The evolution of interview methodologies to inform the co-design of interventions for an implementation initiative to enhance transitions in care practices in primary care

The evolution of interview methodologies to inform the co-design of interventions for an implementation initiative to enhance transitions in care practices in primary care | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The evolution of interview methodologies to inform the co-design of interventions for an implementation initiative to enhance transitions in care practices in primary care Sarah Filiatreault, Ceara Cunningham, Staci Hastings, Jodi Cullum, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6523077/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: People living with chronic health conditions are at risk for poor transitions in care (TiC) because of poor discharge coordination and care integration. An ongoing study in Alberta, Canada called A DiseAse-Inclusive Pathway for Transitions in Care (ADAPT) focuses on co-designing interventions to enhance TiC practices in primary care for high-risk people with chronic diseases. The aim of this paper is to provide an overview of the application and evolution of the qualitative interview methods used in the context of the ADAPT study, and highlight key findings and lessons learned from using each method. Methods: Initial steps for co-design included current state assessments of TiC workflow processes for primary care. To create comprehensive maps of existing processes, qualitative interviewing techniques were applied. The first methodological approaches used were the ORID (Objective, Reflective, Interpretive, and Decisional) framework (Phase 1) and cognitive task analysis (CTA) (Phase 2). Challenges were encountered using both approaches (i.e., Phase 1 lacked detail and Phase 2 was resource intensive). Therefore, a novel hybrid approach was developed (Phase 3). Results: Results from Phase 1 were grouped into five key themes: People, Processes, System, Outcomes, and Solutions. Phase 2 resulted in an in-depth understanding of each key primary care activity during the transition out of acute care. The themes identified in Phase 1 were critical in supporting the evolution of the interview guide and approach in Phase 3. The new hybrid approach allowed immediate incorporation of interview data into a visual current state map highlighting processes and team member involvement throughout a patient’s TiC journey. Conclusion: The new hybrid approach led to a balance of providing enough detail in a timely fashion to better prepare the study to move into identifying opportunities for practice change and intervention co-design. Developing hybrid approaches for rapid qualitative analysis that balance rigor and efficiency is important to advance research to facilitate complex implementation initiatives. qualitative methods rapid qualitative assessment care transitions co-design hybrid designs implementation science Figures Figure 1 Figure 2 Figure 3 Contributions to the Literature Demand for timely results, need for various perspectives, differences across settings, and contextual changes over time require innovative approaches for conducting qualitative interviews in implementation science (i.e., rapid qualitative analysis). To our knowledge, this is the first study combining the ORID framework and CTA to create a hybrid approach for rapid qualitative analysis. The new hybrid approach allowed immediate incorporation of data into a visual current state map highlighting processes and team member involvement. Participants agreed the data visualization technique (i.e., current state map) was highly useful to understand their current practices and help them identify potential areas for improvement. Background Transitions in care (TiC) from acute care to primary care have been a focus of health care improvement for several years ( 1 – 4 ). However, discharge coordination and care integration across settings continues to be a challenge ( 5 ), putting people living with complex chronic health conditions at risk for poor TiCs ( 5 ). People who experience poor TiCs are at higher risk for poorer outcomes such as mortality, emergency department visits, and unplanned hospital readmissions ( 6 ). This risk is greater during the period between hospital discharge and primary care follow-up. Research has shown that timely follow-up with primary care after hospital discharge reduces readmission rates and mortality ( 7 – 9 ). Bricard and Or (2019) and Anderson et al. (2022) found early follow-up with a primary care provider within the first week of discharge reduced 28- and 30-day all-cause readmission risks respectively by nearly 50% ( 7 , 8 ). Similarly, Saxena et al. (2022) observed lower rates of unplanned readmissions and mortality at 90-days among patients who had early follow-up post-hospital discharge ( 9 ). It is clear that primary care is a pivotal component for successful TiCs. Therefore, efforts are needed to design and implement initiatives to enhance primary care practices to support high-quality TiCs. An ongoing study in Alberta, Canada called A DiseAse-Inclusive Pathway for Transitions in Care (ADAPT) focuses on integrating care by collaborating with primary care providers to enhance TiCs. This study is led by Alberta Health Service’s (AHS) Primary Health Care Integration Network, which has been leading the development of the Home to Hospital to Home (H2H2H) transitions guideline for several years ( 10 ). Grounded in implementation science (IS), the ADAPT study is an embedded implementation initiative focused on implementing three of the six core H2H2H guideline elements (admit notification, transition planning, and follow-up to primary care) for Albertans over 18 years of age with heart failure (HF), chronic obstructive pulmonary disease (COPD), liver cirrhosis, and/or chronic kidney disease (CKD). A Patient Transitions Resources team, of 6 patient advisors supports this work and has been involved in its design and implementation of TiC initiatives for the past 5 years. Patients, families, and caregivers are critical partners who lead and support the roll out of the H2H2H guideline. The ADAPT study received ethics approval from the University of Alberta Research Ethics Board (ID:Pro0010674). The purpose of ADAPT is to support and standardize patient transitions by integrating, spreading, and scaling best evidence-based practices across Alberta’s primary care clinics during TiC. The early stages of ADAPT involved gaining understanding about the diverse primary care contexts throughout the province of Alberta to inform the design and preparation for co-designing interventions and guiding the implementation process. Qualitative interviewing has been gaining momentum within the field of IS as an effective method to inform the design and implementation of complex interventions, as well as to gain understanding about contexts across diverse settings ( 11 – 13 ). IS is action orientated and focuses on understanding changes that occurs as a result of implementation strategies and interventions (including the who, what, where, when, and how of those changes) ( 11 ). This type of work usually occurs over a relatively short period of time compared to traditional qualitative research, which tends to be resource intensive (e.g., time and financial) ( 11 – 13 ). The demand for timely results, need for perspectives from various interest groups, differences across implementation settings, and contextual changes over time require new and innovative approaches for conducting qualitative interviews in the context of IS research ( 11 ). Researchers have begun working on qualitative methods for IS which aim to balance rigor and efficiency ( 11 – 13 ). These methods have been called rapid assessment and rapid qualitative analysis ( 11 – 13 ). However, these methods are still evolving, with few examples in the literature ( 13 ). QualRIS (2019) highlight that: “There is a pressing need for methodological innovations to meet the challenges for the rigorous use of qualitative methods in implementation science. There is also great opportunity to advance both qualitative methodology and implementation science in pursuing such innovations” ( 11 ). As this is a new and evolving area, it is important for researchers to share insights into what has worked, what hasn’t, and how new or hybrid approaches have been developed to tackle inherent challenges when designing and conducting complex implementation initiatives. To address these gaps, the objective of this paper is to provide an overview of the application and evolution of the qualitative interview methods used in the context of the ADAPT study, and highlight key findings and lessons learned from the application of each method. Methods The research team applied multiple interview and analysis methods to map out current state activities and processes and understand the needs of clinic teams in preparation of the co-design phase of the ADAPT study. The interview approaches started with general data gathering and shifted to more targeted approaches. The question guides and data evolved from a general understanding of TiC in primary care to mapping distinct processes for TiC activities for providers and their teams in preparation to identify and co-design enhanced practices for TiC. The following section describes the evolution of interview approaches from the start to the final iteration of interviewing to efficiently guide clinic teams into co-design and implementation. Interviews were completed between Summer 2021 to Fall 2024. An overview of interviewing phases and main objective of each are shown in Fig. 1 . In all phases, individual (one-on-one) interviews were conducted virtually using the Zoom Video Communication platform or in-person, to meet the needs of interviewees. Participant sample and recruitment Participants included primary care providers and multidisciplinary team members (e.g., nurses, medical office assistants, and pharmacists). Participants were recruited to participate in the ADAPT study through an existing network of providers previously involved in the development of the H2H2H guideline, which included both convenience and purposive sampling. Recruitment was monitored to ensure it was representative of all five AHS geographical zones in Alberta (North, Edmonton, Central, Calgary, and South), and a mix of geographic regions (i.e., both rural and urban). Further, information about clinic patient volume and the proportion of patients attending who live with a chronic disease was gathered. Participants were asked to focus on their experiences providing follow-up care to patients discharged from acute care and back into their care with one of the four chronic disease groups included in the ADAPT study over the age of 18. Phase 1 During Phase 1, the ORID (Objective, Reflective, Interpretive, and Decisional) framework ( 14 ) was used to conduct interviews to better understand current TiC practices in primary care. ORID is a structured process for facilitating focused conversations to gather feedback on participants’ experiences; analyze facts, feelings, and implications; and reach intellectual decisions ( 14 ). This approach generates qualitative data valuable for evaluating and improving projects or processes ( 14 ). This stage of interviews explored participants’ clinic team environment and processes for following up with patients with COPD, HF, CKD, and/or liver cirrhosis (i.e., ADAPT study patient criteria) after being discharged from an inpatient hospital stay. Participants were asked to identify and describe effective follow-up processes, ineffective processes, improvements they desired for their current follow-up processes, and what their top priorities for change would be. Participants were also asked to provide feedback on a draft process map outlining key primary care workflow processes when patients are discharged from acute care returning to primary care. After reflecting on the process map, participants were asked to identify components that stood out for them, components they liked or disliked, desired changes, and core steps for managing patients during a post-discharge follow-up visit. The ORID structured interview guide is available upon request. During this phase, due to COVID restrictions, recruitment was put on pause. Interviews conducted in this phase included any primary care teams and providers in the province of Alberta (i.e., not only those enrolled in the study as participants). Phase 1 interview data were recorded, transcribed, and checked for accuracy. The data were then analyzed by two researchers for themes using NVivo 12 software using the six-phase inductive thematic analysis approach described by Braun and Clarke (2012) ( 15 ). General surface-level codes were created by each analyst separately and compared afterward for consistency. This was followed by linking broader themes from the data to the initial descriptive codes. Throughout the analysis, inconsistencies and disagreements in coding and themes were examined and discussed until a consensus was reached. Phase 2 Cognitive Task Analysis (CTA) was used in Phase 2 to elicit greater detail of clinic teams’ current follow-up practices and to identify key patterns and variations in practice, as well as leverageable opportunities to address gaps ( 16 ). The interview guide was developed to reflect the iterative process of CTA. The guide included multiple sweeps, starting with general questions on available technologies accessed and a walk-through of primary care clinic processes from initial notification of a patient being admitted to acute care to the follow-up in primary care. This was followed by deepening probes at key transition time points (i.e., patient admitted, patient discharge, follow-up by primary care). To understand if those patient examples represented the norm for patient care and what occurs in more diverse situations, a series of counterfactual questions were asked (e.g., what happens if your patient does not show up for their primary care follow-up visit?). Lastly, a final sweep was done to clarify their mental models around roles and responsibilities of clinic members. Mental models can be defined as a dynamic set of beliefs and values involving how people make sense of events and experiences, solve problems, formulate judgements and ultimately make decision and act ( 17 ). CTA can be used to elicit mental models of team-based post-discharge and follow up with primary care approaches. The CTA interview guide is available upon request. Phase 2 interview data were recorded, transcribed, and checked for accuracy. Data analysis was first conducted by two researchers using a structured CTA approach following core CTA macrocognition categories ( 16 ), followed by re-analysis using thematic analysis ( 15 ). This was done because the first approach made it difficult to depict activities in a pragmatic way. The approaches used in Phases 1 and 2 were both resources intensive; therefore, the research team decided to develop a unique hybrid approach incorporating strengths of both methodologies. Phase 3 During Phase 3, a hybrid interview approach was developed using CTA style questions and ORID concepts/themes. The revised interview guide was developed to more directly reflect the H2H2H Guideline elements of interest (admit notification, transition planning, and follow-up to primary care). Open-ended questions were similar to the questions used in the CTA approach (e.g. Tell me about how you learn about an admit to hospital?). Additional questions connected to best practices in the literature were added to determine if and how certain best practices were being applied. For example, we asked questions concerning the ability to see certain high-risk patients within 14-days of discharge. We also included a summative reflection question at the end of the interview guide that was taken from the original ORID informed interview guide. The purpose of this question was to identify from their overall experience, the work processes that were working well and those that were not working well. Detailed work processes were extracted from interview data to create individualized process map templates outlining clinic and/or provider TiC practices ( 18 ). These maps were then used to support codesign sessions where teams collaboratively reviewed the maps to identify implementation gaps, key workflow areas for optimization, and potential practice changes relevant to the H2H2H guideline. The interview flow was improved by changing the structure of the CTA informed guide to mirror and include focused guideline elements. It also provided an opportunity to ask participants to reflect on practices used for all patient groups/conditions. These changes expanded our understanding of core and disease specific practices used by primary care providers and their teams. The final hybrid interview guide is provided in Additional file 1 . Data analysis for this Phase combined deductive categorization from pre-defined themes derived from Phase 1 results ( 19 ) along with a pragmatic approach to visualization by creating process (i.e., current state) maps ( 18 ). All interviews were recorded and then the data were directly synthesized into a process map template. Directly imputing qualitative data into an a priori synthesis tool, such as a data matrix (or process map) has been stated to be a useful approach in the advancement of rapid qualitative assessment in IS research ( 20 ). Multiple researcher team members conducted interviews (CC, DS, SH, KW, KM). Then a team member experienced in qualitative data synthesis conducted the initial data analysis (CC, DS, or SH). This was followed by research team review and gap analysis (i.e., comparing current state to desired state/ best practices) to identify potential areas for co-design. Using team-based approaches to analysis can improve speed while ensuring trustworthy and credible findings ( 20 , 21 ). Results from the analyses were then presented back to study participants to ensure we interpreted the data accurately and to verify nothing was missing in the process map as a preliminary form of member checking to validate findings ( 22 ). These maps were then further validated in sessions with interview participants and other clinic members involved in the ADAPT study to identify areas for co-designing implementing interventions. Results A total of 55 interviews were conducted. In Phase 1, 17 interviews were conducted with primary care providers and multidisciplinary team members. In Phase 2, two primary care providers were interviewed. In Phase 3, 36 primary care providers and multidisciplinary team members were interviewed. Most participants were interviewed virtually and five were conducted in person. Interviews ranged from 17 mins to 83 mins. Participant characteristics by interview phase are presented in Table 1 . Workload and patient demographics were similar across clinics and interview phase. Participants that worked full-time in a primary care clinic reported an approximate volume of 100 to 120 patients per week. The percentage of patients with chronic disease ranged from 15–90%, with the most commonly reported proportion between 60–70%. Table 1 Demographic Details of Participants by Interview Phase (N = 55) Demographics Phase 1 (n = 17) Phase 2 (n = 2)* Phase 3 (n = 36) AHS Zone, n (%) Calgary 7 (41.2%) . 3 (8.3%) Central 3 (17.6%) . 4 (11.1%) North 3 (17.6%) . 8 (22.2%) Edmonton 2 (11.8%) 1 (50.0%) 21 (58.3%) South 1 (5.9%) . . Area, n (%) Urban/ Suburban 11 (64.7%) 1 (50.0%) 24 (66.7%) Rural/ Remote 6 (35.3%) . 12 (33.3%) Healthcare role, n (%) Primary care provider 13 (76.5%) 2 (100%) 23 (63.9%) Nurse 2 (11.8) . 3 (8.3%) Pharmacist or assistant 1 (5.9%) . 3 (8.3%) Coordinator or navigator 1 (5.9%) . 2 (5.6%) Clinic manager . . 1 (2.8%) Medical office assistant . . 4 (11.1%) Notes : *, location unknown for one participant in Phase 2; primary care provider = physician or nurse practitioner; nurse = registered nurse or licenced practical nurse; pharmacist or assistant = pharmacist or pharmacy assistant; coordinator or navigator = transition coordinator or referral navigator. Phase 1 Findings from the initial set of interviews in Phase 1 were grouped into five key themes: People, Processes, System, Outcomes, and Solutions. These key themes are presented in Fig. 2 in which the theme is seen on the y-axis and the key elements for each theme are visualized along the x-axis. The identified themes were critical in supporting the evolution of the interview guide and approach. The initial series of interviews using the ORID framework supported the perception that clinic variability across the province was present in follow-up processes incorporated by providers and their extended teams. Some providers worked closely with their teams for TiC follow-ups, while others were more physician-centric. There was little evidence suggesting common team-based approaches for TiCs and patient follow-up among clinics or between primary and acute care. Results from this phase also yielded limited detail on outcomes data (e.g. how timely follow-up may decrease readmission to hospital) and what type of actions and processes primary care providers were using upon receiving a discharge summary via the electronic health record. Interviews conducted using the ORID framework were effective in understanding and validating generalized current practices and challenges as they related to TiC. However, the initial results of these interviews were one dimensional in that participants struggled to describe their own workflow in detail. Asking general questions about follow-up processes rather than focusing on specific clinic examples or targeted questions connected to the H2H2H guideline also led to responses that lacked focus and specificity. As the ADAPT study moved to working directly with providers participating in the implementation phase, more detailed data on processes, roles, facilitators, and barriers were required. More specifically, details were needed on what people actually do, versus what people think they should do, say, or reflect on. As a result of the observed limitations of the ORID Framework, a decision was made to incorporate an interviewing technique that better reflected how and why participants were making clinical decisions about TiC practices. Phase 2 The CTA approach was chosen to obtain a higher level of detail on TiC practices and team roles. This approach to elicit provider feedback on their clinical activities and mental models around TiC directly led to more focused and nuanced conversations. Discussing the transition journey for a single patient with one of the targeted diagnoses allowed for an in depth understanding of each key primary care activity that occurred during the transition out of acute care. It also helped explore the extent of team-based care at different transition points. However, this approach was found to be highly resource intense and the results lacked generalizability across the study’s patient groups. Phase 3 We used the results from Phase 1 to help support our approach in Phase 3. Specifically, the themes of ‘People’ and ‘Process’ were used to inform the development of the process mapping template and interview guide. Using the hybrid approach allowed us to immediately incorporate interview data around current identified workflow processes into a visual current state map highlighting processes and primary care team member involvement throughout a patient’s transition journey. The new hybrid approach led to a balance of providing enough detail in a timely fashion to better prepare the study to move into identifying opportunities for practice change and intervention co-design. Further, there was consistent positive feedback from participants about the data visualization approach. Participants generally agreed that the data visualization technique (i.e., process/current state map) was a highly useful way to understand their current practices and help them identify potential areas for improvement (e.g., “Boy, you really know a lot about our system”, and “Nice, that looks beautiful”). This novel method informed from ORID and CTA approaches continues to be applied within the ADAPT study to map and assess current state processes. Figure 3 provides an example of a process map developed from a set of clinic interviews. Discussion Developing hybrid approaches for rapid qualitative analysis that balance rigor and efficiency is important to advance IS research and facilitate complex implementation initiatives ( 11 – 13 ), such as ADAPT. There are few examples in the literature of other researchers developing hybrid approaches for rapid qualitative analysis and applying them in IS research ( 13 ). To our knowledge, we are the first research team to combine the ORID framework and CTA to create a hybrid approach for rapid qualitative analysis. Keniston et al. (2023) developed a hybrid approach over the course of six projects related to the COVID-19 pandemic ( 23 ). Authors state they used phenomenology and an interpretive framework of pragmatism to develop their rapid qualitative method ( 23 ). Holdsworth et al. (2020) used a hybrid approach combining rapid qualitative analysis methods with two IS frameworks (Consolidated Framework for Implementation Research [CFIR] ( 24 ) and RE-AIM ( 25 )) ( 20 ). Both examples were studies that aimed to evaluate the implementation of interventions/initiatives. We found no other examples of research using hybrid rapid qualitative analysis to inform planning and the preparation of co-design and implementation of interventions in the literature. Using pragmatic data visualization methods as part of our hybrid approach also provides a novel contribution to the literature. Salvati et al. (2023) provide one example of the use of process mapping as a data synthesis and visualization tool in IS research ( 26 ). Similar to these authors, we found using process mapping as a data visualization tool was a successful way to systematically make comparisons and identify possible practice patterns and gaps, without losing the inherent rich nature of complex data. This enabled a systematic and transparent approach to understanding complex decision making in healthcare and supported co-design of potential practice changes for clinics enrolled in ADAPT. Additionally, this approach demonstrated the diverse representation of professional roles/members who took part in the interviews across all phases (i.e., 1, 2 and 3). While there are some similarities, primary care teams in Alberta differ vastly in context, funding models and resourcing. This results in a wide array of staff working in each clinic, where scope and responsibilities differ significantly depending on the geography and service delivery model (e.g., centralized or decentralized primary care network). Co-design methods have been cited as crucial to the advancement of effective integrated care ( 27 , 28 ). However, it is rarely described and there have been calls for better reporting of the activities involved, including those activities to inform the planning for co-design ( 28 ). Through detailing our process to develop a novel hybrid approach to qualitative interviewing and the lessons learned during the evolution of our approach, this work can contribute to the advancement of research in integrated care. The positive feedback we have received from clinic teams about this approach, and specifically the process mapping, provides evidence as to its potential value for co-designing interventions, as well as during the implementation phase. Historically, process mapping supports better understanding of complex systems and adaptation of improvement interventions to their local context. However, there is little research on its use in health care ( 18 ). As our team moves from co-design to implementation, we have heard from multiple clinic teams that they would also value having a similar process map to guide and monitor the implementation process to track clinic plans/progress, not just the gap analysis process map generated for co-design. This approach also aligns with how Salvati et al.’s (2023) work progressed ( 26 ). Further, it is highly in-line with participatory design theory ( 29 ), which was a guiding principle in the H2H2H Guideline development ( 30 ). Continuous and iterative co-design with end-users over time evolves to include various products, often used in past phases of implementation, but unique and purposefully different depending on the phase (e.g., planning, implementation, evaluation). Process mapping is a good example of this principle in action. Other researchers undertaking planning for the co-design and implementation of complex interventions can apply our hybrid approach to continue advancing these methods with the aim of improving the rigor and efficiency of rapid qualitative analysis in IS to inform interventions to improve integrated care. To support others interested in using a hybrid method to inform the co-design and implementation of complex interventions, we have outlined our key lessons learned and provided a summary of the strengths and limitations of each approach (see Table 2 ). An early lesson from the interview processes was that different stages of an implementation study required different approaches for data gathering. Initially, a broad understanding of provider and team practices for TiC provided direction and helped formulate additional questions to ask leading up to co-design. As the ADAPT study progressed and providers were formally recruited, there was a desire to obtain highly detailed information on mental models and clinic processes. However, employing an approach that was intentionally very narrow and rigid in its approach did not consider multiple patient groups or support the pragmatic analysis of data. The use of CTA may have been more appropriate if there were fewer patient groups and a more targeted set of activities to discuss across clinics. Learning from the strengths and limitations of each methodology in the first two phases of our work led to the evolution of a hybrid approach in the third and final phase. Table 2 Summary of Strengths and Limitations by Methodology Phase Approach Phase 1: ORID Phase 2: CTA Phase 3: Hybrid Strengths • Supported the hypothesis that provincial clinic variability was present in TiC processes for primary care. • Effective in understanding and validating generalized current practices and challenges. • Produced very detailed responses on clinical activities and mental models. • Allowed for more focused and nuanced conversations. • Provided a detailed understanding of the work of providers and team members. • Extraction of detailed work processes from transcript data to place in a visual map for co-design was. • Validated findings and interpretation by member checking at two points during process increases rigor of the method. • Structured the interview guide to align with study specific elements enhanced interview flow and focus. It also primed participants to identify processes that were working well/not working well by reflecting on the follow-up process as a whole • The interview guide encouraged providers to identify what mattered to them. Limitations • Elicited unidimensional responses (i.e., too general and high level), i.e., participants struggled to describe their own workflow in detail; therefore, did not provide enough detail. • The interview guide did not contain questions about processes and activities; therefore, responses lacked focus and specificity. • Data were too situational to be generalizable to entire population of interest. • Information not high-level enough to be useful during the co-design phase. • CTA analysis process was time intensive and not pragmatic. • Data saturation not assessed. • Potential bias from one researcher conducting initial data analysis. The revised hybrid approach to information gathering was integral for moving into co-design with primary care teams with very limited availability. Phrasing questions that allowed for the consideration of multiple patient groups and entering interview data directly into a process map was found to be an effective strategy. In addition, presenting the information back to teams in the form of a process map supported them in identifying opportunities and designing new practices that emphasize a team approach to patient care. Conducting multiple phases of member checking as a form of validation increased the rigor of this process. The hybrid approach and visualization led to a very collaborative and transparent process to identifying opportunities for practice change. However, this approach is not without its own limitations. First, data saturation was not assessed, making it possible that certain processes may have been missed in the interviews. Second, one researcher conducted the initial data analysis. We attempted to mitigate both these limitations by validating findings through member checking at two points, as well as by reviewing results as a research team and conducting a gap analysis collaboratively. This has been stated to be an effective approach to improve speed while maintaining rigor ( 20 ). This project was undertaken during the COVID pandemic and has continued during the pandemic recovery period, which caused challenges in recruitment and planning for co-design. Initially recruitment was put on pause, due to the stress on the healthcare system. This provided an opportunity to conduct an environmental scan, including interviews assessing any primary care clinics in the province (i.e., not only those not enrolled in the study) to assess a broader base of practices. While this helped to bridge the existing evidence gap around team-based approaches to follow-up post-discharge, the interview data lacked focus and specificity. When the team was able to continue with recruitment for the study, the informational needs had shifted, given what we had already learnt. When conducting IS research the level of detail and robustness of interview data must be balanced with the needs and capacities of participants and the ever-changing landscape of health care systems ( 11 ). It is important for researchers to know when and how to pivot their approach to meet the needs of the various interest groups and end-users we work with. Having flexibility in methods is integral to engaging with potential participants and supporting them to see a direction towards new or enhanced practices in implementation initiatives. Conclusion The newly developed methodology was created to be comprehensive but flexible enough to accommodate the pragmatic nature and short timelines of real-world co-design and implementation projects. This methodology can be a powerful tool to gain the information necessary to co-develop interventions to enhance care integration. Abbreviations Transitions in Care (TiCs), A DiseAse-Inclusive Pathway for Transitions in Care (ADAPT), Alberta Health Service (AHS), Home to Hospital to Home (H2H2H), Implementation Science (IS), heart failure (HF), chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), Objective, Reflective, Interpretive, and Decisional (ORID) framework, Cognitive Tast Analysis (CTA). Declarations Ethics approval and consent to participate This study was designed and conducted according to the principles outlined in the Canadian Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans, which is also in accordance with the Declarations of Helsinki. This study received approval from the University of Alberta Health Research Ethics Board (ID: Pro0010674). Consent for publication N/A Availability of data and materials The datasets generated and analysed during the current study are available from the corresponding author on reasonable request. Competing interests Authors declare they have no competing interests to this study Funding This study is supported by an Alberta Innovates Partnership for Research and Innovation in the Health System Grant. Authors’ contributions SND and JS conceived the research idea. Research study was designed by CC and SND. CC, SH, and DS conducted interviews and initial data analysis. SF, CC, SH, JC, and DS were involved in final data analysis, interpretation, and visualization. SF, CC, SH, JC, and DS were involved in current state map validation sessions. The manuscript was drafted by SF, additional content and draft reviews were provided by CC, SH, JC, DS, and SND. All authors reviewed and approved the final version. Acknowledgements The authors wish to acknowledge Dr. Judy Seidel (Co-PI), Elvira Nurmambetova, Kelly Malach, Kristen Ward and the H2H2H guideline and AHS Primary Health Care teams for their contributions in the overall ADAPT project. References Berre ML, Maimon G, Sourial N, Guériton M, Vedel I. Impact of transitional care services for chronically ill older patients: A systematic evidence review. J Am Geriatr Soc. 2017;65(7):1597–608. Coleman EA, Boult C. Improving the quality of transitional care for persons with complex care needs. J Am Geriatr Soc. 2003;51(4):556–7. Naylor MD, Sochalski JA. 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Implement Sci. 2021;16(1):67. Coutts J. Evaluation Methods. 2020. Braun V, Clarke V. Thematic analysis. In: Cooper H, Long MCP, Panter DL, Rindskopf AT, Sher D KJ, editors. APA handbook of research methods in psychology, Vol 2 Research designs: Quantitative, qualitative, neuropsychological, and biological. American Psychological Association; 2012. pp. 57–71. Potworowski G, Green LA. Cognitive task analysis: methods to improve patient-centered medical home models by understanding and leveraging its knowledge work. Agency for Healthcare Research and Quality; 2013; 2013. Wagner KK, Austin J, Toon L, Barber T, Green LA. Differences in Team Mental Models Associated With Medical Home Transformation Success. Annals Family Med. 2019;17(Suppl 1):S50. Antonacci G, Lennox L, Barlow J, Evans L, Reed J. Process mapping in healthcare: a systematic review. BMC Health Serv Res. 2021;21(1):342. Bingham AJ, Witkowsky P, Vanover C, Mihas P, Saldaña J. Analyzing and interpreting qualitative data: After the interview. Deductive and Inductive Approaches to Qualitative Data Analysis; Vanover C, Mihas P, Saldaña J, Eds. 2022:133–46. Holdsworth LM, Safaeinili N, Winget M, Lorenz KA, Lough M, Asch S, et al. Adapting rapid assessment procedures for implementation research using a team-based approach to analysis: a case example of patient quality and safety interventions in the ICU. Implement Sci. 2020;15(1):12. McNall M, Foster-Fishman P. Methods of Rapid Evaluation, Assessment, and Appraisal. Am J Evaluation - AM J EVAL. 2007;28:151–68. Birt L, Scott S, Cavers D, Campbell C, Walter F. Member Checking: A Tool to Enhance Trustworthiness or Merely a Nod to Validation? Qual Health Res. 2016;26(13):1802–11. Keniston A, McBeth L, Astik G, Auerbach A, Busch J, Kangelaris KN, et al. Practical Applications of Rapid Qualitative Analysis for Operations, Quality Improvement, and Research in Dynamically Changing Hospital Environments. Joint Comm J Qual Patient Saf. 2023;49(2):98–104. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4(1):50. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89(9):1322–7. Salvati ZM, Rahm AK, Williams MS, Ladd I, Schlieder V, Atondo J, et al. A picture is worth a thousand words: advancing the use of visualization tools in implementation science through process mapping and matrix heat mapping. Implement Sci Commun. 2023;4(1):43. Ward ME, De Brún A, Beirne D, Conway C, Cunningham U, English A et al. Using Co-Design to Develop a Collective Leadership Intervention for Healthcare Teams to Improve Safety Culture. Int J Environ Res Public Health [Internet] 2018; 15(6). Slattery P, Saeri AK, Bragge P. Research co-design in health: a rapid overview of reviews. Health Res Policy Syst. 2020;18(1):17. Bjögvinsson E, Ehn P, Hillgren P-A. Design Things and Design Thinking: Contemporary Participatory Design Challenges. Des Issues. 2012;28(3):101–16. Walker RL, Hastings S, Cook C, Cunningham CT, Cook L, Cullum J, et al. Integrating care from home to hospital to home: using participatory design to develop a provincial transitions in care guideline. Int J Integr Care. 2022;22(2):1–13. Supplementary Files Additionalfile1.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6523077","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":475544966,"identity":"9f862a1a-0101-41c3-927e-500bb165e5ed","order_by":0,"name":"Sarah Filiatreault","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIie2PsWrDMBRFnxEoi4NXZYl/4YIhNH+jUKiXQAxdMoSgUFC3zv6NLJlVBO7iD/AUYrx2yFQylBC5a0A4Wwed5S063COiQOA/wj53RrqbEEV2mMIXyimgiSLqFTFAkWTIKTBDlVQzZU6b31XWPJ9ssT5uE8Xas09BFbmwCvND8wJb1q9CGJ55p5DunMKBWSNhx1oKMrG/LtX9yhXIyvxsx1cpUhOzi/czfdhCAxBLt6KkgIm5P+xP+cgg6u/ClpWc7C2fPfnDRm17+Zkiec/3XbGRyfTrrWu8YfewB98HAoFA4J4brYBOZESOgBYAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-8442-1990","institution":"University of Alberta Department of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Filiatreault","suffix":""},{"id":475544967,"identity":"c90e4f1e-8e26-4b53-9e76-0d4b49cea44b","order_by":1,"name":"Ceara Cunningham","email":"","orcid":"","institution":"Alberta Health Services","correspondingAuthor":false,"prefix":"","firstName":"Ceara","middleName":"","lastName":"Cunningham","suffix":""},{"id":475544968,"identity":"b1263c9d-07bf-4b11-9e8b-bee8f1753e50","order_by":2,"name":"Staci Hastings","email":"","orcid":"","institution":"Alberta Health Services","correspondingAuthor":false,"prefix":"","firstName":"Staci","middleName":"","lastName":"Hastings","suffix":""},{"id":475544969,"identity":"d8acb362-3965-4a18-888a-42ad09dd6fd7","order_by":3,"name":"Jodi Cullum","email":"","orcid":"","institution":"Alberta Health Services","correspondingAuthor":false,"prefix":"","firstName":"Jodi","middleName":"","lastName":"Cullum","suffix":""},{"id":475544970,"identity":"544ab2cd-caa7-4379-8a6b-07b8e6d4957d","order_by":4,"name":"Dawn Schroeder","email":"","orcid":"","institution":"Alberta Health Services","correspondingAuthor":false,"prefix":"","firstName":"Dawn","middleName":"","lastName":"Schroeder","suffix":""},{"id":475544971,"identity":"1f8cabbd-8548-426e-ae2c-cef298e0fe74","order_by":5,"name":"Sara N. Davison","email":"","orcid":"","institution":"University of Alberta Department of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"N.","lastName":"Davison","suffix":""}],"badges":[],"createdAt":"2025-04-24 18:08:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6523077/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6523077/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85644293,"identity":"ed2af62c-fa1c-4b8b-b8e2-13f987b29aa8","added_by":"auto","created_at":"2025-06-30 08:10:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":184751,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverview of interview phases\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6523077/v1/5a54dea9da5b9386f8223fce.png"},{"id":85644733,"identity":"4205c26c-72f7-4f55-b972-9015d14e00bf","added_by":"auto","created_at":"2025-06-30 08:18:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":221593,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVisualizing key themes for follow-up to primary care\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6523077/v1/2a2de46758b6556bfec298fe.png"},{"id":85644730,"identity":"cf5ffd60-5d3c-46c2-8a23-58d7b4562e1f","added_by":"auto","created_at":"2025-06-30 08:18:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":224020,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProcess (current state) map example\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6523077/v1/32fe464eb18750d2e51a2b7c.png"},{"id":90563771,"identity":"3462a531-7f9e-4e11-a4c3-a993964daed4","added_by":"auto","created_at":"2025-09-04 06:50:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1260026,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6523077/v1/44adfd19-20e0-41db-b0b3-77103d03f0ee.pdf"},{"id":85644735,"identity":"9f900ab8-778d-4700-9f96-b51be9020776","added_by":"auto","created_at":"2025-06-30 08:18:38","extension":"pdf","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":102003,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6523077/v1/91058a6c12242c2033af4321.pdf"}],"financialInterests":"","formattedTitle":"The evolution of interview methodologies to inform the co-design of interventions for an implementation initiative to enhance transitions in care practices in primary care","fulltext":[{"header":"Contributions to the Literature ","content":"\u003cul\u003e\n \u003cli\u003eDemand for timely results, need for various perspectives, differences across settings, and contextual changes over time require innovative approaches for conducting qualitative interviews in implementation science (i.e., rapid qualitative analysis).\u003c/li\u003e\n \u003cli\u003eTo our knowledge, this is the first study combining the ORID framework and CTA to create a hybrid approach for rapid qualitative analysis.\u003c/li\u003e\n \u003cli\u003eThe new hybrid approach\u0026nbsp;allowed immediate incorporation of data into a visual current state map highlighting processes and team member involvement.\u003c/li\u003e\n \u003cli\u003eParticipants agreed the data visualization technique (i.e., current state map) was highly useful to understand their current practices and help them identify potential areas for improvement.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Background","content":"\u003cp\u003eTransitions in care (TiC) from acute care to primary care have been a focus of health care improvement for several years (\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). However, discharge coordination and care integration across settings continues to be a challenge (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), putting people living with complex chronic health conditions at risk for poor TiCs (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). People who experience poor TiCs are at higher risk for poorer outcomes such as mortality, emergency department visits, and unplanned hospital readmissions (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This risk is greater during the period between hospital discharge and primary care follow-up. Research has shown that timely follow-up with primary care after hospital discharge reduces readmission rates and mortality (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Bricard and Or (2019) and Anderson et al. (2022) found early follow-up with a primary care provider within the first week of discharge reduced 28- and 30-day all-cause readmission risks respectively by nearly 50% (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Similarly, Saxena et al. (2022) observed lower rates of unplanned readmissions and mortality at 90-days among patients who had early follow-up post-hospital discharge (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). It is clear that primary care is a pivotal component for successful TiCs. Therefore, efforts are needed to design and implement initiatives to enhance primary care practices to support high-quality TiCs.\u003c/p\u003e \u003cp\u003eAn ongoing study in Alberta, Canada called A DiseAse-Inclusive Pathway for Transitions in Care (ADAPT) focuses on integrating care by collaborating with primary care providers to enhance TiCs. This study is led by Alberta Health Service\u0026rsquo;s (AHS) Primary Health Care Integration Network, which has been leading the development of the Home to Hospital to Home (H2H2H) transitions guideline for several years (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Grounded in implementation science (IS), the ADAPT study is an embedded implementation initiative focused on implementing three of the six core H2H2H guideline elements (admit notification, transition planning, and follow-up to primary care) for Albertans over 18 years of age with heart failure (HF), chronic obstructive pulmonary disease (COPD), liver cirrhosis, and/or chronic kidney disease (CKD). A Patient Transitions Resources team, of 6 patient advisors supports this work and has been involved in its design and implementation of TiC initiatives for the past 5 years. Patients, families, and caregivers are critical partners who lead and support the roll out of the H2H2H guideline. The ADAPT study received ethics approval from the University of Alberta Research Ethics Board (ID:Pro0010674). The purpose of ADAPT is to support and standardize patient transitions by integrating, spreading, and scaling best evidence-based practices across Alberta\u0026rsquo;s primary care clinics during TiC. The early stages of ADAPT involved gaining understanding about the diverse primary care contexts throughout the province of Alberta to inform the design and preparation for co-designing interventions and guiding the implementation process.\u003c/p\u003e \u003cp\u003eQualitative interviewing has been gaining momentum within the field of IS as an effective method to inform the design and implementation of complex interventions, as well as to gain understanding about contexts across diverse settings (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). IS is action orientated and focuses on understanding changes that occurs as a result of implementation strategies and interventions (including the who, what, where, when, and how of those changes) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). This type of work usually occurs over a relatively short period of time compared to traditional qualitative research, which tends to be resource intensive (e.g., time and financial) (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The demand for timely results, need for perspectives from various interest groups, differences across implementation settings, and contextual changes over time require new and innovative approaches for conducting qualitative interviews in the context of IS research (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Researchers have begun working on qualitative methods for IS which aim to balance rigor and efficiency (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). These methods have been called rapid assessment and rapid qualitative analysis (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). However, these methods are still evolving, with few examples in the literature (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). QualRIS (2019) highlight that: \u0026ldquo;There is a pressing need for methodological innovations to meet the challenges for the rigorous use of qualitative methods in implementation science. There is also great opportunity to advance both qualitative methodology and implementation science in pursuing such innovations\u0026rdquo; (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs this is a new and evolving area, it is important for researchers to share insights into what has worked, what hasn\u0026rsquo;t, and how new or hybrid approaches have been developed to tackle inherent challenges when designing and conducting complex implementation initiatives. To address these gaps, the objective of this paper is to provide an overview of the application and evolution of the qualitative interview methods used in the context of the ADAPT study, and highlight key findings and lessons learned from the application of each method.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe research team applied multiple interview and analysis methods to map out current state activities and processes and understand the needs of clinic teams in preparation of the co-design phase of the ADAPT study. The interview approaches started with general data gathering and shifted to more targeted approaches. The question guides and data evolved from a general understanding of TiC in primary care to mapping distinct processes for TiC activities for providers and their teams in preparation to identify and co-design enhanced practices for TiC. The following section describes the evolution of interview approaches from the start to the final iteration of interviewing to efficiently guide clinic teams into co-design and implementation. Interviews were completed between Summer 2021 to Fall 2024. An overview of interviewing phases and main objective of each are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In all phases, individual (one-on-one) interviews were conducted virtually using the Zoom Video Communication platform or in-person, to meet the needs of interviewees.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipant sample and recruitment\u003c/h2\u003e \u003cp\u003eParticipants included primary care providers and multidisciplinary team members (e.g., nurses, medical office assistants, and pharmacists). Participants were recruited to participate in the ADAPT study through an existing network of providers previously involved in the development of the H2H2H guideline, which included both convenience and purposive sampling. Recruitment was monitored to ensure it was representative of all five AHS geographical zones in Alberta (North, Edmonton, Central, Calgary, and South), and a mix of geographic regions (i.e., both rural and urban). Further, information about clinic patient volume and the proportion of patients attending who live with a chronic disease was gathered. Participants were asked to focus on their experiences providing follow-up care to patients discharged from acute care and back into their care with one of the four chronic disease groups included in the ADAPT study over the age of 18.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePhase 1\u003c/h3\u003e\n\u003cp\u003eDuring Phase 1, the ORID (Objective, Reflective, Interpretive, and Decisional) framework (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) was used to conduct interviews to better understand current TiC practices in primary care. ORID is a structured process for facilitating focused conversations to gather feedback on participants\u0026rsquo; experiences; analyze facts, feelings, and implications; and reach intellectual decisions (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This approach generates qualitative data valuable for evaluating and improving projects or processes (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This stage of interviews explored participants\u0026rsquo; clinic team environment and processes for following up with patients with COPD, HF, CKD, and/or liver cirrhosis (i.e., ADAPT study patient criteria) after being discharged from an inpatient hospital stay. Participants were asked to identify and describe effective follow-up processes, ineffective processes, improvements they desired for their current follow-up processes, and what their top priorities for change would be. Participants were also asked to provide feedback on a draft process map outlining key primary care workflow processes when patients are discharged from acute care returning to primary care. After reflecting on the process map, participants were asked to identify components that stood out for them, components they liked or disliked, desired changes, and core steps for managing patients during a post-discharge follow-up visit. The ORID structured interview guide is available upon request. During this phase, due to COVID restrictions, recruitment was put on pause. Interviews conducted in this phase included any primary care teams and providers in the province of Alberta (i.e., not only those enrolled in the study as participants).\u003c/p\u003e \u003cp\u003ePhase 1 interview data were recorded, transcribed, and checked for accuracy. The data were then analyzed by two researchers for themes using NVivo 12 software using the six-phase inductive thematic analysis approach described by Braun and Clarke (2012) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). General surface-level codes were created by each analyst separately and compared afterward for consistency. This was followed by linking broader themes from the data to the initial descriptive codes. Throughout the analysis, inconsistencies and disagreements in coding and themes were examined and discussed until a consensus was reached.\u003c/p\u003e\n\u003ch3\u003ePhase 2\u003c/h3\u003e\n\u003cp\u003eCognitive Task Analysis (CTA) was used in Phase 2 to elicit greater detail of clinic teams\u0026rsquo; current follow-up practices and to identify key patterns and variations in practice, as well as leverageable opportunities to address gaps (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The interview guide was developed to reflect the iterative process of CTA. The guide included multiple sweeps, starting with general questions on available technologies accessed and a walk-through of primary care clinic processes from initial notification of a patient being admitted to acute care to the follow-up in primary care. This was followed by deepening probes at key transition time points (i.e., patient admitted, patient discharge, follow-up by primary care). To understand if those patient examples represented the norm for patient care and what occurs in more diverse situations, a series of counterfactual questions were asked (e.g., what happens if your patient does not show up for their primary care follow-up visit?). Lastly, a final sweep was done to clarify their mental models around roles and responsibilities of clinic members. Mental models can be defined as a dynamic set of beliefs and values involving how people make sense of events and experiences, solve problems, formulate judgements and ultimately make decision and act (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). CTA can be used to elicit mental models of team-based post-discharge and follow up with primary care approaches. The CTA interview guide is available upon request.\u003c/p\u003e \u003cp\u003ePhase 2 interview data were recorded, transcribed, and checked for accuracy. Data analysis was first conducted by two researchers using a structured CTA approach following core CTA macrocognition categories (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), followed by re-analysis using thematic analysis (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). This was done because the first approach made it difficult to depict activities in a pragmatic way. The approaches used in Phases 1 and 2 were both resources intensive; therefore, the research team decided to develop a unique hybrid approach incorporating strengths of both methodologies.\u003c/p\u003e\n\u003ch3\u003ePhase 3\u003c/h3\u003e\n\u003cp\u003eDuring Phase 3, a hybrid interview approach was developed using CTA style questions and ORID concepts/themes. The revised interview guide was developed to more directly reflect the H2H2H Guideline elements of interest (admit notification, transition planning, and follow-up to primary care). Open-ended questions were similar to the questions used in the CTA approach (e.g. Tell me about how you learn about an admit to hospital?). Additional questions connected to best practices in the literature were added to determine if and how certain best practices were being applied. For example, we asked questions concerning the ability to see certain high-risk patients within 14-days of discharge. We also included a summative reflection question at the end of the interview guide that was taken from the original ORID informed interview guide. The purpose of this question was to identify from their overall experience, the work processes that were working well and those that were not working well. Detailed work processes were extracted from interview data to create individualized process map templates outlining clinic and/or provider TiC practices (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). These maps were then used to support codesign sessions where teams collaboratively reviewed the maps to identify implementation gaps, key workflow areas for optimization, and potential practice changes relevant to the H2H2H guideline. The interview flow was improved by changing the structure of the CTA informed guide to mirror and include focused guideline elements. It also provided an opportunity to ask participants to reflect on practices used for all patient groups/conditions. These changes expanded our understanding of core and disease specific practices used by primary care providers and their teams. The final hybrid interview guide is provided in \u003cb\u003eAdditional file 1\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eData analysis for this Phase combined deductive categorization from pre-defined themes derived from Phase 1 results (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) along with a pragmatic approach to visualization by creating process (i.e., current state) maps (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). All interviews were recorded and then the data were directly synthesized into a process map template. Directly imputing qualitative data into an a priori synthesis tool, such as a data matrix (or process map) has been stated to be a useful approach in the advancement of rapid qualitative assessment in IS research (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Multiple researcher team members conducted interviews (CC, DS, SH, KW, KM). Then a team member experienced in qualitative data synthesis conducted the initial data analysis (CC, DS, or SH). This was followed by research team review and gap analysis (i.e., comparing current state to desired state/ best practices) to identify potential areas for co-design. Using team-based approaches to analysis can improve speed while ensuring trustworthy and credible findings (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Results from the analyses were then presented back to study participants to ensure we interpreted the data accurately and to verify nothing was missing in the process map as a preliminary form of member checking to validate findings (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). These maps were then further validated in sessions with interview participants and other clinic members involved in the ADAPT study to identify areas for co-designing implementing interventions.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA total of 55 interviews were conducted. In Phase 1, 17 interviews were conducted with primary care providers and multidisciplinary team members. In Phase 2, two primary care providers were interviewed. In Phase 3, 36 primary care providers and multidisciplinary team members were interviewed. Most participants were interviewed virtually and five were conducted in person. Interviews ranged from 17 mins to 83 mins. Participant characteristics by interview phase are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Workload and patient demographics were similar across clinics and interview phase. Participants that worked full-time in a primary care clinic reported an approximate volume of 100 to 120 patients per week. The percentage of patients with chronic disease ranged from 15\u0026ndash;90%, with the most commonly reported proportion between 60\u0026ndash;70%.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Details of Participants by Interview Phase (N\u0026thinsp;=\u0026thinsp;55)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhase 1 (n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePhase 2 (n\u0026thinsp;=\u0026thinsp;2)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePhase 3 (n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAHS Zone, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalgary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (41.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEdmonton\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArea, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban/ Suburban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (64.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural/ Remote\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (35.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare role, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary care provider\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (76.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePharmacist or assistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoordinator or navigator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinic manager\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical office assistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNotes\u003c/b\u003e: *, location unknown for one participant in Phase 2; primary care provider\u0026thinsp;=\u0026thinsp;physician or nurse practitioner; nurse\u0026thinsp;=\u0026thinsp;registered nurse or licenced practical nurse; pharmacist or assistant\u0026thinsp;=\u0026thinsp;pharmacist or pharmacy assistant; coordinator or navigator\u0026thinsp;=\u0026thinsp;transition coordinator or referral navigator.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePhase 1\u003c/h2\u003e \u003cp\u003eFindings from the initial set of interviews in Phase 1 were grouped into five key themes: People, Processes, System, Outcomes, and Solutions. These key themes are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e in which the theme is seen on the y-axis and the key elements for each theme are visualized along the x-axis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe identified themes were critical in supporting the evolution of the interview guide and approach. The initial series of interviews using the ORID framework supported the perception that clinic variability across the province was present in follow-up processes incorporated by providers and their extended teams. Some providers worked closely with their teams for TiC follow-ups, while others were more physician-centric. There was little evidence suggesting common team-based approaches for TiCs and patient follow-up among clinics or between primary and acute care. Results from this phase also yielded limited detail on outcomes data (e.g. how timely follow-up may decrease readmission to hospital) and what type of actions and processes primary care providers were using upon receiving a discharge summary via the electronic health record.\u003c/p\u003e \u003cp\u003eInterviews conducted using the ORID framework were effective in understanding and validating generalized current practices and challenges as they related to TiC. However, the initial results of these interviews were one dimensional in that participants struggled to describe their own workflow in detail. Asking general questions about follow-up processes rather than focusing on specific clinic examples or targeted questions connected to the H2H2H guideline also led to responses that lacked focus and specificity.\u003c/p\u003e \u003cp\u003eAs the ADAPT study moved to working directly with providers participating in the implementation phase, more detailed data on processes, roles, facilitators, and barriers were required. More specifically, details were needed on what people actually do, versus what people think they should do, say, or reflect on. As a result of the observed limitations of the ORID Framework, a decision was made to incorporate an interviewing technique that better reflected how and why participants were making clinical decisions about TiC practices.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePhase 2\u003c/h3\u003e\n\u003cp\u003eThe CTA approach was chosen to obtain a higher level of detail on TiC practices and team roles. This approach to elicit provider feedback on their clinical activities and mental models around TiC directly led to more focused and nuanced conversations. Discussing the transition journey for a single patient with one of the targeted diagnoses allowed for an in depth understanding of each key primary care activity that occurred during the transition out of acute care. It also helped explore the extent of team-based care at different transition points. However, this approach was found to be highly resource intense and the results lacked generalizability across the study\u0026rsquo;s patient groups.\u003c/p\u003e\n\u003ch3\u003ePhase 3\u003c/h3\u003e\n\u003cp\u003eWe used the results from Phase 1 to help support our approach in Phase 3. Specifically, the themes of \u0026lsquo;People\u0026rsquo; and \u0026lsquo;Process\u0026rsquo; were used to inform the development of the process mapping template and interview guide. Using the hybrid approach allowed us to immediately incorporate interview data around current identified workflow processes into a visual current state map highlighting processes and primary care team member involvement throughout a patient\u0026rsquo;s transition journey. The new hybrid approach led to a balance of providing enough detail in a timely fashion to better prepare the study to move into identifying opportunities for practice change and intervention co-design. Further, there was consistent positive feedback from participants about the data visualization approach. Participants generally agreed that the data visualization technique (i.e., process/current state map) was a highly useful way to understand their current practices and help them identify potential areas for improvement (e.g., \u0026ldquo;Boy, you really know a lot about our system\u0026rdquo;, and \u0026ldquo;Nice, that looks beautiful\u0026rdquo;). This novel method informed from ORID and CTA approaches continues to be applied within the ADAPT study to map and assess current state processes. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides an example of a process map developed from a set of clinic interviews.\u003c/p\u003e "},{"header":"Discussion","content":"\u003cp\u003eDeveloping hybrid approaches for rapid qualitative analysis that balance rigor and efficiency is important to advance IS research and facilitate complex implementation initiatives (\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), such as ADAPT. There are few examples in the literature of other researchers developing hybrid approaches for rapid qualitative analysis and applying them in IS research (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). To our knowledge, we are the first research team to combine the ORID framework and CTA to create a hybrid approach for rapid qualitative analysis. Keniston et al. (2023) developed a hybrid approach over the course of six projects related to the COVID-19 pandemic (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Authors state they used phenomenology and an interpretive framework of pragmatism to develop their rapid qualitative method (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Holdsworth et al. (2020) used a hybrid approach combining rapid qualitative analysis methods with two IS frameworks (Consolidated Framework for Implementation Research [CFIR] (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) and RE-AIM (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Both examples were studies that aimed to evaluate the implementation of interventions/initiatives. We found no other examples of research using hybrid rapid qualitative analysis to inform planning and the preparation of co-design and implementation of interventions in the literature.\u003c/p\u003e \u003cp\u003eUsing pragmatic data visualization methods as part of our hybrid approach also provides a novel contribution to the literature. Salvati et al. (2023) provide one example of the use of process mapping as a data synthesis and visualization tool in IS research (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Similar to these authors, we found using process mapping as a data visualization tool was a successful way to systematically make comparisons and identify possible practice patterns and gaps, without losing the inherent rich nature of complex data. This enabled a systematic and transparent approach to understanding complex decision making in healthcare and supported co-design of potential practice changes for clinics enrolled in ADAPT. Additionally, this approach demonstrated the diverse representation of professional roles/members who took part in the interviews across all phases (i.e., 1, 2 and 3). While there are some similarities, primary care teams in Alberta differ vastly in context, funding models and resourcing. This results in a wide array of staff working in each clinic, where scope and responsibilities differ significantly depending on the geography and service delivery model (e.g., centralized or decentralized primary care network).\u003c/p\u003e \u003cp\u003eCo-design methods have been cited as crucial to the advancement of effective integrated care (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). However, it is rarely described and there have been calls for better reporting of the activities involved, including those activities to inform the planning for co-design (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Through detailing our process to develop a novel hybrid approach to qualitative interviewing and the lessons learned during the evolution of our approach, this work can contribute to the advancement of research in integrated care. The positive feedback we have received from clinic teams about this approach, and specifically the process mapping, provides evidence as to its potential value for co-designing interventions, as well as during the implementation phase. Historically, process mapping supports better understanding of complex systems and adaptation of improvement interventions to their local context. However, there is little research on its use in health care (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). As our team moves from co-design to implementation, we have heard from multiple clinic teams that they would also value having a similar process map to guide and monitor the implementation process to track clinic plans/progress, not just the gap analysis process map generated for co-design. This approach also aligns with how Salvati et al.\u0026rsquo;s (2023) work progressed (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Further, it is highly in-line with participatory design theory (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), which was a guiding principle in the H2H2H Guideline development (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Continuous and iterative co-design with end-users over time evolves to include various products, often used in past phases of implementation, but unique and purposefully different depending on the phase (e.g., planning, implementation, evaluation). Process mapping is a good example of this principle in action. Other researchers undertaking planning for the co-design and implementation of complex interventions can apply our hybrid approach to continue advancing these methods with the aim of improving the rigor and efficiency of rapid qualitative analysis in IS to inform interventions to improve integrated care.\u003c/p\u003e \u003cp\u003eTo support others interested in using a hybrid method to inform the co-design and implementation of complex interventions, we have outlined our key lessons learned and provided a summary of the strengths and limitations of each approach (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). An early lesson from the interview processes was that different stages of an implementation study required different approaches for data gathering. Initially, a broad understanding of provider and team practices for TiC provided direction and helped formulate additional questions to ask leading up to co-design. As the ADAPT study progressed and providers were formally recruited, there was a desire to obtain highly detailed information on mental models and clinic processes. However, employing an approach that was intentionally very narrow and rigid in its approach did not consider multiple patient groups or support the pragmatic analysis of data. The use of CTA may have been more appropriate if there were fewer patient groups and a more targeted set of activities to discuss across clinics. Learning from the strengths and limitations of each methodology in the first two phases of our work led to the evolution of a hybrid approach in the third and final phase.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Strengths and Limitations by Methodology Phase\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApproach\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhase 1: ORID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePhase 2: CTA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePhase 3: Hybrid\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStrengths\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Supported the hypothesis that provincial clinic variability was present in TiC processes for primary care.\u003c/p\u003e \u003cp\u003e\u0026bull; Effective in understanding and validating generalized current practices and challenges.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026bull; Produced very detailed responses on clinical activities and mental models.\u003c/p\u003e \u003cp\u003e\u0026bull; Allowed for more focused and nuanced conversations.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026bull; Provided a detailed understanding of the work of providers and team members.\u003c/p\u003e \u003cp\u003e\u0026bull; Extraction of detailed work processes from transcript data to place in a visual map for co-design was.\u003c/p\u003e \u003cp\u003e\u0026bull; Validated findings and interpretation by member checking at two points during process increases rigor of the method.\u003c/p\u003e \u003cp\u003e\u0026bull; Structured the interview guide to align with study specific elements enhanced interview flow and focus. It also primed participants to identify processes that were working well/not working well by reflecting on the follow-up process as a whole\u003c/p\u003e \u003cp\u003e\u0026bull; The interview guide encouraged providers to identify what mattered to them.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Elicited unidimensional responses (i.e., too general and high level), i.e., participants struggled to describe their own workflow in detail; therefore, did not provide enough detail.\u003c/p\u003e \u003cp\u003e\u0026bull; The interview guide did not contain questions about processes and activities; therefore, responses lacked focus and specificity.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026bull; Data were too situational to be generalizable to entire population of interest.\u003c/p\u003e \u003cp\u003e\u0026bull; Information not high-level enough to be useful during the co-design phase.\u003c/p\u003e \u003cp\u003e\u0026bull; CTA analysis process was time intensive and not pragmatic.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026bull; Data saturation not assessed.\u003c/p\u003e \u003cp\u003e\u0026bull; Potential bias from one researcher conducting initial data analysis.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe revised hybrid approach to information gathering was integral for moving into co-design with primary care teams with very limited availability. Phrasing questions that allowed for the consideration of multiple patient groups and entering interview data directly into a process map was found to be an effective strategy. In addition, presenting the information back to teams in the form of a process map supported them in identifying opportunities and designing new practices that emphasize a team approach to patient care. Conducting multiple phases of member checking as a form of validation increased the rigor of this process. The hybrid approach and visualization led to a very collaborative and transparent process to identifying opportunities for practice change. However, this approach is not without its own limitations. First, data saturation was not assessed, making it possible that certain processes may have been missed in the interviews. Second, one researcher conducted the initial data analysis. We attempted to mitigate both these limitations by validating findings through member checking at two points, as well as by reviewing results as a research team and conducting a gap analysis collaboratively. This has been stated to be an effective approach to improve speed while maintaining rigor (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis project was undertaken during the COVID pandemic and has continued during the pandemic recovery period, which caused challenges in recruitment and planning for co-design. Initially recruitment was put on pause, due to the stress on the healthcare system. This provided an opportunity to conduct an environmental scan, including interviews assessing any primary care clinics in the province (i.e., not only those not enrolled in the study) to assess a broader base of practices. While this helped to bridge the existing evidence gap around team-based approaches to follow-up post-discharge, the interview data lacked focus and specificity. When the team was able to continue with recruitment for the study, the informational needs had shifted, given what we had already learnt. When conducting IS research the level of detail and robustness of interview data must be balanced with the needs and capacities of participants and the ever-changing landscape of health care systems (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). It is important for researchers to know when and how to pivot their approach to meet the needs of the various interest groups and end-users we work with. Having flexibility in methods is integral to engaging with potential participants and supporting them to see a direction towards new or enhanced practices in implementation initiatives.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe newly developed methodology was created to be comprehensive but flexible enough to accommodate the pragmatic nature and short timelines of real-world co-design and implementation projects. This methodology can be a powerful tool to gain the information necessary to co-develop interventions to enhance care integration.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eTransitions in Care (TiCs), A DiseAse-Inclusive Pathway for Transitions in Care (ADAPT), Alberta Health Service (AHS), Home to Hospital to Home (H2H2H), Implementation Science (IS), heart failure (HF), chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), Objective, Reflective, Interpretive, and Decisional (ORID) framework, Cognitive Tast Analysis (CTA).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was designed and conducted according to the principles outlined in the Canadian Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans, which is also in accordance with the Declarations of Helsinki. This study\u0026nbsp;received approval from\u0026nbsp;the University of Alberta Health Research Ethics Board (ID: Pro0010674).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare they have no competing interests to this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is supported by an Alberta Innovates Partnership for Research and Innovation in the Health System Grant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors’ contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSND and JS conceived the research idea. Research study was designed by CC and SND.\u0026nbsp;CC, SH, and DS conducted interviews and initial data analysis. SF, CC, SH, JC, and DS were involved in final data analysis, interpretation, and visualization. SF, CC, SH, JC, and DS were involved in current state map validation sessions.\u0026nbsp;The manuscript was drafted by SF, additional content and draft reviews were provided by CC, SH, JC, DS, and SND. All authors reviewed and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to acknowledge Dr. Judy Seidel (Co-PI), Elvira Nurmambetova, Kelly Malach, Kristen Ward and the H2H2H guideline and AHS Primary Health Care teams for their contributions in the overall ADAPT project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBerre ML, Maimon G, Sourial N, Gu\u0026eacute;riton M, Vedel I. Impact of transitional care services for chronically ill older patients: A systematic evidence review. J Am Geriatr Soc. 2017;65(7):1597\u0026ndash;608.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColeman EA, Boult C. Improving the quality of transitional care for persons with complex care needs. J Am Geriatr Soc. 2003;51(4):556\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaylor MD, Sochalski JA. Scaling up: Bringing the transitional care model into the mainstream. Issue Brief. 2010;103:1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeeks LE, Barber B, MacDougall ES, Macdonald M, Martin-Misener R, Warner G. An exploration of Canadian transitional care programs for older adults. Healthc Manage Forum. 2021;34(3):163\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColeman EA. Falling through the cracks: Challenges and opportunities for improving transitional care for persons with continuous complex care needs. J Am Geriatr Soc. 2003;51(4):549\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeeks LE, Macdonald M, Martin-Misener R, Helwig M, Bishop A, Iduye DF, et al. The impact of transitional care programs on health services utilization in community-dwelling older adults: a systematic review. JBI Database Syst Reviews Implement Rep. 2018;16(2):345\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBricard D, Or Z. Impact of early primary care follow-up after discharge on hospital readmissions. Eur J Health Econ. 2019;20(4):611\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson A, Mills CW, Willits J, Lisk C, Maksut JL, Khau MT, et al. Follow-up post-discharge and readmission disparities among medicare fee-for-service beneficiaries, 2018. J Gen Intern Med. 2022;37(12):3020\u0026ndash;2028.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaxena FE, Bierman AS, Glazier RH, Wang X, Guan J, Lee DS, et al. Association of Early Physician Follow-up With Readmission Among Patients Hospitalized for Acute Myocardial Infarction, Congestive Heart Failure, or Chronic Obstructive Pulmonary Disease. JAMA Netw Open. 2022;5(7):e2222056.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlberta Health S. Home to Hospital to Home Transitions. Alberta Health Services. 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQualRIS. Qualitative methods in implementation science. National Cancer Institute: Division of Cancer Control \u0026amp; Population Sciences; 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamilton AB, Finley EP. Qualitative methods in implementation research: An introduction. Psychiatry Res. 2019;280:112516.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNevedal AL, Reardon CM, Opra Widerquist MA, Jackson GL, Cutrona SL, White BS, et al. Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR). Implement Sci. 2021;16(1):67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoutts J. Evaluation Methods. 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBraun V, Clarke V. Thematic analysis. In: Cooper H, Long MCP, Panter DL, Rindskopf AT, Sher D KJ, editors. APA handbook of research methods in psychology, Vol 2 Research designs: Quantitative, qualitative, neuropsychological, and biological. American Psychological Association; 2012. pp. 57\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePotworowski G, Green LA. Cognitive task analysis: methods to improve patient-centered medical home models by understanding and leveraging its knowledge work. Agency for Healthcare Research and Quality; 2013; 2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWagner KK, Austin J, Toon L, Barber T, Green LA. Differences in Team Mental Models Associated With Medical Home Transformation Success. Annals Family Med. 2019;17(Suppl 1):S50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntonacci G, Lennox L, Barlow J, Evans L, Reed J. Process mapping in healthcare: a systematic review. BMC Health Serv Res. 2021;21(1):342.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBingham AJ, Witkowsky P, Vanover C, Mihas P, Salda\u0026ntilde;a J. Analyzing and interpreting qualitative data: After the interview. Deductive and Inductive Approaches to Qualitative Data Analysis; Vanover C, Mihas P, Salda\u0026ntilde;a J, Eds. 2022:133\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoldsworth LM, Safaeinili N, Winget M, Lorenz KA, Lough M, Asch S, et al. Adapting rapid assessment procedures for implementation research using a team-based approach to analysis: a case example of patient quality and safety interventions in the ICU. Implement Sci. 2020;15(1):12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcNall M, Foster-Fishman P. Methods of Rapid Evaluation, Assessment, and Appraisal. Am J Evaluation - AM J EVAL. 2007;28:151\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBirt L, Scott S, Cavers D, Campbell C, Walter F. Member Checking: A Tool to Enhance Trustworthiness or Merely a Nod to Validation? Qual Health Res. 2016;26(13):1802\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKeniston A, McBeth L, Astik G, Auerbach A, Busch J, Kangelaris KN, et al. Practical Applications of Rapid Qualitative Analysis for Operations, Quality Improvement, and Research in Dynamically Changing Hospital Environments. Joint Comm J Qual Patient Saf. 2023;49(2):98\u0026ndash;104.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDamschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4(1):50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89(9):1322\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalvati ZM, Rahm AK, Williams MS, Ladd I, Schlieder V, Atondo J, et al. A picture is worth a thousand words: advancing the use of visualization tools in implementation science through process mapping and matrix heat mapping. Implement Sci Commun. 2023;4(1):43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWard ME, De Br\u0026uacute;n A, Beirne D, Conway C, Cunningham U, English A et al. Using Co-Design to Develop a Collective Leadership Intervention for Healthcare Teams to Improve Safety Culture. Int J Environ Res Public Health [Internet] 2018; 15(6).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSlattery P, Saeri AK, Bragge P. Research co-design in health: a rapid overview of reviews. Health Res Policy Syst. 2020;18(1):17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBj\u0026ouml;gvinsson E, Ehn P, Hillgren P-A. Design Things and Design Thinking: Contemporary Participatory Design Challenges. Des Issues. 2012;28(3):101\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalker RL, Hastings S, Cook C, Cunningham CT, Cook L, Cullum J, et al. Integrating care from home to hospital to home: using participatory design to develop a provincial transitions in care guideline. Int J Integr Care. 2022;22(2):1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"qualitative methods, rapid qualitative assessment, care transitions, co-design, hybrid designs, implementation science","lastPublishedDoi":"10.21203/rs.3.rs-6523077/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6523077/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003ePeople living with chronic health conditions are at risk for poor transitions in care (TiC) because of poor discharge coordination and care integration. An ongoing study in Alberta, Canada called A DiseAse-Inclusive Pathway for Transitions in Care (ADAPT) focuses on co-designing interventions to enhance TiC practices in primary care for high-risk people with chronic diseases. The aim of this paper is to provide an overview of the application and evolution of the qualitative interview methods used in the context of the ADAPT study, and highlight key findings and lessons learned from using each method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Initial steps for co-design included current state assessments of TiC workflow processes for primary care. To create comprehensive maps of existing processes, qualitative interviewing techniques were applied. The first methodological approaches used were the ORID (Objective, Reflective, Interpretive, and Decisional) framework (Phase 1) and cognitive task analysis (CTA) (Phase 2). Challenges were encountered using both approaches (i.e., Phase 1 lacked detail and Phase 2 was resource intensive). Therefore, a novel hybrid approach was developed (Phase 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eResults from Phase 1 were grouped into five key themes: People, Processes, System, Outcomes, and Solutions. Phase 2 resulted in an in-depth understanding of each key primary care activity during the transition out of acute care. The themes identified in Phase 1 were critical in supporting the evolution of the interview guide and approach in Phase 3. The new hybrid approach allowed immediate incorporation of interview data into a visual current state map highlighting processes and team member involvement throughout a patient’s TiC journey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThe new hybrid approach led to a balance of providing enough detail in a timely fashion to better prepare the study to move into identifying opportunities for practice change and intervention co-design. Developing hybrid approaches for rapid qualitative analysis that balance rigor and efficiency is important to advance research to facilitate complex implementation initiatives.\u003c/p\u003e","manuscriptTitle":"The evolution of interview methodologies to inform the co-design of interventions for an implementation initiative to enhance transitions in care practices in primary care","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-30 08:10:33","doi":"10.21203/rs.3.rs-6523077/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"40e119ea-10bf-4c20-bd3b-b322fd56c3c3","owner":[],"postedDate":"June 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-04T06:42:04+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-30 08:10:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6523077","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6523077","identity":"rs-6523077","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}