A Web-Based Peer Support Network to Help Care Partners of People With Serious Illness: Co-Design Study.

BACKGROUND: Care partners of people with serious illness experience significant challenges and unmet needs during the patient's treatment period and after their death. Learning from others with shared experiences can be valuable, but opportunities are not consistently available. OBJECTIVE: This study aims to design and prototype a regional, facilitated, and web-based peer support network to help active and bereaved care partners of persons with serious illness be better prepared to cope with the surprises that arise during serious illness and in bereavement. METHODS: An 18-member co-design team included active care partners and those in bereavement, people who had experienced serious illness, regional health care and support partners, and clinicians. It was guided by facilitators and peer network subject-matter experts. We conducted design exercises to identify the functions and specifications of a peer support network. Co-design members independently prioritized network specifications, which were incorporated into an early iteration of the web-based network. RESULTS: The team prioritized two functions: (1) connecting care partners to information and (2) facilitating emotional support. The design process generated 24 potential network specifications to support these functions. The highest priorities included providing a supportive and respectful community; connecting people to trusted resources; reducing barriers to asking for help; and providing frequently asked questions and responses. The network platform had to be simple and intuitive, provide technical support for users, protect member privacy, provide publicly available information and a private discussion forum, and be easily accessible. It was feasible to enroll members in the ConnectShareCare web-based network over a 3-month period. CONCLUSIONS: A co-design process supported the identification of critical features of a peer support network for care partners of people with serious illnesses in a rural setting, as well as initial testing and use. Further testing is underway to assess the long-term viability and impact of the network.

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.

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.