Dissemination and Implementation of a Community Health Worker Intervention for Disparities in Palliative Care (DeCIDE PC): a study protocol for a hybrid type 1 randomized controlled trial
BMC Palliative Care volume 22, Article number: 139 (2023)
There are persistent racial and ethnic health disparities in end-of-life health outcomes in the United States. African American patients are less likely than White patients to access palliative care, enroll in hospice care, have documented goals of care discussions with their healthcare providers, receive adequate symptom control, or die at home. We developed Community Health Worker Intervention for Disparities in Palliative Care (DeCIDE PC) to address these disparities. DeCIDE PC is an integrated community health worker (CHW) palliative care intervention that uses community health workers (CHWs) as care team members to enhance the receipt of palliative care for African Americans with advanced cancer. The overall objectives of this study are to (1) assess the effectiveness of the DeCIDE PC intervention in improving palliative care outcomes amongst African American patients with advanced solid organ malignancy and their informal caregivers, and (2) develop generalizable knowledge on how contextual factors influence implementation to facilitate dissemination, uptake, and sustainability of the intervention.
We will conduct a multicenter, randomized, assessor-blind, parallel-group, pragmatic, hybrid type 1 effectiveness-implementation trial at three cancer centers across the United States. The DeCIDE PC intervention will be delivered over 6 months with CHW support tailored to the individual needs of the patient and caregiver. The primary outcome will be advance care planning. The treatment effect will be modeled using logistic regression. The secondary outcomes are quality of life, quality of communication, hospice care utilization, and patient symptoms.
We expect the DeCIDE PC intervention to improve integration of palliative care, reduce multilevel barriers to care, enhance clinic and patient linkage to resources, and ultimately improve palliative care outcomes for African American patients with advanced cancer. If found to be effective, the DeCIDE PC intervention may be a transformative model with the potential to guide large-scale adoption of promising strategies to improve palliative care use and decrease disparities in end-of-life care for African American patients with advanced cancer in the United States.
Registered on ClinicalTrials.gov (NCT05407844). First posted on June 7, 2022.
Background and rationale
Palliative care is an interdisciplinary approach that aims to improve the quality of life (QOL) of patients with advanced stage illnesses and their families . The American Society of Clinical Oncology (ASCO) recommends early integration of palliative care for all patients with advanced cancer . This approach enables early identification and management of distressing physical, psychosocial, and spiritual issues, facilitates communication and support throughout decision-making processes, and enhances the receipt of goal-concordant care [3, 4].
There are persistent racial and ethnic health disparities in end-of-life health outcomes in the United States. African American patients are less likely than White patients to access or receive palliative care, receive adequate pain control, or enroll in hospice services, all of which results in unnecessary suffering at the end-of-life [5,6,7]. Physician or patient-initiated referral to palliative care is the standard of cancer care for patients with advanced cancer in the United States, but stark and worsening disparities in outcomes suggest this model may be inadequate for African Americans, especially when considering cultural influences and underlying social determinants of health (SDOH). The totality of these disparities results in African American patients failing to receive goal-concordant end-of-life care [5, 6, 8, 9].
Multiple randomized controlled trials have demonstrated the benefit of diverse interventions to improve palliative care utilization; however, few have been implemented [10, 11]. Literature often fails to comprehensively account for multilevel barriers when evaluating existing palliative care programs. Moreover, the lack of racial and ethnic representation in existing studies fails to provide insight into the role of culture and underlying SDOH in palliative care utilization [8, 12]. Furthermore, the opinions and needs of stakeholders (patients, caregivers, oncologists, palliative care providers, and cancer center leaders) have not been adequately addressed and require further evaluation. Lastly, successful studies often fail to consider the role of implementation or dissemination of their findings, which perpetuates the lack of quality palliative and end-of-life care .
Community health workers (CHWs) are non-clinician public health workers who can improve care consistency by addressing SDOH and helping patients from underserved communities overcome barriers to health care. Numerous studies have demonstrated the ability of CHWs to decrease care disparities across multiple levels, settings, and diseases [14,15,16]. CHWs bridge the gap between communities and the healthcare system by delivering culturally sensitive and contextually appropriate care. This has been shown to improve healthcare engagement, self-management, self-efficacy, treatment plan adherence, and health outcomes [17,18,19].
We developed an integrated community health worker (CHW) palliative care intervention, Community Health Worker Intervention for Disparities in Palliative Care (DeCIDE PC). The DeCIDE PC intervention is a theory-driven, stakeholder-informed palliative care intervention, which utilizes CHWs as care team members to enhance the receipt of palliative care for African Americans with advanced cancer [20, 21]. In this role, CHWs may help patients and their families overcome barriers in the adoption of palliative care services by improving provision of non-physician support services, enhancing palliative care education, helping patients navigate the healthcare system, advocating for patients and their families within the healthcare setting, and empowering patients to discuss goals of care and advance care planning (ACP) with their families and care teams. A pilot study demonstrated that this intervention was acceptable, feasible, and effective at mitigating the adverse impact of SDOH and improving palliative care outcomes, such as completion of advance directives. The collective experience of our study team highlights the potential benefit of the DeCIDE PC intervention and supports further investigation [20, 21].
The overall objectives of this study are to:
Assess the effectiveness of the DeCIDE PC intervention in improving palliative care outcomes amongst African American patients with advanced solid organ malignancy and their informal caregivers, and
Develop generalizable knowledge on how contextual factors influence implementation to facilitate dissemination, implementation, and sustainability of the intervention.
These objectives will be accomplished through three specific aims, which are to:
Refine the DeCIDE PC intervention to address multilevel implementation barriers,
Compare the effectiveness of the DeCIDE PC intervention to enhanced standard of care in improving palliative care outcomes, and
Evaluate the implementation of the DeCIDE PC intervention.
We hypothesize that the DeCIDE PC intervention will improve ACP (primary outcome), QOL (principal secondary outcome), and other palliative care outcomes in African American patients with advanced cancer. Further, we anticipate that the findings from this project will inform wider implementation and scale-up of the DeCIDE PC intervention.
We will first use a mixed methods approach to refine the DeCIDE PC intervention by addressing multilevel implementation barriers (Aim 1). This stage will involve gathering input from patients and caregivers through patient-caregiver dyad focus groups and eliciting input from stakeholders in oncology, palliative care, and the community through baseline key informant interviews. Additionally, we will initiate annual environmental scans and establish a Community Advisory Board (CAB) at each enrollment site. The site-specific CABs will be comprised of patients, family members, community members, and health system members. We will aim to recruit 8–10 members at each site. The CABs will meet quarterly and will be asked to review and provide feedback on recruitment and retention approaches, data collection procedures, intervention content and delivery, interpretation of results, and dissemination of findings. Following Aim 1, we will evaluate the effectiveness of the DeCIDE PC intervention in improving palliative care outcomes in African American patients with advanced cancer and their informal caregivers compared to enhanced standard of care (Aim 2). This will be accomplished through a multicenter, randomized, assessor-blind, parallel-group, pragmatic, hybrid type 1 effectiveness-implementation trial with a 1:1 allocation ratio. Finally, we will use a mixed methods approach and employ the CFIR (Consolidated Framework for Implementation Research) and RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) frameworks to evaluate implementation of the DeCIDE PC intervention (Aim 3). This will be achieved through multilevel analysis of intervention delivery and qualitative interviews. An overview of the study design is outlined in Fig. 1. This paper will focus on the protocol related to Aim 2, the randomized controlled trial.
This study will take place at three cancer centers across the United States: Johns Hopkins Hospital (Broadway and Bayview campuses, Baltimore, Maryland), the University of Alabama at Birmingham Hospital (Birmingham, Alabama), and TidalHealth Peninsula Regional (Salisbury, Maryland). These sites were strategically chosen as they represent different socioeconomic, cultural, and demographic features of the African American community, and have established CHW programs.
The intervention will target patients with advanced cancer and their self-designated informal caregivers (patient-caregiver dyads). Eligibility criteria for patients: Adult (≥ 18 years old) patients who (1) self-identify as African American, (2) have advanced solid organ malignancy (AJCC stage III or IV), (3) are English speaking, (4) have intact cognition and an ability to provide informed consent, and (5) have not had any palliative care experience within the last year. Exclusion criteria for patients include: (1) age < 18 years old, (2) unable to read or comprehend English, (3) unable to provide informed consent, and (4) palliative care experience within the last year. Eligibility criteria for caregivers: Adult (≥ 18 years old) caregivers who (1) provide informal (unpaid) care to an eligible African American cancer patient (related or unrelated), (2) are English speaking, and (3) have intact cognition and an ability to provide informed consent. Exclusion criteria for caregivers include: (1) age < 18 years old, (2) unable to read or comprehend English, and (3) unable to provide informed consent. In instances where no caregiver is available or willing to participate, patients will remain eligible to participate in the study individually. The participant flowchart is outlined in Fig. 2.
Study coordinators will approach potential participants in-person or via telephone to discuss the study goals, risks, and alternatives, and obtain oral and written informed consent. Participants will identify a caregiver and a separate informed consent will be obtained.
Additional consent provisions for collection and use of participant data and biological specimens
There are no additional consent provisions for this study.
Intervention group – DeCIDE PC intervention
Participants in the intervention group will receive the DeCIDE PC intervention in addition to standard of care. Following study enrollment, participants randomized to the DeCIDE PC intervention group will be connected with the CHW at their enrollment site. The CHWs will then meet with the patient-caregiver dyad or the patient alone to perform a baseline assessment of their SDOH and barriers to healthcare. Following the baseline assessment, CHWs will perform weekly check-ins and tailor ongoing support to the individual needs of the patient and caregiver. CHWs will have access to the electronic medical record (EMR) at their respective sites to follow their patients’ course of care and communicate with the clinical team through patient notes and direct messaging. The CHW intervention activities will include educating patients on palliative and hospice care, facilitating palliative and hospice care referrals and care team communications, linking patients to community-based resources, empowering patients to discuss their goals of care with their oncologists and encouraging patients to discuss advance care planning with their caregivers and families, removing barriers to care by addressing SDOH, and providing instrumental, logistical, and emotional support [21, 23, 24]. This intervention will be refined based on the findings from Aim 1, which will include input from patients and caregivers, stakeholders, the CAB, and the baseline environmental scan.
We will hire and train one CHW at each enrollment site in the first year of the study. All CHWs will undergo a three-month CHW training program, which will include a combination of synchronous (didactic and problem-based sessions, communication and motivational interviewing skills training), asynchronous, and experiential training components. For the purposes of program evaluation, all CHWs will complete pre- and post-training tests to assess knowledge gain, perceived competence, and satisfaction with the training. CHWs will also undergo longitudinal training throughout the study period. We will also onboard a Palliative Care Liaison at each enrollment site, who will be a member of the palliative care team and will serve as a resource and source of support for the CHW throughout the study. Finally, CHWs will have access to up-to-date palliative care content from national organizations, such as the Center to Advance Palliative Care (CAPC).
Choice of comparator
Comparator group – enhanced standard of care
Participants in the comparison group will receive standard of care in accordance with national and local guidelines for management of their disease. Due to the many known benefits of palliative care for patients with advanced cancer, a brochure on palliative care and its service offerings will also be provided to patients within the enhanced standard of care pathway at the time of enrollment. Additionally, patients may be referred to specialty palliative care at any time throughout the study period at their oncologist’s discretion.
Criteria for discontinuing or modifying allocated interventions
We will discontinue the study intervention at the participant’s request.
Strategies to improve adherence to interventions
To improve adherence to the intervention and survey completion, participants in each dyad will receive monetary compensation ($50 per participant, $100 per dyad) upon completion of the 6-month survey. If the patient passes away prior to administration of the 6-month survey, the patient’s caregiver or family will receive the monetary compensation.
Relevant concomitant care permitted or prohibited during the trial
Patients will be permitted to receive oncologic care throughout the trial. Oncologists may refer patients in the enhanced standard of care group to speciality palliative care, however, to prevent crossover between groups throughout the trial, cannot refer patients to CHW support. Participants will be prohibited from participating in concomitant clinical trials in palliative care.
Provisions for post-trial care
We do not anticipate that participants will suffer harm from trial participation, and therefore do not anticipate the need for additional compensation or ancillary care. Patients will continue to receive oncological standard of care following study completion.
The primary, secondary, and exploratory outcomes are summarized in Table 3. The primary outcome for this study is ACP, defined as a self-reported or documented Advance Directive, such as a living will (LW) or durable power of attorney (DPOA), or a documented discussion of care preferences between the patient and caregiver or the patient and the healthcare team. ACP has been widely used and validated in palliative care studies [25, 26]. Our principal secondary outcome is QOL, measured by the Functional Assessment of Chronic Illness Therapy - Palliative Care (FACIT-Pal) . FACIT-Pal contains five subscales, including physical, social/family, emotional, and functional wellbeing, as well as palliative care. Participants will be provided with a list of statements and asked to rate each statement on a scale of 0 (not at all) to 4 (very much) based on their recollection of the last 7 days. The subscale scores will then be added to generate a total score, with higher scores reflecting a higher QOL. FACIT-Pal has also undergone extensive validation in palliative care studies [27, 28]. Other secondary outcomes include (1) Quality of Communication (QOC), measured by the QOC Questionnaire ; (2) hospice care utilization within 14 days of death; and (3) patient symptoms, measured by the Edmonton Symptom Assessment Scale (ESAS)  and the Center for Epidemiologic Studies Depression Scale (CES-D) .
The timetable for data collection is presented in Table 4. Research coordinators from each enrollment site will screen potential participants for eligibility, obtain informed consent, enroll patients and their caregivers, and perform random allocation. They will then conduct EMR review and administer surveys at baseline (t0), 2 months (t1), and 6 months (t2).
We calculated our sample size to ensure sufficient power to detect a clinically meaningful difference in both our primary outcome (ACP) and our principal secondary outcome (QOL) between the study arms. With an alpha of 0.05 and power of 90%, we estimate a sample size of 56 participant per study arm to detect a 30 percentage point difference in ACP at 6 months, based on effect sizes from previous studies and conservatively assuming that 30% of patients in the enhanced standard care arm will have ACP [26, 36]. After accounting for a 20% attrition rate over the study period, the adjusted final sample size based on our primary outcome is 70 participants per study arm (140 participants total). The sample size calculation based on our principal secondary outcome of QOL, measured by FACIT-Pal, is based on a recent study, which found that palliative care was associated with a standardized mean difference (SMD) in QOL of 0.46 (95% CI 0.08–0.83) . With an alpha of 0.05 and power of 80%, and after accounting for a 20% attrition rate, we estimate a sample size of 80 participants per study arm (160 participants total) to detect a SMD in QOL of 0.5. To ensure adequate power for both outcomes, we will plan to enroll 160 participants. We will seek to recruit a caregiver alongside each patient as a patient-caregiver dyad, but a lack of caregiver participation will not preclude a patient's enrollment. Our total potential sample size for the trial is therefore 320 participants, including 160 patients and 160 caregivers.
The three enrollment sites have well established cancer centers, albeit different patient volumes. Based on the patient volumes at the three enrollment sites, we anticipate that 40% of the patient-caregiver dyads (65 dyads) will be recruited from Johns Hopkins Hospital, 35% (55 dyads) from University of Alabama at Birmingham Hospital, and the remaining 25% (40 dyads) from TidalHealth Peninsula Regional. Study recruitment will occur over 2–4 years. The CAB from each enrollment site will provide insight and advice to guide ongoing recruitment.
Patient-caregiver dyads will be randomized in a 1:1 ratio into one of two groups, the DeCIDE PC intervention group or the enhanced standard of care group. To yield balanced groups, the random allocation sequence will be computer-generated with a block size of 6. Randomization will be stratified by cancer stage (AJCC stage III or IV). Allocation will be entered into the Research Electronic Data Capture (REDCap) database by a unblinded statistician at the central study site who is not directly involved in the study design, study conduct, or participant enrollment. Randomization will be performed immediately after enrollment by unblinded research coordinators through REDCap.
The principal investigators and lead statistician will be blinded to participant randomization. Due to the nature of the intervention, trial participants and oncologists will not be blinded. Additionally, the research coordinators and program manager will not be blinded to treatment allocation. We do not anticipate the need for unblinding, however, any inadvertent unblinding will be reported.
Data collection will be the responsibility of the research coordinators with oversight from the site principal investigators. Investigators will be responsible for ensuring the accuracy, completeness, legibility, and timeliness of the data collection.
Baseline demographics, medical history, performance status, and disease characteristics will be obtained from EMR review. The remaining data will be gathered from EMR review and surveys administered at baseline (within 1 week of enrollment), 2 months, and 6 months. Research coordinators will administer all surveys by telephone and record responses in the central REDCap database, stored on password protected computers on servers within Johns Hopkins University .
Plans to promote participant retention and complete follow-up
To promote participant retention and complete follow-up, research coordinators will make every effort to remain in contact with study participants throughout their time on the study. If a participant is not reachable within 2 weeks of the baseline, 2-month, and 6-month surveys, the research coordinators will attempt to regain contact through three telephone calls, scheduled visits for clinical care, and if necessary, a letter to the participant’s last known mailing address. These attempts will be documented in the participant’s medical record and study file. If issues with retention occur, these will be brought to the CABs to aid in addressing and correcting these issues.
The lead principal investigator and central study team will have access to the data sets from all three enrollment sites. The site principal investigators and research coordinators will only have access to their own site’s data. All electronic data will be stored on password protected computers on servers within Johns Hopkins University. All data collected using paper forms will be stored in a locked filing cabinet within an office assigned to the study team. Study data will be retained in a deidentified manner for 5 years following study completion.
We will assign each participant with a study ID, which will be stored securely on REDCap and will only be accessible to the study team. All stored data will be deidentified.
Plans for collection, laboratory evaluation and storage of biological specimens for genetic or molecular analysis in this trial/future use
This is not applicable to the study.
Statistical analysis plan
Intention-to-treat analysis will be used with each patient to be included in the group to which they were assigned at randomization regardless of adherence to the intervention or crossover. Descriptive statistics will be performed and presented as means with standard deviations, medians with ranges, or frequencies with proportions, overall and by study arm. To estimate the treatment effect on completion of ACP, we will use a logistic regression model with study arm as the primary predictor and enrollment site and cancer stage (AJCC stage III or IV) as the covariates. The exponentiated coefficient for the study arm will estimate the odds ratio of ACP comparing the intervention arm to the enhanced standard of care arm. Any other covariates that are differentially distributed by study arm will also be included in the model for adjustment. To estimate the treatment effect on QOL, we will use generalized mixed-effects linear regression modeling with a random intercept and robust variance estimate. We will use longitudinal generalized mixed-effects modeling methods for all other secondary outcomes. We will report the effect size, standard error, and 95% confidence interval for the estimate of the treatment effects at 6 months.
We do not anticipate significant safety issues associated with the study intervention or participation in the study. However, interim reports of enrollment, outcome completion and safety data will be prepared for the Data and Safety Monitoring Board (DSMB) on a pre-determined schedule. No formal interim analyses for efficacy or futility are planned unless requested by the DSMB.
We do not have any additional analyses planned.
Protocol non-adherence and missing data
We expect missing values to be minimal due to the ability to retrieve the outcome data even for patients who pass away or withdraw from the study through chart review and caregiver-provided information. Missing data on the baseline covariates are expected to be within 5%. Mixed-effects models can account for missing data under the assumption of missing at random (MAR), where it is assumed that missing scores depend on patient covariates in the model as well as the scores at previous time points. In addition, depending on the proportion of losses to follow-up, we will employ a different strategy for sensitivity analyses. If we observe > 5% missing data at the patient-level and an assumption of MAR is plausible, we will perform multiple imputation to address partial data. Missing outcome data will be imputed, and the treatment effect will be estimated under different scenarios to enable comparison of different sensitivity analyses.
Plans to give access to the full protocol, participant-level data and statistical code
We plan to make the full protocol, deidentified participant-level data, and the statistical code available from the corresponding author on reasonable request.
Oversight and monitoring
The coordinating center for this trial is Johns Hopkins University, School of Medicine, Department of Surgery, and Division of Surgical Oncology. The trial steering committee meets weekly and is comprised of the lead principal investigator, program manager, research coordinator, and lead CHW, as well as a senior research program coordinator and the clinical research program administrator within the Department of Surgery at Johns Hopkins University.
Data safety monitoring board
The DSMB is comprised of three independent health services researchers, a community health worker with related expertise, and an unblinded statistician who is not involved in study design or conduct. The DSMB will function independently from the research team throughout the trial to ensure that all study procedures are being performed in accordance with the study protocol. Meetings will be arranged via video conferencing to review protocols, procedures, and concerns related to research integrity. A charter has been established by DSMB members to guide its governance.
Adverse event reporting and harms
This study does not involve any invasive procedures and as such, there are minimal safety concerns for study participants. Participants will be provided with the lead principal investigator’s contact information and will be advised report any adverse events or potential harms directly to the principal investigator.
Frequency and plans for auditing trial conduct
Each enrollment site will perform internal quality control of study conduct, data collection, documentation, and completion.
Quality control at the central study site will include the following procedures: (1) the research coordinator will review documentation of the consenting process and completion of the consent documents; (2) the program manager and lead principal investigator will assess data quality on a monthly basis by conducting a random case review of 5% of all clinical data collected that month to assess for missing or incomplete data and excessive variability; (3) the study team will monitor consistent delivery of the study intervention at each enrollment site throughout the trial through monthly meetings and feedback from the lead CHW; (4) the study team will review protocol deviations on an ongoing basis and will implement corrective actions when the quantity or nature of deviations are deemed to be at a level of concern.
Plans for communicating important protocol amendments to relevant parties
Any significant modifications to the study protocol that could impact study conduct, potential benefits or harms to patients and their caregivers, or participant safety will require a formal protocol amendment. Protocol amendments will be agreed upon by investigators from all enrollment sites and approved by the institutional review board (IRB) at Johns Hopkins University prior to implementation.
The study findings will be presented to the CABs at each enrollment site. We will consider hosting a symposium for all stakeholders, including patients, caregivers, clinicians and other frontline clinical workers, health system leaders, community organizations, advocacy organizations, as well as payors and policymakers. The study findings will also be presented at national and international conferences and a manuscript outlining the study findings will be submitted to a high-impact journal for publication.
The DeCIDE PC intervention utilizes CHWs as palliative care team members with the goal of enhancing palliative care outcomes and reducing disparities for African American patients with advanced cancer. Upon completion of the clinical trial, we will evaluate the implementation of the DeCIDE PC intervention to identify facilitators and barriers to implementation. This will be performed through multilevel analysis of intervention delivery and qualitative interviews with key stakeholders who were involved in implementation of the intervention. We believe this will add insight and context to the summative findings from the effectiveness trial and will contribute to future dissemination efforts.
We expect the DeCIDE PC intervention to improve integration of palliative care, reduce barriers to care, enhance linkage to resources, and improve palliative care outcomes for African American patients with advanced cancer. If found effective, DeCIDE PC may be a transformative model with the potential to guide large-scale adoption of promising strategies to improve palliative care use and will serve as a model for similar action in other academic and community oncology centers.
Availability of data and materials
The full protocol will be available from the corresponding author on reasonable request. This manuscript does not contain participant-level data.
Quality of life
American Society of Clinical Oncology
Social determinants of health
Community health worker
Community health workers
- DeCIDE PC:
Community Health Worker Intervention for Disparities in Palliative Care
Advance care planning
Community Advisory Board
Consolidated Framework for Implementation Research
Reach, Effectiveness, Adoption, Implementation, Maintenance
Standard Protocol Items: Recommendations for Interventional Trials
American Joint Committee on Cancer
Electronic medical record
Center to Advance Palliative Care
Durable power of attorney
Functional Assessment of Chronic Illness Therapy - Palliative Care
Quality of Communication
Edmonton Symptom Assessment Scale
Center for Epidemiologic Studies Depression Scale
Standardized mean difference
Research Electronic Data Capture
Missing at random
Data and Safety Monitoring Board
Institutional review board
Lee KC, Walling AM, Senglaub SS, Kelley AS, Cooper Z. Defining serious illness among adult surgical patients. J Pain Symptom Manag. 2019;58:844–850.e2.
Ferrell BR, Temel JS, Temin S, Alesi ER, Balboni TA, Basch EM, et al. Integration of palliative care into standard oncology care: American society of clinical oncology clinical practice guideline update. J Clin Oncol. 2017;35:96–112.
Higginson IJ, Evans CJ. What is the evidence that palliative care teams improve outcomes for cancer patients and their families? Cancer J Sudbury Mass. 2010;16:423–35.
Hannon B, Swami N, Rodin G, Pope A, Zimmermann C. Experiences of patients and caregivers with early palliative care: a qualitative study. Palliat Med. 2017;31:72–81.
Smith AK, McCarthy EP, Paulk E, Balboni TA, Maciejewski PK, Block SD, et al. Racial and ethnic differences in advance care planning among patients with cancer: impact of terminal illness acknowledgment, religiousness, and treatment preferences. J Clin Oncol Off J Am Soc Clin Oncol. 2008;26:4131–7.
Mack JW, Paulk ME, Viswanath K, Prigerson HG. Racial disparities in the outcomes of communication on medical care received near death. Arch Intern Med. 2010;170:1533–40.
Loggers ET, Maciejewski PK, Paulk E, DeSanto-Madeya S, Nilsson M, Viswanath K, et al. Racial differences in predictors of intensive end-of-life care in patients with advanced cancer. J Clin Oncol Off J Am Soc Clin Oncol. 2009;27:5559–64.
Johnson KS. Racial and ethnic disparities in palliative care. J Palliat Med. 2013;16:1329–34.
Loggers ET, Maciejewski PK, Jimenez R, Nilsson M, Paulk E, Stieglitz H, et al. Predictors of intensive end-of-life and hospice care in latino and white advanced cancer patients. J Palliat Med. 2013;16:1249–54.
Northouse LL, Katapodi MC, Song L, Zhang L, Mood DW. Interventions with Family Caregivers of Cancer Patients: Meta-Analysis of Randomized Trials. CA Cancer J Clin. 2010;:n/a-n/a.
O’Mara AM, St. Germain D, Ferrell B, Bornemann T. Challenges to and lessons learned from conducting palliative care research. J Pain Symptom Manage. 2009;37:387–94.
Kamal AH, Bull J, Wolf SP, Portman D, Strand J, Johnson KS. Unmet needs of African Americans and whites at the time of palliative care consultation. Am J Hosp Palliat Med. 2017;34:461–5.
Demiris G, Parker Oliver D, Capurro D, Wittenberg-Lyles E. Implementation science: implications for intervention research in hospice and palliative care. Gerontologist. 2014;54:163–71.
Ballard M, Montgomery P. Systematic review of interventions for improving the performance of community health workers in low-income and middle-income countries. BMJ Open. 2017;7:e014216.
Gibbons MC, Tyus NC. Systematic review of U.S.-based randomized controlled trials using community health workers. Prog Community Health Partnersh Res Educ Action. 2007;1:371–81.
Cooper LA, Hill MN, Powe NR. Designing and evaluating interventions to eliminate racial and ethnic disparities in health care. J Gen Intern Med. 2002;17:477–86.
Raj A, Ko N, Battaglia TA, Chabner BA, Moy B. Patient navigation for underserved patients diagnosed with breast cancer. Oncologist. 2012;17:1027–31.
Chen LA, Santos S, Jandorf L, Christie J, Castillo A, Winkel G, et al. A Program to enhance completion of screening colonoscopy among Urban minorities. Clin Gastroenterol Hepatol. 2008;6:443–50.
Wells KJ, Battaglia TA, Dudley DJ, Garcia R, Greene A, Calhoun E, et al. Patient navigation: State of the art or is it science? Cancer. 2008;113:1999–2010.
Sedhom R, Nudotor R, Freund KM, Smith TJ, Cooper LA, Owczarzak JT, et al. Can community health workers increase palliative care use for African American patients? A Pilot Study JCO Oncol Pract. 2021;17:e158–67.
Johnston FM, Neiman JH, Parmley LE, Conca-Cheng A, Freund KM, Concannon TW, et al. Stakeholder perspectives on the use of community health workers to improve palliative care use by African Americans with cancer. J Palliat Med. 2019;22:302–6.
Chan A-W, Tetzlaff JM, Altman DG, Laupacis A, Gøtzsche PC, Krleža-Jerić K, et al. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. 2013;158:200.
Hunt BR, Allgood KL, Kanoon JM, Benjamins MR. Keys to the successful implementation of community-based outreach and navigation: lessons from a breast health navigation program. J Cancer Educ. 2017;32:175–82.
Hunt BR, Allgood K, Sproles C, Whitman S. Metrics for the systematic evaluation of community-based outreach. J Cancer Educ. 2013;28:633–8.
Patel MI, Sundaram V, Desai M, Periyakoil VS, Kahn JS, Bhattacharya J, et al. Effect of a lay health worker intervention on goals-of-care documentation and on health care use, costs, and satisfaction among patients with cancer: a randomized clinical trial. JAMA Oncol. 2018;4:1359–66.
Patel MI, Kapphahn K, Dewland M, Aguilar V, Sanchez B, Sisay E, et al. Effect of a community health worker intervention on acute care use, advance care planning, and patient-reported outcomes among adults with advanced stages of cancer: a randomized clinical trial. JAMA Oncol. 2022. https://doi.org/10.1001/jamaoncol.2022.1997.
Lyons KD, Bakitas M, Hegel MT, Hanscom B, Hull J, Ahles TA. Reliability and Validity of the Functional Assessment of Chronic Illness Therapy-Palliative Care (FACIT-Pal) scale. J Pain Symptom Manage. 2009;37:23–32.
Kavalieratos D, Corbelli J, Zhang D, Dionne-Odom JN, Ernecoff NC, Hanmer J, et al. Association between palliative care and patient and caregiver outcomes: a systematic review and meta-analysis. JAMA. 2016;316:2104.
Engelberg R, Downey L, Curtis JR. Psychometric characteristics of a quality of communication questionnaire assessing communication about end-of-life care. J Palliat Med. 2006;9:1086–98.
Subbiah IM, Charone MM, Roszik J, Haider A, Vidal M, Wong A, et al. Association of edmonton symptom assessment system global distress score with overall survival in patients with advanced cancer. JAMA Netw Open. 2021;4:e2117295.
Hann D, Winter K, Jacobsen P. Measurement of depressive symptoms in cancer patients. J Psychosom Res. 1999;46:437–43.
Landen CN, Younger NO, Collins Sharp BA, Underwood PB. Cancer patients’ satisfaction with physicians: Princess Margaret hospital satisfaction with doctor questionnaire results. Am J Obstet Gynecol. 2003;188:1177–9.
Loblaw DA, Bezjak A, Bunston† T. Development and Testing of a Visit-Specific Patient Satisfaction Questionnaire: the Princess Margaret Hospital Satisfaction With Doctor Questionnaire. JCO. 1999;17:1931.
Lo C, Burman D, Hales S, Swami N, Rodin G, Zimmermann C. The FAMCARE-patient scale: measuring satisfaction with care of outpatients with advanced cancer. Eur J Cancer. 2009;45:3182–8.
Weir RC, Proser M, Jester M, Li V, Hood-Ronick CM, Gurewich D. Collecting social determinants of health data in the clinical setting: findings from national PRAPARE implementation. J Health Care Poor Underserved. 2020;31:1018–35.
Patel MI, Khateeb S, Coker T. Association of a lay health worker-led intervention on goals of care, quality of life, and clinical trial participation among low-income and minority adults with cancer. JCO Oncol Pract. 2021;17:e1753–62.
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81.
This study is funded by the National Cancer Institute (NCI), grant number: 1R01CA252101-01A1.
Ethics approval and consent to participate
This study protocol was approved by the IRB at all three enrollment sites (Johns Hopkins Hospital, University of Alabama at Birmingham Hospital, and TidalHealth Peninsula Regional). All methods were carried out in accordance with relevant guidelines and regulations. Informed consent will be obtained from all subjects prior to study participation.
Consent for publication
The authors declare no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Siddiqi, A., Monton, O., Woods, A. et al. Dissemination and Implementation of a Community Health Worker Intervention for Disparities in Palliative Care (DeCIDE PC): a study protocol for a hybrid type 1 randomized controlled trial. BMC Palliat Care 22, 139 (2023). https://doi.org/10.1186/s12904-023-01250-0