The Precision Feedback Knowledge Base has a collection of vignettes that illustrate how the knowledge base can be used by a precision feedback system to prioritize motivating performance information and tailor feedback messages. Each vignette uses a fictional context and providers, called personas, who are representative of some population of providers. The vignette includes narrative description of the function of a precision feedback system, as well as computer-interpretable code and files that can be used to test out the function of the precision feedback system. The narrative part of each vignette is written for clinical feedback system stakeholders, focusing primarily on a researchers and feedback system developers for feedback systems in health care organizations. The purpose of the vignettes is also to increase the findability and transparency of the precision feedback system software to all stakeholders, including healthcare professionals, patients, and communities.
Each vignette is organized around one unit of knowledge about how precision feedback messages can be influential and provide value for healthcare professionals’ clinical practice. These units of knowledge in the knowledge base are written as causal pathway models that specify how feedback works, and which link relevant theories and other known factors of interest to researchers, to enable the use of the feedback system to contribute to the development of generalizable knowledge about how feedback works in healthcare organizations.
The vignettes are written for the context of a collaborative quality initiative in which a network of healthcare organizations share quality and outcomes data to learn to improve clinical practice and the health of patients.
A healthcare quality improvement consortium called the Multicenter Perioperative Outcomes Group (MPOG) uses precision feedback to prioritize motivating performance information about the quality and outcomes of operative cases. Precision feedback is an kind of feedback intervention that prioritizes motivating performance information and customizes its delivery based on the preferences of the feedback recipient, or that of their population segment. Emails with precision feedback about various performance measures are sent each month to anesthesia providers in approximately 35 healthcare institutions. One performance measure that MPOG assesses for operative cases regards the minimization of the use of climate-sensitive anesthetic gases: SUS-04 : Fresh Gas Flow, less than or equal to 2L/min.
Alice is an attending anesthesiologist at Midwest Medicine, a medical-school affiliated hospital. She is motivated to continue improving her practice and that of her team, and who values setting new goals for her and her team to reach. MPOG has not yet elicited preferences from Alice about precision feedback. An organizational preference profile for anesthesia providers at Midwest Medicine has been developed from a cluster analysis of a sample of providers who have taken an online preference survey, and these results are used for Alice and any other anesthesia provider who has not yet taken a preference survey. This profile prioritizes feedback messages about changes in performance involving the achievement of peer benchmarks, drops in performance below a peer average, and improvement towards the peer benchmark, as well as time-series visualization in bar charts and line charts. The Midwest Medicine Anesthesia Provider Preference Profile is a set of relative utilities for attributes of feedback messages that a precision feedback system uses to prioritize performance information and feedback display format.
Bob is a CRNA at Danville Hospital, a community hospital. He cares deeply about the safety of his patients and the efficiency of his team to provide the best care for patients in his community. He is proud of his team’s record of providing high-quality and exceptionally safe care, and the quality awards that his hospital has received in recognition of their exceptional work. Bob prefers to receive notifications about any potential quality issues or significant problems, such as adverse events, that may require special attention from him and his team. Bob prefers to receive these in a brief sentence that does not require him to look at a chart, but which helps him understand that there is some follow-up required to dig into the details of one or more operative cases. Bob took a feedback preference survey which generated a set of relative utilities for feedback message attributes that a precision feedback system can use.
Chikondi is a resident at Max Community hospital. She is focused on improving the quality of care by learning and implementing the best practices during her residency. Chikondi prefers to recieve feedback about changes in her performance compared to her peers and MPOG goals. She prefers recieving her performance in bar charts which will help her view her performance at a glance without having to spend much time. She believes that focusing on her performance change and comparing to the peers and goals will motivate her to perform well each month. Chikondi did not take the preference survey, hence an organizational preference profile of Max Community Hospital is used to generate precision feedback for the group.
Deepa is a dedicated Certified Registered Nurse Anesthetist (CRNA) at Midwest Medicine, a medical-school affiliated hospital. She is committed to delivering the best possible care to her patients. She values the quality of patient care and always strives to improve it by working collaboratively with her team. Deepa is passionate about using data to enhance patient outcomes and regularly reviews feedback reports to identify areas for improvement. Deepa is specifically interested in knowing when her performance is worsening compared to her peers and goals. She values the insights that data can provide and prefers to receive feedback reports that are easy to interpret and act upon. Deepa prefers to receive feedback reports in the form of line charts, which allow her to easily visualize trends over time. She believes that line charts are more effective than other types of charts because they provide a clear and concise representation of data.
Eugene is a resident at Midwest Medicine, a medical-school affiliated hospital. He is commited to improving the quality of his care as he continues to learn best practices throughout his residency. He is motivated by the high performance of his peers, who are committed to continuous learning and improvement together. They have a deep sense of cameraderie, but also competition. Eugene always wants to know about adverse events and drops in performance, since they indicate that he must change something about his practice. As a resident, he prefers to receive this information alongside a line chart, which can help him discern how his performance has changed over time. He likes to see how he compares to his peers and whether he is fallling behind or staying ahead. Eugene has taken a feedback survey which generated a set of relative utilities for feedback messages that is tailed to his preferences.
Fahad is an experienced attending anesthesiologist at Max Community Hospital. Fahad’s hospital struggles to meet quality improvement goals due to their recent staff overturn and general challenges in providing care. Fahad works as part of a quality improvement team at Danville. He pays close attention to monthly emails from MPOG to meet goals and benchmarks by changing his practice, thinking introspectively to allow him to communicate methods of improving personal performance to his team. Excited by the potential of receiving precision feedback, he took a survey which generated relative utilities that deliver feedback in an ideal manner. While Fahad is a top-performer, he always wants to know how he can improve even further. He likes the presence of visual displays such as bar charts and line charts because he uses these as a tool for communication with his team, but dislikes interpretation and prefers to look at the data directly. He often uses the MPOG feedback email to direct his attention to this patients on a case-by-case basis.
Gaile is a resident at Midwest Medicine, a medical-school affiliated hospital. Gaile is always interested in improving their practice and continuing to learn to care for patients to the best of their ability. Gaile has not yet taken the preference survey, so an organizational preference profile of residents at Midwest Medicine is used to generate precision feedback for the group. The resident profile prioritizes positive encouragement with gain-framing messages so that those early in their career feel motivated to continue providing high quality care. The resident profile also prioritizes social comparison, as residents often want to know how they are performing relative to the group overall. Finally, visualizations that are easy to understand at a quick glance are also included, given the busy schedule and time constraints of this group.