Importance Earlier clinician-patient conversations about patients’ values, goals, and preferences in serious illness (ie, serious illness conversations) are associated with better outcomes but occur inconsistently in cancer care.
Objective To evaluate the efficacy of a communication quality-improvement intervention in improving the occurrence, timing, quality, and accessibility of documented serious illness conversations between oncology clinicians and patients with advanced cancer.
Design, Setting, Participants This cluster randomized clinical trial in outpatient oncology was conducted at the Dana-Farber Cancer Institute and included physicians, advanced-practice clinicians, and patients with cancer who were at high risk of death.
Main Outcomes and Measures The primary outcomes (goal-concordant care and peacefulness at the end of life) are published elsewhere. Secondary outcomes are reported herein, including (1) documentation of at least 1 serious illness conversation before death, (2) timing of the initial conversation before death, (3) quality of conversations, and (4) their accessibility in the electronic medical record (EMR).
Results We enrolled 91 clinicians (48 intervention, 43 control) and 278 patients (134 intervention, 144 control). Of enrolled patients, 58% died during the study (n=161); mean age was 62.3 years (95% CI, 58.9-65.6 years); 55% were women (n=88). These patients were cared for by 76 of the 91 enrolled clinicians (37 intervention, 39 control); years in practice, 11.5 (95% CI, 9.2-13.8); 57% female (n=43). Medical record review after patients’ death demonstrated that a significantly higher proportion of intervention patients had a documented discussion compared with controls (96% vs 79%, P = .005) and intervention conversations occurred a median of 2.4 months earlier (median, 143 days vs 71 days, P < .001). Conversation documentation for intervention patients was significantly more comprehensive and patient centered, with a greater focus on values or goals (89% vs 44%, P < .001), prognosis or illness understanding (91% vs 48%, P < .001), and life-sustaining treatment preferences (63% vs 32%, P = .004). Documentation about end-of-life care planning did not differ between arms (80% intervention vs 68% control, P = .08). Significantly more intervention patients had documentation that was accessible in the EMR (61% vs 11%, P < .001).
Conclusions and Relevance This communication quality-improvement intervention resulted in more, earlier, better, and more accessible serious illness conversations documented in the EMR. To our knowledge, this is the first such study to demonstrate improvement in all 4 of these outcomes.
BACKGROUND: Timely documentation of care preferences is an endorsed quality indicator for seriously ill patients admitted to intensive care units. Clinicians document their conversations about these preferences as unstructured free text in clinical notes from electronic health records.
AIM: To apply deep learning algorithms for automated identification of serious illness conversations documented in physician notes during intensive care unit admissions.
DESIGN: Using a retrospective dataset of physician notes, clinicians annotated all text documenting patient care preferences (goals of care or code status limitations), communication with family, and full code status. Clinician-coded text was used to train algorithms to identify documentation and to validate algorithms. The validated algorithms were deployed to assess the percentage of intensive care unit admissions of patients aged >=75 that had care preferences documented within the first 48 h.
SETTING/PARTICIPANTS: Patients admitted to one of five intensive care units.
RESULTS: Algorithm performance was calculated by comparing machine-identified documentation to clinician-coded documentation. For detecting care preference documentation at the note level, the algorithm had F1-score of 0.92 (95% confidence interval, 0.89 to 0.95), sensitivity of 93.5% (95% confidence interval, 90.0% to 98.0%), and specificity of 91.0% (95% confidence interval, 86.4% to 95.3%). Applied to 1350 admissions of patients aged >=75, we found that 64.7% of patient intensive care unit admissions had care preferences documented within the first 48 h.
CONCLUSION: Deep learning algorithms identified patient care preference documentation with sensitivity and specificity approaching that of clinicians and computed in a tiny fraction of time. Future research should determine the generalizability of these methods in multiple healthcare systems.
OBJECTIVE: To develop a set of clinically relevant recommendations to improve the state of advance care planning (ACP) documentation in the electronic health record (EHR).
BACKGROUND: Advance care planning (ACP) is a key process that supports goal-concordant care. For preferences to be honored, clinicians must be able to reliably record, find, and use ACP documentation. However, there are no standards to guide ACP documentation in the electronic health record (EHR).
METHODS: We interviewed 21 key informants to understand the strengths and weaknesses of EHR documentation systems for ACP and identify best practices. We analyzed these interviews using a qualitative content analysis approach and subsequently developed a preliminary set of recommendations. These recommendations were vetted and refined in a second round of input from a national panel of content experts.
RESULTS: Informants identified six themes regarding current inadequacies in documentation and accessibility of ACP information and opportunities for improvement.
DISCUSSION: We offer a set of concise, clinically relevant recommendations, informed by expert opinion, to improve the state of ACP documentation in the EHR.
OBJECTIVE: To develop a set of clinically relevant recommendations to improve the state of advance care planning (ACP) documentation in the electronic health record (EHR).
BACKGROUND: Advance care planning (ACP) is a key process that supports goal-concordant care. For preferences to be honored, clinicians must be able to reliably record, find, and use ACP documentation. However, there are no standards to guide ACP documentation in the electronic health record (EHR).
METHODS: We interviewed 21 key informants to understand the strengths and weaknesses of EHR documentation systems for ACP and identify best practices. We analyzed these interviews using a qualitative content analysis approach and subsequently developed a preliminary set of recommendations. These recommendations were vetted and refined in a second round of input from a national panel of content experts.
RESULTS: Informants identified six themes regarding current inadequacies in documentation and accessibility of ACP information and opportunities for improvement.
DISCUSSION: We offer a set of concise, clinically relevant recommendations, informed by expert opinion, to improve the state of ACP documentation in the EHR.
CONTEXT: Documenting patients' advance care planning wishes is essential to providing value-aligned care, as is having this documentation readily accessible. Little is known about advance care planning documentation practices in the electronic health record.
OBJECTIVES: Describe advance care planning documentation practices and the accessibility of documented discussions in the electronic health record.
METHODS: Participants were primary care patients at the San Francisco VA Medical Center, were =60 years old, and had =2 chronic/serious health conditions. In this cross-sectional study, we assessed the prevalence of advance care planning documentation, including any legal forms/orders and discussions in the prior five years. We also determined accessibility of discussions (i.e., accessible centralized posting vs. inaccessible free-text in progress notes).
RESULTS: The mean age of 414 participants was 71 years (SD ±8), 9% were women, 43% were non-white, and 51% had documented advance care planning including 149 (36%) with forms/orders and 138 (33%) with discussions. Seventy-four participants (50%) with forms/orders lacked accompanying explanatory documentation. Most (55%) discussions were not easily accessible, including 70% of those documenting changes in treatment preferences from prior forms/orders.
CONCLUSION: Half of chronically ill, older participants had documented advance care planning, including one third with documented discussions. However, half of the patients with completed legal forms/orders had no accompanying documented explanatory discussions, and the majority of documented discussions were not easily accessible, even when wishes had changed. Ensuring that patients' preferences are documented and easily accessible is an important patient safety and quality improvement target to ensure patients' wishes are honored.