Glossary
Coproduction of Healthcare Services
Quality Improvement
According to the US Department of Health & Human Services, “Quality improvement (QI) consists of systematic and continuous actions that lead to measurable improvement in health care services and the health status of targeted patient groups.” The aim of quality improvement projects is often to reduce variation in care, increase quality, and identify the best possible practices for the best possible outcomes. To learn more about QI in healthcare, we recommend the Institute for Healthcare Improvement (IHI).
Coproduction Dashboard
More details:
The information displayed in a coproduction dashboard usually comes directly from health questionnaires completed by patients and from information stored in an electronic medical record or a data registry. The dashboard can be used together by the patient, family, and care team during a health care appointment, or can be used separately by the patient and family at home or by the care team in clinic between healthcare appointments.
Personalized, proactive, patient-centered care: “Some information you just can’t get from a chart. Now, we’re walking into a visit prepared with an understanding of what the patient is most concerned about. It allows the visit to be about the patient, not about their disease.” – Inflammatory Bowel Disease Physician
Support Network
A network of patients, families, or others that shares resources and knowledge in order to support wellness and self-care activities. Support networks often take place outside of the traditional healthcare delivery setting.
More details:
Support networks that link patients and families together can foster sharing of information, care advice, personal stories, social and spiritual support, and learning among patients living with similar conditions and their families. Such networks are often co-curated by patients, families, and professionals and provide information to support optimal care experiences, health, and high value care.
Support networks use a variety of mediums including in person interactions, newsletters, online discussion boards, and social network sites. In addition to the benefit of bringing together distributed resources such as health information and self-care knowledge, perceived patient benefits include better understanding of health conditions, greater control of disease management, and improved treatment adherence based on real-world patient experiences.
Examples of virtual support networks:
- PatientsLikeMe: A health information sharing website where patients share personal stories and health data about their conditions to help uncover new knowledge.
- A-CHESS: A relapse prevention platform designed for people with addiction disorders. It provides personalized recovery resources and connections with peers and clinicians.
- Whatnext.com: An online cancer support network that connects people to peers and resources based on a specific diagnosis.
- Ben’s Friends Patient Support Communities: A network of patient support sites for people with rare conditions.
- Glu: An online community for people living with type 1 diabetes designed to accelerate research and amplify the collective voice of those living with T1D.
Examples of face-to-face networks:
- Self-dialysis center, Ryhov, Sweden; Support groups; Alcoholics Anonymous
Feed-Forward Data
In successful patient-provider partnerships, both patients (plus family / caregivers) and clinicians contribute important information that informs the next step in the plan of care. In a coproduction learning health system, this important data is fed-forward to, or sent in advance of, the clinic visit. Patients feed forward data on symptoms, goals, and worries. Clinicians feed forward data on outcomes, test results, and assessments. Both parties have access to all feed-forward data in the shared information environment.
Research Registry
A research registry, sometimes called a patient or clinical registry, “is a collection—for one or more purposes—of standardized information about a group of patients who share a condition or experience” (Workman 2013). These large datasets are powerful tools for measuring the effectiveness of drugs and therapies, improving quality of care, and enabling customization of healthcare services based on health data from thousands of individuals. Research registries allow scientists to better study disease, clinicians to improve their care, and patients to contribute to research and science to benefit their own health and the health of millions of others.
Learning Health System
Defined by the National Academy of Medicine, as “a system in which science, informatics, incentives, and culture are aligned for continuous improvement and innovation, with best practices seamlessly embedded in the delivery process and new knowledge captured as an integral by-product of the delivery experience.”