The Cystic Fibrosis Learning Network: A mixed methods evaluation of program goals, attributes, and impact

Introduction

The Cystic Fibrosis (CF) Foundation sponsored the design, pilot testing, and implementation of the CF Learning Network (CFLN) to explore how the Foundation's Care Center Network (CCN) could become a learning health system. Six years after the design, the Foundation commissioned a formative mixed methods evaluation of the CFLN to assess: CFLN participants' understanding of program goals, attributes, and perceptions of current and future impact.

Methods

We performed semi-structured interviews with CFLN participants to identify perceived goals, attributes, and impact of the network. Following thematic analyses, we developed and distributed a survey to CFLN members and a matched sample of CCN programs to understand whether the themes were unique to the CFLN.

Results

Interviews with 24 CFLN participants were conducted. Interviewees identified the primary CFLN goal as improving outcomes for people living with CF, with secondary goals of providing training in quality improvement (QI), creating a learning community, engaging all stakeholders in improvement, and spreading best practices to the CCN. Project management, use of data, common QI methods, and the learning community were seen as critical to success. Survey responses were collected from 103 CFLN members and 25 CCN members. The data revealed that CFLN respondents were more likely than CCN respondents to connect with other CF programs, routinely use data for QI, and engage patient and family partners in QI.

Conclusions

Our study suggests that the CFLN provides value beyond that achieved by the CCN. Key questions remain about whether spread of the CFLN could improve outcomes for more people living with CF.

Harnessing the Collective Expertise of Patients, Care Partners, Clinical Teams, and Researchers Through a Coproduction Learning Health System: A Case Study of the Dartmouth Health Promise Partnership

The coproduction learning health system (CLHS) model extends the definition of a learning health system to explicitly bring together patients and care partners, health care teams, administrators, and scientists to share the work of optimizing health outcomes, improving care value, and generating new knowledge. The CLHS model highlights a partnership for coproduction that is supported by data that can be used to support individual patient care, quality improvement, and research. We provide a case study that describes the application of this model to transform care within an oncology program at an academic medical center.

Spreading routine serious illness conversations at a single cancer center using a multidisciplinary and patient-family advisory approach

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Background: ASCO Guidelines recommend oncologists conduct serious illness conservations (SIC) for all patients with advanced cancer. We describe the spreading of a multidisciplinary and patient-family advisor (PFA) quality improvement (QI) initiative to conduct routine SIC at a NCI-designated comprehensive cancer center. Methods: This single center study describes the second phase of a learning health system initiative to conduct routine SIC for all seriously ill patients with cancer. Prior work completed included defining patient eligibility (e.g. two-year surprise question), and deploying a SIC template in the electronic health record (EHR) to capture SIC in a centralized location. Phase II can be categorized into three steps: a) increasing communication coach and PFA capacity; b) refining EHR tools to automate tracking and reporting of outcomes; and c) adoption of the Model for Improvement as the QI methodology to guide testing and implementation. For the first three months, each team engaged in preparatory work including: process mapping, key driver diagram development, and SIC Guide training. In the last six months, each team met weekly to set their own team goals, conducted iterative PDSAs, and reviewed run charts of their performance. Patient-level data on SIC documentation was collected through automated EHR tools and provided to the teams on a weekly basis. Results: Over nine months (3/1/2021 to 12/31/21), four teams screened 510 patients with cancer, identified 272 (53%) patients as eligible for SIC, and 178 (65%) of those eligible had a documented SIC from a baseline of 0%. The breakdown of this combined SIC patient count by clinician author is as follows: team A 40 (22%); team B 45 (25%); team C 9 (5%); team D 14 (8%) and specialty palliative care 70 (39%). Each team set modest, initial SIC documentation goals (range 5-15%), and attainment of first SIC documentation goal varied (range 2 to 4 months). We retained all clinician team members during the study period, but 2 out of 3 PFAs left by study period end. Noted challenges with PFA recruitment and retention included: lengthy recruitment, integration into clinical teams, and resistance to change by teams. Conclusions: The multidisciplinary approach, inclusive of specialty palliative care, increased SIC documentation. PFA involvement, as implemented, met with challenges and yielded mixed results. Additional follow-up will be required to assess if gains can be sustained and/or increased.

Eliciting patients' healthcare goals and concerns: Do questions influence responses?

There is increasing interest in asking patients questions before their visits to elicit goals and concerns, which is part of the move to support the concept of coproducing care. The phrasing and delivery of such questions differs across settings and is likely to influence responses. This report describes a study that (i) used a three-level model to categorize the goals and concerns elicited by two different pre-visit questions, and (ii) describes associations between responses elicited and the phrasing and delivery of the two questions. The questions were administered to patients with rheumatic disease, and patients with inflammatory bowel disease (IBD). Paper-based responses from 150 patients with rheumatic disease and 338 patients with IBD were analyzed (163 paper, 175 electronic). The goals and concerns elicited were primarily disease or symptom-specific. The specific goal and concern examples featured in one pre-visit question were more commonly reported in responses to that question, compared to the question without examples. Questions completed electronically before the visit were associated with longer responses than those completed on paper in the waiting room. In conclusion, how and when patients' goals and concerns are elicited appears to have an impact on responses and warrants further investigation.

Interdisciplinary Approach and Patient/Family Partners to Improve Serious Illness Conversations in Outpatient Oncology

PURPOSE:

We aimed to increase Serious Illness Conversations (SIC) from a baseline of, at or near, zero to 25% of eligible patients by December 31, 2020.

METHODS:

We assembled an interdisciplinary team inclusive of a family partner and used the Model for Improvement as our quality improvement framework. The team developed a SMART Aim, key driver diagram, and SIC workflow. Standardized screening for SIC eligibility was implemented using the 2-year surprise question. Team members were trained in SIC communication skills by a trained facilitator and received ongoing coaching in quality improvement. We performed Plan-Do-Study-Act cycles and used audit-feedback data in weekly team meetings to inform iterative Plan-Do-Study-Act cycles. The primary outcome was the percent of eligible patients with documented SIC.

RESULTS:

Over 18 months, three clinics identified 63 eligible patients; of these, 32 (51%) were diagnosed with head and neck cancer and 31 (49%) with sarcoma. The SIC increased from a baseline near zero to 43 of 63 (70%) patients demonstrating three shifts in the median (95% CI). Conversations were interdisciplinary with 25 (57%) by oncology MD, six (14%) by advanced practice registered nurse, and 13 (30%) by specialty palliative care. We targeted four key drivers: (1) standardized work, (2) engaged interdisciplinary team, (3) engaged patients and families, and (4) system-level support.

CONCLUSION:

Our approach was successful in its documentation of end points and required resource investment (training and time) to embed into team workflows. Future work will evaluate scaling the approach across multiple clinics, the patient experience, and outcomes of care associated with oncology clinician–led SIC.

Prioritizing Measures that Matter Within a Person-Centered Oncology Learning Health System

Background

Despite progress in developing learning health systems (LHS) and associated metrics of success, a gap remains in identifying measures to guide the implementation and assessment of the impact of an oncology LHS. Our aim was to identify a balanced set of measures to guide a person-centered oncology LHS.

Methods

A modified Delphi process and clinical value compass framework were used to prioritize measures for tracking LHS performance. A multidisciplinary group of 77 stakeholders, including people with cancer and family members, participated in 3 rounds of online voting followed by 50-minute discussions. Participants rated metrics on perceived importance to the LHS and discussed priorities.

Results

Voting was completed by 94% of participants and prioritized 22 measures within 8 domains. Patient and caregiver factors included clinical health (Eastern Cooperative Oncology Group Performance Status, survival by cancer type and stage), functional health and quality of life (Patient Reported Outcomes Measurement Information System [PROMIS] Global-10, Distress Thermometer, Modified Caregiver Strain Index), experience of care (advance care planning, collaboRATE, PROMIS Self-Efficacy Scale, access to care, experience of care, end-of-life quality measures), and cost and resource use (avoidance and delay in accessing care and medications, financial hardship, total cost of care). Contextual factors included team well-being (Well-being Index; voluntary staff turnover); learning culture (Improvement Readiness, compliance with Commission on Cancer quality of care measures); scholarly engagement and productivity (institutional commitment and support for research, academic productivity index); and diversity, equity, inclusion, and belonging (screening and follow-up for social determinants of health, inclusivity of staff and patients).

Conclusions

The person-centered LHS value compass provides a balanced set of measures that oncology practices can use to monitor and evaluate improvement across multiple domains.

Development of Balanced Whole System Value Measures for Inflammatory Bowel Disease Care in the IBD Qorus Collaborative Using a Modified Delphi Process

BACKGROUND

The IBD Qorus Collaborative aims to reduce variation and increase the value of care for the adult inflammatory bowel disease (IBD) community. To evaluate the success of the collaborative, we aimed to develop a balanced set of outcome measures that reflect a multistakeholder view of value in IBD care. To achieve this, we used the Clinical Value Compass framework and engaged a mixed-stakeholder group to conduct a modified Delphi process. The end result was a 10-measure set to assess the value of IBD care.

METHOD

The modified Delphi process included 3 iterative rounds of blinded voting and interactive webinar-style discussion. We recruited 18 participants for the Delphi panel, including clinicians, researchers, patients, Crohn's & Colitis Foundation staff, and payers. Participants first identified constructs to measure, then identified the tools to measure those constructs. A literature review and environmental scan of current measures in 4 domains were performed, and relevant measures were proposed for discussion and voting in each domain. Throughout the process, participants were invited to contribute additional measures.

CONCLUSION

The modified Delphi process led to selection of 10 value measures across 4 domains: (1) patient experience; (2) functional status; (3) clinical status; and (4) health care costs and utilization. We have successfully completed a 3-stage modified Delphi process to develop a balanced set of value measures for adult IBD care. The value measure set expands upon prior efforts that have established quality measures for IBD care by adding cost and experience of care elements. This work positions IBD Qorus to better assess, study, improve, and demonstrate value at individual, system, and population levels and will inform and empower related research, improvement, and implementation efforts.

Point-of-care dashboards promote coproduction of healthcare services for patients with inflammatory bowel disease

BACKGROUND

Coproduction of healthcare services by patients and professionals is seen as an increasingly important mechanism to support person-centred care delivery. Coproduction invites a deeper understanding of what persons sometimes called 'patients' bring to development of a service. Yet, little is known about tools that may help elicit that information.

OBJECTIVE

Our objective was to explore potential benefits and limitations of an electronic pre-visit survey (PVS) and dashboard by studying uptake and experiences within the inflammatory bowel disease (IBD) community.

METHODS

We conducted a mixed-method evaluation of patients and clinicians using the IBD Qorus PVS and dashboard at 24 programmes participating in the IBD Qorus learning health system. We analysed (i) descriptive statistics and thematic analyses of 537 patient surveys, (ii) semi-structured interviews with seven patients and six care teams and (iii) usage data collected between 25 March 2019 and 26 April 2020.

RESULTS

Nearly two-thirds (64%; n = 38) of clinicians enrolled ≥25 patients into IBD Qorus; 59% (n = 29) of clinicians received ≥25 electronic PVS, with 3834 PVS received during the study period. Post-visit evaluation surveys were completed by patients following 26% (n = 993) of PVS completions. Among patients who reported using the dashboard for 1 or more months (n = 537), two-thirds (65%, n = 344) used the dashboard at a clinic visit and one-third used it outside the clinic (33%, n = 176). Most patients who used the dashboard during a clinic visit said it was helpful in discussions with their clinician (82%), in talking about what matters most (76%) and in making healthcare decisions (71%). Patients using the dashboard during the clinic visit reported higher levels of shared decision-making than those who did not use the dashboard (82% vs. 65%, P < 0.001). This relationship remained significant after controlling for receipt of care at a clinic with the highest levels of patient-reported shared decision-making (odds ratio: 2.1; confidence interval: 1.3-3.3). Patients and clinicians found the greatest value in using the PVS and dashboard to share concerns and symptoms, prepare for a visit and support discussions during the visit. The lack of integration with existing electronic health records (EHRs) limited clinician usage of the PVS and dashboard.

CONCLUSIONS

The PVS and dashboard created a shared language, which supported coproduction and shared decision-making and facilitated a shared understanding of goals, concerns, symptoms and well-being. To support uptake, future systems should reduce implementation burden for healthcare professionals and integrate seamlessly with existing EHR systems and workflows.