Abstract
Introduction
Serious illness communication in oncology increases goal concordant care. Factors associated with the frequency of serious illness conversations are not well understood. Given prior evidence of the association between suboptimal decision-making and clinic time, we aimed to investigate the relationship between appointment time and the likelihood of serious illness conversations in oncology.
Methods
We conducted a retrospective study of electronic health record data from 55 367 patient encounters between June 2019 to April 2020, using generalized estimating equations to model the likelihood of a serious illness conversation across clinic time.
Results
Documentation rate decreased from 2.1 to 1.5% in the morning clinic session (8am-12pm) and from 1.2% to .9% in the afternoon clinic session (1pm-4pm). Adjusted odds ratios for Serious illness conversations documentation rates were significantly lower for all hours of each session after the earliest hour (adjusted odds ratios .91 [95% CI, .84-.97], P = .006 for overall linear trend).
Conclusions
Serious illness conversations between oncologists and patients decrease considerably through the clinic day, and proactive strategies to avoid missed conversations should be investigated.
Introduction
Early serious illness communication in oncology increases goal-concordant care, decreases clinician and caregiver moral distress, and increases hospice near the end of life.1,2 Serious illness conversations (SIC) are discussions between clinicians and patients about the progression of an advanced health condition that could adversely strain the patient’s quality of life or their caregivers’. These conversations typically inquire the patient’s knowledge of their illness and prognosis, deliver new prognostic information, and explore next steps of medical care consistent with the patient’s goals and priorities. 1 Organizations including the National Coalition for Hospice and Palliative Care and the National Comprehensive Cancer Network recommend that oncologists initiate serious illness discussions for patients early in the cancer care continuum. 3 In addition, a majority of surveyed patients and caregivers in oncology prefer earlier and more in-depth goals of care conversations. 4 However, serious illness communication generally does not occur until approximately 1 month before death – if at all. 3
Time pressures and decision fatigue during a busy clinic day may be contributing reasons that prevent clinicians from engaging in necessary conversations.5,6 Aspects of care that are not immediately urgent may be omitted when clinicians fall behind in their schedule throughout the day. Furthermore, as the day progresses, physicians experience a progressive inability to continue making difficult decisions after having made many already, referred to as decision fatigue. 6 Decision fatigue is well characterized in primary care settings. For example, studies have reported that time of day is associated with lower rates of flu vaccinations, cancer screening referrals, and statin prescriptions, as well as greater unwarranted antibiotic and opioid orders by primary care physicians.7-11 However, decision fatigue in serious illness communication has not been described.
Given prior evidence of suboptimal clinician decision-making in non-oncology settings in latter parts of a clinic day or session, we investigated the association between appointment time and likelihood of serious illness conversations. Our work expands knowledge on the frequency and nature of serious illness conversations; and informs interventions that promote proactive communication and goal-concordant cancer care delivery.
Methods
This work presents a secondary post-hoc analysis of a randomized clinical trial (NLM, NCT03984773) among 75 clinicians and 17 696 patients with cancer. 12 Results from the trial were previously published. 13 The trial was conducted between July 2019 to April 2020 and investigated the use of machine-generated mortality predictions and behavioral nudges to clinicians to promote serious illness conversations. The trial protocol and overall study was granted approval by The University of Pennsylvania Institutional Review Board with a waiver of written informed consent. We merged billing and institutional electronic health record (EHR) data from Clarity, an EPIC® reporting database, to identify a cohort of medical oncology encounters from 1 of 9 medical oncology clinics (8 disease-specific clinics within a tertiary practice, 1 general oncology clinic) within a large academic healthcare system. We studied return patient encounters with a clinician (medical oncology physician, nurse practitioner, or physician assistant) from June 17, 2019 to April 17, 2020. New patient encounters, encounters with clinicians with <40 total appointments during the study period, and encounters after the first documented SIC within the study period (Supplementary Figure S1).
While SIC conversations were not audio recorded, SIC documentation was used as a surrogate for serious illness communication, as SIC documentation is a quality metric used by many organizations including the American Society for Clinical Oncology’s Quality Oncology Practice Initiative and the Centers for Medicare and Medicaid Services Oncology Care Model; and has been used to define SIC conversations in prior work.2,14 We ascertained the presence of a SIC from either (1) a specific SIC note type in the EHR, or (2) an SIC smart phrase in clinical progress notes. A smart phrase is a pre-built template or shortcut for entering commonly used phrases, sentences, or paragraphs into a patient’s EHR record. Smart phrases are designed to save time and increase efficiency in documenting patient encounters. The ACP smart phrase in the EHR is customized to pull a pre-defined SIC template, created by the Ariadne Labs, into the note. 14
Appointment times between 8am and 4pm were separated by the hour. For example, all appointments between 8am and 8:59am were assigned to 8am. Visits before 8am and after 4pm were grouped with the 8am and 4pm timepoints, respectively. Oncology clinicians (ie medical oncology physician, nurse practitioner, or physician assistant) in eligible clinics practiced in either a morning (8am to 11am) or afternoon (12pm to 4pm) session and could alternate between morning and afternoon sessions on different days. Time was indicated by grouping appointment times in the order they occur in a session (eg 8am and 12pm were grouped as hour 1). Advanced practice providers (APPs), including physician assistants and nurse practitioners, were consistently assigned to oncology physicians, with a ratio of oncologists to APPs ranging from 1:1 to 2:1.
We use the generalized estimating equation approach, clustering by individual clinician, to estimate the probability of SIC documentation. 15 Session hour (1-5) was included as a categorical variable to calculate the relative odds of documentation for each hour of a session after the first and as a continuous variable for assessing overall linear time trend. We adjusted for patient age, race, ethnicity, and gender, insurance, tumor type and stage, Charlson comorbidity count, and appointment month/year. As the study period coincided with a quality improvement effort to prompt conversations among patients at risk of short-term mortality, we additionally adjusted for whether a patient’s clinician received a conversation prompt for a specific encounter. 13 To evaluate potential bias from the morning to afternoon session transition, we performed a sensitivity analysis using a restricted sample that excluded encounters from 12pm. Our final model includes 11 independent variables and is trained on 55367 observations, which exceeds the minimum recommended sample size for an observational multivariable regression analysis of at least 650 (n = 100 + 50i, i = 11). 16 Two-sided Wald tests were used to test all hypotheses with P < .05 indicating statistical significance. Analyses were performed between December 2021 and February 2023 using R, version 4.0.3. The reporting of the study conforms to STROBE guidelines. 17
Results
Descriptive statistics of patient population.
SIC rates by appointment time. Legend: Absolute serious illness communication rates by oncology clinic appointment hour. 8 – 11 represents typical morning session; 12 – 16 represents typical afternoon session.
Adjusted odds of serious illness communication by session hour.
Note: OR = Odds ratio. Hour represents hour within a morning (8-11am) or afternoon (12-4pm) session.
aModels were adjusted for patient age, race, ethnicity, gender, insurance, tumor type and stage, Charlson comorbidity count, appointment month and year, and whether a conversation prompt was given for the encounter.
bModel does not include 12pm.
Multivariable logistic regression for serious illness conversation outcome.
Discussion
Oncology clinicians’ likelihood of having and documenting serious illness conversations decreases as a clinic session progresses. Falling behind schedule and decision fatigue could be contributing reasons for this effect.5-11 Serious illness conversations involve coordinated efforts between the patients, their healthcare team, and their families to discuss disease trajectory and goals of care. These conversations can require significant time commitments and can be hard to prioritize if delays interfere with clinician schedules. Furthermore, SICs in oncology often cover emotionally charged topics, like unfavorable treatment outcomes, and can discourage clinicians from engaging in such hard conversations towards the end of a clinic session as they experience decision fatigue. Ultimately, lower rates of discussions about goals of care later in a session could result in more aggressive treatment regimens and ICU admissions near end-of-life, as well as fewer hospice referrals. 2
This work expands the literature on how time of day affects clinician decision-making; and mechanisms for delayed serious illness conversations in oncology which could reason the paucity of similar discussions in adjacent fields. 18 We acknowledge some methodological limitations that should be considered in the interpretation of our results. While we only examined return visits and adjusted for important metrics of patient severity, we could not account for unmeasured confounders such as patient and family wishes in this observational study. However, by clustering at the level of the oncologist, we accounted for clinician-specific variation in scheduling and patient risk. Furthermore, the cohort in this observational study constitutes clinicians and patients from a single academic institution where the clinicians had been trained a priori on specific SIC EHR documentation practices, which may restrict the generalizability of our results. We also acknowledge that physicians and patients may have had serious illness conversations without documentation or were not documented using the serious illness conversation template in the EHR, and the frequency of these conversations may be underreported. Finally, a low baseline rate of SICs could limit the conclusions drawn from the study. Although, our findings were similar to rates measured in prior studies (1.9% - 4.9%). 13 The low rate could be explained by the inclusion of all patients, not just decedents, in our analyses; and by the nature of SICs, which are more in-depth and can take longer than traditional advance care planning conversations.
Conclusion
Efforts to improve the quality of care should recognize the time pressure on patients and physicians, the effects of behavioral interventions, and the time costs of improving patient-physician communication. Several straightforward practice changes could address these time pressures. Proactive scheduling of high-risk patients earlier in a clinic session or scheduling separate visits for serious illness communication could facilitate necessary conversations and should be further studied. Alternatively, democratizing serious illness communication to other members of the health care team – including lay health workers – may offload clinicians who are under time pressures from potentially low-quality or missed serious illness communication. 19 Future work should study the downstream effects of time-based decisions for serious illness conversations on end-of-life outcomes (ie chemotherapy treatments in the last 14 days of life, ICU admissions in the last 30 days, and late or non-referrals to hospice). In conclusion, oncologist-patient serious illness communication decreases considerably through the clinic day, reflecting potential time pressures and decision fatigue that warrant proactive strategies to avoid missed conversations.
Supplemental Material
Supplemental material - Time of Clinic Appointment and Serious Illness Communication in Oncology
Supplemental material for Supplemental material - Time of Clinic Appointment and Serious Illness Communication in Oncology by Likhitha Kolla, Jinbo Chen and Ravi B. Parikh in Cancer Control Journal
Footnotes
Acknowledgments
We thank Corey Chivers, PhD, Abigail Doucette, MPH, and Peter E. Gabriel, MD, MSE for assistance with database curation; and Kyunga Ko, BS, Penn Medicine, for providing guidance on analysis. None of these individuals received financial compensation for their contributions.
Author Contributions
Ms. Kolla 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: All authors. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: All authors. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Kolla. Obtained funding: Chen, Parikh. Supervision: Chen, Parikh.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the NIH Medical Scientist Training Program 
(to Ms Kolla) and grants NIH R01-HL138306 (to Dr Chen) and NIH K08-CA-263541 (to Dr Parikh). Dr Parikh reports receiving grants from Humana, the National Institutes of Health, Prostate Cancer Foundation, National Palliative Care Research Center, Conquer Cancer Foundation, and Veterans Administration; personal fees and equity from GNS Healthcare, Inc. And Onc.AI; personal fees from Biofourmis, Cancer Study Group, Thyme Care, Humana, and Nanology; honorarium from Flatiron, Inc. And Medscape; and serving on the board (unpaid) of the Coalition to Transform Advanced Care, all outside the submitted work.
Role of the Funder/Sponsor
The funders 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.
Ethical Approval
The trial protocol and overall study was granted approval by The University of Pennsylvania Institutional Review Board (IRB # 833178, approved on 05/09/2019, Philadelphia, PA, USA) with a waiver of informed consent.
Statement of Human and Animal Rights
This article is a secondary analysis of a randomized control trial (NLM, NCT03984773). All initiatives in the study involving human subjects were conducted in accordance with the Institutional Review Board guidelines of the University of Pennsylvania in Philadelphia, PA, USA. Patient EHR information was de-identified.
Statement of Informed Consent
Study protocol was approved by the University of Pennsylvania Institutional Review Board, with a waiver of informed consent due to minimal risk of the initiative. Verbal consent was obtained from each clinician who participated in the serious illness conversation interviews. Clinicians were not required to participate in the study and could opt out at any point.
Supplemental Material
Supplemental material for this article is available online.
References
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