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Table 1.  Communication Domains That Promote Patient Involvement in Care Through Being Better Engaged, Responded to, Informed, and Debiased
Communication Domains That Promote Patient Involvement in Care Through Being Better Engaged, Responded to, Informed, and Debiased
Table 2.  Adjusted Effects of Intervention on Oncologist-Patient Communication, Quality of Life (QOL), and Utilization of Health Care Resources at the End of Life
Adjusted Effects of Intervention on Oncologist-Patient Communication, Quality of Life (QOL), and Utilization of Health Care Resources at the End of Life
1.
Epstein  RM, Street  RL  Jr.  Patient-Centered Communication in Cancer Care: Promoting Healing and Reducing Suffering. Bethesda, MD: National Cancer Institute, NIH; 2007.
2.
Institute of Medicine.  Assessing and Improving Value in Cancer Care: Workshop Summary. Washington, DC: The National Academies Press; 2009.
3.
National Priorities Partnership. National Priorities and Goals: Aligning Our Efforts to Transform America's Healthcare. Washington, DC: National Quality Forum; 2008.
4.
Institute of Medicine.  Approaching Death: Improving Care at the End of Life. Washington, DC: The National Academies Press; 1997.
5.
DesHarnais  S, Carter  RE, Hennessy  W, Kurent  JE, Carter  C.  Lack of concordance between physician and patient: reports on end-of-life care discussions.  J Palliat Med. 2007;10(3):728-740.PubMedGoogle ScholarCrossref
6.
Parker  SM, Clayton  JM, Hancock  K,  et al.  A systematic review of prognostic/end-of-life communication with adults in the advanced stages of a life-limiting illness: patient/caregiver preferences for the content, style, and timing of information.  J Pain Symptom Manage. 2007;34(1):81-93.PubMedGoogle ScholarCrossref
7.
Institute of Medicine Committee on Approaching Death.  Dying in America: Improving Quality and Honoring Individual Preferences Near the End of Life. Key findings and recommendations. Washington, DC: National Academies Press; 2014.
8.
Weeks  JC, Catalano  PJ, Cronin  A,  et al.  Patients’ expectations about effects of chemotherapy for advanced cancer.  N Engl J Med. 2012;367(17):1616-1625.PubMedGoogle ScholarCrossref
9.
Prigerson  HG, Bao  Y, Shah  MA,  et al.  Chemotherapy use, performance status, and quality of life at the end of life.  JAMA Oncol. 2015;1(6):778-784.PubMedGoogle ScholarCrossref
10.
Wright  AA, Zhang  B, Ray  A,  et al.  Associations between end-of-life discussions, patient mental health, medical care near death, and caregiver bereavement adjustment.  JAMA. 2008;300(14):1665-1673.PubMedGoogle ScholarCrossref
11.
Weeks  JC, Cook  EF, O’Day  SJ,  et al.  Relationship between cancer patients’ predictions of prognosis and their treatment preferences.  JAMA. 1998;279(21):1709-1714.PubMedGoogle ScholarCrossref
12.
Mack  JW, Weeks  JC, Wright  AA, Block  SD, Prigerson  HG.  End-of-life discussions, goal attainment, and distress at the end of life: predictors and outcomes of receipt of care consistent with preferences.  J Clin Oncol. 2010;28(7):1203-1208.PubMedGoogle ScholarCrossref
13.
Mack  JW, Cronin  A, Taback  N,  et al.  End-of-life care discussions among patients with advanced cancer: a cohort study.  Ann Intern Med. 2012;156(3):204-210.PubMedGoogle ScholarCrossref
14.
Hagerty  RG, Butow  PN, Ellis  PM, Dimitry  S, Tattersall  MH.  Communicating prognosis in cancer care: a systematic review of the literature.  Ann Oncol. 2005;16(7):1005-1053.PubMedGoogle ScholarCrossref
15.
Hagerty  RG, Butow  PN, Ellis  PM,  et al.  Communicating with realism and hope: incurable cancer patients’ views on the disclosure of prognosis.  J Clin Oncol. 2005;23(6):1278-1288.PubMedGoogle ScholarCrossref
16.
Frosch  DL, May  SG, Rendle  KA, Tietbohl  C, Elwyn  G.  Authoritarian physicians and patients’ fear of being labeled “difficult” among key obstacles to shared decision making.  Health Aff (Millwood). 2012;31(5):1030-1038.PubMedGoogle ScholarCrossref
17.
Brandes  K, Butow  PN, Tattersall  MH,  et al.  Advanced cancer patients’ and caregivers’ use of a question prompt list.  Patient Educ Couns. 2014;97(1):30-37.PubMedGoogle ScholarCrossref
18.
Walczak  A, Henselmans  I, Tattersall  MH,  et al.  A qualitative analysis of responses to a question prompt list and prognosis and end-of-life care discussion prompts delivered in a communication support program.  Psychooncology. 2015;24(3):287-293.PubMedGoogle ScholarCrossref
19.
Detmar  SB, Aaronson  NK, Wever  LD, Muller  M, Schornagel  JH.  How are you feeling? who wants to know? patients’ and oncologists’ preferences for discussing health-related quality-of-life issues.  J Clin Oncol. 2000;18(18):3295-3301.PubMedGoogle Scholar
20.
Clayton  JM, Butow  PN, Tattersall  MH.  The needs of terminally ill cancer patients versus those of caregivers for information regarding prognosis and end-of-life issues.  Cancer. 2005;103(9):1957-1964.PubMedGoogle ScholarCrossref
21.
Liu  PH, Landrum  MB, Weeks  JC,  et al.  Physicians’ propensity to discuss prognosis is associated with patients’ awareness of prognosis for metastatic cancers.  J Palliat Med. 2014;17(6):673-682.PubMedGoogle ScholarCrossref
22.
Mack  JW, Smith  TJ.  Reasons why physicians do not have discussions about poor prognosis, why it matters, and what can be improved.  J Clin Oncol. 2012;30(22):2715-2717.PubMedGoogle ScholarCrossref
23.
Lamont  EB, Christakis  NA.  Prognostic disclosure to patients with cancer near the end of life.  Ann Intern Med. 2001;134(12):1096-1105.PubMedGoogle ScholarCrossref
24.
Walczak  A, Mazer  B, Butow  PN,  et al.  A question prompt list for patients with advanced cancer in the final year of life: development and cross-cultural evaluation.  Palliat Med. 2013;27(8):779-788.PubMedGoogle ScholarCrossref
25.
Back  AL, Arnold  RM, Baile  WF,  et al.  Efficacy of communication skills training for giving bad news and discussing transitions to palliative care.  Arch Intern Med. 2007;167(5):453-460.PubMedGoogle ScholarCrossref
26.
Curtis  JR, Back  AL, Ford  DW,  et al.  Effect of communication skills training for residents and nurse practitioners on quality of communication with patients with serious illness: a randomized trial.  JAMA. 2013;310(21):2271-2281.PubMedGoogle ScholarCrossref
27.
Tulsky  JA, Arnold  RM, Alexander  SC,  et al.  Enhancing communication between oncologists and patients with a computer-based training program: a randomized trial.  Ann Intern Med. 2011;155(9):593-601.PubMedGoogle ScholarCrossref
28.
Street  RL  Jr, Slee  C, Kalauokalani  DK, Dean  DE, Tancredi  DJ, Kravitz  RL.  Improving physician-patient communication about cancer pain with a tailored education-coaching intervention.  Patient Educ Couns. 2010;80(1):42-47.PubMedGoogle ScholarCrossref
29.
Clayton  JM, Butow  PN, Tattersall  MH,  et al.  Randomized controlled trial of a prompt list to help advanced cancer patients and their caregivers to ask questions about prognosis and end-of-life care.  J Clin Oncol. 2007;25(6):715-723.PubMedGoogle ScholarCrossref
30.
Street  RL. Communication in Medical Encounters: An Ecological Perspective. In: Thompson  TL, Dorsey  AM, Miller  KI, Parrott  R, eds.  Handbook of Health Communication. London, England: Lawrence Erlbaum Associates; 2003:63-89.
31.
Clayton  JM, Butow  PN, Arnold  RM, Tattersall  MH.  Discussing end-of-life issues with terminally ill cancer patients and their carers: a qualitative study.  Support Care Cancer. 2005;13(8):589-599.PubMedGoogle ScholarCrossref
32.
Steinhauser  KE, Christakis  NA, Clipp  EC, McNeilly  M, McIntyre  L, Tulsky  JA.  Factors considered important at the end of life by patients, family, physicians, and other care providers.  JAMA. 2000;284(19):2476-2482.PubMedGoogle ScholarCrossref
33.
Street  RL  Jr, Makoul  G, Arora  NK, Epstein  RM.  How does communication heal? pathways linking clinician-patient communication to health outcomes.  Patient Educ Couns. 2009;74(3):295-301.PubMedGoogle ScholarCrossref
34.
Dimoska  A, Tattersall  MH, Butow  PN, Shepherd  H, Kinnersley  P.  Can a “prompt list” empower cancer patients to ask relevant questions?  Cancer. 2008;113(2):225-237.PubMedGoogle ScholarCrossref
35.
Clayton  JM, Hancock  KM, Butow  PN,  et al.  Clinical practice guidelines for communicating prognosis and end-of-life issues with adults in the advanced stages of a life-limiting illness, and their caregivers.  Med J Aust. 2007;186(12 suppl):S77, S79, S83-108.PubMedGoogle Scholar
36.
Hoerger  M, Epstein  RM, Winters  PC,  et al.  Values and options in cancer care (VOICE): study design and rationale for a patient-centered communication and decision-making intervention for physicians, patients with advanced cancer, and their caregivers.  BMC Cancer. 2013;13(1):188.PubMedGoogle ScholarCrossref
37.
Carroll  T, Epstein  RM, Gramling  R. What are strategies for estimating survival prognosis in advanced cancer? In: Goldstein  N, Morrison  S, eds.  Evidence-based Practice of Palliative Medicine. Cambridge, MA: Elsevier Press; 2012.
38.
Moss  AH, Lunney  JR, Culp  S,  et al.  Prognostic significance of the “surprise” question in cancer patients.  J Palliat Med. 2010;13(7):837-840.PubMedGoogle ScholarCrossref
39.
Street  RL  Jr, Gordon  H, Haidet  P.  Physicians’ communication and perceptions of patients: is it how they look, how they talk, or is it just the doctor?  Soc Sci Med. 2007;65(3):586-598.PubMedGoogle ScholarCrossref
40.
Street  RL  Jr, Krupat  E, Bell  RA, Kravitz  RL, Haidet  P.  Beliefs about control in the physician-patient relationship: effect on communication in medical encounters.  J Gen Intern Med. 2003;18(8):609-616.PubMedGoogle ScholarCrossref
41.
Del Piccolo  L, de Haes  H, Heaven  C,  et al.  Development of the Verona coding definitions of emotional sequences to code health providers’ responses (VR-CoDES-P) to patient cues and concerns.  Patient Educ Couns. 2011;82(2):149-155.PubMedGoogle ScholarCrossref
42.
Zimmermann  C, Del Piccolo  L, Bensing  J,  et al.  Coding patient emotional cues and concerns in medical consultations: the Verona coding definitions of emotional sequences (VR-CoDES).  Patient Educ Couns. 2011;82(2):141-148.PubMedGoogle ScholarCrossref
43.
Back  AL, Arnold  RM, Baile  WF, Tulsky  JA, Fryer-Edwards  K.  Approaching difficult communication tasks in oncology.  CA Cancer J Clin. 2005;55(3):164-177.PubMedGoogle ScholarCrossref
44.
Shields  CG, Coker  CJ, Poulsen  SS,  et al.  Patient-centered communication and prognosis discussions with cancer patients.  Patient Educ Couns. 2009;77(3):437-442.PubMedGoogle ScholarCrossref
45.
Back  AL, Arnold  RM, Quill  TE.  Hope for the best, and prepare for the worst.  Ann Intern Med. 2003;138(5):439-443.PubMedGoogle ScholarCrossref
46.
Kiely  BE, Soon  YY, Tattersall  MH, Stockler  MR.  How long have I got? estimating typical, best-case, and worst-case scenarios for patients starting first-line chemotherapy for metastatic breast cancer: a systematic review of recent randomized trials.  J Clin Oncol. 2011;29(4):456-463.PubMedGoogle ScholarCrossref
47.
Epstein  RM, Street  RL.  A Framework for Patient-Centered Communication in Cancer Care. Patient-Centered Communication in Cancer Care. Bethesda, MD: National Cancer Institute, NIH; 2007:17-38.
48.
Mack  JW, Block  SD, Nilsson  M,  et al.  Measuring therapeutic alliance between oncologists and patients with advanced cancer: the Human Connection Scale.  Cancer. 2009;115(14):3302-3311.PubMedGoogle ScholarCrossref
49.
Williams  GC, Rodin  GC, Ryan  RM, Grolnick  WS, Deci  EL.  Autonomous regulation and long-term medication adherence in adult outpatients.  Health Psychol. 1998;17(3):269-276.PubMedGoogle ScholarCrossref
50.
Maly  RC, Frank  JC, Marshall  GN, DiMatteo  MR, Reuben  DB.  Perceived efficacy in patient-physician interactions (PEPPI): validation of an instrument in older persons.  J Am Geriatr Soc. 1998;46(7):889-894.PubMedGoogle ScholarCrossref
51.
Cohen  SR, Mount  BM, Strobel  MG, Bui  F.  The McGill Quality of Life Questionnaire: a measure of quality of life appropriate for people with advanced disease: a preliminary study of validity and acceptability.  Palliat Med. 1995;9(3):207-219.PubMedGoogle ScholarCrossref
52.
Cella  DF, Tulsky  DS, Gray  G,  et al.  The Functional Assessment of Cancer Therapy scale: development and validation of the general measure.  J Clin Oncol. 1993;11(3):570-579.PubMedGoogle Scholar
53.
Wright  AA, Zhang  B, Keating  NL, Weeks  JC, Prigerson  HG.  Associations between palliative chemotherapy and adult cancer patients’ end of life care and place of death: prospective cohort study.  BMJ. 2014;348:g1219.PubMedGoogle ScholarCrossref
54.
Earle  CC, Park  ER, Lai  B, Weeks  JC, Ayanian  JZ, Block  S.  Identifying potential indicators of the quality of end-of-life cancer care from administrative data.  J Clin Oncol. 2003;21(6):1133-1138.PubMedGoogle ScholarCrossref
55.
Barnato  AE, Farrell  MH, Chang  C-CH, Lave  JR, Roberts  MS, Angus  DC.  Development and validation of hospital “end-of-life” treatment intensity measures.  Med Care. 2009;47(10):1098-1105.PubMedGoogle ScholarCrossref
56.
Li  Z, Tosteson  TD, Bakitas  MA.  Joint modeling quality of life and survival using a terminal decline model in palliative care studies.  Stat Med. 2013;32(8):1394-1406.PubMedGoogle ScholarCrossref
57.
Bakitas  MA, Tosteson  TD, Li  Z,  et al.  Early versus delayed initiation of concurrent palliative oncology care: patient outcomes in the ENABLE III randomized controlled trial.  J Clin Oncol. 2015;33(13):1438-1445.PubMedGoogle ScholarCrossref
58.
Epstein  RM, Franks  P, Fiscella  K,  et al.  Measuring patient-centered communication in patient-physician consultations: theoretical and practical issues.  Soc Sci Med. 2005;61(7):1516-1528.PubMedGoogle ScholarCrossref
59.
Temel  JS, Greer  JA, Admane  S,  et al.  Longitudinal perceptions of prognosis and goals of therapy in patients with metastatic non-small-cell lung cancer: results of a randomized study of early palliative care.  J Clin Oncol. 2011;29(17):2319-2326.PubMedGoogle ScholarCrossref
60.
Enzinger  AC, Zhang  B, Schrag  D, Prigerson  HG.  Outcomes of prognostic disclosure: Associations with prognostic understanding, distress, and relationship with physician among patients with advanced cancer.  J Clin Oncol. 2015;33(32):3809-3816.PubMedGoogle ScholarCrossref
61.
Gramling  RF, Fiscella  K, Xing  G,  et al.  Differences of opinion or inadequate communication? determinants of patient-oncologist prognostic discordance in advanced cancer  [published online July 14, 2016].  JAMA Oncol. doi:10.1001/jamaoncol.2016.1861Google Scholar
62.
Miller  SM.  Monitoring versus blunting styles of coping with cancer influence the information patients want and need about their disease. Implications for cancer screening and management.  Cancer. 1995;76(2):167-177.PubMedGoogle ScholarCrossref
63.
The  AM, Hak  T, Koëter  G, van der Wal  G.  Collusion in doctor-patient communication about imminent death: an ethnographic study.  West J Med. 2001;174(4):247-253.PubMedGoogle ScholarCrossref
64.
de Haes  H, Koedoot  N.  Patient centered decision making in palliative cancer treatment: a world of paradoxes.  Patient Educ Couns. 2003;50(1):43-49.PubMedGoogle ScholarCrossref
65.
Penson  RT, Partridge  RA, Shah  MA, Giansiracusa  D, Chabner  BA, Lynch  TJ  Jr.  Fear of death.  Oncologist. 2005;10(2):160-169.PubMedGoogle ScholarCrossref
66.
Niemiec  CP, Brown  KW, Kashdan  TB,  et al.  Being present in the face of existential threat: the role of trait mindfulness in reducing defensive responses to mortality salience.  J Pers Soc Psychol. 2010;99(2):344-365.PubMedGoogle ScholarCrossref
67.
Burke  BL, Martens  A, Faucher  EH.  Two decades of terror management theory: a meta-analysis of mortality salience research.  Pers Soc Psychol Rev. 2010;14(2):155-195.PubMedGoogle ScholarCrossref
68.
Rodenbach  RA, Rodenbach  KE, Tejani  MA, Epstein  RM.  Relationships between personal attitudes about death and communication with terminally ill patients: how oncology clinicians grapple with mortality.  Patient Educ Couns. 2016;99(3):356-363.PubMedGoogle ScholarCrossref
69.
Shayne  M, Quill  TE.  Oncologists responding to grief.  Arch Intern Med. 2012;172(12):966-967.PubMedGoogle ScholarCrossref
70.
Back  AL, Arnold  RM, Baile  WF,  et al.  Faculty development to change the paradigm of communication skills teaching in oncology.  J Clin Oncol. 2009;27(7):1137-1141.PubMedGoogle ScholarCrossref
71.
Zimmermann  C, Swami  N, Krzyzanowska  M,  et al.  Early palliative care for patients with advanced cancer: a cluster-randomised controlled trial.  Lancet. 2014;383(9930):1721-1730.PubMedGoogle ScholarCrossref
72.
Quill  TE, Abernethy  AP.  Generalist plus specialist palliative care—creating a more sustainable model.  N Engl J Med. 2013;368(13):1173-1175.PubMedGoogle ScholarCrossref
73.
Mitchell  JJ  Jr.  The findings of the Dartmouth Atlas Project: a challenge to clinical and ethical excellence in end-of-life care.  J Clin Ethics. 2011;22(3):267-276.PubMedGoogle Scholar
74.
Cutler  D, Skinner  J, Stern  AD, Wennberg  D. Physician beliefs and patient preferences: a new look at regional variation in health care spending. Working Paper 19320. Cambridge, MA: National Bureau of Economic Research. August 2013. http://www.nber.org/papers/w19320. Accessed August 24, 2016.
75.
Barnato  AE, Cohen  ED, Mistovich  KA, Chang  C-CH.  Hospital end-of-life treatment intensity among cancer and non-cancer cohorts.  J Pain Symptom Manage. 2015;49(3):521-529; e525.Google Scholar
76.
Barnato  AE, Mohan  D, Lane  RK,  et al.  Advance care planning norms may contribute to hospital variation in end-of-life ICU use: a simulation study.  Med Decis Making. 2014;34(4):473-484.PubMedGoogle ScholarCrossref
77.
Barnato  AE, Herndon  MB, Anthony  DL,  et al.  Are regional variations in end-of-life care intensity explained by patient preferences? a study of the US Medicare population.  Med Care. 2007;45(5):386-393.PubMedGoogle ScholarCrossref
78.
Lewin  SA, Skea  ZC, Entwistle  V, Zwarenstein  M, Dick  J.  Interventions for providers to promote a patient-centred approach in clinical consultations.  Cochrane Database Syst Rev. 2001;(4):CD003267.PubMedGoogle Scholar
Original Investigation
January 2017

Effect of a Patient-Centered Communication Intervention on Oncologist-Patient Communication, Quality of Life, and Health Care Utilization in Advanced Cancer: The VOICE Randomized Clinical Trial

Author Affiliations
  • 1Center for Communication and Disparities Research, University of Rochester School of Medicine and Dentistry, Rochester, New York
  • 2Department of Family Medicine, University of Rochester School of Medicine and Dentistry, Rochester, New York
  • 3Department of Psychiatry, University of Rochester School of Medicine and Dentistry, Rochester, New York
  • 4James P Wilmot Cancer Center, University of Rochester School of Medicine and Dentistry, Rochester, New York
  • 5Center for Healthcare Policy and Research, University of California, Davis, Sacramento
  • 6UC Davis Comprehensive Cancer Center, University of California, Davis, Sacramento
  • 7Department of Family and Community Medicine, University of California, Davis, Sacramento
  • 8Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, New York
  • 9Center for Community Health, University of Rochester School of Medicine and Dentistry, Rochester, New York
  • 10Departments of Psychology, Psychiatry, and Medicine, Tulane University, New Orleans, Louisiana
  • 11Tulane Cancer Center, Tulane University, New Orleans, Louisiana
  • 12Department of Pediatrics, University of California, Davis, Sacramento
  • 13School of Nursing, University of Rochester, Rochester, New York
  • 14Division of Palliative Care, University of Rochester School of Medicine and Dentistry, Rochester, New York
  • 15Department of Medicine, University of Rochester School of Medicine and Dentistry, Rochester, New York
  • 16Department of Internal Medicine, University of California, Davis, Sacramento
  • 17Department of Communication, Texas A & M University, College Station
  • 18Houston Center for Healthcare Innovation, Quality, and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas
  • 19Department of Medicine, Baylor College of Medicine, Houston, Texas
  • 20Human Development and Family Studies Department, Purdue University, West Lafayette, Indiana
  • 21Purdue University Center for Cancer Research, Purdue University, West Lafayette, Indiana
  • 22Regenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, Indiana
  • 23Center on Poverty and Health Inequities, Purdue University, West Lafayette, Indiana
  • 24College of Health of Human Sciences, Purdue University, West Lafayette, Indiana
  • 25Fred Hutchinson Cancer Research Center, University of Washington, Seattle
  • 26Cambia Palliative Care Center of Excellence, University of Washington, Seattle
  • 27Centre for Medical Psychology and Evidence-based Decision-making, University of Sydney, Sydney, Australia
  • 28Psycho-oncology Co-operative Research Group, University of Sydney, Sydney, Australia
  • 29School of Psychology, University of Sydney, Sydney, Australia
  • 30Sydney Medical School, University of Sydney, Sydney, Australia
  • 31Royal Prince Alfred Hospital, Sydney, Australia
  • 32University of California, Davis School of Medicine, University of California, Davis, Sacramento
  • 34Department of Social Work, Strong Memorial Hospital, Rochester, New York
  • 35Division of General Medicine, University of California, Davis, Sacramento
JAMA Oncol. 2017;3(1):92-100. doi:10.1001/jamaoncol.2016.4373
Key Points

Question  Can communication between patients with advanced cancer and their oncologists be improved?

Findings  This cluster randomized clinical trial of communication training for oncologists paired with previsit coaching for patients showed clinically and statistically significant improvement in patient-centered communication.

Meaning  Paired communication training for patients and oncologists helps achieve patient-centered care in advanced cancer: engaging patients in consultations (asking questions, expressing preferences), responding to emotions, and providing information about prognosis and treatment choices.

Abstract

Importance  Observational studies demonstrate links between patient-centered communication, quality of life (QOL), and aggressive treatments in advanced cancer, yet few randomized clinical trials (RCTs) of communication interventions have been reported.

Objective  To determine whether a combined intervention involving oncologists, patients with advanced cancer, and caregivers would promote patient-centered communication, and to estimate intervention effects on shared understanding, patient-physician relationships, QOL, and aggressive treatments in the last 30 days of life.

Design, Setting, and Participants  Cluster RCT at community- and hospital-based cancer clinics in Western New York and Northern California; 38 medical oncologists (mean age 44.6 years; 11 (29%) female) and 265 community-dwelling adult patients with advanced nonhematologic cancer participated (mean age, 64.4 years, 146 [55.0%] female, 235 [89%] white; enrolled August 2012 to June 2014; followed for 3 years); 194 patients had participating caregivers.

Interventions  Oncologists received individualized communication training using standardized patient instructors while patients received question prompt lists and individualized communication coaching to identify issues to address during an upcoming oncologist visit. Both interventions focused on engaging patients in consultations, responding to emotions, informing patients about prognosis and treatment choices, and balanced framing of information. Control participants received no training.

Main Outcomes and Measures  The prespecified primary outcome was a composite measure of patient-centered communication coded from audio recordings of the first oncologist visit following patient coaching (intervention group) or enrollment (control). Secondary outcomes included the patient-physician relationship, shared understanding of prognosis, QOL, and aggressive treatments and hospice use in the last 30 days of life.

Results  Data from 38 oncologists (19 randomized to intervention) and 265 patients (130 intervention) were analyzed. In fully adjusted models, the intervention resulted in clinically and statistically significant improvements in the primary physician-patient communication end point (adjusted intervention effect, 0.34; 95% CI, 0.06-0.62; P = .02). Differences in secondary outcomes were not statistically significant.

Conclusions and Relevance  A combined intervention that included oncologist communication training and coaching for patients with advanced cancer was effective in improving patient-centered communication but did not affect secondary outcomes.

Trial Registration  clinicaltrials.gov Identifier: NCT01485627

Introduction

The National Cancer Institute, the National Academy of Medicine, the American Society for Clinical Oncology, and the National Priorities Partnership all call for improved patient-physician communication in the context of serious and life-limiting illnesses, citing effects of good communication on quality of care and quality of life (QOL) and an ethical mandate that patients be offered participation in informed decisions regarding their care.1-4 In advanced cancer, inadequate communication about prognosis and treatment choices is common5-7 and is associated with unrealistic patient expectations regarding curability,8 provision of aggressive treatment that is not concordant with patients’ wishes and enrollment in hospice too late to deliver discernable benefit.8-12 Critical conversations typically do not happen, or happen in hospital shortly before a patient’s death.13

Making high-quality conversations happen is difficult. More than 90% of patients with advanced cancer say they want to be actively involved in their care and value frank and sensitive conversations about QOL, prognosis, and treatment choices.10,14,15 Yet patients are often reluctant to be assertive, ask questions, request clarification, express emotions directly, or state opinions and preferences.16 As death approaches, patients express considerable ambivalence about end-of-life discussions, often indicating that now is “not the right time.”17-20 Similarly, while most clinicians indicate willingness to have these discussions “now,” few follow through.21,22 More typically, clinicians wait for patients to signal interest, then offer prognostic information that is optimistically biased.23,24

Prior attempts to improve patient-physician communication in advanced cancer have had limited impact. Intensive workshops inconsistently improve trainee communication behaviors25,26 and are impractical for busy clinicians. Brief individualized in-office interventions using expert feedback on video recorded encounters improved oncologists’ empathy and patient-reported trust,27 but this approach has not been applied to other communication behaviors, such as delivery of prognostic information. Patient coaching increased discussion of cancer pain,28 and, in palliative care, question prompt lists (QPLs) have increased question-asking29—but only when physicians encouraged patients to ask questions.

The Values and Options in Cancer Care (VOICE) study30 combined 2 interventions, a brief individualized oncologist skill-based training, and individualized patient and caregiver coaching incorporating a QPL. Based on an ecological model of patient-clinician communication, both interventions were designed to promote the involvement in care that patients and families desire but rarely request and emphasized the same communication skills and topics identified in prior research: engaging patients to participate in the consultation, responding to patients’ emotions, informing patients about prognosis and treatment choices, and framing information in a balanced manner.6,18,29,31-35 The primary outcome was patient-centered communication in these domains. Secondary outcomes were shared understanding, patient-physician relationships, QOL, and health care utilization at the end of life.33

Methods
Overview

We conducted a multisite cluster randomized clinical trial (RCT) of an intervention to improve communication between patients (and caregivers when available) and oncologists. Oncologists randomized to the intervention arm participated in individualized communication training using standardized patient-instructors (SPIs), while their patients (with caregivers) participated in an individualized communication coaching session with follow-up telephone calls. After a prerandomization phase designed to assess baseline communication patterns of participating oncologists, we enrolled participants (from August 2012 through June 2014) and followed them until October 2015. We obtained institutional review board approval for all study sites, and participants provided written informed consent and received $15 per questionnaire completed. See the published study description36 and the eAppendix in Supplement 1 for the study protocol and descriptions of the interventions and Supplement 2 for the statistical analysis plan.

Settings and Participants

We conducted the study in community-based cancer clinics (4), academic medical centers (3) and community hospitals (3) in Western New York and Sacramento, California.

Physicians

We recruited medical oncologists who care for patients with nonhematologic cancers at practice meetings at participating clinics. The mean physician age was 44 years; 27 (71%) were male; 17 (45%) were white, 16 (42%) were Asian, and 5 (13%) were of other race.

Patients

With clinic staff, research assistants reviewed clinic rosters of enrolled physicians to contact potentially eligible patients age 21 years or older, able to understand spoken English and provide written informed consent, and who had either stage IV nonhematologic cancer or stage III cancer and whose physician “would not be surprised” if the patient were to die within 12 months.37,38 We excluded inpatients and those in hospice. We first recruited 3 to 4 “prerandomization” patients per physician who agreed to have 1 office visit audio recorded and complete questionnaires before and after the office visit. After physician randomization, we recruited a new cohort of patients, up to 10 per physician, for the cluster RCT (eTable 1 in Supplement 3) until we reached the target sample size of 265 patients. Cluster RCT patients also agreed to an audio recorded office visit and previsit and postvisit questionnaires; in addition, they agreed to participate in intervention or control conditions, complete questionnaires quarterly for 3 years, and to have their medical records abstracted. Patients were blinded to study arm assignment until completion of baseline measures.

Caregivers

Research assistants asked patients to identify “a family member, partner, friend, or other individual involved with your health care issues, preferably someone who comes to physician appointments with you.” Eligible caregivers were 21 years or older and able to understand spoken English and provide written informed consent.

Interventions

The experimental intervention36 included (1) a 2-session in-office physician training (1.75 hours) using a brief video, feedback from standardized patients portraying roles of patients with advanced cancer who also critiqued up to 2 audio recorded study patient visits, and (2) a single 1-hour patient and caregiver coaching session incorporating a question prompt list to help patients bring their most important concerns to their oncologist’s attention at an upcoming office visit, plus up to 3 follow-up phone calls (Table 1; eTable 2 in Supplement 3). Trainers and coaches underwent 3-day on-site trainings. To promote patient-centered communication about disease course, prognosis, treatment decisions and end-of-life care, physician and patient interventions focused on the same 4 key domains of patient-centered communication.36 Intervention sessions were audio recorded and reviewed by lead trainers and investigators using a fidelity checklist. Fidelity was 94% or higher.

All intervention physicians completed both training sessions. All intervention patients received in-person coaching; of the 52% who responded to a mailed survey, 87% “would recommend coaching to other patients with cancer”; and 85% were able to ask “all” or “most” of their “most important” questions. Of the 130 coached patients, 94% participated in ≥1 follow-up call (≥2 calls, 78.7%; 3 calls, 58.3%); reasons for nonparticipation were death and/or illness (47.1%), unreturned phone calls (47.1%) and refusal and/or withdrawal (5.8%). Control physicians and patients received no training.

Data Collection and Outcome Measures

We audio recorded the first physician visit after the coaching session (for intervention) or after study entry (control). The primary outcome was a composite of 4 prespecified communication measures matched to the goals of communication training, described in detail in Table 1engaging patients in consultations (Active Patient Participation Coding [APPC]39), responding to patients’ emotions (Verona VR-CoDES41,42), informing patients about prognosis and treatment choices (Prognostic and Treatment Choices [PTCC] Informing subscale44) and balanced framing of decisions (PTCC Balanced Framing subscale44). The composite score derived from these scales were designed to capture key elements of 6 interrelated functions of communication outlined by the National Cancer Institute: fostering healing relationships (APPC), exchanging information (PTCC), managing uncertainty (PTCC), making decisions (APPC, PTCC), responding to emotions (Verona), and enabling patient self-management (APPC).47 Coding of the 4 measures was performed by teams of trained university students who were audited continuously and blinded to study hypotheses and group assignment. We transformed each of the 4 component scores to z scores based on the prerandomization phase sample means (SDs):

z = (Raw Score – Prerandomization Phase Mean)/Prerandomization Phase SD

The 4-component z-scores were averaged to form the primary outcome, a composite measure with better overall precision and sensitivity than the individual components for assessing intervention effects on the multiple targeted communication goals.

We assessed patient-physician relationships using The Human Connection (THC) scale,48 the Health Care Climate Questionnaire (HCCQ),49 and the Perceived Efficacy in Patient-Physician Interactions (PEPPI) scale50 shortly after the audio recorded visit. Physicians and patients were also asked to estimate 2-year survival and curability of the patient’s cancer on a 7-point scale (100%, about 90%, about 75%, about 50/50, about 25%, about 10%, 0%, don’t know); discordance was defined as 2 or more categories of difference.

We administered QOL questionnaires at 3-month intervals from study entry for up to 3 years and prespecified a composite QOL score to be the average of 5 z-scored subscales: McGill QOL scale single item, McGill Psychological Well-Being subscale, McGill Existential Well-Being subscale, FACT-G Physical Functioning subscale, and FACT-G Social Functioning subscale51,52; all are widely used in research in advanced cancer. Fewer than 3% of follow-up questionnaires were missing.

Trained nurses and physicians abstracted utilization data from medical records at relevant hospitals, offices, and hospice organizations. Based on a review of the literature,9,53-55 we prespecified a composite utilization score of 3 indicators of aggressive treatment in the last 30 days of life (chemotherapy, potentially burdensome interventions, emergency department [ED]/hospital admission) and hospice utilization (eTable 3 in Supplement 3).

Randomization and Blinding

We randomized by physician and stratified by site (New York or California) and oncologist subspecialty (≥50% vs <50% of patients with breast cancer) to balance sex and other unmeasured patient characteristics that might be associated with the communication outcomes. Within strata, we randomly assigned physicians at a 1:1 ratio to intervention or control. We recruited, obtained consent, and enrolled patients based on the arm to which their physician was assigned. We oversampled patients with caregivers to achieve recruitment goals for a companion study of caregiver bereavement. Only the study statisticians were aware of the random number sequences and treatment assignment, preserving blinding among transcriptionists, coders, and abstractors.

Sample Size

To affect utilization and patient outcomes meaningfully, we felt a moderately large effect on communication would be needed. To account for attrition and variance inflation arising from cluster randomization, we used standard formula as well as simulation studies using SAS statistical software to determine that a target sample size of 38 physicians and 265 patients would yield the effective sample needed to provide at least 80% power (2-sided testing, α = .05) to detect standardized effects of 0.50 for the primary communication outcome.36

Statistical Analysis

Between-group comparisons on communication and utilization outcomes were conducted using Wald-type tests from prespecified mixed-effects linear regression models (for continuous outcomes) and generalized estimating equations for binary outcomes, specified to account for the nesting of patients (the units of analysis) within physicians (the units of randomization). For all regression analyses, covariates for study site and breast cancer subspecialty were included to account for the stratified randomization, as well as patient-level covariates to adjust for demographic and cancer characteristics. Between-group comparisons of QOL trajectories were performed using the terminal decline model (TDM) of Li et al56 that accounts for mortality by jointly modeling QOL and survival using piecewise linear regression and exponential hazards regression models, respectively. The TDM parameterizes time counting backward from patient time of death and is specified with 2 periods for each component, the “terminal decline” period nearest death and the more remote period before then; our model extends on Li et al56 to permit the inclusion of study covariates. We chose 9 months and 12 months as the duration of the terminal decline period for QOL and mortality, respectively, based on the observed change point in the data.

For the analysis of communication outcomes, we used the prerandomization data to adjust for between-physician differences among the 38 physician clusters. Hence, the data sets for these mixed models analyses included observations from prerandomization and postrandomization audio recordings, and the models included fixed-effects terms for phase (prerandomization vs postrandomization), study arm, and the interaction of phase and arm. Intervention effects were estimated as the between-arm difference in adjusted mean difference from prerandomization to postrandomization samples. For the other continuous outcomes, only postrandomization data were included, and intervention effects were estimated as adjusted mean differences. In model validation and exploratory analysis, heterogeneity of treatment effects was assessed by adding interaction terms to regression models to compare intervention effects across prespecified subgroups. Residual plots were also used for model validation.

Statistical analyses (Supplement 2) were conducted in version 9.4 of the SAS System.

Results
Study Participants

Of 52 physicians contacted, 43 enrolled and 38 participated in the cluster RCT (eFigure 1 in Supplement 3). Of the 265 participating patients, 194 (73.0%) had an enrolled caregiver. Patient characteristics across study arms were well matched (eTable 1 in Supplement 3); mean age was 64.4 years, 55.0% were female, 11.5% were nonwhite, 28.0% had high school education or less, and 19.0% reported income of $20 000 or less. The mean follow-up for patients was 15 months; by study closing (October 1, 2015), 151 patients had died, 18 had withdrawn, and 1 was lost to follow-up (eFigure 1 in Supplement 3). We abstracted all decedents’ medical records.

Primary Outcome

In fully adjusted models, the composite communication score showed a significant intervention effect (estimated adjusted intervention effect, 0.34; 95% CI, 0.06-0.62; P = .02) (Table 2; eTable 4 in Supplement 3). The sample standard deviation of the composite from the prerandomization cohort was 0.53, hence the estimated intervention effect of 0.34 corresponds to a standardized effect of 0.64, corresponding to 5.7 additional “engaging” statements (a 44% increase), 0.6 additional responses to emotion (a 71% increase), and 1.4 additional statements regarding prognosis and treatment choices (a 38% increase).

Secondary Outcomes

Of the individual communication component measures, only the engaging measure (APPC) was statistically significant. There were no statistically significant effects of the intervention on the PEPPI, THC, or HCCQ scales, or on 2-year survival and curability estimates; 2-year survival discordance was 59% in the intervention group vs 62% for control; corresponding figures for curability discordance were 39% and 44%. Quality of life was stable until 6 to 9 months prior to death, with a terminal decline (eFigure 2 in Supplement 3); overall, QOL differences between intervention and control were not statistically significant. We observed no intervention effects on health care utilization.

Exploratory Outcomes

None of the prespecified candidate effect modifiers were associated with heterogeneity in treatment effects on communication outcomes. Median survival was 16 months: 19 months in the intervention group and 14 months in the control (hazard ratio, 0.84; 95% CI, 0.61-1.15) (eFigure 3 in Supplement 3).

Discussion

In this study, a brief combined intervention targeting physicians, patients with advanced cancer, and their caregivers (when available) promoted patient-centered communication in the near term, with clinically meaningful increases in engaging patients in discussions, responding to emotions and discussions of prognosis and treatment choices. These communication domains are linked; provision of information or emotional support, for example, may depend on a patient cue or request as well as a clinician’s willingness and capacity to respond. Of the 4 communication domains, the most fundamental, engaging patients as active partners in care—being assertive, asking questions, requesting clarification, expressing opinions and preferences to a greater degree than control patients—was independently significant in secondary analyses. Our approach was individualized and tailored to participants’ educational needs; it was theory-based, highly rated by patients, caregivers, and oncologists, and focused on important domains of patient-centered communication but whose incorporation into practice remains elusive.1,9-11 While prior reports suggest that activated patients and those receiving bad news may rate their physicians more harshly,8,57 we did not observe these effects, perhaps because our intervention focused on aligning patient, caregiver, and physician expectations.

Despite calls for improved patient-centered communication between oncologists and their patients and evidence that linking end-of-life discussions with more realistic prognosis estimates, better QOL and reduced utilization of aggressive treatments,8-12 there has been little headway over the past 20 years. Many patients hold unrealistically optimistic prognostic estimates,8,11,21,58,59 which they mistakenly believe their physicians share60; future studies can unravel how to interrupt the temporarily adaptive but ultimately dysfunctional pas de deux, in which physicians, caregivers, and patients avoid, euphemize, or misinterpret these discussions.61-64 Oncologists need better training in the provision of information to patients with varying levels of health numeracy and literacy as well as “terror management,” a defense mechanism that may prompt some patients (and physicians) to respond to fear of death through avoidance and selective attention.65-67 Venues already exist for communication and awareness training during residency and fellowship,25,68,69 and interventions such as ours are feasible for practicing oncologists.

Consistent with prior data,70,71 QOL is remarkably stable during the course of cancer, until the terminal decline. It is possible that the timing of the intervention may have not have been optimized to affect QOL trajectories. Future patient and caregiver interventions might be targeted to key junctures in the clinical course, such disease progression, symptoms, or early declines in QOL. Because patient-centered timing of interventions poses logistic and methodological difficulties, training existing office personnel to coach patients might better adapt to patient needs. While outpatient palliative care consultations may improve QOL, widespread implementation for all patients with advanced cancer is unrealistic; oncologists still need to communicate disease-related information clearly, respond to emotions, help patients make choices, and facilitate referrals when indicated.72

We observed no intervention effects on utilization. The 2 study sites have moderate to high use of palliative care and low to moderate use of aggressive interventions,73 possibly limiting room for improvement. As expected, utilization outcomes clustered by physician, suggesting that addressing underlying physician attributes74and institutional norms75-77 might also be needed to address utilization of aggressive interventions and hospice.

In addition to the study limitations addressed herein, the choice of only 2 study sites may limit generalizability, and the use of more than 1 audio recorded office visit and different measures of patient-centered communication57 may have revealed patterns that were not observed here. Median survival in this study was 16 months, longer than anticipated, during which time the intervention effects may have waned. Lengthier physician interventions may have reinforced skills more effectively, but at a price: longer training could limit participation to only the most motivated physicians. Similarly, longer or more intensive patient interventions might not be feasible for patients who are symptomatic or close to death.

Conclusions

Although clinician-patient communication patterns are difficult to change,78 an intentionally brief communication intervention was effective in improving patient-centered communication in advanced cancer but requires refinement in focus, delivery, support, or timing to promote shared understanding, QOL, and appropriate use of health care at the end of life. The current productivity-oriented practice environment also presents barriers to effective communication. Changes are needed in medical education and health systems to provide communication skills training for physicians, meaningful support for them to participate, and trained personnel to coach patients so that their voices can be heard.

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Article Information

Corresponding Author: Ronald M. Epstein, MD, Center for Communication and Disparities Research, Department of Family Medicine, University of Rochester Medical Center, 1381 South Ave, Rochester, NY 14620 (ronald_epstein@urmc.rochester.edu).

Published Online: September 9, 2016. doi:10.1001/jamaoncol.2016.4373

Author Contributions: Dr Epstein had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Epstein, Duberstein, Fiscella, Hoerger, Tancredi, Gramling, Franks, Kaesberg, Back, Butow, Walczak, Tattersall, Venuti, Hoh, Kravitz.

Acquisition, analysis, or interpretation of data: Epstein, Duberstein, Fenton, Fiscella, Hoerger, Tancredi, Xing, Gramling, Mohile, Franks, Kaesberg, Plumb, Cipri, Street, Shields, Butow, Sullivan, Robinson, Lewis, Kravitz.

Drafting of the manuscript: Epstein, Duberstein, Xing, Sullivan, Robinson.

Critical revision of the manuscript for important intellectual content: Epstein, Duberstein, Fenton, Fiscella, Hoerger, Tancredi, Gramling, Mohile, Franks, Kaesberg, Plumb, Cipri, Street, Shields, Back, Butow, Walczak, Tattersall, Venuti, Hoh, Lewis, Kravitz.

Statistical analysis: Epstein, Duberstein, Hoerger, Tancredi, Xing, Gramling, Franks.

Obtained funding: Epstein, Duberstein, Fiscella, Hoerger, Kravitz.

Administrative, technical, or material support: Epstein, Duberstein, Hoerger, Kaesberg, Plumb, Cipri, Street, Back, Tattersall, Venuti, Robinson, Hoh, Lewis, Kravitz.

Study supervision: Epstein, Duberstein, Fenton, Hoerger, Mohile, Plumb, Cipri, Butow, Sullivan, Kravitz.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported by a grant from the National Cancer Institute (R01 CA140419-05; co–principal investigators: Drs Epstein Kravitz). Dr Duberstein is supported by a grant from the National Cancer Institute (R01CA168387). Dr Hoerger is supported by grants from the National Institutes of Health (T32MH018911, U54GM104940).

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank Gary Morrow, PhD (University of Rochester [UR]), Timothy Quill, MD (UR), and Ted Wun, MD (University of California, Davis [UCD]), for their input on study design; Amy Abernethy, MD (Duke University), for her help with developing the intervention video; Rimaben P. Cabrera, MSW (UCD), Gisela Escalera, MSW (UCD), Iwona Grzela-Juskiewicz, MD (UR), and Martha Tuttle, BA (UR), for recruiting, administering surveys to and following the study patients and their caregivers; Andrew Cyrus Marcy, RN (UR), for medical record abstraction; Don Gaudion, MBA (UR), and Blair Leatherwood, MFA (UCD), for their role in physician training sessions; Charles Kamen, PhD (UR), Rachel Rodenbach, MD (UR), and Josef Bartels, MD (UR), for intervention fidelity assessments; Emma Perry, BA (Texas A&M), and Lindsay N. Fuzzell, MA (Purdue), for supervising the coding of audio recordings and transcripts; Patrick Davis, BS (UR), and Emma Pollock (UR) for coding transcripts and data management; Joseph Duckett (UR) for programing and database management; and Jennifer H. Kim, BA, Morgan McDonald, Jacob Paulson, BS, Syed M. Sajjad, BS, and Juliet Wu, BS (all at UR), for data entry and management. All received payment for their work on the study with the exception of Drs Morrow, Kamen, and Wun. In addition, we thank Mary Lou Pollock (UR) and Carolyn Coleman, BS (UCD), who provided financial and administrative oversight, and Donna Geil, AAS (UR), and Mahala Ruppel, BS (UR), for administrative support. Many thanks to the oncologists, their staff, the patients, and their caregivers who participated in this study.

Previous Presentations: This study was presented at the ASCO Palliative Care in Oncology Symposium; September 9, 2016; San Francisco, California.

References
1.
Epstein  RM, Street  RL  Jr.  Patient-Centered Communication in Cancer Care: Promoting Healing and Reducing Suffering. Bethesda, MD: National Cancer Institute, NIH; 2007.
2.
Institute of Medicine.  Assessing and Improving Value in Cancer Care: Workshop Summary. Washington, DC: The National Academies Press; 2009.
3.
National Priorities Partnership. National Priorities and Goals: Aligning Our Efforts to Transform America's Healthcare. Washington, DC: National Quality Forum; 2008.
4.
Institute of Medicine.  Approaching Death: Improving Care at the End of Life. Washington, DC: The National Academies Press; 1997.
5.
DesHarnais  S, Carter  RE, Hennessy  W, Kurent  JE, Carter  C.  Lack of concordance between physician and patient: reports on end-of-life care discussions.  J Palliat Med. 2007;10(3):728-740.PubMedGoogle ScholarCrossref
6.
Parker  SM, Clayton  JM, Hancock  K,  et al.  A systematic review of prognostic/end-of-life communication with adults in the advanced stages of a life-limiting illness: patient/caregiver preferences for the content, style, and timing of information.  J Pain Symptom Manage. 2007;34(1):81-93.PubMedGoogle ScholarCrossref
7.
Institute of Medicine Committee on Approaching Death.  Dying in America: Improving Quality and Honoring Individual Preferences Near the End of Life. Key findings and recommendations. Washington, DC: National Academies Press; 2014.
8.
Weeks  JC, Catalano  PJ, Cronin  A,  et al.  Patients’ expectations about effects of chemotherapy for advanced cancer.  N Engl J Med. 2012;367(17):1616-1625.PubMedGoogle ScholarCrossref
9.
Prigerson  HG, Bao  Y, Shah  MA,  et al.  Chemotherapy use, performance status, and quality of life at the end of life.  JAMA Oncol. 2015;1(6):778-784.PubMedGoogle ScholarCrossref
10.
Wright  AA, Zhang  B, Ray  A,  et al.  Associations between end-of-life discussions, patient mental health, medical care near death, and caregiver bereavement adjustment.  JAMA. 2008;300(14):1665-1673.PubMedGoogle ScholarCrossref
11.
Weeks  JC, Cook  EF, O’Day  SJ,  et al.  Relationship between cancer patients’ predictions of prognosis and their treatment preferences.  JAMA. 1998;279(21):1709-1714.PubMedGoogle ScholarCrossref
12.
Mack  JW, Weeks  JC, Wright  AA, Block  SD, Prigerson  HG.  End-of-life discussions, goal attainment, and distress at the end of life: predictors and outcomes of receipt of care consistent with preferences.  J Clin Oncol. 2010;28(7):1203-1208.PubMedGoogle ScholarCrossref
13.
Mack  JW, Cronin  A, Taback  N,  et al.  End-of-life care discussions among patients with advanced cancer: a cohort study.  Ann Intern Med. 2012;156(3):204-210.PubMedGoogle ScholarCrossref
14.
Hagerty  RG, Butow  PN, Ellis  PM, Dimitry  S, Tattersall  MH.  Communicating prognosis in cancer care: a systematic review of the literature.  Ann Oncol. 2005;16(7):1005-1053.PubMedGoogle ScholarCrossref
15.
Hagerty  RG, Butow  PN, Ellis  PM,  et al.  Communicating with realism and hope: incurable cancer patients’ views on the disclosure of prognosis.  J Clin Oncol. 2005;23(6):1278-1288.PubMedGoogle ScholarCrossref
16.
Frosch  DL, May  SG, Rendle  KA, Tietbohl  C, Elwyn  G.  Authoritarian physicians and patients’ fear of being labeled “difficult” among key obstacles to shared decision making.  Health Aff (Millwood). 2012;31(5):1030-1038.PubMedGoogle ScholarCrossref
17.
Brandes  K, Butow  PN, Tattersall  MH,  et al.  Advanced cancer patients’ and caregivers’ use of a question prompt list.  Patient Educ Couns. 2014;97(1):30-37.PubMedGoogle ScholarCrossref
18.
Walczak  A, Henselmans  I, Tattersall  MH,  et al.  A qualitative analysis of responses to a question prompt list and prognosis and end-of-life care discussion prompts delivered in a communication support program.  Psychooncology. 2015;24(3):287-293.PubMedGoogle ScholarCrossref
19.
Detmar  SB, Aaronson  NK, Wever  LD, Muller  M, Schornagel  JH.  How are you feeling? who wants to know? patients’ and oncologists’ preferences for discussing health-related quality-of-life issues.  J Clin Oncol. 2000;18(18):3295-3301.PubMedGoogle Scholar
20.
Clayton  JM, Butow  PN, Tattersall  MH.  The needs of terminally ill cancer patients versus those of caregivers for information regarding prognosis and end-of-life issues.  Cancer. 2005;103(9):1957-1964.PubMedGoogle ScholarCrossref
21.
Liu  PH, Landrum  MB, Weeks  JC,  et al.  Physicians’ propensity to discuss prognosis is associated with patients’ awareness of prognosis for metastatic cancers.  J Palliat Med. 2014;17(6):673-682.PubMedGoogle ScholarCrossref
22.
Mack  JW, Smith  TJ.  Reasons why physicians do not have discussions about poor prognosis, why it matters, and what can be improved.  J Clin Oncol. 2012;30(22):2715-2717.PubMedGoogle ScholarCrossref
23.
Lamont  EB, Christakis  NA.  Prognostic disclosure to patients with cancer near the end of life.  Ann Intern Med. 2001;134(12):1096-1105.PubMedGoogle ScholarCrossref
24.
Walczak  A, Mazer  B, Butow  PN,  et al.  A question prompt list for patients with advanced cancer in the final year of life: development and cross-cultural evaluation.  Palliat Med. 2013;27(8):779-788.PubMedGoogle ScholarCrossref
25.
Back  AL, Arnold  RM, Baile  WF,  et al.  Efficacy of communication skills training for giving bad news and discussing transitions to palliative care.  Arch Intern Med. 2007;167(5):453-460.PubMedGoogle ScholarCrossref
26.
Curtis  JR, Back  AL, Ford  DW,  et al.  Effect of communication skills training for residents and nurse practitioners on quality of communication with patients with serious illness: a randomized trial.  JAMA. 2013;310(21):2271-2281.PubMedGoogle ScholarCrossref
27.
Tulsky  JA, Arnold  RM, Alexander  SC,  et al.  Enhancing communication between oncologists and patients with a computer-based training program: a randomized trial.  Ann Intern Med. 2011;155(9):593-601.PubMedGoogle ScholarCrossref
28.
Street  RL  Jr, Slee  C, Kalauokalani  DK, Dean  DE, Tancredi  DJ, Kravitz  RL.  Improving physician-patient communication about cancer pain with a tailored education-coaching intervention.  Patient Educ Couns. 2010;80(1):42-47.PubMedGoogle ScholarCrossref
29.
Clayton  JM, Butow  PN, Tattersall  MH,  et al.  Randomized controlled trial of a prompt list to help advanced cancer patients and their caregivers to ask questions about prognosis and end-of-life care.  J Clin Oncol. 2007;25(6):715-723.PubMedGoogle ScholarCrossref
30.
Street  RL. Communication in Medical Encounters: An Ecological Perspective. In: Thompson  TL, Dorsey  AM, Miller  KI, Parrott  R, eds.  Handbook of Health Communication. London, England: Lawrence Erlbaum Associates; 2003:63-89.
31.
Clayton  JM, Butow  PN, Arnold  RM, Tattersall  MH.  Discussing end-of-life issues with terminally ill cancer patients and their carers: a qualitative study.  Support Care Cancer. 2005;13(8):589-599.PubMedGoogle ScholarCrossref
32.
Steinhauser  KE, Christakis  NA, Clipp  EC, McNeilly  M, McIntyre  L, Tulsky  JA.  Factors considered important at the end of life by patients, family, physicians, and other care providers.  JAMA. 2000;284(19):2476-2482.PubMedGoogle ScholarCrossref
33.
Street  RL  Jr, Makoul  G, Arora  NK, Epstein  RM.  How does communication heal? pathways linking clinician-patient communication to health outcomes.  Patient Educ Couns. 2009;74(3):295-301.PubMedGoogle ScholarCrossref
34.
Dimoska  A, Tattersall  MH, Butow  PN, Shepherd  H, Kinnersley  P.  Can a “prompt list” empower cancer patients to ask relevant questions?  Cancer. 2008;113(2):225-237.PubMedGoogle ScholarCrossref
35.
Clayton  JM, Hancock  KM, Butow  PN,  et al.  Clinical practice guidelines for communicating prognosis and end-of-life issues with adults in the advanced stages of a life-limiting illness, and their caregivers.  Med J Aust. 2007;186(12 suppl):S77, S79, S83-108.PubMedGoogle Scholar
36.
Hoerger  M, Epstein  RM, Winters  PC,  et al.  Values and options in cancer care (VOICE): study design and rationale for a patient-centered communication and decision-making intervention for physicians, patients with advanced cancer, and their caregivers.  BMC Cancer. 2013;13(1):188.PubMedGoogle ScholarCrossref
37.
Carroll  T, Epstein  RM, Gramling  R. What are strategies for estimating survival prognosis in advanced cancer? In: Goldstein  N, Morrison  S, eds.  Evidence-based Practice of Palliative Medicine. Cambridge, MA: Elsevier Press; 2012.
38.
Moss  AH, Lunney  JR, Culp  S,  et al.  Prognostic significance of the “surprise” question in cancer patients.  J Palliat Med. 2010;13(7):837-840.PubMedGoogle ScholarCrossref
39.
Street  RL  Jr, Gordon  H, Haidet  P.  Physicians’ communication and perceptions of patients: is it how they look, how they talk, or is it just the doctor?  Soc Sci Med. 2007;65(3):586-598.PubMedGoogle ScholarCrossref
40.
Street  RL  Jr, Krupat  E, Bell  RA, Kravitz  RL, Haidet  P.  Beliefs about control in the physician-patient relationship: effect on communication in medical encounters.  J Gen Intern Med. 2003;18(8):609-616.PubMedGoogle ScholarCrossref
41.
Del Piccolo  L, de Haes  H, Heaven  C,  et al.  Development of the Verona coding definitions of emotional sequences to code health providers’ responses (VR-CoDES-P) to patient cues and concerns.  Patient Educ Couns. 2011;82(2):149-155.PubMedGoogle ScholarCrossref
42.
Zimmermann  C, Del Piccolo  L, Bensing  J,  et al.  Coding patient emotional cues and concerns in medical consultations: the Verona coding definitions of emotional sequences (VR-CoDES).  Patient Educ Couns. 2011;82(2):141-148.PubMedGoogle ScholarCrossref
43.
Back  AL, Arnold  RM, Baile  WF, Tulsky  JA, Fryer-Edwards  K.  Approaching difficult communication tasks in oncology.  CA Cancer J Clin. 2005;55(3):164-177.PubMedGoogle ScholarCrossref
44.
Shields  CG, Coker  CJ, Poulsen  SS,  et al.  Patient-centered communication and prognosis discussions with cancer patients.  Patient Educ Couns. 2009;77(3):437-442.PubMedGoogle ScholarCrossref
45.
Back  AL, Arnold  RM, Quill  TE.  Hope for the best, and prepare for the worst.  Ann Intern Med. 2003;138(5):439-443.PubMedGoogle ScholarCrossref
46.
Kiely  BE, Soon  YY, Tattersall  MH, Stockler  MR.  How long have I got? estimating typical, best-case, and worst-case scenarios for patients starting first-line chemotherapy for metastatic breast cancer: a systematic review of recent randomized trials.  J Clin Oncol. 2011;29(4):456-463.PubMedGoogle ScholarCrossref
47.
Epstein  RM, Street  RL.  A Framework for Patient-Centered Communication in Cancer Care. Patient-Centered Communication in Cancer Care. Bethesda, MD: National Cancer Institute, NIH; 2007:17-38.
48.
Mack  JW, Block  SD, Nilsson  M,  et al.  Measuring therapeutic alliance between oncologists and patients with advanced cancer: the Human Connection Scale.  Cancer. 2009;115(14):3302-3311.PubMedGoogle ScholarCrossref
49.
Williams  GC, Rodin  GC, Ryan  RM, Grolnick  WS, Deci  EL.  Autonomous regulation and long-term medication adherence in adult outpatients.  Health Psychol. 1998;17(3):269-276.PubMedGoogle ScholarCrossref
50.
Maly  RC, Frank  JC, Marshall  GN, DiMatteo  MR, Reuben  DB.  Perceived efficacy in patient-physician interactions (PEPPI): validation of an instrument in older persons.  J Am Geriatr Soc. 1998;46(7):889-894.PubMedGoogle ScholarCrossref
51.
Cohen  SR, Mount  BM, Strobel  MG, Bui  F.  The McGill Quality of Life Questionnaire: a measure of quality of life appropriate for people with advanced disease: a preliminary study of validity and acceptability.  Palliat Med. 1995;9(3):207-219.PubMedGoogle ScholarCrossref
52.
Cella  DF, Tulsky  DS, Gray  G,  et al.  The Functional Assessment of Cancer Therapy scale: development and validation of the general measure.  J Clin Oncol. 1993;11(3):570-579.PubMedGoogle Scholar
53.
Wright  AA, Zhang  B, Keating  NL, Weeks  JC, Prigerson  HG.  Associations between palliative chemotherapy and adult cancer patients’ end of life care and place of death: prospective cohort study.  BMJ. 2014;348:g1219.PubMedGoogle ScholarCrossref
54.
Earle  CC, Park  ER, Lai  B, Weeks  JC, Ayanian  JZ, Block  S.  Identifying potential indicators of the quality of end-of-life cancer care from administrative data.  J Clin Oncol. 2003;21(6):1133-1138.PubMedGoogle ScholarCrossref
55.
Barnato  AE, Farrell  MH, Chang  C-CH, Lave  JR, Roberts  MS, Angus  DC.  Development and validation of hospital “end-of-life” treatment intensity measures.  Med Care. 2009;47(10):1098-1105.PubMedGoogle ScholarCrossref
56.
Li  Z, Tosteson  TD, Bakitas  MA.  Joint modeling quality of life and survival using a terminal decline model in palliative care studies.  Stat Med. 2013;32(8):1394-1406.PubMedGoogle ScholarCrossref
57.
Bakitas  MA, Tosteson  TD, Li  Z,  et al.  Early versus delayed initiation of concurrent palliative oncology care: patient outcomes in the ENABLE III randomized controlled trial.  J Clin Oncol. 2015;33(13):1438-1445.PubMedGoogle ScholarCrossref
58.
Epstein  RM, Franks  P, Fiscella  K,  et al.  Measuring patient-centered communication in patient-physician consultations: theoretical and practical issues.  Soc Sci Med. 2005;61(7):1516-1528.PubMedGoogle ScholarCrossref
59.
Temel  JS, Greer  JA, Admane  S,  et al.  Longitudinal perceptions of prognosis and goals of therapy in patients with metastatic non-small-cell lung cancer: results of a randomized study of early palliative care.  J Clin Oncol. 2011;29(17):2319-2326.PubMedGoogle ScholarCrossref
60.
Enzinger  AC, Zhang  B, Schrag  D, Prigerson  HG.  Outcomes of prognostic disclosure: Associations with prognostic understanding, distress, and relationship with physician among patients with advanced cancer.  J Clin Oncol. 2015;33(32):3809-3816.PubMedGoogle ScholarCrossref
61.
Gramling  RF, Fiscella  K, Xing  G,  et al.  Differences of opinion or inadequate communication? determinants of patient-oncologist prognostic discordance in advanced cancer  [published online July 14, 2016].  JAMA Oncol. doi:10.1001/jamaoncol.2016.1861Google Scholar
62.
Miller  SM.  Monitoring versus blunting styles of coping with cancer influence the information patients want and need about their disease. Implications for cancer screening and management.  Cancer. 1995;76(2):167-177.PubMedGoogle ScholarCrossref
63.
The  AM, Hak  T, Koëter  G, van der Wal  G.  Collusion in doctor-patient communication about imminent death: an ethnographic study.  West J Med. 2001;174(4):247-253.PubMedGoogle ScholarCrossref
64.
de Haes  H, Koedoot  N.  Patient centered decision making in palliative cancer treatment: a world of paradoxes.  Patient Educ Couns. 2003;50(1):43-49.PubMedGoogle ScholarCrossref
65.
Penson  RT, Partridge  RA, Shah  MA, Giansiracusa  D, Chabner  BA, Lynch  TJ  Jr.  Fear of death.  Oncologist. 2005;10(2):160-169.PubMedGoogle ScholarCrossref
66.
Niemiec  CP, Brown  KW, Kashdan  TB,  et al.  Being present in the face of existential threat: the role of trait mindfulness in reducing defensive responses to mortality salience.  J Pers Soc Psychol. 2010;99(2):344-365.PubMedGoogle ScholarCrossref
67.
Burke  BL, Martens  A, Faucher  EH.  Two decades of terror management theory: a meta-analysis of mortality salience research.  Pers Soc Psychol Rev. 2010;14(2):155-195.PubMedGoogle ScholarCrossref
68.
Rodenbach  RA, Rodenbach  KE, Tejani  MA, Epstein  RM.  Relationships between personal attitudes about death and communication with terminally ill patients: how oncology clinicians grapple with mortality.  Patient Educ Couns. 2016;99(3):356-363.PubMedGoogle ScholarCrossref
69.
Shayne  M, Quill  TE.  Oncologists responding to grief.  Arch Intern Med. 2012;172(12):966-967.PubMedGoogle ScholarCrossref
70.
Back  AL, Arnold  RM, Baile  WF,  et al.  Faculty development to change the paradigm of communication skills teaching in oncology.  J Clin Oncol. 2009;27(7):1137-1141.PubMedGoogle ScholarCrossref
71.
Zimmermann  C, Swami  N, Krzyzanowska  M,  et al.  Early palliative care for patients with advanced cancer: a cluster-randomised controlled trial.  Lancet. 2014;383(9930):1721-1730.PubMedGoogle ScholarCrossref
72.
Quill  TE, Abernethy  AP.  Generalist plus specialist palliative care—creating a more sustainable model.  N Engl J Med. 2013;368(13):1173-1175.PubMedGoogle ScholarCrossref
73.
Mitchell  JJ  Jr.  The findings of the Dartmouth Atlas Project: a challenge to clinical and ethical excellence in end-of-life care.  J Clin Ethics. 2011;22(3):267-276.PubMedGoogle Scholar
74.
Cutler  D, Skinner  J, Stern  AD, Wennberg  D. Physician beliefs and patient preferences: a new look at regional variation in health care spending. Working Paper 19320. Cambridge, MA: National Bureau of Economic Research. August 2013. http://www.nber.org/papers/w19320. Accessed August 24, 2016.
75.
Barnato  AE, Cohen  ED, Mistovich  KA, Chang  C-CH.  Hospital end-of-life treatment intensity among cancer and non-cancer cohorts.  J Pain Symptom Manage. 2015;49(3):521-529; e525.Google Scholar
76.
Barnato  AE, Mohan  D, Lane  RK,  et al.  Advance care planning norms may contribute to hospital variation in end-of-life ICU use: a simulation study.  Med Decis Making. 2014;34(4):473-484.PubMedGoogle ScholarCrossref
77.
Barnato  AE, Herndon  MB, Anthony  DL,  et al.  Are regional variations in end-of-life care intensity explained by patient preferences? a study of the US Medicare population.  Med Care. 2007;45(5):386-393.PubMedGoogle ScholarCrossref
78.
Lewin  SA, Skea  ZC, Entwistle  V, Zwarenstein  M, Dick  J.  Interventions for providers to promote a patient-centred approach in clinical consultations.  Cochrane Database Syst Rev. 2001;(4):CD003267.PubMedGoogle Scholar
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