Integrating PRISM with User-centered Design (PRISM+UCD): Designing clinical decision support for safe opioid prescribing 

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Trinkley, Jason A. Hoppe, Nicole Wagner, Heather Tolle, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7236339/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 : Balancing safe opioid prescribing with effective pain management is essential to addressing the opioid crisis. Increasing clinician adoption of evidence-based safety practices is a public health priority. This project presents a practical, adaptable approach to developing electronic health record (EHR)-embedded clinical decision support (CDS) strategies that promote uptake of opioid safety measures recommended by the Centers for Disease Control and Prevention (CDC). The goal was to design implementation strategies that enhance guideline-concordant opioid prescribing, including a suite of EHR-integrated CDS tools. Methods : Guided by the Practical, Robust Implementation and Sustainability Model (PRISM) and informed by implementation science and user-centered design (UCD), we used an iterative, multi-level engagement process. PRISM served as the theoretical framework for integrating collaborator input and user testing throughout the development cycle. Activities included discovery, design, prototyping, and usability testing. Collaborators included executive decision-makers, informatics leaders, frontline clinicians across diverse settings, representatives from the CDC and National Institute on Drug Abuse, and patients. These methods informed the selection of opioid safety measures, design themes, and workflow considerations, resulting in implementation-ready CDS prototypes. Results : The discovery phase identified a naloxone prescribing alert as a strong candidate for redesign, aligning with CDC guidelines and relevant across all four PRISM domains. The final redesign received mean ratings of 4.0 and 4.2 out of 5 on the Acceptability of Intervention Measure (AIM) from inpatient and outpatient clinicians, respectively. PRISM User-Centered Design Opioid Prescribing Clinical Decision Support Implementation Science Electronic Health Record Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Despite substantial public and governmental attention and investment, the opioid crisis in the United States continues to pose a serious threat to public health. 1 In 2023, 8.6 million people across the U.S. misused opioids. 2 In 2022, there were 81,806 opioid-related deaths in the U.S. 1 The overall rate of unintentional overdoses was 4.3% for prescription opioids and 28.7% for any opioids. 3 These figures underscore the urgent need for strategies that enhance safety at the point of care, specifically when clinicians prescribe opioids, while minimizing disruption to clinical workflows and ensuring applicability across diverse healthcare settings. Opioid therapy is prescribed in a wide range of clinical contexts by various types of clinicians, from primary care to specialty and emergency care. This paper outlines the process and results of co-designing clinical decision support (CDS) tools to aid clinicians in safe opioid prescribing, drawing on implementation science and user-centered design (UCD) frameworks. Opioid Prescribing Guidelines The 2022 Centers for Disease Control and Prevention (CDC) Clinical Practice Guideline for Prescribing Opioids for Pain was a national effort to address the opioid crisis by improving safety in pain management. 4 While the guidelines are not intended to replace clinical judgment, they serve as a resource and provide 12 evidence-supported care recommendations to assist clinicians to safely address pain when utilizing opioid analgesic therapy. The guidelines can be categorized into four areas: 1) decision to initiate opioids for pain; 2) selection of opioid analgesic and dosage; 3) duration of initial opioid prescription and follow up; and 4) assessment of risk and potential harms. The guidelines focus on care for patients over 18 years of age, with acute, subacute, or chronic pain and is not intended to include pain management related to sickle cell disease, cancer-related pain, palliative care, or end-of-life care. 5 The CDC guidelines are intended to support clinical judgment and accommodate individual patient needs, rather than impose a one-size-fits-all approach. For example, Recommendation #8 advises clinicians to mitigate risk when prescribing high-risk opioids by offering naloxone—an opioid antagonist that rapidly reverses overdose. Specifically, the guideline states: “Clinicians should offer naloxone when prescribing opioids, particularly to patients at increased risk for overdose, including patients with a history of overdose, patients with a history of substance use disorder, patients taking benzodiazepines with opioids.” 4 However, the guidelines caution against mandating naloxone prescriptions due to potential cost burdens for patients. 4 Because the guidelines emphasize clinical discretion rather than strict requirements, tracking adherence can be challenging. Therefore, thoughtful design, implementation, and evaluation strategies are needed to promote provider uptake and assess patient benefit. Opioid Prescribing Guidelines Implementation Strategies Implementation strategies refer to methods used to increase adoption, implementation, sustainability and scaling of interventions. 6 , 7 CDS is one of five implementation strategies demonstrating strong evidence of effectiveness and high rates of improvement. 9 – 12 CDS provides an opportunity to support clinicians within their existing workflow to inform care decisions to align with guideline recommendations and has demonstrated promise with opioid safety interventions. 8 Importantly, CDS is often one of several discrete implementation strategies used as part of a multi-component package rather than as a standalone strategy. Other components often implemented with CDS include education, technical assistance, and/or evaluative strategies. 8 Our CDS-based implementation strategy included redesigning workflow, developing and implementing tools for quality monitoring, and reminding clinicians at the point of decision-making. The operationalization of clinician reminders is a type of education, particularly when the reminders are related to clinical practice guidelines. 13 Implementation strategies can be honed by incorporating various perspectives rooted in different levels within the setting where guideline concordance is sought. User-centered design is a method described by Norman and Draper in which there is a focus on the user experience instead of the technology being developed. 14 This crucial and basic focus in the design and development of technologies that support a user has been applied in many ways. 15 – 17 For example, users might be involved in usability testing to identify pain points during the development of an user interface; users might also be granted greater decision making authority in participatory design by identifying what should be developed and how. 17 , 18 The application of UCD along this spectrum is commonly reported in the literature. The flexibility of UCD makes it a particularly useful and nimble method, especially when aligned with theoretical frameworks like Practical, Robust Implementation and Sustainability Model (PRISM) and used in the context of implementation science. 19 , 20 The expected benefits of an implementation science framework, integrated with an UCD approach, include both technology usability as well as CDS alignment with the intervention and strategies on a multi-level scale. 21 Consideration of the setting of where the strategies will be implemented is critical, including workflows and the multiple levels of people directly or indirectly influencing the success of the project. 22 , 23 Purposeful alignment between strategies and the setting is important for building an understanding of the mechanisms of effectiveness of implementation strategies. 24 , 25 The purpose of this research was to develop – and then implement and test – electronic health records (EHR)-based CDS tools for prioritized opioid prescribing guidelines. This work demonstrates a scalable, evidence-informed, process for designing CDS tools that are both usable and contextually aligned, increasing the likelihood of successful implementation and measurable impact. Methods Overview of Setting and Context The setting was a large, university-affiliated health care system in the Rocky Mountain region with 12 hospitals, > 400 clinics, and 1.3 million outpatient and > 500,000 emergency department visits per year. The geographically diverse sites share the same EHR system (Epic: Verona, WI) with a requirement to e-prescribe all medications. 26 The counties served cover approximately 85% of the state’s population. The context of the project focused on the NIH HEAL Initiative®. Specifically, the initiative was designed to support research into adoption and implementation of the 2022 Clinical Practice Guideline for Prescribing Opioids for Pain guidelines. Helping clinicians apply these guidelines at the right time, for the right patient could be supported by implementation science, i.e., PRISM + UCD. For this project, we integrated PRISM with UCD approaches to design implementation strategies for opioid prescribing guidelines, called the PRISM + UCD approach. Informed by UCD principles and methods and the PRISM implementation science framework, we engaged patients (patient advisory board discussion), clinicians (focus groups), and hospital leadership and administration (1:1 interviews) around design of CDS tools and other implementation strategies to support opioid prescribing guideline-based care. The PRISM + UCD approach Our method comprised four UCD phases: discovery, design, prototype, and test. The integration of PRISM ensures that the resulting strategies and CDS for safely prescribing opioids are effectively integrated and sustained within specific settings and contexts. PRISM is an adaptation to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, a well-known implementation planning and evaluation framework. 27 PRISM includes four domains of contextual determinants that span adoption, implementation, and sustainment of an intervention. The four domains are 1) inner setting (internal environment of the organization, i.e., culture): this domain considers patients, clinicians, and organizational leader views and experiences 28 ; 2) characteristics of the individuals involved: the attributes and readiness of those who are responsible for implementing the intervention, i.e., policy makers, payers, external collaborators; 3) intervention characteristics: the resources, processes, and systems within the setting that supports continued implementation and maintenance of the intervention 29 ; and 4) outer setting: this includes factors such as policies, regulations, and broader societal influences that could impact the intervention. PRISM + UCD (Fig. 1 ) can help researchers adapt their interventions to fit local contexts and engage collaborators across phases of the project. 29 The domains are interrelated, and data is produced for insights across the categorical domains during phase 1 of the UCD process, i.e., qualitative discovery. The support this method provides within the domains as described above. The first domain supports learning about the “perspectives on the intervention”, including both the recipient perspective as well as an organizational perspective (including leadership, managers, and frontline clinicians). The second domain provides insights on the characteristics of recipients of the intervention (both patient and organizational). The third domain is implementation and sustainability infrastructure, which includes factors such as the availability of a dedicated team that monitors fidelity to the intervention, trains clinicians on the intervention, shares best practices, and builds out an infrastructure for the sustainability of the intervention. The fourth domain is the external environment, which includes the regulatory environment of the broader health care system, the resources available to fund it, and potential alignment with health system goals. UCD Phase 1: Discovery Patient Advisory Panel: Patient engagement An established research advisory panel was consulted to assess patient priorities and obtain a patient perspective on opioid prescribing and safety. The panel first received an overview of the project, then provided feedback on their priorities and preferences regarding opioid use, best practices, and standardized guidelines in their medical care. We asked the following questions to assess the patient perspective: 1) What are your initial reflections on this project? 2) What aspects of this project might be of value or benefit patients who need opioids for pain management? 3) What aspects of this project might be a concern to patients? 4) What are the best ways to evaluate the outcomes of this project? Health System Leadership interviews One-on-one informal interviews with health system leadership. Interviews ranged between 30 to 60 minutes and were conducted via video conferencing software 30 and field notes were utilized. Recruitment was done through email and professional contacts. Clinicians focus groups We conducted five focus groups of inpatient and outpatient clinicians (MD/DO, PA, NP) licensed to prescribe opioid analgesics in the health system. Recruitment was conducted via email contact, circulated via clinical admin/management announcement emails, and using existing EHR reports of providers recently seeing a similar CDS alert. These individuals were invited to provide input on their individual and/or clinic workflows and practices, their informational needs and preferences, as well as review the design and implementation of CDS to be integrated into the EHR system (Epic; Verona, WI). Focus group participants completed a screening questionnaire and those available during a focus group timeslot with enough other participants (6–9 participants) from the same work setting (inpatient, outpatient, or emergency department) were invited to participate. Focus groups were conducted virtually to maximize representation and assure input from across the state. Qualitative de-identified data on prescribing practices and workflow were collected. Using a semi-structured focus group guide, participants described their current opioid prescribing workflows, prevalence of patients receiving opioid analgesics in their practice, decision processes around prescribing, and individual prescriber suggestions and needs for CDS design and development. Participants also provided feedback on ideal CDS designs in a drawing exercise. The focus groups lasted 90 minutes and were conducted via video conferencing software. 30 All focus groups were audio recorded, transcribed verbatim with identifying information removed, and field notes taken. Thematic saturation was reached after five focus groups with clinicians. Discovery Synthesis Formal thematic/contextual analysis used a matrix-style coding approach to structure analysis on key factors important to the CDS design. The focus group findings informed the design of the CDS. Synthesis: Affinity Grouping Method To synthesize insights from engagement and data collection activities, the qualitative team [BM, BK, JH, KT] analyzed internal notes and focus group transcripts. Otter.ai 31 was used to transcribe audio recordings of the focus groups. The method of analysis consisted of an affinity grouping exercise conducted in Mural 32 , an online collaboration software app. Three team members who facilitated the focus groups and the project PI conducted content analysis using a matrix-style coding approach to structure the analysis on key factors important to the CDS design. Team members reviewed a set amount of the transcripts that were assigned by the qualitative lead. Summary phrases were typed on Mural’s “sticky notes” and mapped together based on similarities in relation to five categories and the collaborator type, e.g., clinician, patient, and leadership. The five categories were as follows: 1) What guidelines are best suited for CDS? 2) What are the desired design features for the relevant CDS? 3) What are the features or elements in CDS users do not want? 4) What are the opportunities for implementation and clinical workflow? 5) What are the potential threats or barriers to the implementation of CDS? These questions facilitated the synthesis of the summaries for guidelines and desired design features and implementation strategies. UCD Phase 2–4: Design, Prototyping, and Testing For UCD phase – 2, which focused on the naloxone co-prescription guideline recommendation, focus group participants referred to existing CDS and made suggestions for improvement. Then in the UCD prototyping phase – 3 these suggestions were used by the study team (KT) to create low fidelity prototypes of the CDS user-interface using Microsoft PowerPoint in which the content varied slightly for primary care versus the emergency department and inpatient settings. These prototypes were then iteratively updated with input from the study team (JH, HT, BK, BM, LS) and the health system’s clinical decision support governance. During the UCD test phase – 4, these prototypes were utilized for focused feedback circulated via email to the 67 clinicians who responded to our focus group solicitation. Feedback was collected using Qualtrics in which participants provided input on specific design features such as response options (e.g., include a ‘comment’ or ‘other’ option), duration of suppressing a CDS based on clinician response, and content displayed within the user interface. 33 Participants were also asked to complete the 4-item Acceptability of Intervention Measure (AIM), a 4-item validated measure using a five-point Likert scale from completely disagree to completely agree. 34 Higher scores on the scale indicate more agreement with the acceptability of the alert. Open-ended responses to the survey were used to create final prototypes built in the EHR. The outcome of these methods is a minimum viable product (MVP) which was shared with analysts to build in the EHR. The study team tested the CDS in test environments of the EHR. 34 Implementation Research Logic Model and Implementation Strategies Based on the outcome of the PRISM + UCD process, we developed an Implementation Research Logic Model (IRLM) tool to guide our work. An IRLM provides collaborators and implementors with a structured opportunity to discuss and align on the core components of the logic model: determinants, implementation strategies (to address facilitators and barriers), the intervention, the mechanism of action, and the outcomes. 35 The IRLM can be applied at multiple stages to identify implementation strategies needed both within and alongside the CDS tool to maximize program impact and sustainability. 35 We then leveraged the Expert Recommendations for Implementing Change (ERIC) taxonomy of implementation strategies. 36 In collaboration with our multilevel team, we discussed which strategies were feasible and appropriate within the given context. Results Affinity Grouping Participants Four patients were engaged through a pre-existing patient and family research advisory panel. 37 Eleven hospital leadership and administration interviews were conducted. Twenty-five clinicians (MD/DO, PA, NP) participated in five focus groups (Table 1 ). These three distinct data collection efforts provided the data for the Affinity Grouping methodology. Table 1 Demographics of focus group participants and qualifying clinicians responding to recruitment Participated in FG N (%) Completed Screening N(%) Gender Man 13(52.0) 23(34.3) Woman 12(48.0 44(65.7) Self-identify 0(0.0) 0(0.0) Age 20–29 0(0.0) 4(6.0) 30–39 13(52.0) 27(40.3) 40–49 7(28.0) 22(32.8) 50–59 4(16.0) 13(19.4) 60 and over 1(4.0) 1(1.5) Clinician Type MD/DO 23(92.0) 49(73.1) NP/PA 2(8.0) 18(26.9) Work Setting Emergency Department 10(40.0) 20(29.9) Inpatient 7(28.0) 18(26.9) Other 3(12.0) 5(7.5) Outpatient 5(20.0) 24(35.8) Affinity Grouping Insights The Mural board Affinity Grouping synthesis (Fig. 2 ) produced three major areas of insights. First, given the potential impact on established workflows, we found that it is easy to quickly lose users of CDS due to poor design. Therefore, streamlined workflows with accurate logic and an intuitive interface are critical. Regarding opioid prescribing guidelines and desired design features for CDS, we found that existing guidelines most suited for redesigned CDS included co-prescribing of naloxone with opioid analgesics, which is aligned with Recommendation #8. Other guidelines suited for redesign included evaluation of opioid prescribing risk and improved processes for referrals for substance abuse treatment, specifically opioid use disorder (OUD). The PRISM + UCD process revealed several key insights: 1) clinicians need timely access to information about patients’ recent prescription opioid use; 2) nurses should also have easy access to this data; and 3) CDS tools should minimize user effort by requiring as few clicks as possible and feature accurate firing logic to avoid disrupting clinical workflows. Second, related to implementation strategies, there are several opportunities for CDS implementation and integration into clinician workflows that may support adoption by clinicians. There is an education gap for clinicians on the updated CDC guidelines. Many system clinicians reported not often interacting with the new CDC guidelines, decreasing familiarity with the new guidelines within our system. Clinicians told us that it would be helpful if individual experts were identified as domain experts for support related to opioid use disorder content, in general, and the current guidelines, specifically. Domain experts might also be local champions in the clinics. According to Leadership, clinicians want to avoid inefficient workflows. Leadership advocates for standardized culture and strategic priority in communications that demonstrate leadership buy-in, while making Patient Reported Outcomes (PRO) useful and data-driven. Patients advocate for relationships with clinicians and value 1:1 conversation, especially when a referral is involved. Third, data from the health system leadership interviews revealed that leadership supported the project as a strategic priority for the system. They provided guidance on the approval process needed for the build and development of CDS tools within the system. Leadership expressed concern at the amount of work associated with collecting data for the sake of collecting data, stressing the need for the data to be useful to clinicians, measuring impact on workflows and outcomes, and be integrated into the workflow. Leadership also suggested that our team take a wider view of hospital activities across the system to avoid duplication of efforts by leveraging existing organizational structures and resources. UCD Phase 2–4 Participants Fifteen of 67 clinicians responded to our Qualtrics survey in which participants provided input on specific design features. UCD Phase 2–4 Results CDS tools were developed utilizing insights gained from all four UCD phases. During the discovery phase – 1, utilizing resources in the hospital system, and subject matter expertise from the team, an existing alert encouraging prescribing naloxone with a high-risk opioid analgesic in the emergency department was identified and adapted to meet the contextual needs across the entire hospital system. This alert is related to Recommendation #8, as discussed in the Background. The MVP low fidelity prototype selected to be built for testing in the EHR test environment is available in Fig. 3 . A total of eight inpatient and emergency department clinicians rated the naloxone alert with an average score of 4 out of 5 on the AIM. Seven outpatient clinicians rated the alert as a 4.2 on the AIM, showing high acceptability of the alert design. Implementation Research Logic Model Based on outputs from the Mural board synthesis, we (BK, JH, HT, KT, BM) developed an IRLM (Fig. 3 ). The logic model depicts PRISM-aligned contextual factors, corresponding implementation strategies – including both CDS tool features and additional strategies described in the ERIC framework – expected implementation strategy mechanisms, and RE-AIM outcomes for implementation of the opioid prescribing guidelines in a range of clinical settings. As shown in Fig. 4 , we identified two main categories of implementation strategies: CDS tools and additional strategies. The additional strategies included those already being employed during the discovery and design stages of the project as well as strategies that were recommended for use during the forthcoming “test” stage of the project. The use of the PRISM + UCD approach itself represents an implementation strategy reflecting ERIC’s “engagement of multilevel partners,” “internal consensus discussions,” and “adapting to context” domains. There were a priori plans to include quality monitoring and mandating change strategies. Additional recommended implementation strategies were selected based on two considerations: 1) conceptual alignment with the PRISM contextual factors identified during discovery and design phases, and 2) feasibility assessments given project resources and study team experience working with the health system. For example, recommendations for champion support strategies reflected clinician preference for having a “go-to” person for sharing best practices for use of the CDS tools in their clinical context. Recommended strategies also included clinician education (on both opioid prescribing guidelines and use of the CDS tools) and clinical leadership support and communication – both explicitly requested by participants in the clinician focus groups. Discussion This work highlights a novel integrated approach to designing implementation strategies by combining PRISM + UCD. This integration enhances the relevance and usability of the strategies and fills a gap in the literature by offering a practical model for designing implementation strategies that are both theory-informed and user-responsive. There are relatively few well-described methods for designing implementation strategies. Implementation mapping, implementation research logic models, and group model building are among the established methods. 38 It is common for implementation strategy design efforts to start with identification of adoption and implementation determinants, such as those described by implementation science frameworks like the PRISM. Identification of determinants is then followed by selection and/or tailoring of discrete implementation strategy components (such as described by the ERIC project) that are thought to address those determinants. 38 For implementation strategies and interventions that are meant to interface with technology, such as CDS tools delivered via the EHR, UCD techniques can be a useful complement to the framework-driven approach. Using PRISM as a guide in the iterative UCD process presented an opportunity to maximize the value of CDS tools. Using a process that includes multiple levels of input from different organizational perspectives to inform the CDS design and development facilitates maximize system-level support, clinician use, positive patient-level health impact, and minimize unintended consequences (e.g. tapering guidelines association with increased heroin use). 39 A comparison of our work that utilizes PRISM + UCD to inform the IRLM reveals a more representative approach to the standard manner by which CDS is traditionally developed. Traditional approaches tend to be top down, not taking into consideration the users of the CDS and how they respond to prompts, nudges, and alerts as clinicians, but also users of an electronic interface that is tedious with clicks. 40 , 41 Additionally, traditional approaches do not incorporate iterative approaches into the design process and may not take into consideration the context in which the CDS is being implemented. 42 Other previous approaches have incorporated UCD that included user involvement and iterative design, which provided rich feedback and an attempt to incorporate this feedback into subsequent iterations. 43 – 46 However, without the presence of the PRISM framework, the assurance of all relative perspectives cannot be guaranteed. Additionally, at a high level, the projects all took a multidisciplinary approach by generally involving diverse collaborators, although the systematic organization of the collaborates was not as refined as what PRISM supports. Our approach combines PRISM + UCD and capitalizes on contextual factor integration at multiple organizational levels. A core strength is that this approach remains nimble and adaptive, which makes space for the UCD element by focusing on and magnifying the expertise and skillsets of vested collaborators who can speak to CDS, and implementation needs. An example of the pragmatic approach we took is the relatively short period of time we were able to successfully design and build the naloxone alert CDS tool in seven months, including three months of PRISM + UCD work, and four months of analyst build time in the local EHR. Simultaneously, we also designed implementation strategies for the CDS in the local health system, which is included in the IRLM. The next steps of this project will be the implementation of the CDS in the local healthcare system. Outcomes of interest are captured in the IRLM, and include Reach, Adoption, Implementation, and Maintenance. All these outcomes will be a good measure of the naloxone CDS strategy built with a PRISM + UCD methodological approach that attempts to take into consideration the full reality of the setting and context in which the strategy is embedded. Limitations One limitation is that there is bias introduced into the study by working with voluntary, self-selected focus groups. Another limitation is that there could be a disconnect between what clinicians are reported valuing in theory and in practice. 47 Conclusions We developed and applied an integrated, rapid-cycle approach to designing CDS tools for safe opioid prescribing across inpatient, emergency, and outpatient settings in a large regional health system. Guided by the PRISM framework and UCD, we identified CDC guideline-aligned safety measures, redesigned a naloxone alert, and produced an implementation-ready CDS tool that received strong usability ratings from clinicians. This work illustrates how combining implementation science with UCD can accelerate the development of context-sensitive, evidence-based CDS strategies. The resulting alert was not only technically feasible but also endorsed by clinical leadership and supported by targeted education and communication strategies to encourage adoption. This integrated methodology offers a scalable model for developing CDS tools that are both clinically relevant and operationally sustainable. Future work will focus on evaluating the real-world impact of the naloxone alert on prescribing behavior and patient outcomes, as well as adapting this approach to other guideline-based interventions. Continued collaborator engagement and iterative refinement will be essential to ensuring long-term success and broader dissemination. Abbreviations EHR – Electronic Health Record CDS – Clinical Decision Support CDC – Center for Disease Control and Prevention PRISM - Practical Robust Implementation and Sustainability Model UCD – User Centered Design AIM – Acceptability of Intervention Measure RE-AIM - Reach, Effectiveness, Adoption, Implementation, and Maintenance MVP – Minimum Viable Product IRLM – Implementation Research Logic Model ERIC - Expert Recommendations for Implementing Change OUD – Opioid Use Disorder PRO – Patient Reported Outcomes Declarations Ethics approval: Ethical approval was obtained by the university’s Institutional Review Board (IRB) (22-2165) and this study adheres to the tenets of the Declaration of Helsinki. Consent to participate: Informed consent was obtained from all individuals to participate in the study. Consent for publication: Not applicable. Competing interests: All authors declare no competing interests. Clinical Trial Number: Not applicable. Funding: Research reported in this publication was supported by the National Institute of Drug Abuse of the National Institutes of Health under Award Number R33DA057610. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Availability of data and materials: Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study. Author contributions: JH, HT, BK, KT, LS, and SH developed, planned, and designed the framework underlying the intervention. JH, HT, BK, BM collected data. JH, HT, BK, BM, and LS performed data analysis. BM, BK, SK, and HT drafted the manuscript. All authors reviewed and edited the manuscript. All authors reviewed the manuscript critically for scientific content, and all authors gave final approval for publication. Acknowledgements All authors have approved the manuscript for submission. Research reported in this publication was supported by the National Institute of Drug Abuse of the National Institutes of Health under Award Number R33DA057610. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. ORCIDs of Authors (https://orcid.org/0000-0002-1080-3961, https://orcid.org/0000-0003-2041-7404, https://orcid.org/0000-0002-3396-6907, https://orcid.org/0000-0002-4796-7994, https://orcid.org/0000-0001-5555-5714, https://orcid.org/0000-0001-6163-7222, https://orcid.org/0000-0003-2958-3249, https://orcid.org/0000-0002-6878-189X, https://orcid.org/0000-0002-4013-5618) References NIDA. Drug Overdose Deaths: Facts and Figures 2024, August 21. Available from: https://nida.nih.gov/research-topics/trends-statistics/overdose-death-rates. Accessed 11 Mar 2025. SAMHSA. 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User-Centered Design to Reduce Inappropriate Blood Transfusion Orders. Appl Clin Inform. 2023;14(1):28-36. Holtzblatt K, Wendell JB, Wood S. Rapid Contextual Design: A How-To Guide to Key Techniques for User-Centered Design: Elsevier; 2004. Hussain Z, Slany W, Holzinger A. Current State of Agile User-Centered Design: A Survey. 5th Symposium of the Workgroup Human-Computer Interaction and Usability for Engineering of the Austrian Computer Society; November 9-10, 2009; Linz, Austria: Springer Berlin Heidelberg; 2009. p. 416-27. Zhai S, Yuwen W, Zyniewicz TL, Sonney J, Hash J, Chen M, Ward TM. Evaluating Behavioral Intervention Technologies: Integrating Human-Centered Design and Implementation Science Outcomes. Digit Health. 2025 Jun 11;11:20552076251348579. Lyon AR Koerner K. User-Centered Design for Psychosocial Intervention Development and Implementation. Clin Psychol (New York). 2016;23(2):180-200. Dopp AR, Parisi KE, Munson SA, & Lyon AR. A glossary of user-centered design strategies for implementation experts. Transl Behav Med. 2019;9(6). Lewis CC, Klasnja P, Lyon AR, Powell BJ, Lengnick-Hall R, Buchanan G, Meza RD, Chan MC, Boynton MH, Weiner BJ. The mechanics of implementation strategies and measures: advancing the study of implementation mechanisms. Implement Sci Commun. 2022;3. Lewis CC, Klasnja P, Powell BJ, Lyon AR, Tuzzio L, Jones S, Walsh-Bailey C, Weiner B. From Classification to Causality: Advancing Understanding of Mechanisms of Change in Implementation Science. Front in Public Health. 2018;6(136). Epic. Verona, WI. 2025. Available from: https://www.epic.com/ Accessed 11 Mar 2025. Feldstein AC, Glasgow RC. A practical, robust implementation and sustainability model (PRISM) for integrating research findings into practice. Jt Comm J Qual Patient Saf. 2008;34(4):228-43. Nilsen P, Bernhardsson S. Context matters in implementation science: a scoping review of determinant frameworks that describe contextual determinants for implementation outcomes. BMC Health Serv Res. 2019;1(189). McCreight MS, Rabin BA, Glasgow RE, Ayele RA, Leonard CA, Gilmartin HM, Frank JW, Hess PL, Burke RE, Battaglia CT. Using the practical, robust implementaion and sustainability model (PRISM) to qualitatively assess multilevel contextual factors to help plan, implement, evaluate, and disseminate health services programs. Transl Behav Med. 2019;9(6):1002-11. Communications ZV. Zoom (Version5.11) [Computer Software] 2024. Available from: https://zoom.us/. Accessed 11 Mar 2025. Otter.ai. Otter.ai 2024. Available from: https://otter.ai/transcription. Accessed 11 Mar 2025. Mural. Mural Whiteboard 2024. Available from: https://mural.co/. Accessed 11 Mar 2025. Qualtrics XM. Qualtrics 2025.Available from: https://www.qualtrics.com/. Accessed 11 Mar 2025. Weiner BJ, Lewis CC, Stanick C, Powell BJ, Dorsey CN, Clary AS, Boynton MH, Halko H. Psychometric assessment of three newly developed implementation outcome measures. Implement Sci. 2017;12:1-12. Smith JD, Li D, Rafferty MR. The Implementation Research Logic Model: a method for planning, executing, reporting, and synthesizing implementation projects. Implement Sci. 2020;15(84). Powell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Matthieu MM, Proctor EK, Kirchner JE. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implement Sci. 2015;10(21). Portalupi LB, Lewis CL, Miller CD, Whiteman-Jones KL, Sather KA, Nease Jr. DE, Matlock DD. Developing a patient and family research advisory panel to include people with significant disease, multimorbidity and advanced age. Fam Pract. 2017;34(3):364-9. Powell BJ, Beidas RS, Lewis CC, Aarons GA, McMillen JC, Proctor EK, Mandell DS. Methods to Improve the Selection and Tailoring of Implementation Strategies. J Behav Health Serv Res. 2017;44(2):177-94. Hussain MI, Reynolds TL, Zheng K. Medication Safety Alert Fatigue may be Reduced via Interaction Design and Clinical Role Tailoring: A Systematic Review. J Am Med Inform Assoc. 2019 Oct 1; 26(10): 1141-1149. Holmgren AJ, Hendrix N, Maisel N, Everson J, Bazemore A, Rotenstein L, Phillips RL, Adler-Milstein J. Electronic Health Record Usability, Satisfaction, and Burnout for Family Physicians. JAMA Netw Open. 2024 Aug 1;7(8):e2426956. Binswanger IA, Glanz JM, Faul M, Shoup JA, Quintana LM, Lyden J, Xu S, Narwaney KJ. The Association between Opioid Discontinuation and Herioin Use: A Nested Case-Control Study. Drug Alcohol Depend. 2020;217. Horsky J, Sherry D, Pan E, Byrne C, Johnston D. Decision Support Evaluation Tools Clinical Decision Support Design. Services DoHaH; 2011. Report No.: HHSP23320095649WC. Sanderson B, Field JD, Kocaballi AB, Estcourt LJ, Magrabi F, Wood EM, Coiera EW. Multicenter, multidisciplinary user-centered design of a clinical decision-support and simulation system for massive transfusion. Transfus. 2023;63(5):993-1004. Gong Y, Kang H. In: ES B, editor. Clinical Decision Support Systems: Theory and Practice. Health Informatics. Switzerland: Springer; 2016. p. 69-86. Brunner J, Chuang E, Goldzweig C, Cain CL, Sugar C, Yano EM. User-centered design to improve clinical decision support in primary care. Int J Med Inform. 2017;104:56-64. Blanes-Selva V, Asensio-Cuesta S, Donate-Martinez A, Mesquita FP, Garcia-Gomez JM. User-centered design of a clinical decision support system for palliative care: insights from healthcare professionals. Digit Health. 2023;9. Trinkley KE, Blakeslee WW, Matlock DD, Kao DP, Van Matre AG, Harrison R, Larson CL, Kostman N, Nelson JA, Lin CT, Malone DC. Clinician preferences for computerised clinical decision support for medications in primary care: a focus group study. BMJ Health Care Inform. 2019;26(1). Additional Declarations No competing interests reported. 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7236339","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498379290,"identity":"561409f2-ab26-431c-880c-28913555739a","order_by":0,"name":"Brad Morse","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYBACAyCWgDCZD0BoKJexgbAWtgSYFrBqYrTwGBCnxVz68MMbjDk2+fLtPR8/89Tcseef3WP+8AeDjeyGA9i1WPalGVswbkuz3HDm7GZpnmPPEmfcOWPYIMGQZoxLi8EZBjMJxm2HDQwkcrcx87AdTjCQyDFsMGA4nIhbC/s3sBb5+W+eMfP8O2wP1pLA8B+PFh6ILQw3eNiYedsOM24AaTnAcACnFssenmKLxG1pBgZn0owl5/YdTpxxI61wZoNBsvFMHFrMedg33vi4zcZAvv3www9vvh2255+RvOHjjwo72T4cWsAgAYuD8SgfBaNgFIyCUUAQAAAxD14PpnT1+QAAAABJRU5ErkJggg==","orcid":"","institution":"University of Colorado Anschutz Medical Campus","correspondingAuthor":true,"prefix":"","firstName":"Brad","middleName":"","lastName":"Morse","suffix":""},{"id":498379291,"identity":"f8d82bd1-a176-4734-a867-74319204b8d4","order_by":1,"name":"Katy E. Trinkley","email":"","orcid":"","institution":"University of Colorado Anschutz Medical Campus","correspondingAuthor":false,"prefix":"","firstName":"Katy","middleName":"E.","lastName":"Trinkley","suffix":""},{"id":498379293,"identity":"0896e406-6ed1-45ee-be4a-ee7b22eb6635","order_by":2,"name":"Jason A. Hoppe","email":"","orcid":"","institution":"University of Colorado Anschutz Medical Campus","correspondingAuthor":false,"prefix":"","firstName":"Jason","middleName":"A.","lastName":"Hoppe","suffix":""},{"id":498379295,"identity":"40538a08-5f8f-4246-8f83-a3f1844944d4","order_by":3,"name":"Nicole Wagner","email":"","orcid":"","institution":"University of Colorado Anschutz Medical Campus","correspondingAuthor":false,"prefix":"","firstName":"Nicole","middleName":"","lastName":"Wagner","suffix":""},{"id":498379296,"identity":"74bcb47e-09fb-4e60-9dc9-413aeeb1afff","order_by":4,"name":"Heather Tolle","email":"","orcid":"","institution":"University of Colorado Anschutz Medical Campus","correspondingAuthor":false,"prefix":"","firstName":"Heather","middleName":"","lastName":"Tolle","suffix":""},{"id":498379298,"identity":"8f7998b7-bc4f-4e5c-ac4c-fec140e4d556","order_by":5,"name":"Sarah V. Kautz","email":"","orcid":"","institution":"University of Colorado Anschutz Health Sciences Building","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"V.","lastName":"Kautz","suffix":""},{"id":498379300,"identity":"42d56c06-2823-4936-9e54-310ce6b5ce56","order_by":6,"name":"Kelly Bookman","email":"","orcid":"","institution":"University of Colorado Anschutz Medical Campus","correspondingAuthor":false,"prefix":"","firstName":"Kelly","middleName":"","lastName":"Bookman","suffix":""},{"id":498379303,"identity":"4b8c5da7-74e0-46ba-9e4e-154684c41d7a","order_by":7,"name":"Lisa M. Schilling","email":"","orcid":"","institution":"University of Colorado Anschutz Medical Campus","correspondingAuthor":false,"prefix":"","firstName":"Lisa","middleName":"M.","lastName":"Schilling","suffix":""},{"id":498379306,"identity":"41217597-1c9d-45ae-a87d-3d5551d39eab","order_by":8,"name":"Stephen Gresham Henry","email":"","orcid":"","institution":"University of California Davis","correspondingAuthor":false,"prefix":"","firstName":"Stephen","middleName":"Gresham","lastName":"Henry","suffix":""},{"id":498379312,"identity":"a364c0a3-f316-4c8a-b66b-f16ca177e7d2","order_by":9,"name":"Bethany M. Kwan","email":"","orcid":"","institution":"University of Colorado Anschutz Medical Campus","correspondingAuthor":false,"prefix":"","firstName":"Bethany","middleName":"M.","lastName":"Kwan","suffix":""}],"badges":[],"createdAt":"2025-07-28 17:38:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7236339/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7236339/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88949998,"identity":"12da6379-a575-4e66-9e04-65e0b8bb9bf3","added_by":"auto","created_at":"2025-08-13 05:42:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":390683,"visible":true,"origin":"","legend":"\u003cp\u003ePRISM-UCD Approach to Design of Clinical Decision Support for Opioid Prescribing Guidelines\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7236339/v1/6f00b970ea9a07018c0264b2.png"},{"id":88950904,"identity":"f4c7c5fb-6a7b-44b5-b8df-38b7cb4b1e1d","added_by":"auto","created_at":"2025-08-13 05:50:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":371262,"visible":true,"origin":"","legend":"\u003cp\u003eMural board synthesis\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7236339/v1/66f5fcb4d00b98f5f6fbfb26.png"},{"id":88950002,"identity":"799b5800-551c-4a1c-b04b-69f01afbe4ed","added_by":"auto","created_at":"2025-08-13 05:42:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":72376,"visible":true,"origin":"","legend":"\u003cp\u003eNaloxone OPA screenshot. © 2025 Epic Systems Corporation.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7236339/v1/4b5d68ee02367c20b9c7c545.png"},{"id":88950012,"identity":"482669c8-edad-42d1-9db0-04d9343787ce","added_by":"auto","created_at":"2025-08-13 05:42:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":760315,"visible":true,"origin":"","legend":"\u003cp\u003eImplementation research logic model for opioid prescribing guideline implementation\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7236339/v1/d19ed921fdfa0957ad7e8571.png"},{"id":104885790,"identity":"5b27bd0c-6edc-409b-ba5e-ab1fac46f538","added_by":"auto","created_at":"2026-03-18 09:59:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2084712,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7236339/v1/debe7938-12f6-44df-9d18-3f682d02efbd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrating PRISM with User-centered Design (PRISM+UCD): Designing clinical decision support for safe opioid prescribing ","fulltext":[{"header":"Background","content":"\u003cp\u003eDespite substantial public and governmental attention and investment, the opioid crisis in the United States continues to pose a serious threat to public health.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e In 2023, 8.6\u0026nbsp;million people across the U.S. misused opioids.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e In 2022, there were 81,806 opioid-related deaths in the U.S.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The overall rate of unintentional overdoses was 4.3% for prescription opioids and 28.7% for any opioids.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e These figures underscore the urgent need for strategies that enhance safety at the point of care, specifically when clinicians prescribe opioids, while minimizing disruption to clinical workflows and ensuring applicability across diverse healthcare settings. Opioid therapy is prescribed in a wide range of clinical contexts by various types of clinicians, from primary care to specialty and emergency care. This paper outlines the process and results of co-designing clinical decision support (CDS) tools to aid clinicians in safe opioid prescribing, drawing on implementation science and user-centered design (UCD) frameworks.\u003c/p\u003e\u003cp\u003e Opioid Prescribing Guidelines\u003c/p\u003e\u003cp\u003eThe 2022 Centers for Disease Control and Prevention (CDC) Clinical Practice Guideline for Prescribing Opioids for Pain was a national effort to address the opioid crisis by improving safety in pain management.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e While the guidelines are not intended to replace clinical judgment, they serve as a resource and provide 12 evidence-supported care recommendations to assist clinicians to safely address pain when utilizing opioid analgesic therapy. The guidelines can be categorized into four areas: 1) decision to initiate opioids for pain; 2) selection of opioid analgesic and dosage; 3) duration of initial opioid prescription and follow up; and 4) assessment of risk and potential harms. The guidelines focus on care for patients over 18 years of age, with acute, subacute, or chronic pain and is not intended to include pain management related to sickle cell disease, cancer-related pain, palliative care, or end-of-life care.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e The CDC guidelines are intended to support clinical judgment and accommodate individual patient needs, rather than impose a one-size-fits-all approach. For example, Recommendation #8 advises clinicians to mitigate risk when prescribing high-risk opioids by offering naloxone—an opioid antagonist that rapidly reverses overdose. Specifically, the guideline states: “Clinicians should offer naloxone when prescribing opioids, particularly to patients at increased risk for overdose, including patients with a history of overdose, patients with a history of substance use disorder, patients taking benzodiazepines with opioids.”\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e However, the guidelines caution against mandating naloxone prescriptions due to potential cost burdens for patients. \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Because the guidelines emphasize clinical discretion rather than strict requirements, tracking adherence can be challenging. Therefore, thoughtful design, implementation, and evaluation strategies are needed to promote provider uptake and assess patient benefit.\u003c/p\u003e\u003cp\u003e Opioid Prescribing Guidelines Implementation Strategies\u003c/p\u003e\u003cp\u003eImplementation strategies refer to methods used to increase adoption, implementation, sustainability and scaling of interventions.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e CDS is one of five implementation strategies demonstrating strong evidence of effectiveness and high rates of improvement.\u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e–\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e CDS provides an opportunity to support clinicians within their existing workflow to inform care decisions to align with guideline recommendations and has demonstrated promise with opioid safety interventions.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Importantly, CDS is often one of several discrete implementation strategies used as part of a multi-component package rather than as a standalone strategy. Other components often implemented with CDS include education, technical assistance, and/or evaluative strategies.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Our CDS-based implementation strategy included redesigning workflow, developing and implementing tools for quality monitoring, and reminding clinicians at the point of decision-making. The operationalization of clinician reminders is a type of education, particularly when the reminders are related to clinical practice guidelines.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e Implementation strategies can be honed by incorporating various perspectives rooted in different levels within the setting where guideline concordance is sought. User-centered design is a method described by Norman and Draper in which there is a focus on the user experience instead of the technology being developed.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e This crucial and basic focus in the design and development of technologies that support a user has been applied in many ways.\u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e–\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e For example, users might be involved in usability testing to identify pain points during the development of an user interface; users might also be granted greater decision making authority in participatory design by identifying what should be developed and how.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e The application of UCD along this spectrum is commonly reported in the literature. The flexibility of UCD makes it a particularly useful and nimble method, especially when aligned with theoretical frameworks like Practical, Robust Implementation and Sustainability Model (PRISM) and used in the context of implementation science.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe expected benefits of an implementation science framework, integrated with an UCD approach, include both technology usability as well as CDS alignment with the intervention and strategies on a multi-level scale.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Consideration of the setting of where the strategies will be implemented is critical, including workflows and the multiple levels of people directly or indirectly influencing the success of the project.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Purposeful alignment between strategies and the setting is important for building an understanding of the mechanisms of effectiveness of implementation strategies.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e The purpose of this research was to develop – and then implement and test – electronic health records (EHR)-based CDS tools for prioritized opioid prescribing guidelines. This work demonstrates a scalable, evidence-informed, process for designing CDS tools that are both usable and contextually aligned, increasing the likelihood of successful implementation and measurable impact.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eOverview of Setting and Context\u003c/p\u003e\u003cp\u003eThe setting was a large, university-affiliated health care system in the Rocky Mountain region with 12 hospitals, \u0026gt; 400 clinics, and 1.3\u0026nbsp;million outpatient and \u0026gt; 500,000 emergency department visits per year. The geographically diverse sites share the same EHR system (Epic: Verona, WI) with a requirement to e-prescribe all medications.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e The counties served cover approximately 85% of the state’s population.\u003c/p\u003e\u003cp\u003eThe context of the project focused on the NIH HEAL Initiative®. Specifically, the initiative was designed to support research into adoption and implementation of the 2022 Clinical Practice Guideline for Prescribing Opioids for Pain guidelines. Helping clinicians apply these guidelines at the right time, for the right patient could be supported by implementation science, i.e., PRISM + UCD. For this project, we integrated PRISM with UCD approaches to design implementation strategies for opioid prescribing guidelines, called the PRISM + UCD approach.\u003c/p\u003e\u003cp\u003e Informed by UCD principles and methods and the PRISM implementation science framework, we engaged patients (patient advisory board discussion), clinicians (focus groups), and hospital leadership and administration (1:1 interviews) around design of CDS tools and other implementation strategies to support opioid prescribing guideline-based care.\u003c/p\u003e\u003cp\u003eThe PRISM + UCD approach\u003c/p\u003e\u003cp\u003eOur method comprised four UCD phases: discovery, design, prototype, and test. The integration of PRISM ensures that the resulting strategies and CDS for safely prescribing opioids are effectively integrated and sustained within specific settings and contexts.\u003c/p\u003e\u003cp\u003ePRISM is an adaptation to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, a well-known implementation planning and evaluation framework.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e PRISM includes four domains of contextual determinants that span adoption, implementation, and sustainment of an intervention. The four domains are 1) inner setting (internal environment of the organization, i.e., culture): this domain considers patients, clinicians, and organizational leader views and experiences\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e; 2) characteristics of the individuals involved: the attributes and readiness of those who are responsible for implementing the intervention, i.e., policy makers, payers, external collaborators; 3) intervention characteristics: the resources, processes, and systems within the setting that supports continued implementation and maintenance of the intervention\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e; and 4) outer setting: this includes factors such as policies, regulations, and broader societal influences that could impact the intervention.\u003c/p\u003e\u003cp\u003ePRISM + UCD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) can help researchers adapt their interventions to fit local contexts and engage collaborators across phases of the project.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e The domains are interrelated, and data is produced for insights across the categorical domains during phase 1 of the UCD process, i.e., qualitative discovery. The support this method provides within the domains as described above. The first domain supports learning about the “perspectives on the intervention”, including both the recipient perspective as well as an organizational perspective (including leadership, managers, and frontline clinicians). The second domain provides insights on the characteristics of recipients of the intervention (both patient and organizational). The third domain is implementation and sustainability infrastructure, which includes factors such as the availability of a dedicated team that monitors fidelity to the intervention, trains clinicians on the intervention, shares best practices, and builds out an infrastructure for the sustainability of the intervention. The fourth domain is the external environment, which includes the regulatory environment of the broader health care system, the resources available to fund it, and potential alignment with health system goals.\u003c/p\u003e\u003cp\u003eUCD Phase 1: Discovery\u003c/p\u003e\u003cp\u003ePatient Advisory Panel: Patient engagement\u003c/p\u003e\u003cp\u003eAn established research advisory panel was consulted to assess patient priorities and obtain a patient perspective on opioid prescribing and safety. The panel first received an overview of the project, then provided feedback on their priorities and preferences regarding opioid use, best practices, and standardized guidelines in their medical care. We asked the following questions to assess the patient perspective: 1) What are your initial reflections on this project? 2) What aspects of this project might be of value or benefit patients who need opioids for pain management? 3) What aspects of this project might be a concern to patients? 4) What are the best ways to evaluate the outcomes of this project?\u003c/p\u003e\u003cp\u003eHealth System Leadership interviews\u003c/p\u003e\u003cp\u003eOne-on-one informal interviews with health system leadership. Interviews ranged between 30 to 60 minutes and were conducted via video conferencing software \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e and field notes were utilized. Recruitment was done through email and professional contacts.\u003c/p\u003e\u003cp\u003eClinicians focus groups\u003c/p\u003e\u003cp\u003eWe conducted five focus groups of inpatient and outpatient clinicians (MD/DO, PA, NP) licensed to prescribe opioid analgesics in the health system. Recruitment was conducted via email contact, circulated via clinical admin/management announcement emails, and using existing EHR reports of providers recently seeing a similar CDS alert. These individuals were invited to provide input on their individual and/or clinic workflows and practices, their informational needs and preferences, as well as review the design and implementation of CDS to be integrated into the EHR system (Epic; Verona, WI). Focus group participants completed a screening questionnaire and those available during a focus group timeslot with enough other participants (6–9 participants) from the same work setting (inpatient, outpatient, or emergency department) were invited to participate. Focus groups were conducted virtually to maximize representation and assure input from across the state. Qualitative de-identified data on prescribing practices and workflow were collected.\u003c/p\u003e\u003cp\u003eUsing a semi-structured focus group guide, participants described their current opioid prescribing workflows, prevalence of patients receiving opioid analgesics in their practice, decision processes around prescribing, and individual prescriber suggestions and needs for CDS design and development. Participants also provided feedback on ideal CDS designs in a drawing exercise. The focus groups lasted 90 minutes and were conducted via video conferencing software.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e All focus groups were audio recorded, transcribed verbatim with identifying information removed, and field notes taken. Thematic saturation was reached after five focus groups with clinicians.\u003c/p\u003e\u003cp\u003eDiscovery Synthesis\u003c/p\u003e\u003cp\u003eFormal thematic/contextual analysis used a matrix-style coding approach to structure analysis on key factors important to the CDS design. The focus group findings informed the design of the CDS.\u003c/p\u003e\u003cp\u003eSynthesis: Affinity Grouping Method\u003c/p\u003e\u003cp\u003eTo synthesize insights from engagement and data collection activities, the qualitative team [BM, BK, JH, KT] analyzed internal notes and focus group transcripts. Otter.ai\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e was used to transcribe audio recordings of the focus groups. The method of analysis consisted of an affinity grouping exercise conducted in Mural\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, an online collaboration software app. Three team members who facilitated the focus groups and the project PI conducted content analysis using a matrix-style coding approach to structure the analysis on key factors important to the CDS design. Team members reviewed a set amount of the transcripts that were assigned by the qualitative lead. Summary phrases were typed on Mural’s “sticky notes” and mapped together based on similarities in relation to five categories and the collaborator type, e.g., clinician, patient, and leadership. The five categories were as follows: 1) What guidelines are best suited for CDS? 2) What are the desired design features for the relevant CDS? 3) What are the features or elements in CDS users do not want? 4) What are the opportunities for implementation and clinical workflow? 5) What are the potential threats or barriers to the implementation of CDS? These questions facilitated the synthesis of the summaries for guidelines and desired design features and implementation strategies.\u003c/p\u003e\u003cp\u003eUCD Phase 2–4: Design, Prototyping, and Testing\u003c/p\u003e\u003cp\u003e For UCD phase – 2, which focused on the naloxone co-prescription guideline recommendation, focus group participants referred to existing CDS and made suggestions for improvement. Then in the UCD prototyping phase – 3 these suggestions were used by the study team (KT) to create low fidelity prototypes of the CDS user-interface using Microsoft PowerPoint in which the content varied slightly for primary care versus the emergency department and inpatient settings. These prototypes were then iteratively updated with input from the study team (JH, HT, BK, BM, LS) and the health system’s clinical decision support governance. During the UCD test phase – 4, these prototypes were utilized for focused feedback circulated via email to the 67 clinicians who responded to our focus group solicitation. Feedback was collected using Qualtrics in which participants provided input on specific design features such as response options (e.g., include a ‘comment’ or ‘other’ option), duration of suppressing a CDS based on clinician response, and content displayed within the user interface.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Participants were also asked to complete the 4-item Acceptability of Intervention Measure (AIM), a 4-item validated measure using a five-point Likert scale from completely disagree to completely agree.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Higher scores on the scale indicate more agreement with the acceptability of the alert. Open-ended responses to the survey were used to create final prototypes built in the EHR. The outcome of these methods is a minimum viable product (MVP) which was shared with analysts to build in the EHR. The study team tested the CDS in test environments of the EHR.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eImplementation Research Logic Model and Implementation Strategies\u003c/p\u003e\u003cp\u003eBased on the outcome of the PRISM + UCD process, we developed an Implementation Research Logic Model (IRLM) tool to guide our work. An IRLM provides collaborators and implementors with a structured opportunity to discuss and align on the core components of the logic model: determinants, implementation strategies (to address facilitators and barriers), the intervention, the mechanism of action, and the outcomes.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e The IRLM can be applied at multiple stages to identify implementation strategies needed both within and alongside the CDS tool to maximize program impact and sustainability.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e We then leveraged the Expert Recommendations for Implementing Change (ERIC) taxonomy of implementation strategies.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e In collaboration with our multilevel team, we discussed which strategies were feasible and appropriate within the given context.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAffinity Grouping Participants\u003c/p\u003e\u003cp\u003eFour patients were engaged through a pre-existing patient and family research advisory panel.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Eleven hospital leadership and administration interviews were conducted. Twenty-five clinicians (MD/DO, PA, NP) participated in five focus groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These three distinct data collection efforts provided the data for the Affinity Grouping methodology.\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\u003eDemographics of focus group participants and qualifying clinicians responding to recruitment\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParticipated in FG\u003c/p\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCompleted Screening\u003c/p\u003e\u003cp\u003eN(%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13(52.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23(34.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWoman\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12(48.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44(65.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-identify\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0(0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0(0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4(6.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u0026ndash;39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13(52.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27(40.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7(28.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22(32.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50\u0026ndash;59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4(16.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13(19.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60 and over\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1(4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1(1.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinician Type\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMD/DO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23(92.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49(73.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNP/PA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2(8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18(26.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork Setting\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmergency Department\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10(40.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20(29.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInpatient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7(28.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18(26.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3(12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5(7.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutpatient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5(20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24(35.8)\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\u003eAffinity Grouping Insights\u003c/p\u003e\u003cp\u003eThe Mural board Affinity Grouping synthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) produced three major areas of insights. First, given the potential impact on established workflows, we found that it is easy to quickly lose users of CDS due to poor design. Therefore, streamlined workflows with accurate logic and an intuitive interface are critical. Regarding opioid prescribing guidelines and desired design features for CDS, we found that existing guidelines most suited for redesigned CDS included co-prescribing of naloxone with opioid analgesics, which is aligned with Recommendation #8. Other guidelines suited for redesign included evaluation of opioid prescribing risk and improved processes for referrals for substance abuse treatment, specifically opioid use disorder (OUD). The PRISM\u0026thinsp;+\u0026thinsp;UCD process revealed several key insights: 1) clinicians need timely access to information about patients\u0026rsquo; recent prescription opioid use; 2) nurses should also have easy access to this data; and 3) CDS tools should minimize user effort by requiring as few clicks as possible and feature accurate firing logic to avoid disrupting clinical workflows.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSecond, related to implementation strategies, there are several opportunities for CDS implementation and integration into clinician workflows that may support adoption by clinicians. There is an education gap for clinicians on the updated CDC guidelines. Many system clinicians reported not often interacting with the new CDC guidelines, decreasing familiarity with the new guidelines within our system. Clinicians told us that it would be helpful if individual experts were identified as domain experts for support related to opioid use disorder content, in general, and the current guidelines, specifically. Domain experts might also be local champions in the clinics. According to Leadership, clinicians want to avoid inefficient workflows. Leadership advocates for standardized culture and strategic priority in communications that demonstrate leadership buy-in, while making Patient Reported Outcomes (PRO) useful and data-driven. Patients advocate for relationships with clinicians and value 1:1 conversation, especially when a referral is involved.\u003c/p\u003e\u003cp\u003eThird, data from the health system leadership interviews revealed that leadership supported the project as a strategic priority for the system. They provided guidance on the approval process needed for the build and development of CDS tools within the system. Leadership expressed concern at the amount of work associated with collecting data for the sake of collecting data, stressing the need for the data to be useful to clinicians, measuring impact on workflows and outcomes, and be integrated into the workflow. Leadership also suggested that our team take a wider view of hospital activities across the system to avoid duplication of efforts by leveraging existing organizational structures and resources.\u003c/p\u003e\u003cp\u003e UCD Phase 2\u0026ndash;4 Participants\u003c/p\u003e\u003cp\u003eFifteen of 67 clinicians responded to our Qualtrics survey in which participants provided input on specific design features.\u003c/p\u003e\u003cp\u003eUCD Phase 2\u0026ndash;4 Results\u003c/p\u003e\u003cp\u003eCDS tools were developed utilizing insights gained from all four UCD phases. During the discovery phase \u0026ndash; 1, utilizing resources in the hospital system, and subject matter expertise from the team, an existing alert encouraging prescribing naloxone with a high-risk opioid analgesic in the emergency department was identified and adapted to meet the contextual needs across the entire hospital system. This alert is related to Recommendation #8, as discussed in the Background. The MVP low fidelity prototype selected to be built for testing in the EHR test environment is available in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. A total of eight inpatient and emergency department clinicians rated the naloxone alert with an average score of 4 out of 5 on the AIM. Seven outpatient clinicians rated the alert as a 4.2 on the AIM, showing high acceptability of the alert design.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eImplementation Research Logic Model\u003c/p\u003e\u003cp\u003eBased on outputs from the Mural board synthesis, we (BK, JH, HT, KT, BM) developed an IRLM (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The logic model depicts PRISM-aligned contextual factors, corresponding implementation strategies \u0026ndash; including both CDS tool features and additional strategies described in the ERIC framework \u0026ndash; expected implementation strategy mechanisms, and RE-AIM outcomes for implementation of the opioid prescribing guidelines in a range of clinical settings. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, we identified two main categories of implementation strategies: CDS tools and additional strategies. The additional strategies included those already being employed during the discovery and design stages of the project as well as strategies that were recommended for use during the forthcoming \u0026ldquo;test\u0026rdquo; stage of the project. The use of the PRISM\u0026thinsp;+\u0026thinsp;UCD approach itself represents an implementation strategy reflecting ERIC\u0026rsquo;s \u0026ldquo;engagement of multilevel partners,\u0026rdquo; \u0026ldquo;internal consensus discussions,\u0026rdquo; and \u0026ldquo;adapting to context\u0026rdquo; domains. There were \u003cem\u003ea priori\u003c/em\u003e plans to include quality monitoring and mandating change strategies. Additional recommended implementation strategies were selected based on two considerations: 1) conceptual alignment with the PRISM contextual factors identified during discovery and design phases, and 2) feasibility assessments given project resources and study team experience working with the health system. For example, recommendations for champion support strategies reflected clinician preference for having a \u0026ldquo;go-to\u0026rdquo; person for sharing best practices for use of the CDS tools in their clinical context. Recommended strategies also included clinician education (on both opioid prescribing guidelines and use of the CDS tools) and clinical leadership support and communication \u0026ndash; both explicitly requested by participants in the clinician focus groups.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis work highlights a novel integrated approach to designing implementation strategies by combining PRISM\u0026thinsp;+\u0026thinsp;UCD. This integration enhances the relevance and usability of the strategies and fills a gap in the literature by offering a practical model for designing implementation strategies that are both theory-informed and user-responsive. There are relatively few well-described methods for designing implementation strategies. Implementation mapping, implementation research logic models, and group model building are among the established methods.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e It is common for implementation strategy design efforts to start with identification of adoption and implementation determinants, such as those described by implementation science frameworks like the PRISM. Identification of determinants is then followed by selection and/or tailoring of discrete implementation strategy components (such as described by the ERIC project) that are thought to address those determinants.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e For implementation strategies and interventions that are meant to interface with technology, such as CDS tools delivered via the EHR, UCD techniques can be a useful complement to the framework-driven approach.\u003c/p\u003e\u003cp\u003eUsing PRISM as a guide in the iterative UCD process presented an opportunity to maximize the value of CDS tools. Using a process that includes multiple levels of input from different organizational perspectives to inform the CDS design and development facilitates maximize system-level support, clinician use, positive patient-level health impact, and minimize unintended consequences (e.g. tapering guidelines association with increased heroin use).\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eA comparison of our work that utilizes PRISM\u0026thinsp;+\u0026thinsp;UCD to inform the IRLM reveals a more representative approach to the standard manner by which CDS is traditionally developed. Traditional approaches tend to be top down, not taking into consideration the users of the CDS and how they respond to prompts, nudges, and alerts as clinicians, but also users of an electronic interface that is tedious with clicks.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Additionally, traditional approaches do not incorporate iterative approaches into the design process and may not take into consideration the context in which the CDS is being implemented.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Other previous approaches have incorporated UCD that included user involvement and iterative design, which provided rich feedback and an attempt to incorporate this feedback into subsequent iterations.\u003csup\u003e\u003cspan additionalcitationids=\"CR44 CR45\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e However, without the presence of the PRISM framework, the assurance of all relative perspectives cannot be guaranteed. Additionally, at a high level, the projects all took a multidisciplinary approach by generally involving diverse collaborators, although the systematic organization of the collaborates was not as refined as what PRISM supports.\u003c/p\u003e\u003cp\u003eOur approach combines PRISM\u0026thinsp;+\u0026thinsp;UCD and capitalizes on contextual factor integration at multiple organizational levels. A core strength is that this approach remains nimble and adaptive, which makes space for the UCD element by focusing on and magnifying the expertise and skillsets of vested collaborators who can speak to CDS, and implementation needs. An example of the pragmatic approach we took is the relatively short period of time we were able to successfully design and build the naloxone alert CDS tool in seven months, including three months of PRISM\u0026thinsp;+\u0026thinsp;UCD work, and four months of analyst build time in the local EHR. Simultaneously, we also designed implementation strategies for the CDS in the local health system, which is included in the IRLM.\u003c/p\u003e\u003cp\u003eThe next steps of this project will be the implementation of the CDS in the local healthcare system. Outcomes of interest are captured in the IRLM, and include Reach, Adoption, Implementation, and Maintenance. All these outcomes will be a good measure of the naloxone CDS strategy built with a PRISM\u0026thinsp;+\u0026thinsp;UCD methodological approach that attempts to take into consideration the full reality of the setting and context in which the strategy is embedded.\u003c/p\u003e\u003cp\u003eLimitations\u003c/p\u003e\u003cp\u003eOne limitation is that there is bias introduced into the study by working with voluntary, self-selected focus groups. Another limitation is that there could be a disconnect between what clinicians are reported valuing in theory and in practice.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe developed and applied an integrated, rapid-cycle approach to designing CDS tools for safe opioid prescribing across inpatient, emergency, and outpatient settings in a large regional health system. Guided by the PRISM framework and UCD, we identified CDC guideline-aligned safety measures, redesigned a naloxone alert, and produced an implementation-ready CDS tool that received strong usability ratings from clinicians. This work illustrates how combining implementation science with UCD can accelerate the development of context-sensitive, evidence-based CDS strategies. The resulting alert was not only technically feasible but also endorsed by clinical leadership and supported by targeted education and communication strategies to encourage adoption.\u003c/p\u003e\u003cp\u003eThis integrated methodology offers a scalable model for developing CDS tools that are both clinically relevant and operationally sustainable. Future work will focus on evaluating the real-world impact of the naloxone alert on prescribing behavior and patient outcomes, as well as adapting this approach to other guideline-based interventions. Continued collaborator engagement and iterative refinement will be essential to ensuring long-term success and broader dissemination.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEHR \u0026ndash; Electronic Health Record\u003c/p\u003e\n\u003cp\u003eCDS \u0026ndash; Clinical Decision Support\u003c/p\u003e\n\u003cp\u003eCDC \u0026ndash; Center for Disease Control and Prevention\u003c/p\u003e\n\u003cp\u003ePRISM - Practical Robust Implementation and Sustainability Model\u003c/p\u003e\n\u003cp\u003eUCD \u0026ndash; User Centered Design\u003c/p\u003e\n\u003cp\u003eAIM \u0026ndash; Acceptability of Intervention Measure\u003c/p\u003e\n\u003cp\u003eRE-AIM - Reach, Effectiveness, Adoption, Implementation, and Maintenance\u003c/p\u003e\n\u003cp\u003eMVP \u0026ndash; Minimum Viable Product\u003c/p\u003e\n\u003cp\u003eIRLM \u0026ndash; Implementation Research Logic Model\u003c/p\u003e\n\u003cp\u003eERIC - Expert Recommendations for Implementing Change\u003c/p\u003e\n\u003cp\u003eOUD \u0026ndash; Opioid Use Disorder\u003c/p\u003e\n\u003cp\u003ePRO \u0026ndash; Patient Reported Outcomes\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval: Ethical approval was obtained by the university\u0026rsquo;s Institutional Review Board (IRB) (22-2165) and this study adheres to the tenets of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eConsent to participate: Informed consent was obtained from all individuals to participate in the study. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication: Not applicable.\u003c/p\u003e\n\u003cp\u003eCompeting interests: All authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClinical Trial Number: Not applicable.\u003c/p\u003e\n\u003cp\u003eFunding:\u0026nbsp;Research reported in this publication was supported by the National Institute of Drug Abuse of the National Institutes of Health under Award Number R33DA057610. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.\u003c/p\u003e\n\u003cp\u003eAuthor contributions: JH, HT, BK, KT, LS, and SH developed, planned, and designed the framework underlying the intervention. JH, HT, BK, BM collected data. JH, HT, BK, BM, and LS performed data analysis. BM, BK, SK, and HT drafted the manuscript. All authors reviewed and edited the manuscript. All authors reviewed the manuscript critically for scientific content, and all authors gave final approval for publication.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eAll authors have approved the manuscript for submission. Research reported in this publication was supported by the National Institute of Drug Abuse of the National Institutes of Health under Award Number R33DA057610. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. ORCIDs of Authors (https://orcid.org/0000-0002-1080-3961, https://orcid.org/0000-0003-2041-7404, https://orcid.org/0000-0002-3396-6907, https://orcid.org/0000-0002-4796-7994, https://orcid.org/0000-0001-5555-5714, https://orcid.org/0000-0001-6163-7222, https://orcid.org/0000-0003-2958-3249, https://orcid.org/0000-0002-6878-189X, https://orcid.org/0000-0002-4013-5618) \u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNIDA. Drug Overdose Deaths: Facts and Figures 2024, August 21. Available from: https://nida.nih.gov/research-topics/trends-statistics/overdose-death-rates. Accessed 11 Mar 2025.\u003c/li\u003e\n\u003cli\u003eSAMHSA. 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CHI \u0026apos;02: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems; 2002, April.\u003c/li\u003e\n\u003cli\u003eMorse B, Soares A, Ytell K, DeSanto K, Allen M, Holliman BD, Lee RS, Kwan BM, Schilling LM. Co-design of the Transgender Health Information Resource: Web-Based Participatory Design. J Particip Med. 2023;15(1):e38078.\u003c/li\u003e\n\u003cli\u003eMorse B, Soares A, Kwan BM, Allen M, Lee RS, Desanto K, Holliman BD, Ytell K, Schilling LM. A Transgender Health Information Resource: Participatory Design Study. JMIR Hum Factors. 2023;15(10):e42382.\u003c/li\u003e\n\u003cli\u003eMorse B, Anstett T, Mistry N, Porter S, Pincus S, Lin CT, Novins-Montague S, Ho PM. User-Centered Design to Reduce Inappropriate Blood Transfusion Orders. Appl Clin Inform. 2023;14(1):28-36.\u003c/li\u003e\n\u003cli\u003eHoltzblatt K, Wendell JB, Wood S. Rapid Contextual Design: A How-To Guide to Key Techniques for User-Centered Design: Elsevier; 2004.\u003c/li\u003e\n\u003cli\u003eHussain Z, Slany W, Holzinger A. Current State of Agile User-Centered Design: A Survey. 5th Symposium of the Workgroup Human-Computer Interaction and Usability for Engineering of the Austrian Computer Society; November 9-10, 2009; Linz, Austria: Springer Berlin Heidelberg; 2009. p. 416-27.\u003c/li\u003e\n\u003cli\u003eZhai S, Yuwen W, Zyniewicz TL, Sonney J, Hash J, Chen M, Ward TM. Evaluating Behavioral Intervention Technologies: Integrating Human-Centered Design and Implementation Science Outcomes. Digit Health. 2025 Jun 11;11:20552076251348579.\u003c/li\u003e\n\u003cli\u003eLyon AR Koerner K. User-Centered Design for Psychosocial Intervention Development and Implementation. Clin Psychol (New York). 2016;23(2):180-200.\u003c/li\u003e\n\u003cli\u003eDopp AR, Parisi KE, Munson SA, \u0026amp; Lyon AR. A glossary of user-centered design strategies for implementation experts. Transl Behav Med. 2019;9(6).\u003c/li\u003e\n\u003cli\u003eLewis CC, Klasnja P, Lyon AR, Powell BJ, Lengnick-Hall R, Buchanan G, Meza RD, Chan MC, Boynton MH, Weiner BJ. The mechanics of implementation strategies and measures: advancing the study of implementation mechanisms. Implement Sci Commun. 2022;3.\u003c/li\u003e\n\u003cli\u003eLewis CC, Klasnja P, Powell BJ, Lyon AR, Tuzzio L, Jones S, Walsh-Bailey C, Weiner B. From Classification to Causality: Advancing Understanding of Mechanisms of Change in Implementation Science. Front in Public Health. 2018;6(136).\u003c/li\u003e\n\u003cli\u003eEpic. Verona, WI. 2025. Available from: https://www.epic.com/ Accessed 11 Mar 2025.\u003c/li\u003e\n\u003cli\u003eFeldstein AC, Glasgow RC. A practical, robust implementation and sustainability model (PRISM) for integrating research findings into practice. Jt Comm J Qual Patient Saf. 2008;34(4):228-43.\u003c/li\u003e\n\u003cli\u003eNilsen P, Bernhardsson S. Context matters in implementation science: a scoping review of determinant frameworks that describe contextual determinants for implementation outcomes. BMC Health Serv Res. 2019;1(189).\u003c/li\u003e\n\u003cli\u003eMcCreight MS, Rabin BA, Glasgow RE, Ayele RA, Leonard CA, Gilmartin HM, Frank JW, Hess PL, Burke RE, Battaglia CT. Using the practical, robust implementaion and sustainability model (PRISM) to qualitatively assess multilevel contextual factors to help plan, implement, evaluate, and disseminate health services programs. Transl Behav Med. 2019;9(6):1002-11.\u003c/li\u003e\n\u003cli\u003eCommunications ZV. Zoom (Version5.11) [Computer Software] 2024. Available from: https://zoom.us/. Accessed 11 Mar 2025.\u003c/li\u003e\n\u003cli\u003eOtter.ai. Otter.ai 2024. Available from: https://otter.ai/transcription. Accessed 11 Mar 2025.\u003c/li\u003e\n\u003cli\u003eMural. Mural Whiteboard 2024. Available from: https://mural.co/. Accessed 11 Mar 2025.\u003c/li\u003e\n\u003cli\u003eQualtrics XM. Qualtrics 2025.Available from: https://www.qualtrics.com/. Accessed 11 Mar 2025.\u003c/li\u003e\n\u003cli\u003eWeiner BJ, Lewis CC, Stanick C, Powell BJ, Dorsey CN, Clary AS, Boynton MH, Halko H. Psychometric assessment of three newly developed implementation outcome measures. Implement Sci. 2017;12:1-12.\u003c/li\u003e\n\u003cli\u003eSmith JD, Li D, Rafferty MR. The Implementation Research Logic Model: a method for planning, executing, reporting, and synthesizing implementation projects. Implement Sci. 2020;15(84).\u003c/li\u003e\n\u003cli\u003ePowell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Matthieu MM, Proctor EK, Kirchner JE. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implement Sci. 2015;10(21).\u003c/li\u003e\n\u003cli\u003ePortalupi LB, Lewis CL, Miller CD, Whiteman-Jones KL, Sather KA, Nease Jr. DE, Matlock DD. Developing a patient and family research advisory panel to include people with significant disease, multimorbidity and advanced age. Fam Pract. 2017;34(3):364-9.\u003c/li\u003e\n\u003cli\u003ePowell BJ, Beidas RS, Lewis CC, Aarons GA, McMillen JC, Proctor EK, Mandell DS. Methods to Improve the Selection and Tailoring of Implementation Strategies. J Behav Health Serv Res. 2017;44(2):177-94.\u003c/li\u003e\n\u003cli\u003eHussain MI, Reynolds TL, Zheng K. Medication Safety Alert Fatigue may be Reduced via Interaction Design and Clinical Role Tailoring: A Systematic Review. J Am Med Inform Assoc. 2019 Oct 1; 26(10): 1141-1149.\u003c/li\u003e\n\u003cli\u003eHolmgren AJ, Hendrix N, Maisel N, Everson J, Bazemore A, Rotenstein L, Phillips RL, Adler-Milstein J. Electronic Health Record Usability, Satisfaction, and Burnout for Family Physicians. JAMA Netw Open. 2024 Aug 1;7(8):e2426956.\u003c/li\u003e\n\u003cli\u003eBinswanger IA, Glanz JM, Faul M, Shoup JA, Quintana LM, Lyden J, Xu S, Narwaney KJ. The Association between Opioid Discontinuation and Herioin Use: A Nested Case-Control Study. Drug Alcohol Depend. 2020;217.\u003c/li\u003e\n\u003cli\u003eHorsky J, Sherry D, Pan E, Byrne C, Johnston D. Decision Support Evaluation Tools Clinical Decision Support Design. Services DoHaH; 2011. Report No.: HHSP23320095649WC.\u003c/li\u003e\n\u003cli\u003eSanderson B, Field JD, Kocaballi AB, Estcourt LJ, Magrabi F, Wood EM, Coiera EW. Multicenter, multidisciplinary user-centered design of a clinical decision-support and simulation system for massive transfusion. Transfus. 2023;63(5):993-1004.\u003c/li\u003e\n\u003cli\u003eGong Y, Kang H. In: ES B, editor. Clinical Decision Support Systems: Theory and Practice. Health Informatics. Switzerland: Springer; 2016. p. 69-86.\u003c/li\u003e\n\u003cli\u003eBrunner J, Chuang E, Goldzweig C, Cain CL, Sugar C, Yano EM. User-centered design to improve clinical decision support in primary care. Int J Med Inform. 2017;104:56-64.\u003c/li\u003e\n\u003cli\u003eBlanes-Selva V, Asensio-Cuesta S, Donate-Martinez A, Mesquita FP, Garcia-Gomez JM. User-centered design of a clinical decision support system for palliative care: insights from healthcare professionals. Digit Health. 2023;9.\u003c/li\u003e\n\u003cli\u003eTrinkley KE, Blakeslee WW, Matlock DD, Kao DP, Van Matre AG, Harrison R, Larson CL, Kostman N, Nelson JA, Lin CT, Malone DC. Clinician preferences for computerised clinical decision support for medications in primary care: a focus group study. BMJ Health Care Inform. 2019;26(1).\u003c/li\u003e\n\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":"PRISM, User-Centered Design, Opioid Prescribing, Clinical Decision Support, Implementation Science, Electronic Health Record","lastPublishedDoi":"10.21203/rs.3.rs-7236339/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7236339/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eBalancing safe opioid prescribing with effective pain management is essential to addressing the opioid crisis. Increasing clinician adoption of evidence-based safety practices is a public health priority. This project presents a practical, adaptable approach to developing electronic health record (EHR)-embedded clinical decision support (CDS) strategies that promote uptake of opioid safety measures recommended by the Centers for Disease Control and Prevention (CDC). The goal was to design implementation strategies that enhance guideline-concordant opioid prescribing, including a suite of EHR-integrated CDS tools.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e Guided by the Practical, Robust Implementation and Sustainability Model (PRISM) and informed by implementation science and user-centered design (UCD), we used an iterative, multi-level engagement process. PRISM served as the theoretical framework for integrating collaborator input and user testing throughout the development cycle. Activities included discovery, design, prototyping, and usability testing. Collaborators included executive decision-makers, informatics leaders, frontline clinicians across diverse settings, representatives from the CDC and National Institute on Drug Abuse, and patients. These methods informed the selection of opioid safety measures, design themes, and workflow considerations, resulting in implementation-ready CDS prototypes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e The discovery phase identified a naloxone prescribing alert as a strong candidate for redesign, aligning with CDC guidelines and relevant across all four PRISM domains. The final redesign received mean ratings of 4.0 and 4.2 out of 5 on the Acceptability of Intervention Measure (AIM) from inpatient and outpatient clinicians, respectively.\u003c/p\u003e","manuscriptTitle":"Integrating PRISM with User-centered Design (PRISM+UCD): Designing clinical decision support for safe opioid prescribing ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-13 05:42:40","doi":"10.21203/rs.3.rs-7236339/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":"06609613-fb6e-4033-9a9d-9d71cea8760a","owner":[],"postedDate":"August 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T09:57:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-13 05:42:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7236339","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7236339","identity":"rs-7236339","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}