Abstract
Background
Training health professionals in serious illness conversations is important for patients with serious illnesses and for their caregivers. However, most training focuses on individual clinicians rather than on healthcare teams. Caregivers of their patients are highly sensitive to changes in communication dynamics in the healthcare setting. We aimed to compare the impact of a team-based training program in serious illness conversations with that of an individual clinician-focused training program on the burden of care of caregivers of patients with serious illnesses, and the sustainability of these impacts over time.
Methods
We performed a secondary analysis of caregivers’ data from a preliminary cluster randomized trial in the USA and Canada in which 42 primary care clinics were randomized to an interprofessional team-based training arm (intervention) or an individual clinician-focused training arm (control). Seriously ill patients who had had a serious illness conversation with the trained clinicians were asked to refer a caregiver. We used the Zarit Burden Interview (range: 0–48) to assess caregiver burden immediately after the serious illness conversation (T1), six months later (T2) and 12 months later (T3). Statistical analyses using a linear mixed model were performed to compare caregiver burden between the two arms at the three times.
Results
We included 192 caregivers from 42 primary care clinics. Most were female (67.8%); aged 65–74 (28.6%). The mean caregiver burden scores were low, and similar in both the arms at the three times. The difference in mean burden between the two study arms was 1.05 (95% CI -1.47 to 3.59; p = 0.40), -0.24 (95% CI -2.57 to 2.08; p = 0.82), and 0.09 (95% CI -2.61 to 2.81; p = 0.94) at T1, T2 and T3 respectively. The p-value of the interaction term between study arm and time was p = 0.47. Mean difference between arms after performing a model with time effect and after adjusting was 0.90 (95% CI -0.76 to 2.57; p = 0.28). Various other factors such as caregivers feeling anxious or depressed were associated with caregiver burden.
Conclusion
Analysis showed that there was no difference between perceived caregiver burden after the interprofessional team-based training approach and after the individual clinician-focused training approach. Our study did however underline the importance of recognizing other factors influencing caregiver well-being.
Trial registration
ClinicalTrials.gov (ID: NCT03577002).
Supplementary Information
The online version contains supplementary material available at 10.1186/s12877-025-06324-7.
Keywords: Health care professional training, Family caregivers, Caregiver burden, Advance care planning, Zarit burden interview, Serious illness conversations
Background
According to a 2019 United Nations report, the number of older people (aged 60 and over) is expected to triple by 2050, accounting for 16% of the world population [1]. Many older people live with serious or chronic illnesses, often leading to partial or total loss of autonomy. Caregivers play an increasingly important role in their care and decision-making [2]. Often, in their frequent interactions with the healthcare system, patients with serious illnesses may undergo aggressive tests and unwanted treatments that can be invasive or painful and do not always align with their wishes [3, 4]. Advance Care Planning (ACP) is a dialogue between the patient, their healthcare professional(s) and their caregivers that allows patients to express their goals and values regarding potential future care in the event of decision-making incapacity [5]. ACP leads to an improvement in the quality of life, a better mood, a reduction in non-beneficial medical care at the end of life, lower expenditures, sustainment of goal-concordant care, and positive outcomes for the family [6, 7]. Primary care is recognized as the ideal setting for conducting ACP as primary care professionals have more frequent interactions and a longitudinal relationship with their patients [7]. “Serious illness conversations” is a broad term that applies to both “in-the-moment” shared medical decision making—commonly referred to as goals of care conversations—and the traditional ACP conversations intended to help patients prepare for the future. The goal of serious illness conversations is to help patients explore the future more generally without focusing only on specific treatment options. Unlike with ACP, with serious illness conversations the patient has already been diagnosed with a serious illness and a clinician is involved in the conversation [8].
However, despite their willingness to engage in serious illness conversations, primary care professionals report that they often lack sufficient time and training [9, 10]. The Serious Illness Care Program (SICP) is a systematic care delivery model created by a team of palliative care experts that aims to enable healthcare professionals to better initiate and lead serious illness conversations [11]. The program uses the Serious Illness Conversation Guide [11]. The SICP has been extended to primary care settings, showing evidence of acceptance and benefits [12]. Its primary goal is to allow more frequent, in-depth, and early conversations between clinicians and seriously ill patients, centered around their goals, values, and priorities, with the aim of positively influencing future care [13]. The SICP aims to make awareness of and respect for patients' priorities the norm rather than the exception [13]. The SICP training was originally developed with an individual clinician-focused approach, but an interprofessional team-based approach was also developed, as it has been shown that an interprofessional approach may facilitate serious illness conversations by reducing the time commitment required of clinicians [5]. In addition, several studies suggest that the effects of such an approach, because it involves sharing out the tasks and time commitments required for serious illness conversations, may be more sustainable over time [14, 15].
However, little is known about long-term impacts of educational health interventions. Two systematic reviews on educational health interventions note that few studies report on their long-term outcomes [16, 17]. Long-term follow-up gives trainees more time to internalize and practise newly acquired capabilities, and indicates their likelihood of sustaining them into the future. A lack of long-term outcomes may hide the true effects of any intervention. Such outcomes are critical to ensuring sustained change in clinical practice and patient care [18].
Patients and primary care professionals, however, are not the only people involved in end-of-life care. Caregivers play an increasingly important role in patient care and decision-making of patients with serious illnesses [2]. When healthcare professionals communicate clearly about their loved one’s prognosis and care options, caregivers feel more confident, their emotional and logistical burdens are reduced, and they can avoid last-minute, high-stress decision making [19]. If healthcare professionals are trained in a team-based approach, with the burden of delivering difficult news distributed across the whole team, messaging to the caregiver is consistent across the whole team, the illness is better managed, and care is better coordinated. In addition, as caregivers’ needs change over time, team-based training could allow the different professionals on the team to sustain caregiver support through the different stages of their loved one’s illness [20].
However, although it has been documented that training primary care professionals to improve health practices has a positive impact on the burden of care of caregivers [21, 22], we do not have a clear picture of the impact of an interprofessional team-based versus an individual clinician-focused approach to training healthcare professionals in serious illness conversations on the burden of care of caregivers, and to what extent these impacts are sustained over time.
Therefore, we hypothesized that a team-based approach to training healthcare professionals may have advantages over an individual approach in producing a sustained reduction in caregiver burden.
The data from our study is taken from a parent study that compared the impact of two different formats of training in serious illness conversations from the patient point of view: its primary outcomes were days at home and patient-reported goal-concordant care. The parent study found that both had increased after training, but the difference between formats was not statistically significant. However, as secondary stakeholders, caregivers experience quite different outcomes from patients, such as stress levels, anticipation of bereavement, and burden of care—changes that may not be evident in primary patient outcomes. Examining downstream impacts on caregivers could offer additional insights into how or whether the format (team or individual) of the training influenced caregivers’ burden of care through, for example, improved coordination or consistency in messaging.
Our study therefore aimed to evaluate the impacts on caregiver burden of training primary care professionals in serious illness conversations using the two training approaches (individual vs. team-based), and on the sustainability of these impacts over time.
Methods
Study design and setting
We performed a secondary analysis of a multicenter, parallel-group cluster randomized trial comparing team-based to individual clinician-focused implementation of the SICP training in primary care [23] with post-intervention measures immediately after the intervention, six months and 12 months later.
The parent study’s primary outcomes were patient-reported goal-concordant care and days at home. The trial was registered in ClinicalTrials.gov: NCT03577002 and its protocol is published [23]. The study took place from January 2018 to August 2022 in primary care clinics located in five states in the United States (Colorado, Iowa, North Carolina, Oregon, Wisconsin) and two provinces in Canada (Quebec and Ontario).
Results of our secondary analysis are reported according to the CONSERVE 2021 statement for cluster randomized trials conducted during the COVID-19 pandemic [24].
Recruitment and participants
Primary care clinics (clusters) were recruited from seven Practice-Based Research Networks (PBRN) in five USA states and two Canadian provinces under the supervision of the joint coordinating center at Oregon Health & Science University and Université Laval, Quebec. The primary care clinics were provided with information about the study. To be eligible to participate, primary care clinics had to: (1) be able to provide at least 30 participants; (2) accept to be randomized to either study arm; (3) have sufficient interprofessional staff to participate in the interprofessional team-based arm, including medical assistants, nurses, social workers, and community health workers; (4) be untrained in any other standardized ACP program.
Caregivers were the primary participants of our study as caregiver burden was its main outcome. Caregivers play a significant role in patient care and are sensitive to changes in communication dynamics within the healthcare setting. Research has shown that improved clinician-patient communication can indirectly benefit caregivers by reducing uncertainty, alleviating emotional stress, and enhancing their ability to plan care [25]. After the first serious illness conversation with their primary care professional post-training, patients with serious illnesses were invited by their primary care professional to participate in the study. Once the patient gave consent, they were asked about their preference to include a caregiver, friend, or family member involved in their healthcare in the study. Patients provided the research team with the names and contact details of potential caregivers. Subsequently, a member from the research team contacted the potential caregivers to invite them to participate. Caregivers received the intervention from clinics that were randomized to either the individually trained group or the team-trained group, ensuring that their experience reflected the training model implemented in their respective clinic.
Randomization
The units of randomization were the primary care clinics. They were randomly assigned to either the interprofessional arm or the individual arm. A random number generator was used by a biostatistician who had no contact with the primary care clinics or PBRNs and who remained blinded until the completion of the primary analyses. Personnel at the PBRNs, primary care clinics, and the joint coordinating center were not involved in randomization. However, investigators, PBRN leadership, primary care clinics, and research staff were not blinded to the assignment. Primary care clinics and participating primary care professionals could not be blinded to their assigned study arm as they needed to actively undergo training, i.e., implement either the intervention or the control. Caregivers, as the primary participants of this study, received the intervention from clinics that had been randomized to either individual training or the team-based training, ensuring that their experience was shaped by the training model implemented in their respective clinics. Further details regarding the randomization process are available elsewhere [23].
Intervention and comparator arms
We adapted the original Ariadne Labs SICP to create an abbreviated version for this trial. We then developed a new interprofessional training approach [26]. Both training approaches lasted three hours: a 1.5-h online module (Part A), and a 1.5-h in-person role-play session (Part B). Training materials included the Serious Illness Conversation Guide, a tool designed by Ariadne Labs to facilitate communication with patients with serious illnesses [27].
Original serious illness care program
The original SICP is a multicomponent, structured communication intervention designed to (1) identify patients with serious illnesses; (2) train clinicians to use the Serious Illness Conversation Guide to structure serious illness conversations with patients; (3) ‘trigger’ clinicians to have conversations using the guide with enrolled patients; (4) prepare patients for the conversation by providing them with a letter encouraging them to think about some of the topics raised in the guide; (5) guide clinicians in conducting values and goals conversations; (6) document outcomes of the discussion in a structured format in the electronic medical record and (7) provide patients with a Family Communication Guide to help them continue the discussion at home with their loved ones (11).
Intervention arm: interprofessional team-based approach
Our new training was based on the interprofessional shared decision-making model and previous workshops [28, 29]. Our new team-based approach focused on maximizing the expertise and efficient use of time of each team member to facilitate serious illness conversations. In this approach, the steps are the same as those in individual training, but the tasks are shared among different primary care professionals in the team. Teams consist of primary care clinicians and one or more additional persons with different professions or practice roles (e.g., nurses, care managers, social workers, medical assistants, chaplains, peer counselors, community health workers). Emphasis was placed on the following: (a) establishing a common understanding of the process and goals of care related to serious illnesses among team members; (b) recognizing the contributions of each team member; (c) maintaining continuous communication within the team; and (d) acknowledging organizational or functional constraints specific to each profession. More details on the development of the team-based training approach are published elsewhere [26].
Control arm: individual clinician-focused approach
The individual clinician-focused approach assumed that serious illness conversations would take place with a single primary care clinician (i.e. physician, nurse practitioner, physician assistant or resident) who identifies the appropriate patients, leads the serious illness conversations and documents their discussions in the patient’s medical record.
Outcomes and measures
We measured caregiver burden as our main outcome. Caregiver burden refers to the emotional, financial and physical difficulties and burdens faced by family caregivers when caring for someone with serious or chronic illnesses or with loss of autonomy [30]. We assessed caregiver burden using the brief version of the Zarit Burden Interview (ZBI) [31]. This is a 12-item self-administered questionnaire frequently used to assess the effect of caregiving on caregivers’ quality of life. We also measured sustainability of the impact of the two training approaches on caregiver burden by repeating the ZBI at six months and then again at 12 months. Sustainability of impact refers to the persistence of intervention effects over time [32]. In our study specifically, it refers to the long-term impact on caregiver burden of each training approach at six and then 12 months post-intervention.
Data collection
Primary care professionals were trained. Caregiver data were collected after a serious illness conversation between the patient and the primary care professionals. After the caregivers provided informed consent, they completed a self-administered questionnaire developed for this study and based on the various measures described above (Supplementary file 1). Caregivers completed questionnaires immediately after the serious illness conversation, and then six months and 12 months later.
Sample size
Since this was a secondary analysis of a primary study, there was no a priori sample size calculated for this substudy focused on caregivers. Patients were asked to identify their caregivers. Information on the primary study sampling strategy is reported in the published study protocol [23]. Caregivers received the intervention through clinics randomized to either the individual or team-based training groups. A total of 192 caregivers participated (n = 110 in the team-based group, n = 82 in the individual group).
Data analysis
We performed descriptive analysis for all variables. Categorical variables were described using absolute and relative frequencies (numbers, percentages). Continuous variables were described using central tendency measures (means, medians) and measures of dispersion (standard deviations, minimum and maximum). The caregiver burden was treated as a continuous variable. The total ZBI score, that is the sum of the scores obtained for each item, ranges from 0 (no burden) to 48 (severe burden). Total ZBI score can indicate little or no burden (between 0 and 10); moderate burden (above 10 and lower than 20) or severe burden (above 20) [22, 23]. Since the caregiver burden did not follow a normal distribution, we performed a linear mixed model to analyze it [33]. To account for clustering, we used the practice identifier as a random factor when fitting the models.
We performed bivariate analysis through a linear mixed model for each variable of interest to analyze its effect on caregiver burden. We then selected all statistically significant variables (p < 0.20) from the bivariate analysis to perform a multivariate model through a linear mixed model. We then performed a manual stepwise backward selection based on the variable significance (p < 0.05) in the final adjusted model. To compare the sustainability of the training effect on caregivers, we determined the p-value of the interaction term between study arm and time.
All analyses were performed using Statistical Analysis Software (SAS) 9.4.
Results
Characteristics of primary care clinics and caregivers
A total of 45 primary care clinics were recruited and randomized into both study arms. Forty primary care clinics were trained, 19 using the individual clinician-focused approach and 21 using the interprofessional team-based approach. Thirty-eight primary care clinics, 19 in each arm, referred patients and caregivers (Fig. 1). Characteristics of randomized primary care clinics are illustrated in Table 1. A total of 192 caregivers (110 in the interprofessional arm, 82 in the individual arm) consented to participate and 171 caregivers (89.06%) completed the ZBI at T1, 144 (75.00%) at T2 and 130 (67.71%) at T3. Most caregivers were female (67.8%), Caucasian (80.2%), aged from 65 to 74 years old (28.6%), had completed at least college or a two-year degree (32.4%), and lived with the patient (63%). Most caregivers were the patient’s spouse (51.6%) (Table 2).
Fig. 1.
Flow chart of participant recruitment
Table 1.
Characteristics of participating primary care clinics
| Practices | Clinician (n, %) | Interprofessional (n, %) | Total (n, %) |
|---|---|---|---|
| Number of practices | 22 (100) | 23 (100) | 45 (100) |
| Country | |||
| United States | 16 (72.7) | 17 (73.9) | 33 (73.3) |
| Canada | 6 (27.3) | 6 (26.1) | 12 (26.7) |
| Size (of Primary Care Clinics) | |||
| Small (2–5) | 2 (9.0) | 6 (26.1) | 8 (17.8) |
| Medium (6–12) | 10 (45.5) | 9 (39.1) | 19 (45.2) |
| Large (13–85) | 10 (45.5) | 8 (34.8) | 18 (40.0) |
| Geographical setting | |||
| Rural | 8 (36.4) | 12 (52.2) | 20 (44.4) |
| Suburban | 5 (22.7) | 3 (13.0) | 8 (17.8) |
| Urban | 9 (40.9) | 8 (34.8) | 17 (37.8) |
| Ownership | |||
| Hospital/health system | 18 (81.8) | 13 (56.6) | 31 (68.9) |
| Physician or physician group | 4 (18.2) | 7 (30.4) | 11 (24.4) |
| Federally Qualified Health Center | 0 (0.0) | 3 (13.0) | 3 (6.7) |
| Specialty | |||
| Family medicine | 19 (82.6) | 15 (68.2) | 34 (75.5) |
| Internal medicine | 3 (13.0) | 5 (22.7) | 8 (17.8) |
| Both Family and internal medicine | 1 (4.4) | 2 (9.1) | 3 (6.7) |
| Size of Primary Care Clinics, median (min–max) | 12 (3 to 40) | 8 (4 to 46) | 10 (3 to 46) |
Table 2.
Caregiver characteristics
| Arm | |||
|---|---|---|---|
| Individual | Interprofessional | Total | |
| n Clusters | 19 | 19 | 38 |
| n Caregivers | 82 | 110 | 192 |
| Country, n (%) | |||
| United-States | 61 (74.4) | 62 (56.4) | 123 (64.1) |
| Canada | 21 (25.6) | 48 (43.6) | 69 (35.9) |
| Age, n (%) | |||
| 25–34 | - | 1 (0.9) | 1 (0.5) |
| 35–44 | 2 (2.4) | 4 (3.6) | 6 (3.2) |
| 45–54 | 10 (12.2) | 8 (7.3) | 18 (9.3) |
| 55–64 | 18 (21.9) | 30 (27.3) | 48 (25.1) |
| 65–74 | 21 (25.6) | 34 (30.9) | 55 (28.6) |
| 75 or older | 19 (23.3) | 24 (21.8) | 43 (22.4) |
| Missing | 12 (14.6) | 9 (8.2) | 21 (10.9) |
| Sex, n (%) | |||
| Male | 16 (19.6) | 25 (22.3) | 41 (21.3) |
| Female | 54 (65.8) | 76 (69.6) | 130 (67.8) |
| Missing | 12 (14.6) | 9 (8.1) | 21 (10.9) |
| Race, n (%) | |||
| Caucasians | 64 (78.0) | 90 (81.8) | 154 (80.2) |
| Black or African American | 3 (3.8) | 4 (3.6) | 7 (3.6) |
| Asian | 2 (2.5) | 3 (2.7) | 5 (2.6) |
| Middle Eastern | - | 1 (0.9) | 1 (0.5) |
| Mixed race | 1 (1.2) | 1 (0.9) | 2 (1.2) |
| Other race | - | 1 (0.91) | 1 (0.52) |
| Missing | 12 (14.5) | 11 (10.1) | 23 (11.9) |
| Relationship with patients, n (%) | |||
| Spouse | 44 (53.7) | 55 (50.0) | 99 (51.6) |
| Ex-spouse | 1 (1.2) | - | 1 (0.5) |
| Parent | 1 (1.2) | 2 (1.8) | 3 (1.6) |
| Friend | - | 3 (2.8) | 3 (1.6) |
| Daughter | 20 (24.4) | 35 (31.8) | 55 (28.7) |
| Son | 5 (6.1) | 6 (5.5) | 11 (5.7) |
| Partner | - | 1 (0.9) | 1 (0.5) |
| Sibling | 3 (3.7) | 1 (0.9) | 4 (2.0) |
| Significant other | 1 (1.2) | - | 1 (0.5) |
| Other relative | 2 (2.4) | 2 (1.8) | 4 (2.0) |
| Other | 2 (2.4) | 2 (1.8) | 4 (2.0) |
| Missing | 3 (3.7) | 3 (2.7) | 6 (3.3) |
| Education, n (%) | |||
| Grade 8 or less | 1 (1.2) | 4 (3.6) | 5 (2.6) |
| Some high school but did not graduate | 2 (2.4) | 13 (11.8) | 15 (7.8) |
| High school graduate or GED | 20 (24.4) | 21 (19.1) | 41 (21.4) |
| Some college or 2-year degree | 26 (31.7) | 36 (32.7) | 62 (32.4) |
| 4-year college graduate | 10 (12.3) | 15 (13.6) | 25 (13.0) |
| More than 4-year college degree | 11 (13.4) | 12 (10.9) | 23 (11.9) |
| Missing | 12 (14.6) | 9 (8.3) | 21 (10.9)) |
| Patient’s main condition n (%) | |||
| Cancer | 15 (18.3) | 22 (20.1) | 37 (19.3) |
| Cardiovascular | 10 (12.2) | 26 (23.6) | 36 (18.8) |
| Lung disease | 5 (6.1) | 3 (2.7) | 8 (4.1) |
| Diabetes and kidney problems | 4 (4.9) | 5 (4.6) | 9 (4.7) |
| Ulcer/stomach/liver/gastrointestinal problems | 1 (1.2) | 2 (1.8) | 3 (1.6) |
| Blood disease | - | 1 (0.9) | 1 (0.5) |
| Depression and anxiety | 2 (2.4) | 2 (1.8) | 4 (2.1) |
| Musculoskeletal | 1 (1.2) | 1 (0.9) | 2 (1.0) |
| Neurological | 3 (3.7) | 3 (2.7) | 6 (3.1) |
| Immune/auto immune | 5 (6.1) | 3 (2.7) | 8 (4.2) |
| Functional problems | 6 (7.3) | 11 (10.0) | 17 (8.8) |
| Multiple systems (not cancer) | 2 (2.4) | 3 (2.7) | 5 (2.6) |
| Missing | 28 (34.2) | 28 (25.5) | 56 (29.2) |
| Cohabitation, n (%) | |||
| No | 23 (28.1) | 29 (26.4) | 52 (27.1) |
| Yes | 48 (58.5) | 73 (66.4) | 121 (63.0) |
| Missing | 11 (13.4) | 8 (7.2) | 19 (9.9) |
Caregiver burden
The caregiver burden mean score (standard deviation (SD)) was 11.3/48 (8.5) (n = 101) in the interprofessional arm at T1; 9.1/48 (6.8) (n = 80) at T2 and 9.9/48 (8.3) (n = 74) at T3. The mean score (SD) was 10.8/48 (9.0) (n = 70); scores in the individual arm were 10.8/48 (9.0) (n = 70) at T1, 10.1/48 (8.2) (n = 64) at T2 and 9.2/48 (8.0) (n = 56) at T3 (Table 3).
Table 3.
Distribution of caregiver burden of care
| Burden of care (Means) | ||||||
|---|---|---|---|---|---|---|
| Individual | Interprofessional | Total | ||||
| N | Mean (SD) | N | Mean (SD) | N | Mean (SD) | |
| Burden of care score T1 | 70 | 10.8 (9.0) | 101 | 11.3 (8.5) | 171 | 11.1 (8.7) |
| Burden of care score T2 | 64 | 10.1 (8.2) | 80 | 9.1 (6.8) | 144 | 9.5 (7.4) |
| Burden of care score T3 | 56 | 9.2 (8.0) | 74 | 9.9 (8.3) | 130 | 9.6 (7.9) |
SD standard deviation
T1: after the serious illness conversation
T2: 6 months after the serious illness conversation
T3: 12 months after the serious illness conversation
The difference in mean burden between the two study arms was 1.05 (95% CI −1.47 to 3.59; p = 0.40), −0.24 (95% CI −2.57 to 2.08; p = 0.82), and 0.09 (95% CI −2.61 to 2.81; p = 0.94) at T1, T2 and T3 respectively. We adjusted for other variables such as caregiver’s overall health, caregiver’s mental or emotional health, anxiety, patient spending any night in a nursing home or rehab in the past six months and caregiver’s social life at T1, caregiver’s mental or emotional health and caregiver’s social life and caregiver’s ethnicity at T2, and at T3, caregiver’s mental or emotional health and patient having received palliative care in the past six months (Table 4). The p-value of the interaction term between study arm and time was p = 0.47.
Table 4.
Mean difference of burden of care at each time point
| Burden of care (Means differences) | ||||||
|---|---|---|---|---|---|---|
| Unadjusted model | Adjusted model* | |||||
| Estimate | CI 95% | p value | Estimate | CI 95% | p value | |
| (N = 171) | (N = 162) | |||||
| T1 | 0.78 | - 2.63; 4.19 | 0.64 | 1.05 | - 1.47; 3.59 | 0.40 |
| (N = 144) | (N = 137) | |||||
| T2 | - 0.98 | - 3.53; 1.57 | 0.43 | - 0.24 | - 2.57; 2.08 | 0.82 |
| (N = 130) | (N = 122) | |||||
| T3 | 0.75 | - 2.13; 3.63 | 0.59 | 0.09 | - 2.61; 2.81 | 0.94 |
95% CI confidence interval at 95%
Significance threshold (P < 0.05)
Mixed linear regression test
T1: after the serious illness conversation; T2: 6 months after the serious illness conversation; T3: 12 months after the serious illness conversation
*Adjusted for caregiver’s overall health, caregiver’s mental or emotional health, anxiety, patient spending any night in nursing home/rehab in past 6 months and caregiver’s social life at T1, caregiver’s mental or emotional health and caregiver’s social life at T2, and at T3, caregiver’s mental or emotional health and patient having palliative care in past 6 months
Since the interaction term between the study arm and time was not statistically significant, we performed a model with time effect (the variables from the three time points were combined into a single time point). The mean difference between study arms was then −0.16 (95% CI: −2.32 to 2.00; p = 0.88). After adjusting for caregivers’ overall mental or emotional health, anxiety, depression, social roles, and the patient’s use of an emergency department in the past six months, the mean difference between arms was 0.90 (95% CI: −0.76 to 2.57; p = 0.28). There were no statistically significant differences in the perceived level of caregiver burden between the two arms (p = 0.28) (Table 5).
Table 5.
Final model with time effect
| Burden of care (Means differences) | |||||
|---|---|---|---|---|---|
| Unadjusted model | Adjusted model * | ||||
| Estimate | CI 95% | P-value | Estimate | CI 95% | P-value |
| −0.16 | −2.17; 2.19 | 0.88 | 0,90 | - 0.79; 2.49 | 0.28 |
95%CI: confidence interval at 95%
Significance threshold (P < 0.05)
Mixed linear regression test
*Adjusted for caregivers’ overall mental or emotional health, anxiety, depression, social roles, and the patient’s use of an emergency department in the past 6 months
Discussion
Our study aimed to assess the impact on caregivers’ burden of care of training primary care professionals in serious illness conversations using two different training approaches, individual and interprofessional, and the sustainability of these impacts on caregiver burden over time. There were no significant differences in impact on caregiver burden between the individual and interprofessional team training arms, and no changes in caregiver burden from the initial post-conversation measurement to six and 12 months later in either arm. From the perspective of caregiver burden, the two training approaches had the same impacts and their effects remained stable over time.
First, while the parent study found no statistically significant difference in patient outcomes (days at home and patient-reported goal-concordant care) between the two training approaches [23, 34], both had improved after training, reflecting an increased confidence among all the trained health professionals to conduct serious illness conversations [35]. A study at Massachusetts General Hospital, which adapted the Serious Illness Care Program for medical students and residents, also found that both groups reported increased confidence in conducting serious illness conversations after training [36]. Yet this increased confidence to engage with patients did not lead to an alleviation of the burden of care. This result has important implications for both clinical practice and future research. Clinically, it reinforces the feasibility of flexible training models allowing healthcare teams to adopt either approach without compromising caregiver outcomes. From a research perspective, these findings highlight the need to further explore and refine team-based interventions that explicitly involve caregivers in the conversation process. In Stanford University’s Team-Based Serious Illness Program, team members conduct serious illness conversations with both patients and caregivers. A qualitative study of this program found that team-based SICP distributed work burden and allowed timed conversations in alignment with patient needs. It also highlighted the benefits of flexibility in situations of high staff turnover. However, role ambiguity sometimes created disjointed or irregular communication between team members, leading to missed or multiple conversations with patients, causing patient and caregiver frustration [20].
Second, we expected a decrease in caregiver burden over time as the trained health team collectively takes charge of communicating with the patient about the progress of their serious illness. But the level of burden of care remained consistent for caregivers, whether their loved one’s healthcare professional had been trained individually or using a team-based approach.
The stability of caregiver burden over time reinforces the need to explore additional training for conversations with caregivers themselves regarding their loved ones’ serious illnesses. However, expanding the conversation to include caregivers may not be enough. Existing literature suggests that caregivers often neglect their own well-being, failing to maintain proper nutrition, physical activity, and healthcare appointments, which could add to sustained burden levels [37]. Structured follow-up and psychoeducational resources, requiring a multidisciplinary team-based approach, may be needed to address their needs more comprehensively.
A qualitative pilot study could examine whether a structured team training approach that includes serious illness discussions with caregivers and long-term multi-disciplinary support has a measurable impact on caregiver burden. This would help determine if SICP multidisciplinary training that explicitly includes caregivers could reduce caregiver distress and improve overall care experiences.
Finally, our results also raise the question of whether caregiver burden is primarily influenced by factors beyond the nature of the healthcare provider's training, such as intrinsic caregiver characteristics or broader systemic support structures. While serious illness conversations play a crucial role in improving communication and shared decision-making, they may not be sufficient to significantly reduce caregiver burden. Studies have shown that caregivers experience high levels of psychological, emotional, and physical stress which are best alleviated through structured support systems rather than communication interventions alone [38]. Practical measures such as respite care, home health services, and financial support have been identified as key factors in reducing caregiver burden and improving their well-being [39]. Future interventions should consider integrating these elements alongside communication strategies to provide a more comprehensive support system for caregivers.
Limitations
First, this is a secondary analysis of a controlled randomized trial assessing an intervention targeting primary care professionals. Our objective may have been too ambitious since the intervention did not target caregivers and our outcome was indirect. The recruitment of caregivers constitutes the main potential source of bias in our study. Randomization was carried out at the primary care clinics. Although primary care clinics’ characteristics were comparable in both arms, the same cannot be said for caregivers. Caregivers with a severe burden may have been unwilling to participate in the study because they were overwhelmed by their responsibilities. An important loss to follow-up would be another limitation to raise especially since our study focused on sustainability and required a lengthy time commitment. Additionally, the composition of the multidisciplinary teams in the interprofessional training arm was not standardized across sites. Teams could include different combinations of healthcare professionals such as nurses, social workers and dietitians. Heterogeneity in team structure should be considered when interpreting the findings and may warrant further investigation in future studies.
Conclusion
Our study compared the sustainability of the impact of two approaches to training primary care professionals in serious illness conversations, team-based and individual-focused, measured immediately after a post-training serious illness conversation, at six months, and at 12 months, on caregiver burden. We found that caregiver burden did not depend significantly on the time that had elapsed since the serious illness conversation. We also found that there was no statistically significant difference between the caregiver burden observed in each arm. Our results suggest that there may be a place for a larger role for caregivers in serious illness conversations and training for primary care professionals should reflect this, for example, by including a module focusing on caregivers. Accompanying caregivers is especially appropriate in the context of interprofessional serious illness conversations training, as it constitutes a task that could be performed by another trained healthcare professional, giving clinicians the time to focus on the patients themselves. Caregivers could receive valuable support from other professionals in caring for their seriously ill loved one, and a future team-based intervention seems inevitable for this population. A further study could pilot a training program that had more of a focus on caregivers.
Supplementary Information
Acknowledgements
We acknowledge the precious work of Louisa Blair for her editorial help with the manuscript and Stéphane Turcotte for his vital insights in the statistical analysis. We also thank the members of the Meta-LARC ACP Cluster Randomized Trial team for their involvement in this project.
Collaborators Meta-LARC ACP Cluster Randomized Trial team
Angela K. Combe, Oregon Health & Science University
Annette M. Totten, Oregon Health & Science University
Barcey T. Levy, University of Iowa
Cat Halliwell, University of Colorado
David A. Dorr, Oregon Health & Science University
David Nowels, University of Colorado
Deb Constien, Patient-partner
Deborah Dokken, Patient-partner
Donald E. Nease, Jr., University of Colorado
Dr. B. Angeloe Burch Sr., Patient-partner
Elizabeth Fernley, Oregon Health & Science University
France Légaré, Université Laval
Gail Drey, Patient-partner
Gurnoor Kaur Brar, University of Toronto
Jacqueline D. Alikhaani, Patient-partner
James Pantelas, Patient-partner
Jean-Sebastien Paquette, Université Laval
Jeanette M. Daly, University of Iowa
Jessica E. Ma, Duke University
Jodi Lapidus, Oregon Health & Science University
Judy Katz, Patient-partner
Kate Hanrahan, University of Iowa
Kathy Kastner, Patient-partner
Katrina Ramsey, Oregon Health & Science University
Keith Provin, Patient-partner
Kirsten Wentlandt, University Health Network, Toronto
Kylie Lanman, Oregon Health & Science University
LeAnn C Michaels, Oregon Health & Science University
Lyle J. Fagnan, Oregon Health & Science University
Mary F. Henningfield, PhD, University of Wisconsin-Madison
Mary M. Minniti, Patient-partner
Matthew Howard, Oregon Health & Science University
Megan Schmidt, University of Iowa
Meredith K. Warman, University of Colorado
Michelle Greiver, University of Toronto
Olga Petrova, Patient-partner
Patrick M. Archambault, Université Laval
Peter Kim, University of Iowa
Rowena J. Dolor, Duke University
Sabrina Guay-Bélanger, VITAM—Centre de recherche en santé durable
Sarah Bumatay, Oregon Health & Science University
Sarina Schrager, University of Wisconsin-Madison
Sean Rice, Oregon Health & Science University
Sharon E. Straus, University of Toronto
Shelbey Hagen, University of Wisconsin-Madison
Shigeko (Seiko) Izumi, Oregon Health & Science University
Souleymane Gadio, VITAM—Centre de recherche en santé durable
Suélène Georgina Dofara, VITAM—Centre de recherche en santé durable
Susan Lowe, Oregon Community Health Information Network—Columbia Gorge Health Council
Taryn Bogdewiecz, University of Colorado.
Abbreviations
- ACP
Advance Care Planning
- PBRN
Practice-Based Research Network
- PROMIS
Patient-Reported Outcomes Measurement Information System
- SD
Standard Deviation
- SICP
Serious Illness Care Program
- ZBI
Zarit Burden Interview
Authors’ contributions
AT, FL, LM, SI, SGB, SGD, PA, and JSP conceived the primary study and participated in its design and/or coordination. KLL and SG performed analysis. KLL, OQA, SG, CBU, SGD, DAB, SGB, LPR and FL interpreted the results and the implications of the study. KLL drafted the preliminary manuscript before submitting it to co-authors. OQA, CBU, SGD, SGB and FL substantively revised it. All authors read and approved the final manuscript.
AT, FL, LM, SI, SGB, SGD, PA, and JSP conceived the primary study and participated in its design and/or coordination. KLL and SG performed analysis. KLL, OQA, SG, CBU, SGD, DAB, SGB, LPR and FL interpreted the results and the implications of the study. KLL drafted the preliminary manuscript before submitting it to co-authors. OQA, CBU, SGD, SGB and FL substantively revised it. All authors read and approved the final manuscript.
Funding
Research reported in this article was funded through a Patient-Centered Outcomes Research Institute (PCORI) Award (PLC-1609–36277). The results presented in this article are solely the responsibility of the authors and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute (PCORI), its Board of Governors or Methodology Committee. FL holds a Tier 1 Canada Research Chair in Shared Decision Making and Knowledge Mobilization. PA held a FRQS Clinical Scholar Award for the duration of this project. The financial providers are not involved in the project.
Data availability
Data for United States sites will be available on the Patient-Centered Outcomes Institute (PCORI) data repository once the review process is complete. For Canadian sites, accessing data requires an ethics application submitted to the appropriate Research Ethics Board (REB) due to provincial laws and regulations. In Quebec, applications should be submitted to the Research Ethics Board of the Centre Intégré Universitaire de Santé et de services sociaux (CIUSSS) de la Capitale-Nationale in Quebec City. For Ontario, applications should be submitted to the Health Sciences Research Ethics Board of the University of Toronto.
Declarations
Ethics approval and consent to participate
All participants gave informed consent. The parent study received approval from the Trial Innovation Network Single IRB at Vanderbilt University Medical Center (IRB#181084) for the American sites. For sites in Quebec, the study was approved by the Research Ethics Committee of the Centre Intégré Universitaire de Santé et de Services Sociaux de la Capitale-Nationale (ethics number #MP1320191526), and for sites in Ontario, it was approved by the Health Sciences Research Ethics Board of the University of Toronto (#36631) (23). The study was conducted in accordance with the principles of the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
France Légaré, Email: france.legare@fmed.ulaval.ca.
Meta-LARC ACP Cluster Randomized Trial team:
Angela K Combe, Barcey T. Levy, Cat Halliwell, David A. Dorr, David Nowels, Deb Constien, Deborah Dokken, Donald E. Nease, Jr, B. Angeloe Burch, Sr, Elizabeth Fernley, Gail Drey, Gurnoor Kaur Brar, Jacqueline D. Alikhaani, James Pantelas, Jeanette M. Daly, Jessica E. Ma, Jodi Lapidus, Judy Katz, Kate Hanrahan, Kathy Kastner, Katrina Ramsey, Keith Provin, Kirsten Wentlandt, Kylie Lanman, Lyle J. Fagnan, Mary F. Henningfield, Mary M. Minniti, Matthew Howard, Megan Schmidt, Meredith K. Warman, Michelle Greiver, Olga Petrova, Peter Kim, Rowena J. Dolor, Sarah Bumatay, Sarina Schrager, Sean Rice, Sharon E. Straus, Shelbey Hagen, Susan Lowe, and Taryn Bogdewiecz
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data for United States sites will be available on the Patient-Centered Outcomes Institute (PCORI) data repository once the review process is complete. For Canadian sites, accessing data requires an ethics application submitted to the appropriate Research Ethics Board (REB) due to provincial laws and regulations. In Quebec, applications should be submitted to the Research Ethics Board of the Centre Intégré Universitaire de Santé et de services sociaux (CIUSSS) de la Capitale-Nationale in Quebec City. For Ontario, applications should be submitted to the Health Sciences Research Ethics Board of the University of Toronto.