Applying Human-Centered Design to Refinement of the Jumpstart Guide, a Clinician- and Patient-Facing Goals-of-Care Discussion Priming Tool

Applying human-centered design to adapt the Jumpstart Guide for goals-of-care discussions in persons living with dementia

BACKGROUND

Goals-of-care discussions (GOCD) are uncommon in persons living with dementia (PLWD) despite the likelihood of eventual loss of decisional capacity in the population. The Jumpstart Guide, an existing serious illness communication priming tool, can improve GOCD in certain populations, but has not previously been adapted for use among PLWD and their caregivers.

METHODS

Using human-centered design (HCD), we adapted the Jumpstart Guide for use with PLWD and their caregivers. We conducted qualitative interviews with clinicians and caregivers of PLWD. Six team members conducted qualitative rapid analysis of interviews leading to the development of summary templates and integrative matrices. Four iterations of the Jumpstart Guide led to the final version.

RESULTS

Thirteen clinicians and 11 caregivers were interviewed. Interviews provided key insights into the unique barriers PLWD and their caregivers face during GOCD, including discomfort with accepting a dementia diagnosis and concern with using "serious illness" to describe dementia, as is commonly done in palliative care. Clinicians described differences in GOCD with PLWD compared to other serious illnesses, and the challenge of getting patients and families to think about future health states. Interviews led to Jumpstart Guide adaptations in the following domains: (1) format and structure, (2) content, and (3) specific language. Suggested changes included prioritizing naming a decision-maker, changing conversation prompts to improve accessibility and understandability, ensuring the Jumpstart Guide could be used with patients as well as their caregivers, and altering language to avoid references to "serious illness" and "abilities."

CONCLUSION

Using HCD yielded valuable insights from clinicians and caregivers about the unique barriers to conducting GOCD among PLWD and their caregivers. These insights were used to adapt the Jumpstart Guide for use with PLWD and their caregivers, which is currently being tested in a pragmatic randomized controlled trial in outpatient clinics.

Project EPIC (Early Palliative Care In COPD): A Formative and Summative Evaluation of the EPIC Telehealth Intervention

CONTEXT

Early, concurrent palliative care interventions in chronic obstructive pulmonary disease (COPD) are limited. Project EPIC (Early Palliative Care In COPD) is a multiphase mixed methods study working to fill this gap.

OBJECTIVES

To conduct a formative and summative evaluation of EPIC, a telephonic nurse coach-led early palliative care intervention for COPD adapted from the ENABLE© intervention in cancer.

METHODS

Phase I Formative Evaluation: Patients with moderate-to-very-severe COPD, family caregivers, and pulmonary and palliative care clinicians rated the acceptability and feasibility of EPIC (≥4 out of five on a Likert-scale survey). Phase II Summative Evaluation: Patients and family caregivers in Phase I participated in a pilot of the three month EPIC prototype to evaluate intervention and data collection feasibility (≥70% completion) and to seek qualitative feedback.

RESULTS

Phase I Formative Evaluation: Patients (n=10), family caregivers (n=10), pulmonary clinicians (n=6), and palliative care clinicians (n=6) found EPIC acceptable and feasible to support adaptation, while priority early palliative care needs in COPD from our prior research mapped well to the EPIC prototype. Phase II Summative Evaluation: Patients (n=5; ages 49-72, 40% moderate COPD, 40% Black) and their family caregivers (n=5; ages 51-73, 40% Black) completed 100% of EPIC prototype components, including weekly telephone sessions, a one month follow-up call, Advance Directive, palliative care clinic attendance, and 95% of monthly phone data collection sessions. Feedback from participants about EPIC was all positive.

CONCLUSION

EPIC was acceptable and feasible in patients with COPD and their family caregivers. Larger feasibility and effectiveness trials are warranted.

Assessment of Natural Language Processing of Electronic Health Records to Measure Goals-of-Care Discussions as a Clinical Trial Outcome

IMPORTANCE

Many clinical trial outcomes are documented in free-text electronic health records (EHRs), making manual data collection costly and infeasible at scale. Natural language processing (NLP) is a promising approach for measuring such outcomes efficiently, but ignoring NLP-related misclassification may lead to underpowered studies.

OBJECTIVE

To evaluate the performance, feasibility, and power implications of using NLP to measure the primary outcome of EHR-documented goals-of-care discussions in a pragmatic randomized clinical trial of a communication intervention.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study compared the performance, feasibility, and power implications of measuring EHR-documented goals-of-care discussions using 3 approaches: (1) deep-learning NLP, (2) NLP-screened human abstraction (manual verification of NLP-positive records), and (3) conventional manual abstraction. The study included hospitalized patients aged 55 years or older with serious illness enrolled between April 23, 2020, and March 26, 2021, in a pragmatic randomized clinical trial of a communication intervention in a multihospital US academic health system.

MAIN OUTCOMES AND MEASURES

Main outcomes were natural language processing performance characteristics, human abstractor-hours, and misclassification-adjusted statistical power of methods of measuring clinician-documented goals-of-care discussions. Performance of NLP was evaluated with receiver operating characteristic (ROC) curves and precision-recall (PR) analyses and examined the effects of misclassification on power using mathematical substitution and Monte Carlo simulation.

RESULTS

A total of 2512 trial participants (mean [SD] age, 71.7 [10.8] years; 1456 [58%] female) amassed 44 324 clinical notes during 30-day follow-up. In a validation sample of 159 participants, deep-learning NLP trained on a separate training data set from identified patients with documented goals-of-care discussions with moderate accuracy (maximal F1 score, 0.82; area under the ROC curve, 0.924; area under the PR curve, 0.879). Manual abstraction of the outcome from the trial data set would require an estimated 2000 abstractor-hours and would power the trial to detect a risk difference of 5.4% (assuming 33.5% control-arm prevalence, 80% power, and 2-sided α = .05). Measuring the outcome by NLP alone would power the trial to detect a risk difference of 7.6%. Measuring the outcome by NLP-screened human abstraction would require 34.3 abstractor-hours to achieve estimated sensitivity of 92.6% and would power the trial to detect a risk difference of 5.7%. Monte Carlo simulations corroborated misclassification-adjusted power calculations.

CONCLUSIONS AND RELEVANCE

In this diagnostic study, deep-learning NLP and NLP-screened human abstraction had favorable characteristics for measuring an EHR outcome at scale. Adjusted power calculations accurately quantified power loss from NLP-related misclassification, suggesting that incorporation of this approach into the design of studies using NLP would be beneficial.

Advance Care Planning Conversations: Laying the Foundation for Goal-Concordant Care at End of Life

The delivery of culturally congruent, person-centered, family-focused quality care requires an exploration of the values, beliefs, and preferences of those we serve [13]. Nuanced advance care planning conversations lay the foundation for shared decision making and promotes the delivery of goal-concordant care. This chapter will provide clinicians with guidance and resources to aid this process with a focus on contextualized communication with those with serious illness.

Improving communication about goals of care for hospitalized patients with serious illness: Study protocol for two complementary randomized trials

BACKGROUND

Although goals-of-care discussions are important for high-quality palliative care, this communication is often lacking for hospitalized older patients with serious illness. Electronic health records (EHR) provide an opportunity to identify patients who might benefit from these discussions and promote their occurrence, yet prior interventions using the EHR for this purpose are limited. We designed two complementary yet independent randomized trials to examine effectiveness of a communication-priming intervention (Jumpstart) for hospitalized older adults with serious illness.

METHODS

We report the protocol for these 2 randomized trials. Trial 1 has two arms, usual care and a clinician-facing Jumpstart, and is a pragmatic trial assessing outcomes with the EHR only (n = 2000). Trial 2 has three arms: usual care, clinician-facing Jumpstart, and clinician- and patient-facing (bi-directional) Jumpstart (n = 600). We hypothesize the clinician-facing Jumpstart will improve outcomes over usual care and the bi-directional Jumpstart will improve outcomes over the clinician-facing Jumpstart and usual care. We use a hybrid effectiveness-implementation design to examine implementation barriers and facilitators.

OUTCOMES

For both trials, the primary outcome is EHR documentation of a goals-of-care discussion within 30 days of randomization; additional outcomes include intensity of end-of-life care. Trial 2 also examines patient- or family-reported outcomes assessed by surveys targeting 3-5 days and 4-8 weeks after randomization including quality of goals-of-care communication, receipt of goal-concordant care, and psychological symptoms.

CONCLUSIONS

This novel study incorporates two complementary randomized trials and a hybrid effectiveness-implementation approach to improve the quality and value of care for hospitalized older adults with serious illness.

CLINICAL TRIALS REGISTRATION

STUDY00007031-A and STUDY00007031-B.

Efficacy of a Communication-Priming Intervention on Documented Goals-of-Care Discussions in Hospitalized Patients With Serious Illness: A Randomized Clinical Trial

IMPORTANCE

High-quality goals-of-care communication is critical to delivering goal-concordant, patient-centered care to hospitalized patients with chronic life-limiting illness. However, implementation and documentation of goals-of-care discussions remain important shortcomings in many health systems.

OBJECTIVE

To evaluate the efficacy, feasibility, and acceptability of a patient-facing and clinician-facing communication-priming intervention to promote goals-of-care communication for patients hospitalized with serious illness.

DESIGN, SETTING, AND PARTICIPANTS

This randomized clinical trial enrolled patients from November 6, 2018, to February 18, 2020. The setting was 2 hospitals in an academic health care system in Seattle, Washington. Participants included hospitalized adults with chronic life-limiting illness, aged 65 years or older and with markers of frailty, or aged 80 years or older. Data analysis was performed from August 2020 to August 2021.

INTERVENTION

Patients were randomized to usual care with baseline questionnaires (control) vs the Jumpstart communication-priming intervention. Patients or surrogates in the intervention group and their clinicians received patient-specific Jumpstart Guides populated with data from questionnaires and the electronic health records (EHRs) that were designed to prompt and guide a goals-of-care discussion.

MAIN OUTCOMES AND MEASURES

The primary outcome was EHR documentation of a goals-of-care discussion between randomization and hospital discharge. Additional outcomes included patient-reported or surrogate-reported goals-of-care discussions, patient-reported or surrogate-reported quality of communication, and intervention feasibility and acceptability.

RESULTS

Of 428 eligible patients, this study enrolled 150 patients (35% enrollment rate; mean [SD] age, 59.2 [13.6] years; 66 women [44%]; 132 [88%] by patient consent and 18 [12%] by surrogate consent). Seventy-five patients each were randomized to the intervention and control groups. Compared with the control group, the cumulative incidence of EHR-documented goals-of-care discussions between randomization and hospital discharge was higher in the intervention group (16 of 75 patients [21%] vs 6 of 75 patients [8%]; risk difference, 13% [95% CI, 2%-24%]; risk ratio, 2.67 [95% CI, 1.10-6.44]; P = .04). Patient-reported or surrogate-reported goals-of-care discussions did not differ significantly between groups (30 of 66 patients [45%] vs 36 of 66 patients [55%]), although the intrarater consistency of patient and surrogate reports was poor. Patient-rated or surrogate-rated quality of communication did not differ significantly between groups. The intervention was feasible and acceptable to patients, surrogates, and clinicians.

CONCLUSIONS AND RELEVANCE

In this randomized clinical trial, a patient-facing and clinician-facing communication priming intervention for seriously ill, hospitalized patients promoted EHR-documented goals-of-care discussions before discharge with good feasibility and acceptability. Communication-priming interventions should be reexamined in a larger randomized clinical trial to better understand their effectiveness in the inpatient setting.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03746392.

Communicating Risk for Obesity in Early Life: Engaging Parents Using Human-Centered Design Methodologies

OBJECTIVE

Pediatricians are well positioned to discuss early life obesity risk, but optimal methods of communication should account for parent preferences. To help inform communication strategies focused on early life obesity prevention, we employed human-centered design methodologies to identify parental perceptions, concerns, beliefs, and communication preferences about early life obesity risk.

METHODS

We conducted a series of virtual human-centered design research sessions with 31 parents of infants <24 months old. Parents were recruited with a human intelligence task posted on Amazon's Mechanical Turk, via social media postings on Facebook and Reddit, and from local community organizations. Human-centered design techniques included individual short-answer activities derived from personas and empathy maps as well as group discussion.

RESULTS

Parents welcomed a conversation about infant weight and obesity risk, but concerns about health were expressed in relation to the future. Tone, context, and collaboration emerged as important for obesity prevention discussions. Framing the conversation around healthy changes for the entire family to prevent adverse impacts of excess weight may be more effective than focusing on weight loss.

CONCLUSIONS

Our human-centered design approach provides a model for developing and refining messages and materials aimed at increasing parent/provider communication about early life obesity prevention. Motivating families to engage in obesity prevention may require pediatricians and other health professionals to frame the conversation within the context of other developmental milestones, involve the entire family, and provide practical strategies for behavioral change.