Prioritizing Primary Care Patients for a Communication Intervention Using the "Surprise Question": a Prospective Cohort Study

The Surprise Question and clinician-predicted prognosis: systematic review and meta-analysis

BACKGROUND

The Surprise Question, 'Would you be surprised if this person died within the next year?' is a simple tool that can be used by clinicians to identify people within the last year of life. This review aimed to determine the accuracy of this assessment, across different healthcare settings, specialties, follow-up periods and respondents.

METHODS

Searches were conducted of Medline, Embase, AMED, PubMed and the Cochrane Central Register of Controlled Trials, from inception until 01 January 2024. Studies were included if they reported original data on the ability of the Surprise Question to predict survival. For each study (including subgroups), sensitivity, specificity, positive and negative predictive values and accuracy were determined.

RESULTS

Our dataset comprised 56 distinct cohorts, including 68 829 patients. In a pooled analysis, the sensitivity of the Surprise Question was 0.69 ((0.64 to 0.74) I2=97.2%), specificity 0.69 ((0.63 to 0.74) I2=99.7%), positive predictive value 0.40 ((0.35 to 0.45) I2=99.4%), negative predictive value 0.89 ((0.87 to 0.91) I2=99.7%) and accuracy 0.71 ((0.68 to 0.75) I2=99.3%). The prompt performed best in populations with high event rates, shorter timeframes and when posed to more experienced respondents.

CONCLUSIONS

The Surprise Question demonstrated modest accuracy with considerable heterogeneity across the population to which it was applied and to whom it was posed. Prospective studies should test whether the prompt can facilitate timely access to palliative care services, as originally envisioned.

PROSPERO REGISTRATION NUMBER

CRD32022298236.

Looking Beyond Mortality Prediction: Primary Care Physician Views of Patients' Palliative Care Needs Predicted by a Machine Learning Tool

OBJECTIVES

 To assess primary care physicians' (PCPs) perception of the need for serious illness conversations (SIC) or other palliative care interventions in patients flagged by a machine learning tool for high 1-year mortality risk.

METHODS

 We surveyed PCPs from four Brigham and Women's Hospital primary care practice sites. Multiple mortality prediction algorithms were ensembled to assess adult patients of these PCPs who were either enrolled in the hospital's integrated care management program or had one of several chronic conditions. The patients were classified as high or low risk of 1-year mortality. A blinded survey had PCPs evaluate these patients for palliative care needs. We measured PCP and machine learning tool agreement regarding patients' need for an SIC/elevated risk of mortality.

RESULTS

 Of 66 PCPs, 20 (30.3%) participated in the survey. Out of 312 patients evaluated, 60.6% were female, with a mean (standard deviation [SD]) age of 69.3 (17.5) years, and a mean (SD) Charlson Comorbidity Index of 2.80 (2.89). The machine learning tool identified 162 (51.9%) patients as high risk. Excluding deceased or unfamiliar patients, PCPs felt that an SIC was appropriate for 179 patients; the machine learning tool flagged 123 of these patients as high risk (68.7% concordance). For 105 patients whom PCPs deemed SIC unnecessary, the tool classified 83 as low risk (79.1% concordance). There was substantial agreement between PCPs and the tool (Gwet's agreement coefficient of 0.640).

CONCLUSIONS

 A machine learning mortality prediction tool offers promise as a clinical decision aid, helping clinicians pinpoint patients needing palliative care interventions.

Relationship of life expectancy with quality of life and health-related hope among Japanese patients receiving home medical care: The Zaitaku Evaluative Initiatives and Outcome Study

Spiritual care for patients' quality of life (QOL) and hope should be included in home medical care for patients with limited life expectancy. This study aimed to analyze the associations between estimated life expectancy, QOL, and hope among patients receiving home medical care in Japan. This multicenter cross-sectional study involved 29 home medical care facilities in Japan. Patients were categorized by estimated life expectancy, as assessed by home medical care physicians. The outcomes were QOL measured via the Quality-of-Life Scale for Elderly Patients Receiving Professional Home Care (QOL-HC: higher score indicates better QOL), the domain scores of health-related hope ("health," "role and connectedness," and "something to live for"; higher scores indicate higher levels of hope), and life functioning measured using the WHO Disability Assessment Schedule 2.0 (WHODAS 2.0; higher score indicates worse functioning and disability). QOL-HC scores were significantly higher in patients with shorter life expectancy (< 6 m vs. ≥ 1 y, adjusted mean differences: 0.7 points [95%CI 0.1 to 1.3]). Regarding health-related hope, "something to live for" scores were associated with shorter life expectancy (< 6 m vs. ≥ 1 y, -17.7 points [-34.2 to -1.2]), whereas "role and connectedness" scores did not change remarkably with shorter life expectancy (< 6 m vs. ≥ 1 y, -3.3 points [-16.4 to 9.8]). Furthermore, shorter life expectancy was associated with higher WHODAS 2.0 scores (< 6 m vs. ≥ 1 y, 19.6 points [4.3 to 34.8]). Home medical care physicians who engage in spiritual care should facilitate thoughtful dialogue with their patients by recognizing declines in life functions and hope for fulfilment, which are associated with short life expectancy.

Lessons Learned About System-Level Improvement in Serious Illness Communication: A Qualitative Study of Serious Illness Care Program Implementation in Five Health Systems

BACKGROUND

Serious illness communication is a key element of high-quality care, but it is difficult to implement in practice. The Serious Illness Care Program (SICP) is a multifaceted intervention that contributes to more, earlier, and better serious illness conversations and improved patient outcomes. This qualitative study examined the organizational and implementation factors that influenced improvement in real-world contexts.

METHODS

The authors performed semistructured interviews of 30 health professionals at five health systems that adopted SICP as quality improvement initiatives to investigate the organizational and implementation factors that appeared to influence improvement.

RESULTS

After SICP implementation across the organizations studied, approximately 4,661 clinicians have been trained in serious illness communication and 56,712 patients had had an electronic health record (EHR)-documented serious illness conversation. Facilitators included (1) visible support from leaders, who financially invested in an implementation team and champions, expressed the importance of serious illness communication as an institutional priority, and created incentives for training and documenting serious illness conversations; (2) EHR and data infrastructure to foster performance improvement and accountability, including an accessible documentation template, a reporting system, and customized data feedback for clinicians; and (3) communication skills training and sustained support for clinicians to problem-solve communication challenges, reflect on communication experiences, and adapt the intervention. Inhibitors included leadership inaction, competing priorities and incentives, variable clinician acceptance of EHR and data tools, and inadequate support for clinicians after training.

CONCLUSION

Successful implementation appeared to rely on multilevel organizational strategies to prioritize, reward, and reinforce serious illness communication. The insights derived from this research may function as an organizational road map to guide implementation of SICP or related quality initiatives.

Interdisciplinary Approach and Patient/Family Partners to Improve Serious Illness Conversations in Outpatient Oncology

PURPOSE:

We aimed to increase Serious Illness Conversations (SIC) from a baseline of, at or near, zero to 25% of eligible patients by December 31, 2020.

METHODS:

We assembled an interdisciplinary team inclusive of a family partner and used the Model for Improvement as our quality improvement framework. The team developed a SMART Aim, key driver diagram, and SIC workflow. Standardized screening for SIC eligibility was implemented using the 2-year surprise question. Team members were trained in SIC communication skills by a trained facilitator and received ongoing coaching in quality improvement. We performed Plan-Do-Study-Act cycles and used audit-feedback data in weekly team meetings to inform iterative Plan-Do-Study-Act cycles. The primary outcome was the percent of eligible patients with documented SIC.

RESULTS:

Over 18 months, three clinics identified 63 eligible patients; of these, 32 (51%) were diagnosed with head and neck cancer and 31 (49%) with sarcoma. The SIC increased from a baseline near zero to 43 of 63 (70%) patients demonstrating three shifts in the median (95% CI). Conversations were interdisciplinary with 25 (57%) by oncology MD, six (14%) by advanced practice registered nurse, and 13 (30%) by specialty palliative care. We targeted four key drivers: (1) standardized work, (2) engaged interdisciplinary team, (3) engaged patients and families, and (4) system-level support.

CONCLUSION:

Our approach was successful in its documentation of end points and required resource investment (training and time) to embed into team workflows. Future work will evaluate scaling the approach across multiple clinics, the patient experience, and outcomes of care associated with oncology clinician–led SIC.

The utility of the surprise question: A useful tool for identifying patients nearing the last phase of life? A systematic review and meta-analysis

BACKGROUND

The surprise question is widely used to identify patients nearing the last phase of life. Potential differences in accuracy between timeframe, patient subgroups and type of healthcare professionals answering the surprise question have been suggested. Recent studies might give new insights.

AIM

To determine the accuracy of the surprise question in predicting death, differentiating by timeframe, patient subgroup and by type of healthcare professional.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

Electronic databases PubMed, Embase, Cochrane Library, Scopus, Web of Science and CINAHL were searched from inception till 22nd January 2021. Studies were eligible if they used the surprise question prospectively and assessed mortality. Sensitivity, specificity, negative predictive value, positive predictive value and c-statistic were calculated.

RESULTS

Fifty-nine studies met the inclusion criteria, including 88.268 assessments. The meta-analysis resulted in an estimated sensitivity of 71.4% (95% CI [66.3-76.4]) and specificity of 74.0% (95% CI [69.3-78.6]). The negative predictive value varied from 98.0% (95% CI [97.7-98.3]) to 88.6% (95% CI [87.1-90.0]) with a mortality rate of 5% and 25% respectively. The positive predictive value varied from 12.6% (95% CI [11.0-14.2]) with a mortality rate of 5% to 47.8% (95% CI [44.2-51.3]) with a mortality rate of 25%. Seven studies provided detailed information on different healthcare professionals answering the surprise question.

CONCLUSION

We found overall reasonable test characteristics for the surprise question. Additionally, this study showed notable differences in performance within patient subgroups. However, we did not find an indication of notable differences between timeframe and healthcare professionals.

Video Images about Decisions for Ethical Outcomes in Kidney Disease (VIDEO-KD): the study protocol for a multi-centre randomised controlled trial

INTRODUCTION

Older patients with advanced chronic kidney disease (CKD) often are inadequately prepared to make informed decisions about treatments including dialysis and cardiopulmonary resuscitation. Further, evidence shows that patients with advanced CKD do not commonly engage in advance care planning (ACP), may suffer from poor quality of life, and may be exposed to end-of-life care that is not concordant with their goals. We aim to study the effectiveness of a video intervention on ACP, treatment preferences and other patient-reported outcomes.

METHODS AND ANALYSIS

The Video Images about Decisions for Ethical Outcomes in Kidney Disease trial is a multi-centre randomised controlled trial that will test the effectiveness of an intervention that includes a CKD-related video decision aid followed by recording personal video declarations about goals of care and treatment preferences in older adults with advancing CKD. We aim to enrol 600 patients over 5 years at 10 sites.

ETHICS AND DISSEMINATION

Regulatory and ethical aspects of this trial include a single Institutional Review Board mechanism for approval, data use agreements among sites, and a Data Safety and Monitoring Board. We intend to disseminate findings at national meetings and publish our results.

TRIAL REGISTRATION NUMBER

NCT04347629.

Patient Identification for Serious Illness Conversations: A Scoping Review

Serious illness conversations aim to align medical care and treatment with patients’ values, goals, priorities, and preferences. Timely and accurate identification of patients for serious illness conversations is essential; however, existent methods for patient identification in different settings and population groups have not been compared and contrasted. This study aimed to examine the current literature regarding patient identification for serious illness conversations within the context of the Serious Illness Care Program and/or the Serious Illness Conversation Guide. A scoping review was conducted using the Joanna Briggs Institute guidelines. A comprehensive search was undertaken in four databases for literature published between January 2014 and September 2021. In total, 39 articles met the criteria for inclusion. This review found that patients were primarily identified for serious illness conversations using clinical/diagnostic triggers, the ’surprise question’, or a combination of methods. A diverse assortment of clinicians and non-clinical resources were described in the identification process, including physicians, nurses, allied health staff, administrative staff, and automated algorithms. Facilitators and barriers to patient identification are elucidated. Future research should test the efficacy of adapted identification methods and explore how clinicians inform judgements surrounding patient identification.

Implementation and Effectiveness of Integrating Palliative Care Into Ambulatory Care of Noncancer Serious Chronic Illness: Mixed Methods Review and Meta-Analysis

PURPOSE

To perform a mixed methods review to evaluate the effectiveness and implementation of models for integrating palliative care into ambulatory care for US adults with noncancer serious chronic illness.

METHODS

We searched 3 electronic databases from January 2000 to May 2020 and included qualitative, mixed methods studies and randomized and nonrandomized controlled trials. For each study, 2 reviewers abstracted data and independently assessed for quality. We conducted meta-analyses as appropriate and graded strength of evidence (SOE) for quantitative outcomes.

RESULTS

Quantitative analysis included 14 studies of 2,934 patients. Compared to usual care, models evaluated were not more effective for improving patient health-related quality of life (HRQOL) (standardized mean difference [SMD] of 4 of 8 studies, 0.19; 95% CI, ‒0.03 to 0.41) (SOE: moderate) or for patient depressive symptom scores (SMD of 3 of 9 studies, ‒0.09; 95% CI, ‒0.35 to 0.16) (SOE: moderate). Models might have little to no effect on patient satisfaction (SOE: low) but were more effective for increasing advance directive (AD) documentation (relative risk, 1.62; 95% CI, 1.35 to 1.94) (SOE: moderate). Qualitative analysis included 5 studies of 146 patients. Patient preferences for appropriate timing of palliative care varied; costs, additional visits, and travel were considered barriers to implementation.

CONCLUSION

Models might have little to no effect on decreasing overall symptom burden and were not more effective than usual care for improving HRQOL or depressive symptom scores but were more effective for increasing AD documentation. Additional research should focus on identifying and addressing characteristics and implementation factors critical to integrating models to improve ambulatory, patient-centered outcomes.

Primary Care Professionals' Self-Efficacy Surrounding Advance Care Planning and Its Link to Sociodemographics, Background and Perceptions: A Cross-Sectional Study

Primary care (PC) professionals have been considered the most appropriate practitioners for leading Advance care planning (ACP) processes with advanced chronic patients. Aim: To explore how PC doctors’ and nurses’ self-efficacy surrounding ACP is linked to their sociodemographic characteristics, background and perceptions of ACP practices. Methods: A cross-sectional study was performed. Sociodemographics, background and perceptions about ACP in practice were collected using an online survey. The Advance Care Planning Self-Efficacy Spanish (ACP-SEs) scale was used for the self-efficacy measurement. Statistical analysis: Bivariate, multivariate and backward stepwise logistic regression analyses were performed to identify variables independently related to a higher score on the ACP-SEs. Results: N = 465 participants, 70.04% doctors, 81.47% female. The participants had a mean age of 46.45 years and 66.16% had spent >15 years in their current practice. The logistic regression model showed that scoring ≤ 75 on the ACP-SEs was related to a higher score on feeling sufficiently trained, having participated in ACP processes, perceiving that ACP facilitates knowledge of preferences and values, and perceiving that ACP improves patients’ quality of life. Conclusion: Professionals with previous background and those who have a positive perception of ACP are more likely to feel able to carry out ACP processes with patients.

Implementing Serious Illness Communication Processes in Primary Care: A Qualitative Study

PURPOSE

Primary care clinicians face barriers to engaging patients in conversations about prognosis, values, and goals ("serious illness conversations"). We introduced a structured, multi-component intervention, the Serious Illness Care Program (SICP), to facilitate conversations in the primary care setting. We present findings of a qualitative study to explore practical aspects of program implementation.

METHODS

We conducted semi-structured interviews of participating primary care physicians, nurse care coordinators, and social workers and coded transcripts to assess the activities used to integrate SICP into the workflow.

RESULTS

We conducted interviews with 14 of 46 clinicians from 6 primary care clinics, stopping with thematic saturation. Qualitative analysis revealed major themes around activities in the timing of the conversation (before, during, and after) and overarching insights about the program. Clinicians used a variety of strategies to adapt program components while preserving key program goals, including processes to generate accountability to ensure that conversations happen in busy clinical workflows. The interviews revealed changes to clinicians' mindset and norms, such as the recognition of the need to start conversations earlier in the illness course and the use of more expansive models of prognostic communication that address function and quality of life. Data also revealed indicators of sustainable behavior change and the spread of communication practices to patients outside the intended program scope.

CONCLUSION

SICP served as a framework for primary care clinicians to integrate serious illness communication into routine care. The shifts in processes employed by inter-professional clinicians revealed comprehensive models for prognostic communication and creative workflows to ensure that patients with complex illnesses had proactive, longitudinal, and patient-centered serious illness conversations and care planning.

A systematic intervention to improve serious illness communication in primary care: Effect on expenses at the end of life

BACKGROUND

At a population level, conversations between clinicians and seriously ill patients exploring patients' goals and values can drive high-value healthcare, improving patient outcomes and reducing spending.

METHODS

We examined the impact of a quality improvement intervention to drive better communication on total medical expenses in a high-risk care management program. We present our analysis of secondary expense outcomes from a prospective implementation trial of the Serious Illness Care Program, which includes clinician training, coaching, tools, and system interventions. We included patients who died between January 2014 and September 2016 who were selected for serious illness conversations, using the "Surprise Question," as part of implementation of the program in fourteen primary care clinics.

RESULTS

We evaluated 124 patients and observed no differences in total medical expenses between intervention and comparison clinic patients. When comparing patients in intervention clinics who did and did not have conversations, we observed lower average monthly expenses over the last 6 ($6297 vs. $8,876, p = 0.0363) and 3 months ($7263 vs. $11,406, p = 0.0237) of life for patients who had conversations.

CONCLUSIONS

Possible savings observed in this study are similar in magnitude to previous studies in advance care planning and specialty palliative care but occur earlier in the disease course and in the context of documented conversations and a comprehensive, interprofessional case management program.

IMPLICATIONS

Programs designed to drive more, earlier, and better serious illness communication hold the potential to reduce costs.

LEVEL OF EVIDENCE

Prospectively designed trial, non-randomized sample, analysis of secondary outcomes.