Physicians’ Attitudes Regarding the Use of Prognostic Models in End-of-life Care (316-B)
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with self-reported declining health over the past year (n ¼ 21,870), identified from 4 MHOS cohorts (1998-2000, 1999-2001, 2000-2002, and 2001-2003). A logistic regression model was derived to predict 6-month mortality, using soci- odemographic characteristics, comorbidities, and health-related quality of life (HRQOL), as- certained by measures of activities of daily living (ADLs) and the Short Form-36 (SF-36); k-fold cross-validation was used to evaluate model per- formance, which was compared to existing prog- nostic tools. Result. The PROMPT incorporated 11 variables including 4 HRQOL domains: general health perceptions, ADLs, social functioning, and en- ergy/fatigue. The model demonstrated good discrimination (c-statistic ¼ .75) and calibra- tion. Overall diagnostic accuracy was superior to existing tools. At cutpoints of 10%-70% esti- mated 6-month mortality risk, sensitivity and specificity ranged from 83.4%-0.8% and 51.1%- 99.9%, respectively, and positive likelihood ratios at all mortality risk cutpoints $ 40% ex- ceeded 5.0. Corresponding positive and nega- tive predictive values were 23.1%-64.1% and 94.5%-85.3%. Over 50% of patients with esti- mated 6-month mortality risk $ 30% died within 12 months. Conclusion. The PROMPT, a new prognostic model based on patient-reported HRQOL, dem- onstrates promising performance in estimating 6-month mortality, and provides an evidence- based means of confirming poor prognosis in community-dwelling elderly patients. Implications for research, policy, or practice. The PROMPT has potential clinical utility in hospice referral decisions. More work is needed to evaluate the PROMPT’s performance in di- verse populations. Physicians’ Attitudes Regarding the Use of Prognostic Models in End-of-life Care (316-B) Paul Han, MD MA MPH, Maine Medical Center Research Institute, Portland, ME. Norbert Hootsmans Maine Medical Center, Portland, ME. Sarah Hallen, MD, Maine Medical Center, Portland, ME. (All authors listed above for this session have dis- closed no relevant financial relationships.) Objectives 1. Recognize physicians’ attitudes regarding the benefits and challenges of using prognostic models in end-or-life care. 2. Recognize the importance of shared decision making in the use of prognostic models in end-of-life care. Background. Prognostic models are increasingly common and potentially useful in clinical prac- tice; however, little is known about physicians’ attitudes regarding the use of these models in end-of-life (EOL) care. Research objectives. To explore physicians’ atti- tudes regarding prognostic models in general and a specific new model, the Patient Reported Outcome Mortality Prediction Tool (PROMPT), which utilizes patient-reported outcome infor- mation to predict 6-month mortality in elderly patients. Method. A qualitative study was conducted using individual in-depth interviews with 17 attending physicians representing 5 different specialties: Cardiology, General Internal Medicine, Geriat- rics, Pulmonary/Critical Care, Nephrology, and Oncology. Semi-structured interviews explored physicians’ attitudes regarding benefits and challenges in the use of prognostic models such as the PROMPT. Interview transcripts were audiorecorded, transcribed, and analyzed using software-assisted coding. Result. Physicians perceived several benefits of prognostic models in EOL care: (a) to resolve prognostic ambiguity due to conflicting infor- mation or opinions, (b) to provide confidence in prognostic assessments and EOL decisions, (c) to trigger advance care planning, and (d) to persuade patients and families about specific treatment decisions. Physicians also identified several challenges to prognostic model use: (a) physician factors (discomfort with death, lack of training in communicating prognostic infor- mation); (b) patient factors (innumeracy, fear of death, preferences against prognostic disclo- sure); and (c) practical factors (patient burden, inadequate physician time and reimbursement). Conclusion. Physicians’ attitudes suggest both benefits and challenges in the use of prognostic models in EOL care, including the need to re- spect patients’ needs and preferences for infor- mation and participation in EOL decision making, and to develop strategies to help physi- cians communicate prognostic information in Vol. 43 No. 2 February 2012 347 Schedule With Abstracts
Transcript of Physicians’ Attitudes Regarding the Use of Prognostic Models in End-of-life Care (316-B)
Vol. 43 No. 2 February 2012 347Schedule With Abstracts
with self-reported declining health over the pastyear (n ¼ 21,870), identified from 4 MHOScohorts (1998-2000, 1999-2001, 2000-2002, and2001-2003). A logistic regression model wasderived to predict 6-month mortality, using soci-odemographic characteristics, comorbidities,and health-related quality of life (HRQOL), as-certained by measures of activities of daily living(ADLs) and the Short Form-36 (SF-36); k-foldcross-validation was used to evaluate model per-formance, which was compared to existing prog-nostic tools.
Result. The PROMPT incorporated 11 variablesincluding 4 HRQOL domains: general healthperceptions, ADLs, social functioning, and en-ergy/fatigue. The model demonstrated gooddiscrimination (c-statistic ¼ .75) and calibra-tion. Overall diagnostic accuracy was superiorto existing tools. At cutpoints of 10%-70% esti-mated 6-month mortality risk, sensitivity andspecificity ranged from 83.4%-0.8% and 51.1%-99.9%, respectively, and positive likelihoodratios at all mortality risk cutpoints $ 40% ex-ceeded 5.0. Corresponding positive and nega-tive predictive values were 23.1%-64.1% and94.5%-85.3%. Over 50% of patients with esti-mated 6-month mortality risk$ 30% died within12 months.
Conclusion. The PROMPT, a new prognosticmodel based on patient-reported HRQOL, dem-onstrates promising performance in estimating6-month mortality, and provides an evidence-based means of confirming poor prognosis incommunity-dwelling elderly patients.
Implications for research, policy, or practice.The PROMPT has potential clinical utility inhospice referral decisions. More work is neededto evaluate the PROMPT’s performance in di-verse populations.
Physicians’ Attitudes Regarding the Useof Prognostic Models in End-of-life Care(316-B)Paul Han, MD MA MPH, Maine Medical CenterResearch Institute, Portland, ME. NorbertHootsmans Maine Medical Center, Portland,ME. Sarah Hallen, MD, Maine Medical Center,Portland, ME.(All authors listed above for this session have dis-closed no relevant financial relationships.)
Objectives1. Recognize physicians’ attitudes regarding the
benefits and challenges of using prognosticmodels in end-or-life care.
2. Recognize the importance of shared decisionmaking in the use of prognostic models inend-of-life care.
Background. Prognostic models are increasinglycommon and potentially useful in clinical prac-tice; however, little is known about physicians’attitudes regarding the use of these models inend-of-life (EOL) care.
Research objectives. To explore physicians’ atti-tudes regarding prognostic models in generaland a specific new model, the Patient ReportedOutcome Mortality Prediction Tool (PROMPT),which utilizes patient-reported outcome infor-mation to predict 6-month mortality in elderlypatients.
Method. A qualitative study was conducted usingindividual in-depth interviews with 17 attendingphysicians representing 5 different specialties:Cardiology, General Internal Medicine, Geriat-rics, Pulmonary/Critical Care, Nephrology, andOncology. Semi-structured interviews exploredphysicians’ attitudes regarding benefits andchallenges in the use of prognostic modelssuch as the PROMPT. Interview transcriptswere audiorecorded, transcribed, and analyzedusing software-assisted coding.
Result. Physicians perceived several benefits ofprognostic models in EOL care: (a) to resolveprognostic ambiguity due to conflicting infor-mation or opinions, (b) to provide confidencein prognostic assessments and EOL decisions,(c) to trigger advance care planning, and (d)to persuade patients and families about specifictreatment decisions. Physicians also identifiedseveral challenges to prognostic model use: (a)physician factors (discomfort with death, lackof training in communicating prognostic infor-mation); (b) patient factors (innumeracy, fearof death, preferences against prognostic disclo-sure); and (c) practical factors (patient burden,inadequate physician time and reimbursement).
Conclusion. Physicians’ attitudes suggest bothbenefits and challenges in the use of prognosticmodels in EOL care, including the need to re-spect patients’ needs and preferences for infor-mation and participation in EOL decisionmaking, and to develop strategies to help physi-cians communicate prognostic information in
348 Vol. 43 No. 2 February 2012Schedule With Abstracts
a patient-centered, understandable, and effi-cient manner.
Implications for research, policy, or practice.Optimal use of prognostic models in EOL carerequires shared decision making between physi-cians and patients. More research is needed todevelop interventions and tools to achieve thisbroader goal.
Forecasting and Foretelling: AssociationBetween Expected Survival Time andCharacteristics of Prognosis Communicationin Palliative Care Consultations (316-C)Robert Gramling, MD DSc, University of Roches-ter, Rochester, NY. Sally Norton, PhD RN FPCN,University of Rochester, Rochester, NY. SusanLadwig, MPH, University of Rochester MedicalCenter, Rochester, NY. Maureen Metzger, RNMS, University of Rochester School of Nursing,Rochester, NY. Jane Deluca, PhD RN, Universityof Rochester, Rochester, NY. Ronald Epstein,MD, University of Rochester, Rochester, NY.Timothy Quill, MD, University of Rochester,Rochester, NY. Stewart Alexander, PhD, DukeUniversity, Durham, NC.(All authors listed above for this session have dis-closed no relevant financial relationships.)
Objectives1. Describe two aspects of what is known
about prognostication in advanced illness:that prognosis communication happensinfrequently and that it is often framedoptimistically.
2. Describe what this study adds to the existingliterature.
3. Describe one strength and one limitation ofthe methods used to measure prognosiscommunication.
Background. Prognostication is an important,yet often neglected, aspect of decision-makingin advanced illness involving both forecasting(forming an estimate about the future) and fore-telling (communicating a forecast).
Research objectives. To describe the relation be-tween forecasting and foretelling in palliativecare consultations with hospitalized patients.
Method. We audio-recorded 75 initial conversa-tions occurring during palliative care consulta-tions with hospitalized adult patients. We codedeach segment (a length of uninterruptedspeech) for the occurrence and linguistic
framing (language cues indicating a pessimisticor optimistic perspective) of prognosis content.We linked conversations to the medical record(including standardized palliative care consulta-tion forms) and a palliative care clinician assess-ment of survival prognosis.
Result. The mean frequency of physician seg-ments containing prognosis information in-creased incrementally with clinical markers ofshorter survival time (lower Palliative Perfor-mance Scores, PPS) [PPS > 60 ¼ 2.4 segments;PPS 40-50 ¼ 4.4 segments; PPS 10-30 ¼ 6.2 seg-ments, p < 0.05] and with physician expecta-tions for shorter survival time [ > 2 weeks ¼4.5 segments; 1 day to 2 weeks ¼ 5.7 segments;< 24 hours ¼ 7.7 segments, p < 0.05]. Thesefindings persisted in multivariate analyses.The majority of segments contained no linguis-tic framing cues, however pessimistic cueswere more common when physicians expectedshorter survival.
Conclusion. Forecasts indicating a shorter sur-vival time are associated with more frequentforetelling in inpatient palliative care consulta-tions. Foretelling generally did not involve opti-mistic/pessimistic linguistic cues; howeverphysicians used more pessimistic cues among pa-tients with shorter expected survival times.
Implications for research, policy, or practice.These findings suggest that palliative care clini-cians adapt prognosis communication behaviorsas death nears. The pattern of communicationsuggests increased efforts to prepare patients/families about "what to expect" and to balanceclinician/patient/family tendencies for overlyoptimistic expectations. More work is neededto understand the degree to which such commu-nication approaches enhance patient/family-centered care, reduce suffering, and aid inbereavement.
Cost Savings Vary By Length of Stay forIn-Patients Receiving Palliative CareConsult Services (317-A)Helene Starks, PhD MPH, University of Washing-ton, Seattle, WA. Song Wang, PhD, University ofWashington, Seattle, WA.(All authors listed above for this session have dis-closed no relevant financial relationships withthe following exception: Wang is employed byAmgen, Inc and receives a salary.)
