Rapid Action & Learning Intensives (RALI)

The Rapid Action Learning Intensive (RALI) is a new learning tool we've developed to spread and scale the successful change ideas discovered in our learning collaboratives. We piloted RALI in summer 2023, based on the Foundations of Equity learning collaborative. We made changes to the model based on participant feedback and officially launched our first RALI, RALI for Sociodemographic Data (RALI-SDD), the following spring. We have since extended the RALI model to other topics. 

RALI was initially piloted as a synchronous learning opportunity that distilled the learnings from the Foundations of Equity Learning Collaborative into a series of easily operationalized steps to follow to improve sociodemographic data collection rates. Based on learnings from that pilot, RALI was adapted into a self-directed program that teams could work through at the pace that best suits them. In its current iteration, RALI is a hybrid model that allows teams to work independently at their own pace yet offers scheduled learning sessions for those who prefer a more structured approach. 

Although self-paced and self-directed, RALI is a coach-supported learning model. Participating teams get access to online modules, a workbook, curated external resources, and the dedicated support of an Alliance Quality Improvement Coach, as well as the option to join scheduled learning sessions, when available. The online modules, the workbooks, and QI coaching are available in both English and French. Other resources are provided in the language(s) available. 

To learn more or sign up, email QI@AllianceON.org. Currently, RALI is available to Alliance-member organizations only. 

The Rapid Action and Learning Intensive on sociodemographic data (RALI-SDD) is an initiative that aims to support centres to adopt, adapt, and apply the learnings from the Foundations of Equity Learning Collaborative.

RALI-SDD was launched in Spring 2024, with a focus on improving sociodemographic data completeness. The program guides primary health care teams through the implementation of a validated process for collecting high-quality, useable sociodemographic data; properly inputting it in their EMR; and using EMR data for testing and learning. 

The first phase of any improvement effort is goal-setting. RALI-SDD begins by helping teams create a SMART quality improvement goal related to sociodemographic data collection. It then leads them through documenting and analysing their existing process, so they can understand what changes are necessary. 

The data collection process at the heart of RALI-SDD, which we refer to as the 7-Step Process,  was informed by learnings from our Foundations of Equity learning collaborative. Each of the 7 steps includes both "tight" (must-do) and "loose" (variable) elements. For example, giving each client a sociodemographic data form is a tight step, it has loose elements which include who gives the form to the client, what is the order or layout of the questions on the form, what format the form is in, and how the form is shared with the client. Participating teams develop their own, customized version of the process by optimizing the loose elements.

After a team customizes their 7-step process, RALI guides them through testing their new process with iterative plan-do-study-act (PDSA) cycles, based on the Institute for Healthcare Improvement's (IHI) Model for Improvement. Teams implement the process on a small scale, then monitor their sociodemographic data completeness and usability to determine how well the process is working for them. Based on the results of that testing, they may proceed to scale up the process or adjust some of the loose elements.

The final phase of RALI-SDD is to transition from testing to implementation of the 7-Step Process across  each participating organization. Drawing from implementation science, the COM-B theory of change and the Centre for Implementation's StrategEase, we created a collection of tools that can help participating teams build their implementation plan. 

Patient-Reported Outcome Measures (PROMS) capture data about how clients perceive their health and wellbeing. These tools empower patients to be partners in their care and help us understand whether an intervention is helping a client reach their health goals. In the fall of 2022, the Alliance launched a pilot project to test the use of the EQ-5D PROMs tool at 6 Community Health Centres. We learned where the tool supported collaborative care planning and program evaluation as well as best practices for implementation and use of the EQ-5D PROMs tool.

The Rapid Action Learning Intensive on Patient Reported Outcome Measures (RALI-PROMs) is an initiative that aims to support centres to adopt, adapt, and apply the learnings from the Alliance’s PROMs pilot project. Participating teams will be supported in implementing PROMs data collection through learning sessions, QI coaching support as well as resources such as the RALI-PROMs how-to guide and workbook. 

Implementation of a PROMs process and collection of PROMs data will be useful for organizations who are interested in: 

• Supporting goal-centered care and co-creation of care plans.
• Informing clinical practice by identifying health issues that may otherwise go unnoticed by providers and clients.
• Monitoring changes in symptoms and health concerns in a standardized manner.
• Evaluating and improving program and/or service delivery when completed at baseline and follow-up. 

Similar to RALI-SDD, a how-to guide and workbook has been developed to support teams in implementing PROMs data collection. Within it include implementation steps as well as the RALI-PROMs Intervention: The 7-Step Process. This outlines the core elements for any PROMs process to ensure effective administration of the EQ-5D tool and collection and use of PROMs data.