Abstract
Clinical guidelines recommend implantable cardioverter-defibrillators (ICDs) to prevent sudden cardiac death in patients with systolic heart failure. Black patients are less likely to receive an ICD. This randomized trial examined the use of a video decision support tool with Black patients and subsequent decisions to agree to ICD implantation.
Background:
Racial disparities in implantable cardioverter-defibrillator (ICD) implantation are multifactorial and are partly explained by higher refusal rates.
Objective:
To assess the effectiveness of a video decision support tool for Black patients eligible for an ICD.
Design:
Multicenter, randomized clinical trial conducted between September 2016 and April 2020. (ClinicalTrials.gov: NCT02819973)
Setting:
Fourteen academic and community-based electrophysiology clinics in the United States.
Participants:
Black adults with heart failure who were eligible for a primary prevention ICD.
Intervention:
An encounter-based video decision support tool or usual care.
Measurements:
The primary outcome was the decision regarding ICD implantation. Additional outcomes included decisional conflict, ICD implantation within 90 days, the effect of racial concordance on outcomes, and the time patients spent with clinicians.
Results:
Of the 330 randomly assigned patients, 311 contributed data for the primary outcome. Among those randomly assigned to the video group, assent to ICD implantation was 58.6% compared with 59.4% in the usual care group (difference, −0.8 percentage point [95% CI, −13.2 to 11.1 percentage points]). Compared with usual care, participants in the video group had a higher mean knowledge score (difference, 0.7 [CI, 0.2 to 1.1]) and a similar decisional conflict score (difference, −2.6 [CI, −5.7 to 0.4]). The ICD implantation rate within 90 days was 65.7%, with no differences by intervention. Participants randomly assigned to the video group spent less time with their clinician than those in the usual care group (mean, 22.1 vs. 27.0 minutes; difference, −4.9 minutes [CI, −9.4 to −0.3 minutes]). Racial concordance between video and study participants did not affect study outcomes.
Limitation:
The Centers for Medicare & Medicaid Services implemented a requirement for shared decision making for ICD implantation during the study.
Conclusion:
A video-based decision support tool increased patient knowledge but did not increase assent to ICD implantation.
Primary Funding Source:
Patient-Centered Outcomes Research Institute.
Keywords: Decision making, Heart failure, Implantable cardioverter defibrillators, Racial and ethnic issues, Shared Decision Making Among Black Patients at Risk for Cardiac Arrest
Sudden cardiac arrest (SCA) is the leading cause of death in the United States, accounting for approximately 400 000 deaths annually (1, 2). Clinical practice guidelines recommend implantable cardioverter-defibrillator (ICD) implantation for primary prevention of SCA among patients with systolic heart failure (3). Despite a greater risk profile, Black patients are less likely than White patients to receive an ICD (4–10). Although there are many contributors to racial disparities in ICD implantation, historically, Black patients have been less likely than White patients to assent to invasive cardiovascular procedures, including ICD implantation (11–17). Shared, well-informed decision making is critical for patients contemplating ICD implantation and their families (18, 19). Effectively communicating the benefits of ICD therapy and its short- and long-term risks is difficult, and the decision to undergo ICD implantation is complex (18). A single-center pilot study found that an encounter-based video decision support tool increased assent to ICD implantation among Black patients compared with usual care (20). Conversely, White patients had a lower assent rate in the video group compared with usual care.
Black patients who perceive racism in the health care system may be more likely to prefer a physician of their own race or ethnicity (21). The effect of racial concordance on shared decision making (SDM) is unknown in the context of decision making for ICDs.
The aim of this large multicenter study was to assess the effect of an encounter-based video decision support tool among Black patients compared with usual care on assent to ICD implantation, decisional conflict, patient knowledge of sudden cardiac death and ICDs, and ICD implantation within 90 days. The effect of racial concordance between study participants and clinicians and patients in the video was explored for the decision regarding ICD implantation. We also determined the effect of the video decision support tool on time spent with the clinician during the study enrollment encounter.
Methods
Design Overview
The VIVID (Educational Videos to Address Racial Disparities in Implantable Cardioverter Defibrillator Therapy Via Innovative Designs) study was a multisite, randomized, parallel-design trial conceived to determine the efficacy of a video decision support tool to increase knowledge of SCA and ICDs, decrease decisional conflict, and increase assent to ICD implantation among Black patients eligible for a de novo primary prevention ICD. Participants were randomly assigned in a 1:1:1 ratio to 1 of 3 groups: a group that viewed a concordant video featuring actual Black patients (not actors) and a Black clinician, a group that viewed a discordant video featuring White patients and a White clinician, or a group that received usual care. Given that Black patients have a disproportionately higher burden of SCA and experience inequities in ICD implantation compared with White patients, we limited enrollment to self-identified Black patients. Moreover, in the pilot study, video-based decision support increased assent to ICD implantation in Black but not White participants. Recruitment began on 1 September 2016, enrollment ended on 31 December 2019, and follow-up concluded on 1 April 2020. The institutional review boards at the coordinating center (Duke Clinical Research Institute) and at all participating sites approved the study. The trial protocol is available at Annals.org. Written informed consent was obtained from all patients.
Changes in Outcomes and Sample Sizes
The trial was originally planned to enroll 480 patients and assess 2 co–primary end points: the decision regarding ICD implantation in the video group compared with the usual care group, and the decision regarding ICD implantation by racial concordance in the video groups (22). Because of lower-than-expected enrollment, the study did not achieve sufficient statistical power to address both primary outcomes. On 27 February 2020, the protocol was revised to change the co–primary outcomes to a single primary outcome. The primary outcome was changed to the decision regarding ICD implantation for the video group compared with usual care, and the decision regarding ICD implantation by racial concordance was made a secondary outcome. This change was made before unblinding or any statistical analyses were done.
Setting and Participants
Patients were enrolled from 14 sites in the United States that included private and public academic institutions and community practices (Supplement Table 1, available at Annals.org). In September 2017, the site at the University of California, San Francisco, was closed due to challenges with site-based research at its community hospital. Patients were enrolled from ambulatory electrophysiology clinics, as the decision-making process in the ambulatory setting differs from that for hospitalized patients considering ICD implantation.
Members of the study team at each site determined ICD candidacy before or during the scheduled encounter and introduced the study to the patient. At the time of the electrophysiology clinic encounter, for patients who opted to participate, a study team member reviewed study procedures and obtained informed consent. Patients were eligible for inclusion if they were not hospitalized, had an ejection fraction of 35% or less, had New York Heart Association (NYHA) class I to III symptoms of heart failure, were aged 18 years or older, and self-identified as Black or African American. Exclusion criteria were consistent with class III recommendations from the consensus guidelines from the American Heart Association, the American College of Cardiology, and the Heart Rhythm Society, which recommend ICD implantation for primary prevention of SCA in patients with systolic heart failure (23). Patients with a planned subcutaneous ICD implant were also excluded (Supplement Table 2, available at Annals.org). The 1 patient who was classified as having NYHA class IV symptoms and was being considered for advanced heart failure therapies was deemed to be an ICD candidate. The patient was enrolled, as the exclusion criteria did not explicitly state that patients with class IV symptoms could not be enrolled.
Randomization and Interventions
To ensure that each intervention was equally represented within each site, the trial statistician generated a random permuted block design with block size of 3 for each group within each site. Randomization was stratified by site to account for differences in site characteristics. Study participants were aware that there were 2 videos but were blinded to differences between them. Blinding of clinicians was not feasible given the type of intervention and the design of the study. The study followed the CONSORT (Consolidated Standards of Reporting Trials) reporting guidelines for randomized clinical trials (Figure). There were no crossovers of assignments during the trial.
Figure.
Study flow diagram. The figure shows participant inclusion from prescreening to randomization, culminating in the analysis of the primary and secondary outcomes. * At this time point, we attempted to contact participants via a telephone call from the study call center to ascertain their decision regarding implantation of an implantable cardioverter-defibrillator and to administer the decisional conflict scale and the knowledge questionnaire. The number shown represents the number of participants who could not be reached.
Decision Support Video
The development and pilot testing of our video-based decision support tool have been described previously (20). The videos contained educational segments with animation, physician commentary, and narratives from actual patients with ICDs who spanned various ages, socioeconomic backgrounds, and education levels. Each video followed the same conceptual framework, and the viewing time for each was approximately 26.5 minutes (Supplement Table 3, available at Annals.org).
Usual Care
The usual care group included clinician counseling and informational handouts used by many practices to discuss ICD implantation decisions with their patients but did not include the interventional video. Participants randomly assigned to usual care had no change in the routine way their clinician, health system, or practice shared information to assist with the decision about ICD implantation. We collected survey data on what usual care entailed at the site level at the onset and conclusion of the study. Among the 14 sites that were participating at the beginning of the study, 64% reported routinely using tools to support the clinical team in discussing ICD implantation with study participants. The most common tools were handouts (71%). At the conclusion of the study, 11 of the remaining 13 sites reported information about usual care practices. Among these, 2 sites reported use of a decision support tool other than a video or handout that was not in use at baseline.
In February 2018, the Centers for Medicare & Medicaid Services (CMS) amended the national coverage determination to require an SDM interaction before ICD implantation for patients with primary prevention indications. Sites were queried about how the CMS mandate changed their approach to SDM. Among the sites that provided information on usual care practices at the conclusion of the study, 4 indicated no change in their SDM practices, 5 had begun using a decision support tool routinely, 1 had increased its use of written information, and 1 was considering creating its own video-based decision support tool (Supplement Figure, available at Annals.org).
Outcomes and Follow-up
The primary outcome was the decision regarding ICD implantation, assessed at 7 days after randomization. The 2 video groups were combined, and the percentage of participants assenting to an ICD in the overall video group was compared with the percentage in the usual care group.
Secondary outcomes included ICD implantation within 90 days of enrollment, participant knowledge, decisional conflict, and the effect of racial concordance between study participants and patients and clinicians in the video on the decision regarding ICD implantation. A previously validated knowledge score (scale of 0 to 13) and decisional conflict score (scale of 0 to 100) were used to assess knowledge of SCA and ICD therapy and decisional conflict (20) (see Appendix A in the Supplement, available at Annals.org). Finally, the time patients spent with clinicians was tracked during the encounter by research assistants and study coordinators using Apple iPad timers and was compared between the video and usual care groups (see the Technical Appendix in the Supplement, available at Annals.org).
Statistical Analysis
Power
For the primary outcome, based on data from the pilot study, we estimated 20% higher assent to ICD implantation in the combined video group compared with the usual care group, with an assent rate of 60% for those assigned to the video groups. With an effect size of 20%, 294 patients were needed for 90% power.
Analysis of the Primary Outcome
The proportion of patients in the combined video group who assented to ICD implantation was compared with the proportion in the usual care group using the Pearson χ2 test. As mentioned earlier, in February 2018, CMS amended the national coverage determination to require an SDM interaction before ICD implantation. Given the potential for this policy change to affect comparisons with usual care, the CMS mandate status was characterized as a binary variable (before vs. after the mandate was implemented), and its interaction with the treatment assignment variable was assessed using a logistic regression model to determine the effect on our primary outcome. The model was adjusted for other variables that may affect the decision regarding ICD implantation (educational attainment, marital status, type of cardiomyopathy, NYHA class, preintervention knowledge, and decisional conflict score). If the interaction was significant at the 0.05 level, estimates of the treatment effect (with CIs) were provided across levels of the variable.
Analysis of Secondary Outcomes
ICD Implantation Rates
The proportions of patients with an ICD implanted within 90 days of study enrollment were compared between the groups using the Pearson χ2 test.
Knowledge and Decisional Conflict
The association of treatment assignment with knowledge score and decisional conflict after the intervention was determined via a linear regression (analysis of covariance) that included treatment assignment as an independent variable while adjusting for preintervention scores, as advocated by Vickers and Altman (24).
Effect of Racial Concordance on the Decision Regarding ICD Implantation Within 90 Days
We compared the 2 video groups—with Black participants (concordant) and with White participants (discordant)—using the same analyses described earlier for the primary outcome.
Time Spent With the Clinician
The t test was used for comparisons of continuous variables between the video and usual care groups.
Missing Data
Fewer than 6% of participants had missing data; therefore, we used complete-case analysis. We did not perform sensitivity analyses because of the low rate of missingness. Details and patterns of missing data by intervention are provided in Supplement Table 4 (available at Annals.org).
Role of the Funding Source
The funders had no role in the design of the study; collection, management, analysis, or interpretation of the data; writing of the manuscript; or the decision to submit the manuscript for publication.
Results
Participant Characteristics
Overall, 12 598 patients were screened across the 14 sites. Of the 457 eligible patients, 343 were enrolled, for an enrollment rate of 75%. The study enrolled and randomly assigned 343 Black patients to a video decision support tool with a Black clinician and Black patients (concordant) (n = 114), a video with a White clinician and White patients (discordant) (n = 114), or usual care (n = 115). Thirteen participants were withdrawn from the study after randomization (9 were found to be ineligible shortly after enrollment, 2 were eligible but were unable to complete the baseline visit, and 2 requested to be withdrawn). The analysis included 330 participants (108 in the racially concordant video group, 111 in the racially discordant video group, and 111 in the usual care group). Data on the primary outcome were available for 311 of the 330 participants who were eligible for the analysis (Figure). Characteristics of patients who were withdrawn from the study and those who did not have data on the primary outcome are provided in Supplement Table 4.
Baseline characteristics were balanced across groups (Table 1). The mean age of the participants was 59.6 years, and 36.8% were women. The mean ejection fraction was 24.9%, 68.1% of participants had a nonischemic cause of their systolic heart failure, and approximately 94% had NYHA class II or III symptoms.
Table 1.
Participant Characteristics at Baseline*
| Characteristic | Video Group (n = 219) |
Usual Care Group (n = 111) |
All Participants (n = 330) |
|---|---|---|---|
| Mean age (SD), y | 59.1 (12.4) | 60.4 (11.8) | 59.6 (12.2) |
| Women, n (%) | 86 (39.4) | 35 (31.5) | 121 (36.8) |
| Highest educational attainment, n (%) | |||
| None | 2 (0.9) | 2 (1.9) | 4 (1.3) |
| Grade school | 10 (4.7) | 10 (9.3) | 20 (6.3) |
| High school | 91 (43.1) | 43 (39.8) | 134 (42.0) |
| High school equivalency certificate | 12 (5.7) | 9 (8.3) | 21 (6.6) |
| College or technical school | 69 (32.7) | 36 (33.3) | 105 (32.9) |
| Graduate or professional degree | 21 (10.0) | 7 (6.5) | 28 (8.8) |
| Prefer not to answer | 6 (2.8) | 1 (0.9) | 7 (2.2) |
| Annual household income, n (%) | |||
| <$7500 | 38 (18.3) | 14 (13.2) | 52 (16.6) |
| $7501–$15 000 | 28 (13.5) | 21 (19.8) | 49 (15.6) |
| $15 001–$25 000 | 31 (14.9) | 12 (11.3) | 43 (13.7) |
| $25 001–$75 000 | 46 (22.1) | 23 (21.7) | 69 (22.0) |
| $75 001–$100 000 | 13 (6.2) | 5 (4.7) | 18 (5.7) |
| >$100 000 | 10 (4.8) | 3 (32.8) | 13 (4.1) |
| Prefer not to answer | 42 (20.2) | 28 (26.4) | 70 (22.3) |
| “Yes” answers on PHQ-2, n (%) | |||
| Has patient been depressed every day in the past 2 weeks? | 41 (18.9) | 22 (19.8) | 63 (19.2) |
| Has patient been less able to enjoy things in the past 2 weeks? | 99 (45.6) | 50 (45.5) | 149 (45.6) |
| Mean HRQL SF-12 score (scale of 0–100) (SD) | |||
| Physical Component Summary | 39.9 (9.9) | 37.4 (9.7) | 39.0 (9.9) |
| Mental Component Summary | 50.9 (10.6) | 50.9 (11.6) | 50.9 (10.9) |
| Medical history, n (%) | |||
| Atrial fibrillation | 34 (15.5) | 13 (11.8) | 47 (14.3) |
| Coronary artery bypass grafting | 24 (11.0) | 14 (12.7) | 38 (11.6) |
| Percutaneous coronary intervention | 36 (16.4) | 16 (14.5) | 52 (15.8) |
| Diabetes mellitus | 97 (44.3) | 48 (43.6) | 145 (44.1) |
| High blood pressure | 195 (89.0) | 97 (88.2) | 292 (89.0) |
| Hyperlipidemia | 111 (50.7) | 64 (58.2) | 175 (53.2) |
| Myocardial infarction | 44 (20.1) | 20 (18.2) | 64 (19.5) |
| Pulmonary disease | 26 (11.9) | 18 (16.4) | 44 (13.4) |
| Renal insufficiency | 39 (17.8) | 30 (27.3) | 69 (21.0) |
| Syncope | 23 (10.5) | 7 (6.4) | 30 (9.1) |
| Mean left ventricular ejection fraction (SD), % | 25.1 (7.0) | 24.6 (7.1) | 24.9 (7.0) |
| Most recent NYHA class, n (%) | |||
| I | 10 (4.9) | 7 (6.7) | 17 (5.5) |
| II | 118 (58.1) | 118 (60.0) | 178 (58.0) |
| III | 74 (36.5) | 37 (35.6) | 111 (36.2) |
| IV† | 1 (0.5) | 0 (0.0) | 1 (0.3) |
| Mean QRS interval on electrocardiogram (SD), ms | 111.1 (25.2) | 117.2 (27.4) | 113.1 (26.1) |
| Type of cardiomyopathy, n (%) | |||
| Ischemic | 59 (26.9) | 32 (29.1) | 91 (27.7) |
| Nonischemic | 150 (68.5) | 74 (67.3) | 224 (68.1) |
| Mixed | 10 (4.6) | 4 (3.6) | 14 (4.3) |
| Medication history, n (%) | |||
| ACEi/ARB | 68 (71.7) | 75 (68.8) | 232 (70.7) |
| Aldosterone antagonist | 56 (25.6) | 25 (22.7) | 81 (24.6) |
| β-Blocker | 206 (94.1) | 101 (92.7) | 307 (93.6) |
| Digoxin | 7 (3.2) | 5 (4.5) | 12 (3.6) |
| Amiodarone | 15 (6.8) | 7 (6.4) | 22 (6.7) |
| Oral anticoagulant | 74 (33.8) | 39 (35.5) | 113 (34.3) |
| Antiplatelet | 108 (49.3) | 53 (48.2) | 161 (48.9) |
ACEi = angiotensin-converting enzyme inhibitor; ARB = angiotensin-receptor blocker; HRQL SF-12 = Health-Related Quality of Life Short Form-12; NYHA = New York Heart Association; PHQ-2 = Patient Health Questionnaire-2.
Some participants declined to answer certain demographic questions. The following items had missing data: age (n = 1), gender (n = 1), educational attainment (n = 11), household income (n = 16), PHQ-2 question about being depressed (n = 2), PHQ-2 question about being less able to enjoy things (n = 3), HRQL SF-12 (n = 1), medical history (n = 1), left ventricular ejection fraction (n = 2), NYHA class (n = 23), QRS interval (n = 3), type of cardiomyopathy (n = 3), ACEi use (n = 2), aldosterone antagonist use (n = 1), β-blocker use (n = 2), digoxin use (n = 1), amiodarone use (n = 1), oral anticoagulant use (n = 1), and antiplatelet use (n = 1).
One patient who was classified as having NYHA class IV symptoms and was being considered for advanced heart failure therapies was deemed to be a candidate for an implantable cardioverter-defibrillator.
Assessment of markers of social determinants of health (SDOH) showed that 41.4% of participants were married and 31.6% reported being single and never married. Forty-two percent of participants completed high school, and 32.9% were college or technical school graduates. Among those who reported their annual household income, more than half reported an income between $7501 and $75 000, and 16.6% reported an income below $7500; 23.7% worked full-time, and 29.4% lived more than 30 miles from their electrophysiology clinic. In addition, 64.8% reported being depressed or experiencing symptoms of anhedonia (Table 1).
Among participants in the video group, assent to ICD implantation was 58.6% (95% CI, 51.6% to 65.2%), compared with 59.4% (CI, 49.2% to 68.9%) in the usual care group (difference, −0.8 percentage point [CI, −13.2 to 11.1 percentage points]). One third of participants were unsure of their decision, and approximately 8% declined ICD implantation at 7 days after exposure to the intervention; there was no statistically significant difference between the video and usual care groups (Table 2). No intervention interaction was observed with regard to the CMS mandate for an SDM encounter for ICD implantation. Rates of ICD implantation within 90 days were 64.8% in the video group and 66.7% in the usual care group (difference, −2.4 percentage points [CI, −13.9 to 9.1 percentage points]) (Table 2).
Table 2.
Primary and Secondary Outcomes, by Intervention
| Outcomes | Video Group (n = 219) | Usual Care Group (n = 111) | P Value |
|---|---|---|---|
| Primary outcome: ICD decision at 7 d, n (% [95% CI])* | 0.99 | ||
| Yes | 123 (58.6 [51.6 to 65.2]) | 60 (59.4 [49.2 to 68.9]) | |
| No | 17 (8.1 [4.9 to 12.9]) | 8 (7.9 [3.7 to 15.5]) | |
| Unsure | 70 (33.3 [27.1 to 40.2]) | 33 (33 [23.9 to 42.8]) | |
| Secondary outcomes | |||
| ICD implantation at 90 d, n (% [95% CI]) | 142 (64.8 [58.1 to 71.1]) | 74 (66.7 [57.6 to 75.7]) | 0.66 |
| Knowledge score (scale of 0–13)† | |||
| Mean score before intervention (SD) | 6.0 (5.7 to 6.3) | 6.1 (5.6 to 6.6) | 0.73 |
| Mean score 1 wk after intervention (SD) | 9.0 (8.7 to 9.3) | 8.4 (8.0 to 8.8) | 0.010 |
| Adjusted mean difference (95% CI)‡ | 0.7 (0.2 to 1.1) | 0.003 | |
| Decisional conflict score (scale of 0–100)§ | |||
| Mean score before intervention (SD) | 33.5 (31.2 to 35.8) | 36.3 (32.9 to 39.7) | 0.170 |
| Mean score 1 wk after intervention (SD) | 22.9 (21.1 to 24.8) | 26.3 (23.3 to 29.2) | 0.047 |
| Adjusted mean difference (95% CI)‡ | −2.6 (−5.7 to 0.4) | 0.088 | |
| Time spent with clinician, min | |||
| Mean time (SD) | 22.1 (17.0) | 27.0 (20.8) | 0.027 |
| Difference (95% CI) | −4.9 (−9.4 to −0.3) | ||
ICD = implantable cardioverter-defibrillator.
Data were available for 311 participants (210 [96%] in the video group and 101 [91%] in the usual care group).
Data on knowledge score before the intervention were available for 218 participants in the video group and 111 in the usual care group. Data on knowledge score 1 week after the intervention were available for 216 participants in the video group and 111 in the usual care group.
Adjusted for scores before the intervention.
Data on decisional conflict score before the intervention were available for 218 participants in the video group and 111 in the usual care group. Data on decisional conflict score 1 week after the intervention were available for 208 participants in the video group and 102 in the usual care group.
The adjusted mean knowledge score after the intervention was 0.7 point higher (CI, 0.2 to 1.1 points; P = 0.003) in the video group than in the usual care group. The adjusted mean decisional conflict score 1 week after the intervention was lower in the video group (22.9 [CI, 21.1 to 24.8]) than in the usual care group (26.3 [CI, 23.3 to 29.2]), but the difference was not statistically significant (−2.6 [CI, −5.7 to 0.4]; P = 0.088).
Effect of Racial Concordance on Assent to ICD Implantation
There was no difference in assent to ICD implantation between participants who viewed the racially concordant video (54 of 102 [52.9%]) and those who viewed the racially discordant video (69 of 108 [63.9%]) (difference, −11 percentage points [CI, −24 to 3 percentage points]) (Table 3).
Table 3.
Racial Concordance, by Video Group*
| Outcome | Concordant Video Group (n = 108) | Discordant Video Group (n = 111) | P Value |
|---|---|---|---|
| ICD decision at 7 d, n (% [95% CI]) | 0.21 | ||
| Yes | 54 (52.9 [42.8–62.8]) | 69 (63.9 [54.0–72.7]) | |
| No | 8 (7.8 [3.7–15.3]) | 9 (8.3 [4.1–15.6]) | |
| Unsure | 40 (39.2 [29.8–49.4]) | 30 (27.8 [19.8–37.4]) |
ICD = implantable cardioverter-defibrillator.
Data were available for 200 participants (102 in the concordant video group and 108 in the discordant video group).
Time Spent With the Clinician
Participants in the video group spent less time with their provider (mean, 22.1 minutes) than participants in the usual care group (mean, 27.0 minutes) (difference, −4.9 minutes [CI, −9.4 to −0.3 minutes]).
Assent to ICD implantation was assessed by presence of renal insufficiency, NYHA class, and study site. Twenty-one percent of patients had a history of renal insufficiency (17.8% in the video group and 27.3% in the usual care group). Assent to ICD implantation was 58.2% among patients with renal insufficiency and 59.3% among those without renal insufficiency. In the video group, patients with renal insufficiency were more likely to assent to an ICD than those without renal insufficiency. Conversely, in the usual care group, patients with renal insufficiency were less likely than those without renal insufficiency to assent to an ICD. Assent to ICD implantation was 70.2% among patients with NYHA class III symptoms, 53.3% for those with NYHA class II symptoms, and 60.0% for those with NYHA class I symptoms, and assent did not differ by randomization group. Assent to ICD implantation varied across sites, ranging from 40.7% to 100%. Academic sites had a slightly higher assent rate than community sites (60.6% and 55.6%, respectively) (Supplement Table 5, available at Annals.org).
Discussion
VIVID was a multicenter randomized clinical trial that evaluated the effect of an encounter-based video decision support tool on decision making for ICD implantation in a sample of Black adults with heart failure who were at risk for SCA. Approximately 60% of the participants assented to ICD implantation, and there was no difference between the video and usual care groups. Although there was lower decisional conflict among participants in the video group than in the usual care group, the difference was not statistically significant. Overall, 66% of the participants had an ICD implanted within 90 days of study enrollment, and there were no differences between the video and usual care groups. Compared with usual care, the decision support video increased patient knowledge and decreased the time clinicians spent with participants. A racially concordant video that featured Black patients and a Black clinician did not increase assent to ICD implantation compared with a racially discordant video that included White patients and a White clinician.
To our knowledge, this is the first randomized study to assess the effect of a decision support tool for ICD implantation among Black patients (based on a search of PubMed and MEDLINE on 12 December 2022 for publications in English using the keywords disparities, inequities, Black race, cardiovascular disease, and implantable cardioverter defibrillator). We found no differences in assent to ICD implantation between the video and usual care groups, which is consistent with other studies of SDM support tools in cardiovascular disease. Notably, other cardiovascular studies have shown a decrease in intervention uptake relative to usual care with use of a decision support tool (25, 26). Allen and colleagues (27) assessed the effectiveness of a shared decision support intervention for patients considering destination therapy with a left ventricular assist device. They found no differences in decisional conflict between the intervention and control groups, and patient-reported treatment choice at 1 month favored device therapy more in the control group (95%) than in the intervention group (59%) (P < 0.001). Moreover, rates of device implantation by 6 months were 80% in the control group and 54% in the intervention group. In the VIVID study, the ICD implantation rate by 90 days was 66% and did not differ by treatment group.
The VIVID pilot study found an increase in assent to ICD implantation in Black patients in the video group compared with the usual care group while having assent rates that were similar overall to rates in this study (approximately 60%) (20). There are several potential reasons for the different findings. The findings of the pilot study, which included 59 patients (22 of whom were Black), may have been attributable to chance. Contemporary usual care may have improved partly because of the CMS requirement for SDM, although our analysis did not reveal differences in the outcome before and after the CMS mandate. Although it is difficult to ascertain with this study design, bias among clinicians may be decreasing, thus improving communication with patients and improving usual care.
There are probably multiple contributors to Black patients being less likely to assent to ICD implantation, including adverse SDOH and cultural values; patient and clinician communication; health system–related factors, such as access to care; insurance coverage; and patient comorbidities. Despite the use of decision support videos that improved patient knowledge, there was a 40% refusal rate for ICD implantation, and uncertainty remained around the decision regarding implantation. Patients were enrolled from electrophysiology clinics because they had overcome the barrier of referral to subspecialty care, which is a known impediment to health equity. Consequently, in this study, access to care does not appear to explain ICD uptake. Overall, with the exception of younger age, patients in this study had clinical profiles similar to those of patients with heart failure in prior clinical trials of ICDs; thus, differences in clinical profiles are unlikely to explain the findings (28). The aversion to risk related to cardiac procedures in Black communities is prevalent and complex in its underpinnings, and it represents additional opportunities for research that examines the effect of measures of SDOH on ICD decision making and qualitative research methods that offer more granular insights.
Clinicians caring for patients in the video group spent less time with patients. Time constraints have been cited as a barrier to routine adoption of SDM (29, 30). Clinicians are under constant pressure to see more patients and engage with electronic health records, which reduces the time that is available for patient interaction. Although this study did not assess time with clinicians among White patients, data support the notion that when time pressures exist, clinicians’ biases and stereotypes about certain populations are more likely to emerge and negatively affect provider–patient communication, which in turn negatively affects the SDM process for Black patients (31, 32).
This study did not capture data on insurance status, which may have influenced decision making. Given the predominance of non-Black clinicians participating in the study, we were unable to account for concordance between the patient’s race and the clinician’s race, which may have affected the decision regarding ICD implantation. The study did not incorporate the OPTION (Observing Patient Involvement) scale, a psychometric measure that assesses the extent to which clinicians involve patients in the decision-making process, which may have provided insights into usual care throughout the study (33). Finally, we targeted persons who had access to highly specialized care, defined by their presence in a cardiac electrophysiology clinic; consequently, our findings are not generalizable to patients who, for various reasons, including adverse SDOH, may not have this degree of access to care.
In conclusion, among Black patients who were eligible for an ICD, use of an encounter-based video decision support tool increased patient knowledge but did not affect assent to ICD implantation or actual ICD implantation compared with usual care.
Supplementary Material
Financial Support:
This work was supported by a Patient-Centered Outcomes Research Institute Program Award (contract number AD-1503–29746).
Footnotes
Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M22-2934.
Data Sharing Statement: The authors have indicated they will not be sharing data.
Supplement. Supplemental Material
Supplement Study Protocol. VIVID Study Protocol
Contributor Information
Kevin L. Thomas, Department of Medicine and Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina.
Sana M. Al-Khatib, Department of Medicine and Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina.
Andrzej S. Kosinski, Duke Clinical Research Institute, Durham, North Carolina.
Samuel F. Sears, Jr., Department of Psychology, East Carolina University, Greenville, North Carolina.
Nancy M. Allen LaPointe, Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina.
Larry R. Jackson, II, Department of Medicine, Duke University School of Medicine, Duke Clinical Research Institute, Durham, North Carolina.
Daniel D. Matlock, Division of Geriatric Medicine, University of Colorado School of Medicine, Aurora, Colorado.
Daniel Haithcock, Georgia Arrhythmia Associates, Macon, Georgia.
B. Judson Colley, III, Jackson Heart Clinic, Jackson, Mississippi.
David S. Hirsh, Department of Medicine, Emory University, Atlanta, Georgia.
Eric D. Peterson, Department of Medicine, University of Texas Southwestern, Dallas, Texas.
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