 Jul 22;162(14):1611-8. doi: 10.1001/archinte.162.14.1611.

Morrison RS, Chichin E, Carter J, Burack O, Lantz M, Meier DE. The effect of a social work intervention to enhance advance care planning documentation in the nursing home. J Am Geriatr Soc. 2005 Feb;53(2):290-4. doi: 10.1111/j.1532-5415.2005.53116.x.

Silveira MJ, Kim SY, Langa KM. Advance directives and outcomes of surrogate decision making before death. N Engl J Med. 2010 Apr 1;362(13):1211-8. doi: 10.1056/NEJMsa0907901.

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. BMJ. 2010 Mar 23;340:c1345. doi: 10.1136/bmj.c1345.

Chiarchiaro J, Buddadhumaruk P, Arnold RM, White DB. Prior Advance Care Planning Is Associated with Less Decisional Conflict among Surrogates for Critically Ill Patients. Ann Am Thorac Soc. 2015 Oct;12(10):1528-33. doi: 10.1513/AnnalsATS.201504-253OC.

Molloy DW, Guyatt GH, Russo R, Goeree R, O'Brien BJ, Bedard M, Willan A, Watson J, Patterson C, Harrison C, Standish T, Strang D, Darzins PJ, Smith S, Dubois S. Systematic implementation of an advance directive program in nursing homes: a randomized controlled trial. JAMA. 2000 Mar 15;283(11):1437-44. doi: 10.1001/jama.283.11.1437.

Levy C, Morris M, Kramer A. Improving end-of-life outcomes in nursing homes by targeting residents at high-risk of mortality for palliative care: program description and evaluation. J Palliat Med. 2008 Mar;11(2):217-25. doi: 10.1089/jpm.2007.0147.

Hirdes JP, Poss JW, Mitchell L, Korngut L, Heckman G. Use of the interRAI CHESS scale to predict mortality among persons with neurological conditions in three care settings. PLoS One. 2014 Jun 10;9(6):e99066. doi: 10.1371/journal.pone.0099066. eCollection 2014.

Hirdes JP, Frijters DH, Teare GF. The MDS-CHESS scale: a new measure to predict mortality in institutionalized older people. J Am Geriatr Soc. 2003 Jan;51(1):96-100. doi: 10.1034/j.1601-5215.2002.51017.x.

Tjam EY, Heckman GA, Smith S, Arai B, Hirdes J, Poss J, McKelvie RS. Predicting heart failure mortality in frail seniors: comparing the NYHA functional classification with the Resident Assessment Instrument (RAI) 2.0. Int J Cardiol. 2012 Feb 23;155(1):75-80. doi: 10.1016/j.ijcard.2011.01.031. Epub 2011 Feb 3.

Flacker JM, Kiely DK. Mortality-related factors and 1-year survival in nursing home residents. J Am Geriatr Soc. 2003 Feb;51(2):213-21. doi: 10.1046/j.1532-5415.2003.51060.x.

Austin CA, Mohottige D, Sudore RL, Smith AK, Hanson LC. Tools to Promote Shared Decision Making in Serious Illness: A Systematic Review. JAMA Intern Med. 2015 Jul;175(7):1213-21. doi: 10.1001/jamainternmed.2015.1679.

Casarett D, Karlawish J, Morales K, Crowley R, Mirsch T, Asch DA. Improving the use of hospice services in nursing homes: a randomized controlled trial. JAMA. 2005 Jul 13;294(2):211-7. doi: 10.1001/jama.294.2.211.

Vandervoort A, Houttekier D, Van den Block L, van der Steen JT, Vander Stichele R, Deliens L. Advance care planning and physician orders in nursing home residents with dementia: a nationwide retrospective study among professional caregivers and relatives. J Pain Symptom Manage. 2014 Feb;47(2):245-56. doi: 10.1016/j.jpainsymman.2013.03.009. Epub 2013 Jun 21.

Ampe S, Sevenants A, Smets T, Declercq A, Van Audenhove C. Advance care planning for nursing home residents with dementia: policy vs. practice. J Adv Nurs. 2016 Mar;72(3):569-81. doi: 10.1111/jan.12854. Epub 2015 Nov 12.

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