You are here

Article Text

Article menu
Nursing
Protocol
Study protocol for Care cOORDInatioN And sympTom managEment (COORDINATE) programme: a feasibility study
  1. Binu Koirala1,
  2. Sarah Badawi1,
  3. Steven Frost2,
  4. Caleb Ferguson2,
  5. David N Hager3,
  6. Lara Street4,
  7. Nancy Perrin1,
  8. Cheryl Dennison Himmelfarb1,
  9. Patricia Davidson2
  1. 1Johns Hopkins University School of Nursing, Baltimore, Maryland, USA
  2. 2University of Wollongong, Wollongong, New South Wales, Australia
  3. 3Medicine, Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
  4. 4The Johns Hopkins Hospital, Baltimore, Maryland, USA
  1. Correspondence to Dr Binu Koirala; bkoiral1{at}jhu.edu

Abstract

Introduction Sustainable approaches to support care coordination and symptom management needs of critically ill adults living with multimorbidity are needed to combat the challenges and complexity that multimorbidity presents. The study aims to test the feasibility of the Care cOORDInatioN And sympTom managEment (COORDINATE) intervention to improve health outcomes of adults living with multimorbidity.

Methods and analysis A multicomponent nurse-driven intervention was developed using experience-based co-design and human-centred design. Inclusion criteria include (1) age 55 years and older, (2) admitted to an intermediate care unit, (3) presence of two or more chronic health conditions and (4) signed informed consent. Data collection will occur at baseline (time of recruitment predischarge) and 6 weeks and 3 months following hospital discharge. Outcome of interest from this feasibility study is to evaluate the financial, technical and logistic feasibility of a full-scale study including data collection and protocol adherence. Additionally, Cohen’s d effect sizes for the change in outcomes over time will be computed to establish power calculations required for a full-scale study. The protocol was prepared in accordance with Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklist.

Ethics and dissemination The study has been reviewed and approved by the Institutional Review Board of Johns Hopkins Medical Institutions. Given the success of this feasibility study, the potential for the COORDINATE intervention to decrease the symptom burden and improve participant quality of life among critically ill people with multimorbidity will be tested in a full-scale study, and findings will be actively disseminated.

Trial registration number NCT05985044.

  • quality of life
  • adult intensive & critical care
  • quality in health care
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjopen-2023-072846

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    STRENGTHS AND LIMITATIONS OF THIS STUDY

    • The study aims to test the feasibility of the Care cOORDInatioN And sympTom managEment (COORDINATE) intervention to establish power calculation.

    • The innovation in this intervention is embedded in the heterogeneity of the population, the locus of care, the use of participatory approaches for intervention development and the need for transitional and supportive care strategies for multimorbidity management which is increasingly a characteristic of healthcare delivery.

    • As a single-arm feasibility study, assumptions on the effectiveness of the COORDINATE intervention on outcomes will be limited and contextual.

    • The intervention was developed and will be implemented at a single site, and additional work will be needed to understand the context of care and implement intervention within other communities.

    Introduction

    Multimorbidity is common and is the coexistence of two or more chronic conditions in the same individual.1 These individuals live with a higher symptom burden and accelerated functional decline that affects quality of life,2–4 which can lead to higher caregiver strain and burden.5 In the USA only, the prevalence of multimorbidity is estimated to be 50% for individuals under 65 years of age, 62% for those aged 65–74 years, 75.5% for those aged 75–84 and 81.5% for those 85 years and older.4 6 With the population ageing, advances in medical care, and increased longevity, the prevalence of multimorbidity is expected to increase globally.7 With this comes a rise in the utilisation of healthcare and costs of care.6 8 9 People with multimorbidity create a particular challenge to care coordination, because they require more holistic person-centred approaches that balance many competing priorities, needs and goals.10 Moreover, most healthcare specialties are configured around single diseases and organs. Hospitalisation can be a window of opportunity to initiate interventions to promote recovery, resilience and care coordination, decrease symptom burden and in turn enhance quality of life.

    Intermediate care units (IMCUs), also known as high dependency units (HDUs), are widely used to care for critically ill patients requiring more intensive monitoring or nursing care than is provided on hospital acute care wards but who do not have intensive care needs (such as advanced airway management or mechanical ventilation).11 Half of the patients admitted to intermediate care have multimorbidity11 12 and have higher symptom burden. Preliminary data suggest intermediate care patients do not necessarily access comprehensive care services because of the organ-centred arrangement of programmes (eg, chronic heart failure, chronic obstructive airway disease and chronic renal failure). Further, individuals living with multimorbidity are not often categorised into single disease-specific categories such as cardiac, respiratory and gastrointestinal because of multiple comorbid conditions and symptoms and have a greater potential for complications, including worse overall management of chronic disease needs.13 Although the challenges of efficiently and effectively managing care among those with multimorbidity have been recognised, the complexity of the care coordination and possible strategies to help manage these issues are not well identified. Hence, person-centred interventions focused on care coordination and symptom management by empowering patients to interact effectively with the complex care system could be a promising method for improving the health outcomes of critically ill patients living with multimorbidity.

    Methods and analysis

    Trial design and purpose

    The paper discusses the rationale and design of a single-arm pilot feasibility study of a nurse-driven multicomponent intervention, Care cOORDInatioN And sympTom managEment (COORDINATE), to improve health outcomes among patients living with multimorbidity. The programme includes five individualised, synchronous sessions for patients conducted in person (visit 1) and followed by phone calls (visits 2–5) over 6 weeks. The COORDINATE intervention was developed using experience-based co-design (EBCD) and human-centred design (HCD). The EBCD and HCD methodologies facilitated the person-centred approach of intervention components by considering the needs and preferences of patients, family caregivers and healthcare providers in improving health outcomes when living with multimorbidity. The innovation in this intervention is embedded in the heterogeneity of the population, the locus of care and the need for transitional and supportive care strategies for multimorbidity management. The study flow process followed to help identify, develop and pilot test the COORDINATE intervention is summarised in figure 1.

    Figure 1
    Figure 1

    Study flow diagram.

    The purpose of this feasibility study is to evaluate the financial, technical and administrative or logistic feasibility of a full-scale study including issues of data collection and protocol adherence. Additionally, an initial effect size of the COORDINATE intervention will be evaluated to establish the power calculations required for a full-scale study. The protocol is prepared in accordance with Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines.14

    Sample and setting

    Patients will be eligible to participate if they meet the following criteria: (1) aged 55 years and older, (2) have two or more chronic health conditions identified in the electronic medical record and (3) are willing to provide informed consent. Patients will be excluded if they cannot speak English or have a documented cognitive impairment that would prevent them from participating. Patients will be approached in the IMCU of an academic teaching hospital while they are in-patient before discharge.

    Intervention development with patient and public involvement

    The study used participatory approaches, EBCD and HCD, to develop a multimorbidity management COORDINATE programme. Participatory approaches to service improvements are effective methods for addressing gaps in knowledge and informing the next step with the involvement as well as exploration of experiences and needs of stakeholders.15 Increasing evidence suggests that user, patient and public, partnership in the intervention development not only improves its quality focus and effectiveness but also leads to the improvement in outcomes, safety, quality and cost.15 Hence, the use of EBCD and HCD methodology helped capture and understand the end users’ need and design the COORDINATE intervention.

    Use of experience-based co-design (EBCD)

    EBCD is an innovative participatory research methodology for collaboratively exploring and using individual experiences/emotions of patients, family members and healthcare providers for a more holistic understanding of needs.16 17 EBCD is an effective means for understanding how to make the best use of data about patient experience to improve the quality of care and culture of health services to cocreate feasible and acceptable interventions.18 Preliminary work for this study followed a six-stage process (table 1) of EBCD and worked with patients living with multimorbidity, their family caregivers and healthcare professionals through iterative rounds of data collection, analysis, validation and development of strategies to address challenges in multimorbidity care delivery processes. The process started with the preparation for the study (Stage 1) followed by the narrative interviews (Stages 2 and 3) to understand the disease trajectories in the context of multimorbidity and identify improvement priorities for multimorbidity management with patients, family caregivers and healthcare providers. The co-design part (Stages 4 and 5) of the process was the innovative aspect of validating needs and identifying improvement priorities for the multimorbidity management programme. All the inputs from the interviews and co-design events were analysed and summarised19 as a multimorbidity management toolkit and disseminated to the stakeholders (Stage 6). Rigorous appraisals and details of the EBCD process have been published, and an online toolkit was available to guide this work.20

    View this table:
    Table 1

    Stages of experience-based co-design methodology

    Use of human-centred design (HCD)

    The use of HCD in this project complemented the EBCD process. HCD is a person-first, collaborative process used to understand and define problems, identify opportunities, generate ideas and make tools that support positive change.21 This process prioritises end users’ and important stakeholders’ needs, values and lived experiences. Human-centred methods such as storytelling, journey mapping, priority ranking and intervention prototyping were used to identify end users’ needs and preferences and design the intervention’s components. Storytelling is a narrative tool that is currently used in a diverse range of fields to elicit personal narratives that capture experiences, processes and contexts.22 Individual narrative interviews in Stages 2 and 3 of EBCD process followed a storytelling approach of HCD to help identify what were the good and bad experiences of study participants when living with and caring for patients with multimorbidity. The co-design event used the journey map and priority ranking exercise with the participants. The patient experience journey mapping is known to use for a better understanding of patients’ journey with a phenomenon, their pain points and successes.23 The journey mapping activity helped validate and identify improvement priorities for multimorbidity management. The ranking exercise was valuable to understand the priority of improvement strategies.

    Findings from the interviews, co-design events and components of the multimorbidity management toolkit developed from EBCD were analysed using the intervention prototype methodology. Key challenges and recommendations from the early work were grouped into key themes. Then the ideas under each theme were mapped based on their importance and feasibility and identified as intervention components. Evidence-supporting intervention components were also explored to help identify interventions to which these components were used that could be adapted for this population. Key findings from this work identified five improvement priorities: communication, patient-provider relationship, caregiver support, availability of resources for symptom/disease assessment and management and care coordination, and follow-up care.19 Through an extensive process of EBCD, HCD and evidence evaluation, the final identified COORDINATE intervention components include need assessment, question prompt list, goals discussion, and symptom assessment and tracking.

    Intervention components

    The intervention consists of four main components: (1) needs assessment, (2) question prompt list, (3) goals discussion and (4) symptom assessment and tracking (online supplemental file 1). A summary of intervention components and the rationale for choosing these components with literature is presented in table 2. The interventionist will guide the individual patient through the first few months of discharge. In contrast to a patient navigator model where the role is more facilitative, in this programme, the intervention seeks to empower and coach the individual on a journey commensurate with their needs.

    View this table:
    Table 2

    Intervention component and evidence basis for component selection

    Participant timeline: intervention journey

    The intervention will start with the enrolment of a patient living with multimorbidity. The intervention consists of one in-person predischarge visit by the study team and four follow-up telephone calls (at 48hour, 1-week, 4-week and 6-week postdischarge). The sequence of intervention events and timing of the intervention components is presented in figure 2. Participants’ eligibility will be examined at the time of recruitment.

    Figure 2
    Figure 2

    Intervention journey.

    Outcomes

    The outcomes of interest for this feasibility study are to evaluate the financial, technical and administrative or logistic feasibility of a full-scale study including issues of data collection, questionnaire use and protocol adherence. Additionally, to establish power calculations required for a full-scale study using primary outcome variables of full-scale study. The primary outcomes for the full-scale study include quality of life and symptom burden, and secondary outcomes include pain, fatigue, social support, resilience, self-efficacy and healthcare utilisation (emergency visits, hospitalisations and critical care admissions). The list of outcomes with measures that will be used for data collection is identified in table 3. A follow-up survey at the end of intervention implementation (6-week follow-up) includes items on the intervention’s satisfaction and acceptability/feasibility among study participants.

    View this table:
    Table 3

    Outcomes and measurements

    Sample size

    As a pilot feasibility study, the analyses will likely not have adequate power to detect significant differences in outcomes. Hence, effect sizes, rather than statistical significance, will be examined for evidence of the effectiveness of the intervention with a target sample size of 25.

    Recruitment

    Prospective-consecutive participants meeting eligibility criteria will be approached for the study using convenience and purposive sampling from the IMCU.

    Data collection and management

    After informed consent (online supplemental material), participants will complete the baseline survey. Data on patient demographics and outcome surveys (table 3) will be collected at the time of recruitment (baseline data), 6-week follow-up and 3-month follow-up. Data will be collected from participants’ self-reports and medical records. Reflection of study team members on the financial, technical and administrative feasibility of the intervention implementation will be collected from the principal investigator (PI), interventionists and research assistants involved in recruitment and data collection. The team will prepare a standard intervention protocol with guidance on communication techniques, details of intervention components, and possible/potential questions and scripts to use by interventionists among participants. The team members will audio record intervention and reflections to improve adherence to intervention protocol and implications for bigger trial intervention development. Team members will meet every week to reflect on the project activities and discuss issues of data collection, protocol adherence and questionnaire use.

    All study data will be stored in a secure, password-protected and Health Insurance Portability and Accountability Act (HIPPA)-compliant server, and only study team members can access it. These are OneDrive, REDCap and encrypted and password-protected safe desktops. Any hard copies of source data are stored in a locked cabinet in a locked office. The PI will notify the Data Safety Monitoring Committee and the Institutional Review Board (IRB) within 48 hours of becoming aware of any serious adverse event.

    Statistical methods for data analysis

    Descriptive and exploratory analysis will be used for all study variables. Continuous variables will be described using means and SD or median and interquartile ranges. Categorical variables will be described using frequency and percentages. Cohen’s d effect sizes for the change in outcomes over time will be computed. Generalised estimating equations (GEE) will be used to examine the change in primary and secondary outcomes over time. Intervention acceptability and feasibility in financial, technical and logistic aspects will be examined using both qualitative and quantitative data. Qualitative analysis will be conducted from reflection data of study team members recruiting participants, collecting data and delivering the intervention and interview data from selected participants who completed the intervention and left the intervention if agreed to be interviewed. The quantitative data from satisfaction and feasibility items will be descriptively analysed (mean, range, percentages). Further, an evaluation of participant recruitment and retention rates will be performed.

    Ethics and dissemination

    Ethical approval

    The study will be conducted in accordance with the Institutional Review Board of Johns Hopkins University, as well as the approved study protocol (IRB00244792).

    Informed consent

    A physical as well as a survey using REDCap e-consent will be used to review the consent form and obtain a signature if the participant is interested. The research assistant will review the informed consent with the participants and enough time and opportunities will be provided to ask questions before agreeing to be involved in the study. The participant will be provided with a printed consent form in their intervention package.

    Risks and benefits

    This trial is developed with deliberate attention towards minimising the risk of harm to participants. There are no physical risks to participants. However, the potential risks of the study include time involvement, fatigue and emotional distress because of the severity of the disease, recall of their experience and the nature of some questions in the survey. All participants are informed about the potential risks of participating during the informed consent process. Participants are allowed to withdraw or stop the study at any time. The research team including the PI and research assistants are and will be registered nurses or graduate nursing students who are experienced in caring for patients living with chronic and complex disease conditions. Any adverse events, unanticipated problems and study deviations will be documented on designated forms and reported within 48 hours, by the PI to the Data Safety Monitoring Committee of the study monitoring entity, PROMOTE centre (Promoting Resilience in Persons with Multiple Chronic Conditions) and IRB. If deemed necessary by the monitoring entity or IRB, study activities will be paused until problems are resolved.

    The study procedure will provide an opportunity to discuss and empower patients for care coordination, symptom tracking and symptom management. The pilot test of the intervention is anticipated to reduce symptom burden and improve quality of life. Additionally, the intervention is expected to decrease pain and fatigue, enhance resilience, self-efficacy and social support and reduce healthcare utilisation among participants involved in the study. Participants are compensated for their time and involvement with a $25 gift card given at three time points: baseline, 6-weeks and 3-month follow-up survey completion.

    Dissemination

    Multiple platforms will be used to disseminate the research findings. This will involve the use of academic media such as peer-reviewed journal articles and presentations at national and international conferences; social media such as Facebook, Instagram, Twitter and LinkedIn; media such as newspapers, radio and television; as well as community engagement activities such as clinical site events, stakeholder meetings or community forums.

    Access to data

    Common data will be submitted to NIH Common Data Elements (CDE) Repository. Additional data will be available on request.

    Conclusion

    The study is being conducted to determine the feasibility of a COORDINATE intervention for patients living with multimorbidity to establish power calculations and evaluate the financial, technical and logistic feasibility of a full-scale study to help improve quality of life and decrease symptom burden. This intervention is novel in its use of EBCD and HCD for its development, focus on individualisation with diverse disease/condition and flexibility of standard intervention components to address the specific person-centred needs of the patients living with multimorbidity.

    Ethics statements

    Patient consent for publication

    Acknowledgments

    The research team acknowledges the following: all the patients, families and healthcare providers that were involved in the preliminary phase of the study interviews, co-design events, and their direct and indirect input for the intervention development. Human-centred design experts, Vidisha Agarwalla and Kennedy McDaniel, provided the necessary guidance in using human-centred design and methods. Dr Anna Peeler for her contribution to the preliminary work related to experience-based design. Co-design event facilitators include Dr Rebecca Wright and graduate nursing students. Support received from the school of nursing and clinical staff, research assistants and research honors students during project activities.

    References

    1. ↵
      1. Smith SM,
      2. O’Dowd T
      . Chronic diseases: what happens when they come in multiples Br J Gen Pract 2007;57:268–70.
      OpenUrlFREE Full Text
    2. ↵
      1. Pisu M,
      2. Azuero A,
      3. Halilova KI, et al
      . Most Impactful factors on the health-related quality of life of a geriatric population with cancer. Cancer 2018;124:596–605. doi:10.1002/cncr.31048
      OpenUrl
    3. ↵
      1. Eckerblad J,
      2. Theander K,
      3. Ekdahl A, et al
      . Symptom burden in community-dwelling older people with Multimorbidity: a cross-sectional study. BMC Geriatr 2015;15:1. doi:10.1186/1471-2318-15-1
    4. ↵
      1. Klompstra L,
      2. Ekdahl AW,
      3. Krevers B, et al
      . Factors related to health-related quality of life in older people with Multimorbidity and high health care consumption over a two-year period. BMC Geriatr 2019;19:187. doi:10.1186/s12877-019-1194-z
    5. ↵
      1. Kuzuya M,
      2. Enoki H,
      3. Hasegawa J, et al
      . Impact of Caregiver burden on adverse health outcomes in community-dwelling dependent older care recipients. Am J Geriatr Psychiatry 2011;19:382–91. doi:10.1097/JGP.0b013e3181e9b98d
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      1. Salive ME
      . Multimorbidity in older adults. Epidemiol Rev 2013;35:75–83. doi:10.1093/epirev/mxs009
      OpenUrlCrossRefPubMedWeb of Science
    7. ↵
      1. Goodman RA,
      2. Posner SF,
      3. Huang ES, et al
      . Defining and measuring chronic conditions: Imperatives for research, policy, program, and practice. Prev Chronic Dis 2013;10:E66. doi:10.5888/pcd10.120239
    8. ↵
      1. Glynn LG,
      2. Valderas JM,
      3. Healy P, et al
      . The prevalence of Multimorbidity in primary care and its effect on health care utilization and cost. Fam Pract 2011;28:516–23. doi:10.1093/fampra/cmr013
      OpenUrlCrossRefPubMedWeb of Science
    9. ↵
      1. Vogeli C,
      2. Shields AE,
      3. Lee TA, et al
      . Multiple chronic conditions: prevalence, health consequences, and implications for quality, care management, and costs. J Gen Intern Med 2007;22:391–5. doi:10.1007/s11606-007-0322-1
      OpenUrlCrossRefPubMedWeb of Science
    10. ↵
      1. Koirala B,
      2. Peeler A,
      3. Dennison Himmelfarb C, et al
      . Living with multiple chronic conditions: how we achieve Holistic care and optimize health outcomes. J Adv Nurs 2023;79:e7–9. doi:10.1111/jan.15433 Available: https://onlinelibrary.wiley.com/toc/13652648/79/2
      OpenUrl
    11. ↵
      1. Simpson CE,
      2. Sahetya SK,
      3. Bradsher RW, et al
      . Outcomes of emergency medical patients admitted to an intermediate care unit with detailed admission guidelines. Am J Crit Care 2017;26:e1–10. doi:10.4037/ajcc2017253
      OpenUrlAbstract/FREE Full Text
    12. ↵
      1. Hager DN,
      2. Tanykonda V,
      3. Noorain Z, et al
      . Hospital mortality prediction for intermediate care patients: assessing the Generalizability of the intermediate care unit severity score (IMCUSS). J Crit Care 2018;46:94–8. doi:10.1016/j.jcrc.2018.05.009
      OpenUrl
    13. ↵
      1. Ong KY,
      2. Lee PSS,
      3. Lee ES
      . Patient-centred and not disease-focused: a review of guidelines and Multimorbidity. Singapore Med J 2020;61:584–90. doi:10.11622/smedj.2019109
      OpenUrl
    14. ↵
      1. Chan A-W,
      2. Tetzlaff JM,
      3. Altman DG, et al
      . SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med 2013;158:200–7. doi:10.7326/0003-4819-158-3-201302050-00583
      OpenUrlCrossRefPubMedWeb of Science
    15. ↵
      1. Leask CF,
      2. Sandlund M,
      3. Skelton DA, et al
      . Framework, principles and recommendations for Utilising Participatory Methodologies in the Co-creation and evaluation of public health interventions. Res Involv Engagem 2019;5:2. doi:10.1186/s40900-018-0136-9
    16. ↵
      1. Blackwell RWN,
      2. Lowton K,
      3. Robert G, et al
      . Using experience-based Co-design with older patients, their families and staff to improve palliative care experiences in the emergency Department: A reflective critique on the process and outcomes. Int J Nurs Stud 2017;68:83–94. doi:10.1016/j.ijnurstu.2017.01.002
      OpenUrlPubMed
    17. ↵
      1. Borgstrom E,
      2. Barclay S
      . Experience-based design, Co-design and experience-based Co-design in palliative and end-of-life care. BMJ Support Palliat Care 2019;9:60–6. doi:10.1136/bmjspcare-2016-001117
      OpenUrlAbstract/FREE Full Text
    18. ↵
      1. Robert G,
      2. Cornwell J,
      3. Locock L, et al
      . Patients and staff as Co-designers of Healthcare services. BMJ 2015;350:g7714. doi:10.1136/bmj.g7714
    19. ↵
      1. Koirala B,
      2. Moore R,
      3. Li D, et al
      . Living with Multimorbidity: experience organizing a virtual Co‐Design event with patients and health care providers. J Women’s Health 2022.
    20. ↵
      1. The Point of Care Foundation
      . EBCD: Experience-based co-design toolkit. London: The Point of Care Foundation, 2018.
    21. ↵
      1. IDEO
      . The Field Guide to Human-centered Design. Design Kit: IDEO, 2015.
    22. ↵
      1. A. Gausepohl K,
      2. W. Winchester W,
      3. L. Smith-Jackson T, et al
      . A conceptual model for the role of Storytelling in design: Leveraging narrative inquiry in user-centered design (UCD). Health Technol 2016;6:125–36. doi:10.1007/s12553-015-0123-1
      OpenUrl
    23. ↵
      1. Joseph AL,
      2. Kushniruk AW,
      3. Borycki EM
      . Patient journey mapping: Current practices, challenges and future opportunities in Healthcare. Knowledge Management & E-Learning: An International J 2020;12:387–404.
      OpenUrl
      1. National Guideline Centre (UK)
      . Multimorbidity: Assessment, Prioritisation and Management of Care for People with Commonly Occurring Multimorbidity. National Institute for Health and Care Excellence: Guidelines, 2016.
      1. Bombard Y,
      2. Baker GR,
      3. Orlando E, et al
      . Engaging patients to improve quality of care: a systematic review. Implement Sci 2018;13:98. doi:10.1186/s13012-018-0784-z
      1. Hjelmfors L,
      2. Mårtensson J,
      3. Strömberg A, et al
      . Communication about prognosis and end-of-life in heart failure care and experiences using a heart failure question prompt list. Int J Environ Res Public Health 2022;19:4841. doi:10.3390/ijerph19084841
      1. Brandes K,
      2. Linn AJ,
      3. Butow PN, et al
      . The characteristics and effectiveness of question prompt list interventions in oncology: a systematic review of the literature. Psychooncology 2015;24:245–52. doi:10.1002/pon.3637
      OpenUrlCrossRefPubMed
      1. Schwarze ML,
      2. Buffington A,
      3. Tucholka JL, et al
      . Effectiveness of a question prompt list intervention for older patients considering major surgery: A Multisite randomized clinical trial. JAMA Surg 2020;155:6–13. doi:10.1001/jamasurg.2019.3778
      OpenUrl
      1. Wittink MN,
      2. Yilmaz S,
      3. Walsh P, et al
      . Customized care: an intervention to improve communication and health outcomes in Multimorbidity. Contemp Clin Trials Commun 2016;4:214–21. doi:10.1016/j.conctc.2016.10.002
      OpenUrl
      1. Association AD
      . 5. facilitating behavior change and well-being to improve health outcomes: standards of medical care in Diabetes-2021. Diabetes Care 2021;44:S53–72. doi:10.2337/dc21-S005
      OpenUrlAbstract/FREE Full Text
      1. Bailey RR
      . Goal setting and action planning for health behavior change. Am J Lifestyle Med 2019;13:615–8. doi:10.1177/1559827617729634
      OpenUrl
      1. Epton T,
      2. Currie S,
      3. Armitage CJ
      . Unique effects of setting goals on behavior change: systematic review and meta-analysis. J Consult Clin Psychol 2017;85:1182–98. doi:10.1037/ccp0000260
      OpenUrl
      1. Williams PD,
      2. Lantican LS,
      3. Bader JO, et al
      . Symptom monitoring, alleviation, and self-care among Mexican Americans during cancer treatment. Clin J Oncol Nurs 2014;18:547–54. doi:10.1188/14.CJON.547-554
      OpenUrl
      1. Hui D,
      2. Bruera E
      . The Edmonton symptom assessment system 25 years later: past, present, and future developments. J Pain Symptom Manage 2017;53:630–43. doi:10.1016/j.jpainsymman.2016.10.370
      OpenUrlPubMed
      1. Bruera E,
      2. Kuehn N,
      3. Miller MJ, et al
      . The Edmonton symptom assessment system (ESAS): a simple method for the assessment of palliative care patients. J Palliat Care 1991;7:6–9. doi:10.1177/082585979100700202
      OpenUrlPubMed
      1. Busija L,
      2. Pausenberger E,
      3. Haines TP, et al
      . Adult measures of general health and health-related quality of life: medical outcomes study short form 36-item (SF-36) and short form 12-item (SF-12) health surveys, Nottingham health profile (NHP), sickness impact profile (SIP), medical outcomes study short form 6D (SF-6D), health utilities index mark 3 (Hui3), quality of well-being scale (QWB), and assessment of quality of life (Aqol). Arthritis Care Res (Hoboken) 2011;63:S383–412. doi:10.1002/acr.20541
      OpenUrl
      1. PROMIS
      . n.d. Domain frameworks PROMIS adult self-reported health. Available: https://www.assessmentcenter.net/documents/PROMIS%20Pain%20Intensity%20Scoring%20Manual.pdf2015
      1. Merriwether EN,
      2. Rakel BA,
      3. Zimmerman MB, et al
      . Reliability and construct validity of the patient-reported outcomes measurement information system (PROMIS) instruments in women with Fibromyalgia. Pain Med 2017;18:1485–95. doi:10.1093/pm/pnw187
      OpenUrl
      1. Ameringer S,
      2. Elswick RK,
      3. Menzies V, et al
      . Psychometric evaluation of the patient-reported outcomes measurement information system fatigue-short form across diverse populations. Nurs Res 2016;65:279–89. doi:10.1097/NNR.0000000000000162
      OpenUrlCrossRefPubMed
      1. Mitchell PH,
      2. Powell L,
      3. Blumenthal J, et al
      . A short social support measure for patients recovering from myocardial infarction: the ENRICHD social support inventory. J Cardiopulm Rehabil 2003;23:398–403. doi:10.1097/00008483-200311000-00001
      OpenUrlCrossRefPubMed
      1. Smith BW,
      2. Dalen J,
      3. Wiggins K, et al
      . The brief resilience scale: assessing the ability to bounce back. Int J Behav Med 2008;15:194–200. doi:10.1080/10705500802222972
      OpenUrlCrossRefPubMedWeb of Science
      1. Chesney MA,
      2. Neilands TB,
      3. Chambers DB, et al
      . A validity and reliability study of the coping self-efficacy scale. Br J Health Psychol 2006;11:421–37. doi:10.1348/135910705X53155
      OpenUrlCrossRefPubMedWeb of Science

    Supplementary materials

    • Supplementary Data

      This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    Footnotes

    • Twitter @davidnhager

    • Contributors BK and PD conceptualised the study. BK, SB, DNH, LS, NP, CDH and PMD were involved in the planning of the study. BK is the study’s principal investigator and is responsible for conducting the study. SF and CF provided feedback on the planning and conduct of the study. All authors provided their expertise for the intervention development and continuous refinement, critically appraised and approved the reporting in a manuscript, and assumed responsibility for the content of the manuscript.

    • Funding Dr Koirala is supported by the NINR P30 NR18093, the Building Interdisciplinary Research Careers in Women's Health (BIRCWH, K12HD085845; PI: Daniel Ernest Ford) program, and the Johns Hopkins School of Nursing Discovery and Innovation Award. The content is solely the responsibility of the authors and does not necessarily represent the official views of the supporting agencies.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods and analysis section for further details.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.